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	<title>bioRxiv Channel: Donders Institute for Brain, Cognition and Behaviour</title>
	<link>https://biorxiv.org</link>
	<description>
	This feed contains articles for bioRxiv Channel "Donders Institute for Brain, Cognition and Behaviour"
	</description>

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	<title>bioRxiv</title>
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	<item rdf:about="https://biorxiv.org/cgi/content/short/108753v1?rss=1">
<title>
<![CDATA[
Frequency-specific directed interactions in the human brain network for language 
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</title>
<link>
https://biorxiv.org/cgi/content/short/108753v1?rss=1"
</link>
<description><![CDATA[
The brains remarkable capacity for language requires bidirectional interactions between functionally specialized brain regions. We used magnetoencephalography to investigate interregional interactions in the brain network for language, while 102 participants were reading sentences. Using Granger causality analysis, we identified inferior frontal cortex and anterior temporal regions to receive widespread input, and middle temporal regions to send widespread output. This fits well with the notion that these regions play a central role in language processing. Characterization of the functional topology of this network, using data-driven matrix factorization, which allowed for partitioning into a set of subnetworks, revealed directed connections at distinct frequencies of interaction. Connections originating from temporal regions peaked at alpha frequency, whereas connections originating from frontal and parietal regions peaked at beta frequency. These findings indicate that processing different types of linguistic information may depend on the contributions of distinct brain rhythms.nnOne Sentence SummaryCommunication between language relevant areas in the brain is supported by rhythmic synchronization, where different rhythms reflect the direction of information flow.
]]></description>
<dc:creator>Schoffelen, J. M.</dc:creator>
<dc:creator>Hulten, A.</dc:creator>
<dc:creator>Lam, N.</dc:creator>
<dc:creator>Marquand, A.</dc:creator>
<dc:creator>Udden, J.</dc:creator>
<dc:creator>Hagoort, P.</dc:creator>
<dc:date>2017-02-15</dc:date>
<dc:identifier>doi:10.1101/108753</dc:identifier>
<dc:title><![CDATA[Frequency-specific directed interactions in the human brain network for language]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-02-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/175000v1?rss=1">
<title>
<![CDATA[
Neural entrainment determines the words we hear 
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</title>
<link>
https://biorxiv.org/cgi/content/short/175000v1?rss=1"
</link>
<description><![CDATA[
Low-frequency neural entrainment to rhythmic input has been hypothesized as a canonical mechanism that shapes sensory perception in time. Neural entrainment is deemed particularly relevant for speech analysis, as it would contribute to the extraction of discrete linguistic elements from continuous acoustic signals. Yet, its causal influence in speech perception has been difficult to establish. Here, we provide evidence that oscillations build temporal predictions about the duration of speech tokens that directly influence perception. Using magnetoencephalography (MEG), we studied neural dynamics during listening to sentences that changed in speech rate. We observed neural entrainment to preceding speech rhythms persisting for several cycles after the change in rate. The sustained entrainment was associated with changes in the perceived duration of the last words vowel, resulting in the perception of words with radically different meanings. These findings support oscillatory models of speech processing, suggesting that neural oscillations actively shape speech perception.
]]></description>
<dc:creator>Kosem, A.</dc:creator>
<dc:creator>Bosker, H. R.</dc:creator>
<dc:creator>Takashima, A.</dc:creator>
<dc:creator>Meyer, A.</dc:creator>
<dc:creator>Jensen, O.</dc:creator>
<dc:creator>Hagoort, P.</dc:creator>
<dc:date>2017-08-10</dc:date>
<dc:identifier>doi:10.1101/175000</dc:identifier>
<dc:title><![CDATA[Neural entrainment determines the words we hear]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-08-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2019.12.25.884775v1?rss=1">
<title>
<![CDATA[
No title, no theme: The joined neural space between speakers and listeners during production and comprehension of multi sentence discourse 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2019.12.25.884775v1?rss=1"
</link>
<description><![CDATA[
Speakers and listeners usually interact in larger discourses than single words or even single sentences. The goal of the present study was to identify the neural bases reflecting how the mental representation of the situation denoted in a multi-sentence discourse (situation model) is constructed and shared between speakers and listeners. An fMRI study using a variant of the ambiguous text paradigm was designed. Speakers produced ambiguous texts in the scanner and listeners subsequently listened to these texts in different states of ambiguity: preceded by a highly informative, intermediately informative or no title at all. Conventional BOLD activation analyses in listeners, as well as inter-subject correlation analyses between the speakers and the listeners hemodynamic time courses were performed. Critically, only the processing of disambiguated, coherent discourse with an intelligible situation model representation involved (shared) activation in bilateral lateral parietal and medial prefrontal regions. This shared spatiotemporal pattern of brain activation between the speaker and the listener suggests that the process of memory retrieval in medial prefrontal regions and the binding of retrieved information in the lateral parietal cortex constitutes a core mechanism underlying the communication of complex conceptual representations.
]]></description>
<dc:creator>Heidlmayr, K.</dc:creator>
<dc:creator>Weber, K.</dc:creator>
<dc:creator>Takashima, A.</dc:creator>
<dc:creator>Hagoort, P.</dc:creator>
<dc:date>2019-12-27</dc:date>
<dc:identifier>doi:10.1101/2019.12.25.884775</dc:identifier>
<dc:title><![CDATA[No title, no theme: The joined neural space between speakers and listeners during production and comprehension of multi sentence discourse]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-12-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/653147v1?rss=1">
<title>
<![CDATA[
Learning lexical-syntactic biases: An fMRI study on how we connect words and syntactic information 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/653147v1?rss=1"
</link>
<description><![CDATA[
Language processing often involves learning new words and how they relate to each other. These relations are realized through syntactic information connected to a word, e.g. a word can be verb or a noun, or both, like the word  run. In a behavioral and an fMRI task we showed that words and their syntactic properties, i.e. lexical items which were either syntactically ambiguous or unambiguous, can be learned through the probabilities of co-occurrence in an exposure session and subsequently used in a production task. Novel words were processed within regions of the language network (left inferior frontal and posterior middle temporal gyrus) and more syntactic options led to higher activations herein, even when the words were shown in isolation, suggesting combined lexical-syntactic representation. When words were shown in untrained grammatical contexts, activation in left inferior frontal cortex increased. This might reflect competition between the newly learned representation and the presented information. The results elucidate the lexical nature of the neural representations of lexical-syntactic information within the language network and the specific role of the left inferior frontal cortex in unification of the novel words with the surrounding context.
]]></description>
<dc:creator>Weber, K.</dc:creator>
<dc:creator>Meyer, A.</dc:creator>
<dc:creator>Hagoort, P.</dc:creator>
<dc:date>2019-05-30</dc:date>
<dc:identifier>doi:10.1101/653147</dc:identifier>
<dc:title><![CDATA[Learning lexical-syntactic biases: An fMRI study on how we connect words and syntactic information]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-05-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/714998v1?rss=1">
<title>
<![CDATA[
Stimulus-modality independent activation of the brain network for language 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/714998v1?rss=1"
</link>
<description><![CDATA[
The meaning of a sentence can be understood, whether presented in written or spoken form. Therefore it is highly probable that brain processes supporting language comprehension are at least partly independent of sensory modality. To identify where and when in the brain language processing is independent of sensory modality, we directly compared neuromagnetic brain signals of 200 human subjects (102 males) either reading or listening to sentences. We used multiset canonical correlation analysis to align individual subject data in a way that boosts those aspects of the signal that are common to all, allowing us to capture word-by-word signal variations, consistent across subjects and at a fine temporal scale. Quantifying this consistency in activation across both reading and listening tasks revealed a mostly left hemispheric cortical network. Areas showing consistent activity patterns include not only areas previously implicated in higher-level language processing, such as left prefrontal, superior & middle temporal areas and anterior temporal lobe, but also parts of the control-network as well as subcentral and more posterior temporal-parietal areas. Activity in this supramodal sentence processing network starts in temporal areas and rapidly spreads to the other regions involved. The findings do not only indicate the involvement of a large network of brain areas in supramodal language processing, but also indicate that the linguistic information contained in the unfolding sentences modulates brain activity in a word-specific manner across subjects.
]]></description>
<dc:creator>Arana, S. L.</dc:creator>
<dc:creator>Marquand, A. F.</dc:creator>
<dc:creator>Hulten, A.</dc:creator>
<dc:creator>Hagoort, P.</dc:creator>
<dc:creator>Schoffelen, J. M.</dc:creator>
<dc:date>2019-07-26</dc:date>
<dc:identifier>doi:10.1101/714998</dc:identifier>
<dc:title><![CDATA[Stimulus-modality independent activation of the brain network for language]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-07-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/696310v1?rss=1">
<title>
<![CDATA[
Speaking in the brain: The interaction between words and syntax in producing sentences 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/696310v1?rss=1"
</link>
<description><![CDATA[
This neuroimaging study investigated the neural infrastructure of sentence-level language production. We compared brain activation patterns, as measured with BOLD-fMRI, during production of sentences which differed in verb argument structures (intransitives, transitives, ditransitives) and the lexical status of the verb (known verbs or pseudo-verbs). An example for the type of sentence to be produced started a mini-block of six sentences with the same structure. For each trial, participants were first given the (pseudo-)verb followed by three geometric shapes to serve as verb arguments in the sentences. Production of sentences with known verbs yielded greater activation compared to those with pseudo-verbs in the core language network of left inferior frontal gyrus, the left posterior middle temporal gyrus, and a more posterior middle temporal region extending into the angular gyrus (LpMTG/AG), analogous to effects observed in language comprehension. Increasing the number of verb arguments led to greater activation in an overlapping left pMTG/AG area, particularly for known verbs, as well as in the bilateral precuneus. Thus, producing sentences with more complex structures using existing verbs lead to increased activation in the language network, suggesting some reliance on memory retrieval of stored lexical-syntactic information during sentence production. This study thus provides evidence from sentence-level language production in line with functional models of the language network that have so far been mainly based on single word production, comprehension and processing in aphasia.
]]></description>
<dc:creator>Takashima, A.</dc:creator>
<dc:creator>Konopka, A.</dc:creator>
<dc:creator>Meyer, A.</dc:creator>
<dc:creator>Hagoort, P.</dc:creator>
<dc:creator>Weber, K.</dc:creator>
<dc:date>2019-07-09</dc:date>
<dc:identifier>doi:10.1101/696310</dc:identifier>
<dc:title><![CDATA[Speaking in the brain: The interaction between words and syntax in producing sentences]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-07-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/806059v1?rss=1">
<title>
<![CDATA[
Biasing the perception of spoken words with tACS 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/806059v1?rss=1"
</link>
<description><![CDATA[
Recent neuroimaging evidence suggests that the frequency of entrained oscillations in auditory cortices influences the perceived duration of speech segments, impacting word perception (Kosem et al. 2018). We further tested the causal influence of neural entrainment frequency during speech processing, by manipulating entrainment with continuous transcranial alternating current stimulation (tACS) at distinct oscillatory frequencies (3 Hz and 5.5 Hz) above the auditory cortices. Dutch participants listened to speech and were asked to report their percept of a target Dutch word, which contained a vowel with an ambiguous duration. Target words were presented either in isolation (first experiment) or at the end of spoken sentences (second experiment). We predicted that the frequency of the tACS current would influence neural entrainment and therewith how speech is perceptually sampled, leading to a perceptual over- or underestimation of the vowel duration. Experiment 1 revealed no significant result. In contrast, results from experiment 2 showed a significant effect of tACS frequency on target word perception. Faster tACS lead to more long-vowel word percepts, in line with previous findings suggesting that neural oscillations are instrumental in the temporal processing of speech. The different results from the two experiments suggest that the impact of tACS is dependent on the sensory context. tACS may have a stronger effect on spoken word perception when the words are presented in a continuous stream of speech as compared to when they are isolated, potentially because prior (stimulus-induced) entrainment of brain oscillations might be a prerequisite for tACS to be effective.
]]></description>
<dc:creator>Kosem, A.</dc:creator>
<dc:creator>Bosker, H. R.</dc:creator>
<dc:creator>Jensen, O.</dc:creator>
<dc:creator>Hagoort, P.</dc:creator>
<dc:creator>Riecke, L.</dc:creator>
<dc:date>2019-10-16</dc:date>
<dc:identifier>doi:10.1101/806059</dc:identifier>
<dc:title><![CDATA[Biasing the perception of spoken words with tACS]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/366427v1?rss=1">
<title>
<![CDATA[
Do we predict upcoming speech content in naturalistic environments? 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/366427v1?rss=1"
</link>
<description><![CDATA[
The ability to predict upcoming actions is a characteristic hallmark of cognition and therefore not surprisingly a central topic in cognitive science. It remains unclear, however, whether the predictive behaviour commonly observed in strictly controlled lab environments generalizes to rich, everyday settings. In four virtual reality experiments, we tested whether a well-established marker of linguistic prediction (i.e. anticipatory eye movements as observed in the visual world paradigm) replicated when increasing the naturalness of the paradigm by means of i) immersing participants in naturalistic everyday scenes, ii) increasing the number of distractor objects present, iii) manipulating the location of referents in central versus peripheral vision, and iv) modifying the proportion of predictable nounreferents in the experiment. Robust anticipatory eye movements were observed, even in the presence of 10 objects (hereby testing working memory) and when only 25% of all sentences contained a visually present referent (hereby testing error-based learning). The anticipatory effect disappeared, however, when referents were placed in peripheral vision. Together, our findings suggest that working memory may play an important role in predictive processing in everyday communication, but only in contexts where upcoming referents have been explicitly attended to prior to encountering the spoken referential act. Methodologically, our study confirms that ecological validity and experimental control may go hand in hand in future studies of human predictive behaviour.
]]></description>
<dc:creator>Heyselaar, E.</dc:creator>
<dc:creator>Peeters, D.</dc:creator>
<dc:creator>Hagoort, P.</dc:creator>
<dc:date>2018-07-10</dc:date>
<dc:identifier>doi:10.1101/366427</dc:identifier>
<dc:title><![CDATA[Do we predict upcoming speech content in naturalistic environments?]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/501437v1?rss=1">
<title>
<![CDATA[
The Relation between Alpha/Beta Oscillations and the Encoding of Sentence induced Contextual Information 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/501437v1?rss=1"
</link>
<description><![CDATA[
Within the sensory domain, alpha/beta oscillations have been frequently linked to the prediction of upcoming sensory input. Here, we investigated whether oscillations at these frequency bands serve as a neural marker in the context of linguistic input prediction as well. Specifically, we hypothesized that if alpha/beta oscillations do index language prediction, their power should modulate during sentence processing, indicating stronger engagement of underlying neuronal populations involved in the linguistic prediction process. Importantly, the modulation should monotonically relate to the degrees of predictability of incoming words based on past context. Specifically, we expected that the more predictable the last word of a sentence, the stronger the alpha/beta power modulation. To test this, we measured neural responses with magnetoencephalography of healthy individuals (of either sex) during exposure to a set of linguistically matched sentences featuring three distinct levels of sentence context constraint (high, medium and low constraint). We observed fluctuations in alpha/beta power before last word onset, and also modulations in M400 amplitude after last word onset that are known to gradually relate to semantic predictability. In line with previous findings, the M400 amplitude was monotonically related to the degree of context constraint, with a high constraining context resulting in the strongest amplitude decrease. In contrast, alpha/beta power was non-monotonically related to context constraints. The strongest power decrease was observed for intermediate constraints, followed by high and low constraints. While the monotonous M400 amplitude modulation fits within a framework of prediction, the non-monotonous oscillatory results are not easily reconciled with this idea.nnSIGNIFICANCE STATEMENTNeural activity in the alpha (8-10Hz) and beta (16-20) frequency ranges have been related to the prediction of upcoming sensory input. It remains still debated whether these frequency bands relate to language prediction as well. In this magnetoencephalography study, we recorded alpha/beta oscillatory activity while participants listened to sentences whose ending had varying degree of predictability based on past linguistic information. Our results show that alpha/beta power modulations were non-monotonically related to the degree of linguistic predictability: the strongest modulation of alpha/beta power was observed for intermediate levels of linguistic predictability during sentence reading. Together, the results emphasize that alpha/beta oscillations cannot directly be linked to predictability in language, but potentially relate to attention or control operations during language processing.
]]></description>
<dc:creator>Terporten, R.</dc:creator>
<dc:creator>Schoffelen, J.-M.</dc:creator>
<dc:creator>Dai, B.</dc:creator>
<dc:creator>Hagoort, P.</dc:creator>
<dc:creator>Koesem, A.</dc:creator>
<dc:date>2018-12-19</dc:date>
<dc:identifier>doi:10.1101/501437</dc:identifier>
<dc:title><![CDATA[The Relation between Alpha/Beta Oscillations and the Encoding of Sentence induced Contextual Information]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-12-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/191494v1?rss=1">
<title>
<![CDATA[
Binding language: Structuring sentences through precisely timed oscillatory mechanisms 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/191494v1?rss=1"
</link>
<description><![CDATA[
Syntactic binding refers to combining words into larger structures. Using EEG, we investigated the neural processes involved in syntactic binding. Participants were auditorily presented two-word sentences (i.e. a pronoun and pseudoverb such as  she dotches, for which syntactic binding can take place) and wordlists (i.e. two pseudoverbs such as  pob dotches, for which no binding can occur). Comparing these two conditions, we targeted syntactic binding while minimizing contributions of semantic binding and of other cognitive processes such as working memory. We found a converging pattern of results using two distinct analysis approaches: one approach using frequency bands as defined in previous literature, and one data-driven approach in which we looked at the entire range of frequencies between 3-30 Hz without the constraints of pre-defined frequency bands. In the syntactic binding (relative to the wordlist) condition, a power increase was observed in the alpha and beta frequency range shortly preceding the presentation of the target word that requires binding, which was maximal over frontal-central electrodes. Our interpretation is that these signatures reflect that language comprehenders expect the need for binding to occur. Following the presentation of the target word in a syntactic binding context (relative to the wordlist condition), an increase in alpha power maximal over a left lateralized cluster of frontal-temporal electrodes was observed. We suggest that this alpha increase relates to syntactic binding taking place. Taken together, our findings suggest that increases in alpha and beta power are reflections of distinct the neural processes underlying syntactic binding.
]]></description>
<dc:creator>Segaert, K.</dc:creator>
<dc:creator>Mazaheri, A.</dc:creator>
<dc:creator>Hagoort, P.</dc:creator>
<dc:date>2017-09-20</dc:date>
<dc:identifier>doi:10.1101/191494</dc:identifier>
<dc:title><![CDATA[Binding language: Structuring sentences through precisely timed oscillatory mechanisms]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/585844v1?rss=1">
<title>
<![CDATA[
Laminar Specific fMRI Reveals Directed Interactions in Distributed Networks During Language Processing 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/585844v1?rss=1"
</link>
<description><![CDATA[
Laminar resolution, functional magnetic resonance imaging (lfMRI) is a noninvasive technique with the potential to distinguish top-down and bottom-up signal contributions on the basis of laminar specific interactions between distal regions. Hitherto, lfMRI could not be demonstrated for either whole-brain distributed networks or for complex cognitive tasks. We show that lfMRI can reveal whole-brain directed networks during word reading. We identify distinct, language critical regions based on their association with the top-down signal stream and establish lfMRI for the noninvasive assessment of directed connectivity during task performance.
]]></description>
<dc:creator>Sharoh, D.</dc:creator>
<dc:creator>van Mourik, T.</dc:creator>
<dc:creator>Bains, L. J.</dc:creator>
<dc:creator>Segaert, K.</dc:creator>
<dc:creator>Weber, K.</dc:creator>
<dc:creator>Hagoort, P.</dc:creator>
<dc:creator>Norris, D. G.</dc:creator>
<dc:date>2019-03-28</dc:date>
<dc:identifier>doi:10.1101/585844</dc:identifier>
<dc:title><![CDATA[Laminar Specific fMRI Reveals Directed Interactions in Distributed Networks During Language Processing]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-03-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/546325v1?rss=1">
<title>
<![CDATA[
Neuronal memory for language processing 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/546325v1?rss=1"
</link>
<description><![CDATA[
In language processing, an interpretation is computed incrementally within memory while utterances unfold in time. Here, we investigate the nature of this processing memory in a spiking network model of sentence comprehension. We show that the history dependence of neuronal responses endows circuits of biological neurons with adequate memory to assign semantic roles and resolve binding relations between words in a stream of language input. A neurobiological read-write memory is proposed where short-lived spiking activity encodes information into coupled dynamic variables that move at slower timescales. This state-dependent network does not rely on persistent activity, excitatory feedback, or synaptic plasticity for storage. Instead, information is maintained in adaptive neuronal conductances and can be accessed directly during comprehension without cued retrieval of previous input words. This work provides a step towards a computational neurobiology of language.
]]></description>
<dc:creator>Fitz, H.</dc:creator>
<dc:creator>Uhlmann, M.</dc:creator>
<dc:creator>van den Broek, D.</dc:creator>
<dc:creator>Duarte, R.</dc:creator>
<dc:creator>Hagoort, P.</dc:creator>
<dc:creator>Petersson, K. M.</dc:creator>
<dc:date>2019-02-11</dc:date>
<dc:identifier>doi:10.1101/546325</dc:identifier>
<dc:title><![CDATA[Neuronal memory for language processing]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-02-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/793729v1?rss=1">
<title>
<![CDATA[
Gamma-cycle duration predicts instantaneous amplitude, spike rate and synchrony in macaque V1. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/793729v1?rss=1"
</link>
<description><![CDATA[
Circuits of excitatory and inhibitory neurons can generate rhythmic activity in the gamma frequency-range (30-80Hz). Individual gamma-cycles show spontaneous variability in amplitude and duration. The mechanisms underlying this variability are not fully understood. We recorded local-field-potentials (LFPs) and spikes from awake macaque V1, and developed a noise-robust method to detect gamma-cycle amplitudes and durations. Amplitudes and durations showed a weak but positive correlation. This correlation, and the joint amplitude-duration distribution, is well reproduced by a dampened harmonic oscillator driven by stochastic noise. We show that this model accurately fits LFP power spectra and is equivalent to a linear PING (Pyramidal Interneuron Network Gamma) circuit. The model recapitulates two additional features of V1 gamma: (1) Amplitude-duration correlations decrease with oscillation strength; (2) Amplitudes and durations exhibit strong and weak autocorrelations, respectively, depending on oscillation strength. Finally, longer gamma-cycles are associated with stronger spike-synchrony, but lower spike-rates in both (putative) excitatory and inhibitory neurons. In sum, V1 gamma-dynamics are well described by the simplest possible model of gamma: A linear harmonic oscillator driven by noise.
]]></description>
<dc:creator>Spyropoulos, G.</dc:creator>
<dc:creator>Dowdall, J. R.</dc:creator>
<dc:creator>Scholvinck, M. L.</dc:creator>
<dc:creator>Bosman, C. A.</dc:creator>
<dc:creator>Lima, B.</dc:creator>
<dc:creator>Peter, A.</dc:creator>
<dc:creator>Onorato, I.</dc:creator>
<dc:creator>Klon-Lipok, J.</dc:creator>
<dc:creator>Roese, R.</dc:creator>
<dc:creator>Neuenschwander, S.</dc:creator>
<dc:creator>Singer, W.</dc:creator>
<dc:creator>Vinck, M.</dc:creator>
<dc:creator>Fries, P.</dc:creator>
<dc:date>2019-10-05</dc:date>
<dc:identifier>doi:10.1101/793729</dc:identifier>
<dc:title><![CDATA[Gamma-cycle duration predicts instantaneous amplitude, spike rate and synchrony in macaque V1.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.05.14.050310v1?rss=1">
<title>
<![CDATA[
Functional Connectivity of the Precuneus Reflects Effectiveness of Visual Restitution Training in Chronic Hemianopia 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.05.14.050310v1?rss=1"
</link>
<description><![CDATA[
Visual field defects in chronic hemianopia can improve through visual restitution training, yet not all patients benefit equally from this long and exhaustive process. Here, we asked if resting-state functional connectivity prior to visual restitution could predict training success. In two training sessions of eight weeks each, 20 patients with chronic hemianopia performed a visual discrimination task by directing spatial attention towards stimuli presented in either hemifield, while suppressing eye movements. We examined two effects: a sensitivity change in the attended (trained) minus the unattended (control) hemifield (i.e., a training-specific improvement), and an overall improvement (i.e., a total change in sensitivity after both sessions). We then identified five visual resting-state networks and evaluated their functional connectivity in relation to both training effects. We found that the functional connectivity strength between the anterior Precuneus and the Occipital Pole Network was positively related to the attention modulated (i.e., training-specific) improvement. No such relationship was found for the overall improvement or for the other visual networks of interest. Our finding suggests that the anterior Precuneus plays a role in training-induced visual field improvements. The resting-state functional connectivity between the anterior Precuneus and the Occipital Pole Network may thus serve as an imaging-based biomarker that quantifies a patients potential capacity to direct spatial attention. This may help to identify hemianopia patients that are most likely to benefit from visual restitution training.
]]></description>
<dc:creator>Halbertsma, H. N.</dc:creator>
<dc:creator>Elshout, J. A.</dc:creator>
<dc:creator>Bergsma, D. P.</dc:creator>
<dc:creator>Norris, D. G.</dc:creator>
<dc:creator>Cornelissen, F. W.</dc:creator>
<dc:creator>van den Berg, A. V.</dc:creator>
<dc:creator>Haak, K. V.</dc:creator>
<dc:date>2020-05-15</dc:date>
<dc:identifier>doi:10.1101/2020.05.14.050310</dc:identifier>
<dc:title><![CDATA[Functional Connectivity of the Precuneus Reflects Effectiveness of Visual Restitution Training in Chronic Hemianopia]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-05-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.05.12.090175v1?rss=1">
<title>
<![CDATA[
Comparing fMRI responses measured at 3 versus 7 Tesla across human cortex, striatum, and brainstem 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.05.12.090175v1?rss=1"
</link>
<description><![CDATA[
Significant progress has been made in ultra-high field functional magnetic resonance imaging (fMRI) at 7 Tesla (T). While fMRI at 7 T promises a general increase in sensitivity compared to lower field strengths, the benefits may be most pronounced for specific applications. The current study aimed to evaluate the relative benefit of 7 T over 3 T fMRI for the assessment of task-evoked fMRI responses in different brain regions. We compared the amplitude of task-evoked responses between 3 T and 7 T measured from the same human participants. Participants performed a challenging random dot motion discrimination task with delayed monetary feedback, which animal physiology has linked to several cortical and subcortical structures including extrastriate (dorsal) visual cortical areas, the striatum, and the brainstem including dopaminergic midbrain nuclei. We quantified the evoked fMRI responses in each of these brain regions during the decision interval and the post-feedback interval of the task, and compared them between brain regions and field strengths. The dependence of response amplitudes on field strength during the decision interval differed between cortical, striatal, and brainstem regions, with a generally bigger 7 T vs. 3 T benefit in subcortical (in particular brainstem) structures. We also found stronger differential responses during easy than hard decisions at 7 T for the dopaminergic nuclei, possibly reflecting reward expectation. Our results demonstrate the potential of 7 T fMRI for illuminating the contribution of small brainstem nuclei to the orchestration of cognitive computations in the human brain.

HighlightsO_LIWe compared 7 T to 3 T fMRI during perceptual decision-making under uncertainty.
C_LIO_LIDifferences between 7 T and 3 T evoked responses and tSNR varied across the brain.
C_LIO_LIEvoked responses in dopaminergic brainstem nuclei were bigger at 7 T than 3 T.
C_LIO_LIThe responses of dopaminergic nuclei are consistent with reward expectation.
C_LIO_LIResults highlight the potential of 7 T fMRI for imaging small brainstem nuclei.
C_LI
]]></description>
<dc:creator>Colizoli, O.</dc:creator>
<dc:creator>de Gee, J. W.</dc:creator>
<dc:creator>van der Zwaag, W.</dc:creator>
<dc:creator>Donner, T. H.</dc:creator>
<dc:date>2020-05-14</dc:date>
<dc:identifier>doi:10.1101/2020.05.12.090175</dc:identifier>
<dc:title><![CDATA[Comparing fMRI responses measured at 3 versus 7 Tesla across human cortex, striatum, and brainstem]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-05-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/533513v1?rss=1">
<title>
<![CDATA[
Yellow strawberries and red bananas: The influence of object-colour knowledge on emerging object representations in the brain 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/533513v1?rss=1"
</link>
<description><![CDATA[
The ability to rapidly and accurately recognise complex objects is a crucial function of the human visual system. To recognise an object, we need to bind incoming visual features such as colour and form together into cohesive neural representations and integrate these with our pre-existing knowledge about the world. For some objects, typical colour is a central feature for recognition; for example, a banana is typically yellow. Here, we applied multivariate pattern analysis on time-resolved neuroimaging (magnetoencephalography) data to examine how object-colour knowledge affects emerging object representations over time. Our results from 20 participants (11 female) show that the typicality of object-colour combinations influences object representations, although not at the initial stages of object and colour processing. We find evidence that colour decoding peaks later for atypical object-colour combinations in comparison to typical object-colour combinations, illustrating the interplay between processing incoming object features and stored object-knowledge. Taken together, these results provide new insights into the integration of incoming visual information with existing conceptual object knowledge.

Significance StatementTo recognise objects, we have to be able to bind object features such as colour and shape into one coherent representation and compare it to stored object knowledge. The magnetoencephalography data presented here provide novel insights about the integration of incoming visual information with our knowledge about the world. Using colour as a model to understand the interaction between seeing and knowing, we show that there is a unique pattern of brain activity for congruently coloured objects (e.g., a yellow banana) relative to incongruently coloured objects (e.g., a red banana). This effect of object-colour knowledge only occurs after single object features are processed, demonstrating that conceptual knowledge is accessed relatively late in the visual processing hierarchy.
]]></description>
<dc:creator>Teichmann, L.</dc:creator>
<dc:creator>Quek, G. L.</dc:creator>
<dc:creator>Robinson, A.</dc:creator>
<dc:creator>Grootswagers, T.</dc:creator>
<dc:creator>Carlson, T.</dc:creator>
<dc:creator>Rich, A.</dc:creator>
<dc:date>2019-01-30</dc:date>
<dc:identifier>doi:10.1101/533513</dc:identifier>
<dc:title><![CDATA[Yellow strawberries and red bananas: The influence of object-colour knowledge on emerging object representations in the brain]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-01-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.05.08.083758v1?rss=1">
<title>
<![CDATA[
Differential functional neural circuitry behind autism subtypes with marked imbalance between social-communicative and restricted repetitive behavior symptom domains 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.05.08.083758v1?rss=1"
</link>
<description><![CDATA[
Social-communication (SC) and restricted repetitive behaviors (RRB) are autism diagnostic symptom domains. SC and RRB severity can markedly differ within and between individuals and may be underpinned by different neural circuitry and genetic mechanisms. Modeling SC-RRB balance could help identify how neural circuitry and genetic mechanisms map onto such phenotypic heterogeneity. Here we developed a phenotypic stratification model that makes highly accurate (97-99%) out-of-sample SC=RRB, SC>RRB, and RRB>SC subtype predictions. Applying this model to resting state fMRI data from the EU-AIMS LEAP dataset (n=509), we find that while the phenotypic subtypes share many commonalities in terms of intrinsic functional connectivity, they also show replicable differences within some networks compared to a typically-developing group (TD). Specifically, the somatomotor network is hypoconnected with perisylvian circuitry in SC>RRB and visual association circuitry in SC=RRB. The SC=RRB subtype show hyperconnectivity between medial motor and anterior salience circuitry. Genes that are highly expressed within these networks show a differential enrichment pattern with known autism-associated genes, indicating that such circuits are affected by differing autism-associated genomic mechanisms. These results suggest that SC-RRB imbalance subtypes share many commonalities, but also express subtle differences in functional neural circuitry and the genomic underpinnings behind such circuitry.
]]></description>
<dc:creator>Bertelsen, N.</dc:creator>
<dc:creator>Landi, I.</dc:creator>
<dc:creator>Bethlehem, R. A. I.</dc:creator>
<dc:creator>Seidlitz, J.</dc:creator>
<dc:creator>Busuoli, E. M.</dc:creator>
<dc:creator>Mandelli, V.</dc:creator>
<dc:creator>Satta, E.</dc:creator>
<dc:creator>Trakoshis, S.</dc:creator>
<dc:creator>Auyeung, B.</dc:creator>
<dc:creator>Kundu, P.</dc:creator>
<dc:creator>Loth, E.</dc:creator>
<dc:creator>Dumas, G.</dc:creator>
<dc:creator>Baumeister, S.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>Bolte, S.</dc:creator>
<dc:creator>Bourgeron, T.</dc:creator>
<dc:creator>Charman, T.</dc:creator>
<dc:creator>Durston, S.</dc:creator>
<dc:creator>Ecker, C.</dc:creator>
<dc:creator>Holt, R.</dc:creator>
<dc:creator>Johnson, M. H.</dc:creator>
<dc:creator>Jones, E. J. H.</dc:creator>
<dc:creator>Mason, L.</dc:creator>
<dc:creator>Meyer-Lindenberg, A.</dc:creator>
<dc:creator>Moessnang, C.</dc:creator>
<dc:creator>Oldehinkel, M.</dc:creator>
<dc:creator>Persico, A.</dc:creator>
<dc:creator>Tillmann, J.</dc:creator>
<dc:creator>Williams, S. C. R.</dc:creator>
<dc:creator>Spooren, W.</dc:creator>
<dc:creator>Murphy, D. G. M.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>EU-AIMS LEAP group,</dc:creator>
<dc:creator>Baron-Cohen, S.</dc:creator>
<dc:creator>Lai, M.-C.</dc:creator>
<dc:creator>Lombardo, M. V.</dc:creator>
<dc:date>2020-05-10</dc:date>
<dc:identifier>doi:10.1101/2020.05.08.083758</dc:identifier>
<dc:title><![CDATA[Differential functional neural circuitry behind autism subtypes with marked imbalance between social-communicative and restricted repetitive behavior symptom domains]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-05-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/702340v1?rss=1">
<title>
<![CDATA[
Loss of acid sphingomyelinase ameliorates disease progression in a vertebrate model of Glucocerebrosidase deficiency 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/702340v1?rss=1"
</link>
<description><![CDATA[
The additive effect of genetic risk variants on overall disease risk is a plausible but frequently unproven hypothesis. To test this hypothesis, we assessed the biological effect of combined glucocerebrosidase (GCase) and acid sphingomyelinase (ASM) deficiency. Variants in both glucocerebrosidase1 (GBA1) and sphingomyelinase (SMPD1) are genetic risk factors for Parkinsons disease. Unexpectedly, ASM deficiency resulted in normalized behaviour and prolonged survival in gba1-/-;smpd1-/- double-mutant zebrafish compared to gba1-/-. RNAseq-based pathway analysis confirmed a profound rescue of neuronal function and intracellular homeostasis. We identified complete reciprocal rescue of mitochondrial respiratory chain function and abolished lipid membrane oxidation in gba1-/-;smpd1-/- compared to gba1-/- or smpd1-/- as the underlying rescue mechanism. Complementing in vitro experiments demonstrated an unexpected reduction of -synuclein levels in human cell lines with combined GCase and ASM deficiency. Our study highlights the importance of functional validation for any putative interactions between genetic risk factors and their overall effect on disease-relevant mechanisms rather than readily assuming an additive effect.

SummaryThe additive effect of genetic risk variants on disease risk is a popular but typically unproven hypothesis. We investigated this hypothesis mechanistically for Parkinsons disease risk factors and provide evidence of an unexpected rescue effect on neuronal function and survival.
]]></description>
<dc:creator>Keatinge, M.</dc:creator>
<dc:creator>Gegg, M.</dc:creator>
<dc:creator>Watson, L.</dc:creator>
<dc:creator>Mortiboys, H.</dc:creator>
<dc:creator>Bui, H.</dc:creator>
<dc:creator>van Leens, A.</dc:creator>
<dc:creator>Lefeber, D.</dc:creator>
<dc:creator>MacDonald, R.</dc:creator>
<dc:creator>Schapira, A.</dc:creator>
<dc:creator>Bandmann, O.</dc:creator>
<dc:date>2019-07-14</dc:date>
<dc:identifier>doi:10.1101/702340</dc:identifier>
<dc:title><![CDATA[Loss of acid sphingomyelinase ameliorates disease progression in a vertebrate model of Glucocerebrosidase deficiency]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-07-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.05.07.082479v1?rss=1">
<title>
<![CDATA[
Methods for quantitative susceptibility and R2* mapping in whole post-mortem brains at 7T 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.05.07.082479v1?rss=1"
</link>
<description><![CDATA[
Susceptibility weighted magnetic resonance imaging (MRI) is sensitive to the local concentration of iron and myelin. Here, we describe a robust image processing pipeline for quantitative susceptibility mapping (QSM) and R2* mapping of fixed post-mortem, whole-brain data. Using this pipeline, we compare the resulting quantitative maps in brains from patients with amyotrophic lateral sclerosis (ALS) and controls, with validation against iron and myelin histology.

Twelve post-mortem brains were scanned with a multi-echo gradient echo sequence at 7T, from which susceptibility and R2* maps were generated. Semi-quantitative histological analysis for ferritin (the principal iron storage protein) and myelin proteolipid protein was performed in the primary motor, anterior cingulate and visual cortices.

Magnetic susceptibility and R2* values in primary motor cortex were higher in ALS compared to control brains. Magnetic susceptibility and R2* showed positive correlations with both myelin and ferritin estimates from histology. Four out of nine ALS brains exhibited clearly visible hyperintense susceptibility and R2* values in the primary motor cortex.

Our results demonstrate the potential for MRI-histology studies in whole, fixed post-mortem brains to investigate the biophysical source of susceptibility weighted MRI signals in neurodegenerative diseases like ALS.
]]></description>
<dc:creator>Wang, C.</dc:creator>
<dc:creator>Foxley, S.</dc:creator>
<dc:creator>Ansorge, O.</dc:creator>
<dc:creator>Bangerter-Christensen, S.</dc:creator>
<dc:creator>Chiew, M.</dc:creator>
<dc:creator>Leonte, A.</dc:creator>
<dc:creator>Menke, R. A.</dc:creator>
<dc:creator>Mollink, J.</dc:creator>
<dc:creator>Pallebage-Gamarallage, M.</dc:creator>
<dc:creator>Turner, M. R.</dc:creator>
<dc:creator>Miller, K. L.</dc:creator>
<dc:creator>Tendler, B. C.</dc:creator>
<dc:date>2020-05-08</dc:date>
<dc:identifier>doi:10.1101/2020.05.07.082479</dc:identifier>
<dc:title><![CDATA[Methods for quantitative susceptibility and R2* mapping in whole post-mortem brains at 7T]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-05-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.05.05.077834v1?rss=1">
<title>
<![CDATA[
Cortical Thickness Trajectories across the Lifespan: Data from 17,075 healthy individuals aged 3-90 years 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.05.05.077834v1?rss=1"
</link>
<description><![CDATA[
Delineating age-related cortical trajectories in healthy individuals is critical given the association of cortical thickness with cognition and behaviour. Previous research has shown that deriving robust estimates of age-related brain morphometric changes requires large-scale studies. In response, we conducted a large-scale analysis of cortical thickness in 17,075 individuals aged 3-90 years by pooling data through the Lifespan Working group of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium. We used fractional polynomial (FP) regression to characterize age-related trajectories in cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma (LMS) method. Inter-individual variability was estimated using meta-analysis and one-way analysis of variance. Overall, cortical thickness peaked in childhood and had a steep decrease during the first 2-3 decades of life; thereafter, it showed a gradual monotonic decrease which was steeper in men than in women particularly in middle-life. Notable exceptions to this general pattern were entorhinal, temporopolar and anterior cingulate cortices. Inter-individual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results reconcile uncertainties about age-related trajectories of cortical thickness; the centile values provide estimates of normative variance in cortical thickness, and may assist in detecting abnormal deviations in cortical thickness, and associated behavioural, cognitive and clinical outcomes.
]]></description>
<dc:creator>Frangou, S.</dc:creator>
<dc:creator>Modabbernia, A.</dc:creator>
<dc:creator>Doucet, G. E.</dc:creator>
<dc:creator>Papachristou, E.</dc:creator>
<dc:creator>Williams, S. C.</dc:creator>
<dc:creator>Agartz, I.</dc:creator>
<dc:creator>Aghajani, M.</dc:creator>
<dc:creator>Akudjedu, T. N.</dc:creator>
<dc:creator>Albajes-Eizagirre, A.</dc:creator>
<dc:creator>Alnaes, D.</dc:creator>
<dc:creator>Alpert, K. I.</dc:creator>
<dc:creator>Andersson, M.</dc:creator>
<dc:creator>Andreasen, N.</dc:creator>
<dc:creator>Andreassen, O. A.</dc:creator>
<dc:creator>Asherson, P.</dc:creator>
<dc:creator>Banaschewski, T.</dc:creator>
<dc:creator>Bargallo, N.</dc:creator>
<dc:creator>Baumeister, S.</dc:creator>
<dc:creator>Baur-Streubel, R.</dc:creator>
<dc:creator>Bertolino, A.</dc:creator>
<dc:creator>Bonvino, A.</dc:creator>
<dc:creator>Boomsma, D. I.</dc:creator>
<dc:creator>Borgwardt, S.</dc:creator>
<dc:creator>Bourque, J.</dc:creator>
<dc:creator>Brandeis, D.</dc:creator>
<dc:creator>Breier, A.</dc:creator>
<dc:creator>Brodaty, H.</dc:creator>
<dc:creator>Brouwer, R. M.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Busatto, G. F.</dc:creator>
<dc:creator>Buckner, R. L.</dc:creator>
<dc:creator>Calhoun, V.</dc:creator>
<dc:creator>Canales-Rodriguez, E. J.</dc:creator>
<dc:creator>Cannon, D. M.</dc:creator>
<dc:creator>Caseras, X.</dc:creator>
<dc:creator>Castellanos, F. X.</dc:creator>
<dc:creator>Cervenka, S.</dc:creator>
<dc:creator>Chaim-Avancini, T.</dc:creator>
<dc:date>2020-05-07</dc:date>
<dc:identifier>doi:10.1101/2020.05.05.077834</dc:identifier>
<dc:title><![CDATA[Cortical Thickness Trajectories across the Lifespan: Data from 17,075 healthy individuals aged 3-90 years]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-05-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.05.05.079475v1?rss=1">
<title>
<![CDATA[
Subcortical Volume Trajectories across the Lifespan: Data from 18,605 healthy individuals aged 3-90 years 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.05.05.079475v1?rss=1"
</link>
<description><![CDATA[
Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalised on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine the age-related morphometric trajectories of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum early in life; the volume of the basal ganglia showed a gradual monotonic decline thereafter while the volumes of the thalamus, amygdala and the hippocampus remained largely stable (with some degree of decline in thalamus) until the sixth decade of life followed by a steep decline thereafter. The lateral ventricles showed a trajectory of continuous enlargement throughout the lifespan. Significant age-related increase in inter-individual variability was found for the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to derive risk predictions for the early identification of diverse clinical phenotypes.
]]></description>
<dc:creator>Dima, D.</dc:creator>
<dc:creator>Papachristou, E.</dc:creator>
<dc:creator>Modabbernia, A.</dc:creator>
<dc:creator>Doucet, G. E.</dc:creator>
<dc:creator>Agartz, I.</dc:creator>
<dc:creator>Aghajani, M.</dc:creator>
<dc:creator>Akudjedu, T. N.</dc:creator>
<dc:creator>Albajes-Eizagirre, A.</dc:creator>
<dc:creator>Alnaes, D.</dc:creator>
<dc:creator>Alpert, K. I.</dc:creator>
<dc:creator>Andersson, M.</dc:creator>
<dc:creator>Andreasen, N.</dc:creator>
<dc:creator>Andreassen, O. A.</dc:creator>
<dc:creator>Asherson, P.</dc:creator>
<dc:creator>Banaschewski, T.</dc:creator>
<dc:creator>Bargallo, N.</dc:creator>
<dc:creator>Baumeister, S.</dc:creator>
<dc:creator>Baur-Streubel, R.</dc:creator>
<dc:creator>Bertolino, A.</dc:creator>
<dc:creator>Bonvino, A.</dc:creator>
<dc:creator>Boomsma, D. I.</dc:creator>
<dc:creator>Borgwardt, S.</dc:creator>
<dc:creator>Bourque, J.</dc:creator>
<dc:creator>Brandeis, D.</dc:creator>
<dc:creator>Breier, A.</dc:creator>
<dc:creator>Brodaty, H.</dc:creator>
<dc:creator>Brouwer, R. M.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Busatto, G. F.</dc:creator>
<dc:creator>Buckner, R. L.</dc:creator>
<dc:creator>Calhoun, V.</dc:creator>
<dc:creator>Canales-Rodriguez, E. J.</dc:creator>
<dc:creator>Cannon, D. M.</dc:creator>
<dc:creator>Caseras, X.</dc:creator>
<dc:creator>Castellanos, F. X.</dc:creator>
<dc:creator>Cervenka, S.</dc:creator>
<dc:creator>Chaim-Avancini, T. M.</dc:creator>
<dc:creator>Ching, C. R.</dc:creator>
<dc:creator>Cl</dc:creator>
<dc:date>2020-05-07</dc:date>
<dc:identifier>doi:10.1101/2020.05.05.079475</dc:identifier>
<dc:title><![CDATA[Subcortical Volume Trajectories across the Lifespan: Data from 18,605 healthy individuals aged 3-90 years]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-05-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.05.07.082453v1?rss=1">
<title>
<![CDATA[
Cadherin-13 is a critical regulator of GABAergic modulation in human stem cell derived neuronal networks 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.05.07.082453v1?rss=1"
</link>
<description><![CDATA[
Activity in the healthy brain relies on concerted interplay of excitation (E) and inhibition (I) via balanced synaptic communication between glutamatergic and GABAergic neurons. A growing number of studies imply that disruption of this E/I balance is a commonality in many brain disorders, however, obtaining mechanistic insight into these disruptions, with translational value for the human patient, has typically been hampered by methodological limitations. Cadherin-13 (CDH13) has strongly been associated to attention-deficit/hyperactivity disorder and comorbid disorders such as autism and schizophrenia. CDH13 localises at inhibitory presynapses, specifically of parvalbumin (PV) and somatostatin (SST) expressing GABAergic neurons. However, the mechanism by which CDH13 regulates the function of inhibitory synapses in human neurons remains unknown. Starting from human induced pluripotent stem cells, we established a robust method to generate a homogenous population of SST and PV expressing GABAergic neurons (iGABA) in vitro, and co-cultured these with glutamatergic neurons at defined E/I ratios on micro-electrode arrays. We identified functional network parameters that are most reliably affected by GABAergic modulation as such, and through alterations of E/I balance by reduced expression of CDH13 in iGABAs. We found that CDH13-deficiency in iGABAs decreased E/I balance by means of increased inhibition. Moreover, CDH13 interacts with Integrin-{beta}1 and Integrin-{beta}3, which play opposite roles in the regulation of inhibitory synaptic strength via this interaction. Taken together, this model allows for standardized investigation of the E/I balance in a human neuronal background and can be deployed to dissect the cell-type specific contribution of disease genes to the E/I balance.
]]></description>
<dc:creator>Mossink, B.</dc:creator>
<dc:creator>van Rhijn, J.-R.</dc:creator>
<dc:creator>Wang, S.</dc:creator>
<dc:creator>van Hugte, E.</dc:creator>
<dc:creator>Linda, K.</dc:creator>
<dc:creator>Bak, J.</dc:creator>
<dc:creator>Verboven, A. H.</dc:creator>
<dc:creator>Selten, M.</dc:creator>
<dc:creator>Anania, A.</dc:creator>
<dc:creator>Jansen, S.</dc:creator>
<dc:creator>Keller, J. M.</dc:creator>
<dc:creator>Klein Gunnewiek, T.</dc:creator>
<dc:creator>Schoenmaker, C.</dc:creator>
<dc:creator>Oudakker, A.</dc:creator>
<dc:creator>Frega, M.</dc:creator>
<dc:creator>van Bokhoven, H.</dc:creator>
<dc:creator>Schubert, D.</dc:creator>
<dc:creator>Nadif Kasri, N.</dc:creator>
<dc:date>2020-05-07</dc:date>
<dc:identifier>doi:10.1101/2020.05.07.082453</dc:identifier>
<dc:title><![CDATA[Cadherin-13 is a critical regulator of GABAergic modulation in human stem cell derived neuronal networks]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-05-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/755603v1?rss=1">
<title>
<![CDATA[
An integrated analysis across separate task domains reveals a lack of common processing in the ADHD brain 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/755603v1?rss=1"
</link>
<description><![CDATA[
Attention-Deficit/Hyperactivity Disorder (ADHD) is associated with altered functioning in multiple cognitive domains and neural networks. This paper offers an overarching biological perspective across these. We applied a novel strategy that extracts functional connectivity modulations in the brain across one (Psingle), two (Pmix) or three (Pall) cognitive tasks and compared the pattern of modulations between participants with ADHD (n-89), unaffected siblings (n=93) and controls (n=84; total N=266; age range=8-27 years).

Participants with ADHD had significantly fewer Pall connections (modulated regardless of task), but significantly more task-specific (Psingle) connectivity modulations than the other groups. The amplitude of these Psingle modulations was significantly higher in ADHD. Unaffected siblings showed a similar degree of Pall connectivity modulation as controls but a similar degree of Psingle connectivity modulation as ADHD probands. Pall connections were strongly reproducible at the individual level in controls, but showed marked heterogeneity in both participants with ADHD and unaffected siblings.

The pattern of reduced task-generic and increased task-specific connectivity modulations in ADHD may be interpreted as reflecting a less efficient functional brain architecture due to a reduction in the ability to generalise processing pathways across multiple cognitive domains. The higher amplitude of unique task-specific connectivity modulations in ADHD may index a more "effortful" coping strategy. Unaffected siblings displayed a task connectivity profile in between that of controls and ADHD probands, supporting an endophenotype view. Our approach provides a new perspective on the core neural underpinnings of ADHD.
]]></description>
<dc:creator>Chauvin, R. J.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Oldehinkel, M.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Hartman, C.</dc:creator>
<dc:creator>Heslenfeld, D. J.</dc:creator>
<dc:creator>Hoekstra, P. J.</dc:creator>
<dc:creator>Oosterlaan, J.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>Mennes, M.</dc:creator>
<dc:date>2019-09-05</dc:date>
<dc:identifier>doi:10.1101/755603</dc:identifier>
<dc:title><![CDATA[An integrated analysis across separate task domains reveals a lack of common processing in the ADHD brain]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.03.26.007559v1?rss=1">
<title>
<![CDATA[
Action enhances predicted touch 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.03.26.007559v1?rss=1"
</link>
<description><![CDATA[
It is widely believed that predicted tactile action outcomes are perceptually attenuated. The present experiments determined whether predictive mechanisms always generate attenuation, or instead can enhance perception - as typically observed in sensory cognition domains outside of action. We manipulated probabilistic expectations in a paradigm often used to demonstrate tactile attenuation. Participants produced actions and subsequently rated the intensity of forces on a passive finger. Experiment 1 confirmed previous findings that action outcomes are perceived less intensely than passive stimulation, but demonstrated more intense perception when active finger stimulation was removed. Experiments 2 and 3 manipulated prediction explicitly and found that expected touch during action is perceived more intensely than unexpected touch. Computational modelling suggested that expectations increase the gain afforded to expected tactile signals. These findings challenge a central tenet of prominent motor control theories and demonstrate that sensorimotor predictions do not exhibit a qualitatively distinct influence on tactile perception.

Statement of RelevancePerception of expected action outcomes is thought to be attenuated. Such a mechanism may be adaptive because surprising inputs are more useful - e.g., signalling the need to take new courses of action - and is thought to explain why we cannot tickle ourselves and unusual aspects of action and awareness in clinical populations. However, theories outside of action purport that predicted events are perceptually facilitated, allowing us to generate largely accurate representations of our noisy sensory world. We do not know whether action predictions really alter perception differently from other predictions because different manipulations have been performed. Here we perform similar manipulations and demonstrate that action predictions can enhance, rather than attenuate, touch. We thereby demonstrate that action predictions may not have a qualitatively distinct influence on perception, such that we must re-examine theories concerning how predictions influence perception across domains and clinical theories based upon their assumptions.
]]></description>
<dc:creator>Thomas, E. R.</dc:creator>
<dc:creator>Yon, D.</dc:creator>
<dc:creator>de Lange, F. P.</dc:creator>
<dc:creator>Press, C.</dc:creator>
<dc:date>2020-03-26</dc:date>
<dc:identifier>doi:10.1101/2020.03.26.007559</dc:identifier>
<dc:title><![CDATA[Action enhances predicted touch]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-03-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/708552v1?rss=1">
<title>
<![CDATA[
Common neural and transcriptional correlates of inhibitory control across emotion, memory, and response inhibition 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/708552v1?rss=1"
</link>
<description><![CDATA[
Inhibitory control is crucial for regulating emotions, and it may also enable memory control. However, evidence for their shared neurobiological correlates is limited. Here, we report meta-analyses of neuroimaging studies on emotion regulation, or memory control, and link neural commonalities to transcriptional commonalities using the Allen Human Brain Atlas (AHBA). Based on 95 fMRI studies, we reveal a role of the right inferior parietal lobule embedded in a frontal-parietal-insular network during emotion and memory control, which is similarly recruited during response inhibition. These co-activation patterns also overlap with the networks associated with "inhibition", "cognitive control", and "working memory" when consulting the Neurosynth. Using the AHBA, we demonstrate that emotion and memory control-related brain activity patterns are associated with transcriptional profiles of a specific set of "inhibition-related" genes. Gene ontology enrichment analysis of these "inhibition-related" genes reveal associations with the neuronal transmission and risk for major psychiatric disorders as well as seizures and alcoholic dependence. In summary, this study identified a neural network and a set of genes associated with inhibitory control across emotion regulation, memory control. These findings facilitate our understanding of the neurobiological correlates of inhibitory control and may contribute to the development of novel brain stimulation and pharmacological interventions.
]]></description>
<dc:creator>Liu, W.</dc:creator>
<dc:creator>Peeters, N.</dc:creator>
<dc:creator>Fernandez, G.</dc:creator>
<dc:creator>Kohn, N.</dc:creator>
<dc:date>2019-07-19</dc:date>
<dc:identifier>doi:10.1101/708552</dc:identifier>
<dc:title><![CDATA[Common neural and transcriptional correlates of inhibitory control across emotion, memory, and response inhibition]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-07-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/868406v1?rss=1">
<title>
<![CDATA[
Asymptotic limits of sensorimotor adaptation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/868406v1?rss=1"
</link>
<description><![CDATA[
After extended practice, motor adaptation reaches a limit in which learning appears to stop, despite the fact that residual errors persist. What prevents the brain from eliminating the residual errors? Here we found that the adaptation limit was causally dependent on the second order statistics of the perturbation; when variance was high, learning was impaired and large residual errors persisted. However, when learning relied solely on explicit strategy, both the adaptation limit and its dependence on perturbation variability disappeared. In contrast, when learning depended entirely, or in part on implicit learning, residual errors developed. Residual errors in implicit performance were caused by variance-dependent modifications to error sensitivity, not forgetting. These observations are consisted with a model of learning in which the implicit system becomes more sensitive to error when errors are consistent, but forgets this memory of errors over time. Thus, residual errors in motor adaptation are a signature of the implicit learning system, caused by an error sensitivity that depends on the history of past errors.
]]></description>
<dc:creator>Albert, S. T.</dc:creator>
<dc:creator>Jang, J.</dc:creator>
<dc:creator>Sheahan, H. R.</dc:creator>
<dc:creator>Teunissen, L.</dc:creator>
<dc:creator>Vandevoorde, K.</dc:creator>
<dc:creator>Shadmehr, R.</dc:creator>
<dc:date>2019-12-08</dc:date>
<dc:identifier>doi:10.1101/868406</dc:identifier>
<dc:title><![CDATA[Asymptotic limits of sensorimotor adaptation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-12-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/804641v1?rss=1">
<title>
<![CDATA[
XTRACT - Standardised protocols for automated tractography and connectivity blueprints in the human and macaque brain 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/804641v1?rss=1"
</link>
<description><![CDATA[
We present a new software package with a library of standardised tractography protocols devised for the robust automated extraction of white matter tracts both in the human and the macaque brain. Using in vivo data from the Human Connectome Project (HCP) and the UK Biobank and ex vivo data for the macaque brain datasets, we obtain white matter atlases, as well as atlases for tract endpoints on the white-grey matter boundary, for both species. We illustrate that our protocols are robust against data quality, generalisable across two species and reflect the known anatomy. We further demonstrate that they capture inter-subject variability by preserving tract lateralisation in humans and tract similarities stemming from twinship in the HCP cohort. Our results demonstrate that the presented toolbox will be useful for generating imaging-derived features in large cohorts, and in facilitating comparative neuroanatomy studies. The software, tractography protocols, and atlases are publicly released through FSL, allowing users to define their own tractography protocols in a standardised manner, further contributing to open science.
]]></description>
<dc:creator>Warrington, S.</dc:creator>
<dc:creator>Bryant, K. L.</dc:creator>
<dc:creator>Khrapitchev, A. A.</dc:creator>
<dc:creator>Sallet, J.</dc:creator>
<dc:creator>Charquero-Ballester, M.</dc:creator>
<dc:creator>Douaud, G.</dc:creator>
<dc:creator>Jbabdi, S.</dc:creator>
<dc:creator>Mars, R. B.</dc:creator>
<dc:creator>Sotiropoulos, S. N.</dc:creator>
<dc:date>2019-10-15</dc:date>
<dc:identifier>doi:10.1101/804641</dc:identifier>
<dc:title><![CDATA[XTRACT - Standardised protocols for automated tractography and connectivity blueprints in the human and macaque brain]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.05.01.070540v1?rss=1">
<title>
<![CDATA[
An altered cognitive strategy associated with reduction of synaptic inhibition in the prefrontal cortex after social play deprivation in rats 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.05.01.070540v1?rss=1"
</link>
<description><![CDATA[
Sensory driven activity during early life is critical for setting up the proper connectivity of the sensory cortices. Here we ask if social play behavior, a particular form of social interaction that is highly abundant during post-weaning development, is equally important for setting up connections in the developing prefrontal cortex (PFC). Young rats were deprived from social play with peers for 3 weeks during the period in life when social play behavior normally peaks (P21-42; SPD rats), followed by resocialization until adulthood. We recorded synaptic currents in L5 cells in slices from medial PFC of adult SPD and control rats and observed that inhibitory synaptic currents were reduced in SPD slices, while excitatory synaptic currents were unaffected. This was associated with a decrease in perisomatic inhibitory synapses from parvalbumin-positive GABAergic cells. In parallel experiments, adult SPD rats achieved more reversals in a probabilistic reversal learning task (PRL), which depends on the integrity of the PFC. They appeared to use a different cognitive strategy than controls. One hour of intense play during SPD did not prevent the decrease in inhibitory synaptic inputs and had only a limited effect on behavioral outcomes in the PRL. Our data demonstrate the importance of unrestricted social play for the development of inhibitory synapses in the PFC and cognitive skills in adulthood.
]]></description>
<dc:creator>Omrani, A.</dc:creator>
<dc:creator>Bijlsma, A.</dc:creator>
<dc:creator>Spoelder, M.</dc:creator>
<dc:creator>Verharen, J. P. H.</dc:creator>
<dc:creator>Bauer, L.</dc:creator>
<dc:creator>Cornelis, C.</dc:creator>
<dc:creator>van Dorland, R.</dc:creator>
<dc:creator>Vanderschuren, L. J. M. J.</dc:creator>
<dc:creator>Wierenga, C. J.</dc:creator>
<dc:date>2020-05-03</dc:date>
<dc:identifier>doi:10.1101/2020.05.01.070540</dc:identifier>
<dc:title><![CDATA[An altered cognitive strategy associated with reduction of synaptic inhibition in the prefrontal cortex after social play deprivation in rats]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-05-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.04.30.070318v1?rss=1">
<title>
<![CDATA[
The influence of auditory attention on rhythmic speech entrainment 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.04.30.070318v1?rss=1"
</link>
<description><![CDATA[
Language comprehension relies on integrating words into progressively more complex structures, like phrases and sentences. This hierarchical structure building is reflected in rhythmic neural activity across multiple timescales in E/MEG (Ding et al., 2016, 2017).

How does selective attention across levels of the hierarchy influence the expression of these rhythms?

We investigated these questions in an EEG study of 72 healthy human volunteers listening to streams of monosyllabic isochronous English words that were either unrelated (scrambled condition) or composed of four-word-sequences building meaningful sentences (sentential condition). Importantly, there were no physical cues between four-word-sentences but boundaries were marked by syntactic structure and thematic role assignment. Participants were divided into three attention groups: from passive listening (passive group) to attending to individual words (word group) or sentences (sentence group). The passive and word group were naive to the sentential structure of the stimulus material, while the sentence group were not.

We found significant entrainment at word- and sentence rate across all three groups, with sentence entrainment linked to left middle temporal gyrus and right superior temporal gyrus. Goal-directed attention to words did not enhance word-rate-entrainment suggesting that word entrainment relies on largely automatic mechanisms. Importantly, goal-directed attention to sentences relative to words significantly increased sentence-rate-entrainment over left inferior frontal gyrus. This attentional modulation of rhythmic EEG activity at the sentential level highlights the role of attention in integrating individual words into complex linguistic structures.

SIGNIFICANCE STATEMENTNeural activity is known to entrain to physical characteristics of auditory stimuli. However, entrainment also occurs with structures lacking physical cues but rather require comprehension of the stimulus meaning - for example, entrainment to sentences in speech even without acoustic gaps separating these higher linguistic structures.

We investigated how goal-directed attention to low-level (words) and high-level (sentences) linguistic structures influences entrainment strength. Whilst sentence entrainment occurred independently of selective attention, it increased with goal-directed attention towards sentences. Conversely, no such attentional effect was found for word entrainment.

While goal-directed attention towards sentences strengthens entrainment, it is no prerequisite for it to occur, suggesting that low attentional effort is required for sentence comprehension, potentially reflecting the importance of speech in humans.
]]></description>
<dc:creator>Sokoliuk, R.</dc:creator>
<dc:creator>Degano, G.</dc:creator>
<dc:creator>Melloni, L.</dc:creator>
<dc:creator>Noppeney, U.</dc:creator>
<dc:creator>Cruse, D.</dc:creator>
<dc:date>2020-05-02</dc:date>
<dc:identifier>doi:10.1101/2020.04.30.070318</dc:identifier>
<dc:title><![CDATA[The influence of auditory attention on rhythmic speech entrainment]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-05-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.04.30.069989v1?rss=1">
<title>
<![CDATA[
Detecting neural state transitions underlying event segmentation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.04.30.069989v1?rss=1"
</link>
<description><![CDATA[
Segmenting perceptual experience into meaningful events is a key cognitive process that helps us make sense of what is happening around us in the moment, as well as helping us recall past events. Nevertheless, little is known about the underlying neural mechanisms of the event segmentation process. Recent work has suggested that event segmentation can be linked to regional changes in neural activity patterns. Accurate methods for identifying such activity changes are important to allow further investigation of the neural basis of event segmentation and its link to the temporal processing hierarchy of the brain. In this study, we introduce a new set of elegant and simple methods to study these mechanisms. We introduce a method for identifying the boundaries between neural states in a brain area and a complementary one for identifying the number of neural states. Furthermore, we present the results of a comprehensive set of simulations and analyses of empirical fMRI data to provide guidelines for reliable estimation of neural states and show that our proposed methods outperform the current state-of-the-art in the literature. This methodological innovation will allow researchers to make headway in investigating the neural basis of event segmentation and information processing during naturalistic stimulation.

HighlightsO_LIBoundaries between meaningful events are related to neural state transitions.
C_LIO_LINeural states are temporarily stable regional brain activity patterns.
C_LIO_LIWe introduce novel methods for data-driven detection of neural state boundaries.
C_LIO_LIThese methods can identify the location and the number of neural state boundaries.
C_LIO_LISimulations and empirical data support the reliability and validity of our methods.
C_LI
]]></description>
<dc:creator>Geerligs, L.</dc:creator>
<dc:creator>Güclü, U.</dc:creator>
<dc:creator>van Gerven, M.</dc:creator>
<dc:date>2020-05-02</dc:date>
<dc:identifier>doi:10.1101/2020.04.30.069989</dc:identifier>
<dc:title><![CDATA[Detecting neural state transitions underlying event segmentation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-05-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.04.29.067561v1?rss=1">
<title>
<![CDATA[
Durable memories and efficient neural coding through mnemonic training using the method of loci 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.04.29.067561v1?rss=1"
</link>
<description><![CDATA[
Mnemonic techniques, such as the method of loci, can powerfully boost memory. Here, we compared memory athletes ranked among the worlds top 50 in memory sports to mnemonics-naive controls. In a second study, participants completed a six-weeks memory training, working memory training, or no intervention. Behaviorally, memory training enhanced durable, longer-lasting memories. fMRI during encoding and recognition revealed task-based activation decreases in lateral prefrontal, as well as in parahippocampal and retrosplenial cortices in both memory athletes and participants after memory training, partly associated with better performance after four months. This was complemented by hippocampal-neocortical coupling during consolidation, which was stronger the more durable memories participants formed. Our findings are the first to demonstrate that mnemonic training boosts durable memory formation via decreased task-based activation and increased consolidation thereafter. This is in line with conceptual accounts of neural efficiency and highlights a complex interplay of neural processes critical for extraordinary memory.
]]></description>
<dc:creator>Wagner, I. C.</dc:creator>
<dc:creator>Konrad, B. N.</dc:creator>
<dc:creator>Schuster, P.</dc:creator>
<dc:creator>Weisig, S.</dc:creator>
<dc:creator>Repantis, D.</dc:creator>
<dc:creator>Ohla, K.</dc:creator>
<dc:creator>Kühn, S.</dc:creator>
<dc:creator>Fernandez, G.</dc:creator>
<dc:creator>Steiger, A.</dc:creator>
<dc:creator>Lamm, C.</dc:creator>
<dc:creator>Czisch, M.</dc:creator>
<dc:creator>Dresler, M.</dc:creator>
<dc:date>2020-04-30</dc:date>
<dc:identifier>doi:10.1101/2020.04.29.067561</dc:identifier>
<dc:title><![CDATA[Durable memories and efficient neural coding through mnemonic training using the method of loci]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-04-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.04.29.067454v1?rss=1">
<title>
<![CDATA[
Rapid invisible frequency tagging reveals nonlinear integration of auditory and visual semantic information 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.04.29.067454v1?rss=1"
</link>
<description><![CDATA[
During communication in real-life settings, the brain integrates information from auditory and visual modalities to form a unified percept of our environment. In the current magnetoencephalography (MEG) study, we used rapid invisible frequency tagging (RIFT) to generate steady-state evoked fields and investigated the integration of audiovisual information in a semantic context. We presented participants with videos of an actress uttering action verbs (auditory; tagged at 61 Hz) accompanied by a gesture (visual; tagged at 68 Hz, using a projector with a 1440 Hz refresh rate). Integration difficulty was manipulated by lower-order auditory factors (clear/degraded speech) and higher-order visual factors (congruent/incongruent gesture). We identified MEG spectral peaks at the individual (61/68 Hz) tagging frequencies. We furthermore observed a peak at the intermodulation frequency of the auditory and visually tagged signals (fvisual - fauditory = 7 Hz), specifically when lower-order integration was easiest because signal quality was optimal. This intermodulation peak is a signature of nonlinear audiovisual integration, and was strongest in left inferior frontal gyrus and left temporal regions; areas known to be involved in speech-gesture integration. The enhanced power at the intermodulation frequency thus reflects the ease of lower-order audiovisual integration and demonstrates that speech-gesture information interacts in higher-order language areas. Furthermore, we provide a proof-of-principle of the use of RIFT to study the integration of audiovisual stimuli, in relation to, for instance, semantic context.
]]></description>
<dc:creator>Drijvers, L.</dc:creator>
<dc:creator>Spaak, E.</dc:creator>
<dc:creator>Jensen, O.</dc:creator>
<dc:date>2020-04-30</dc:date>
<dc:identifier>doi:10.1101/2020.04.29.067454</dc:identifier>
<dc:title><![CDATA[Rapid invisible frequency tagging reveals nonlinear integration of auditory and visual semantic information]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-04-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.04.28.065474v1?rss=1">
<title>
<![CDATA[
Self-reported sleep problems are related to cortical thinning in aging but not memory decline and amyloid-β accumulation - results from the Lifebrain consortium 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.04.28.065474v1?rss=1"
</link>
<description><![CDATA[
BackgroundOlder persons with poor sleep are more likely to develop neurodegenerative disease, but the causality underlying this association is unclear. To move towards explanation, we examine whether sleep quality and quantity are similarly associated with brain changes across the adult lifespan.

MethodsAssociations between self-reported sleep parameters (Pittsburgh Sleep Quality Index;PSQI) and longitudinal cortical change were tested using five samples from the Lifebrain consortium (n=2205, 4363 MRIs, 18-92 years). Analyses were augmented by considering episodic memory change, gene expression from the Allen Human Brain Atlas, and amyloid-beta (A{beta}) accumulation (n=1980).

ResultsPSQI components sleep problems and low sleep quality were related to thinning of the right lateral temporal cortex. The association with sleep problems emerged after 60 years, especially in regions with high expression of genes related to oligodendrocytes and S1 pyramidal neurons. BMI and symptoms of depression had negligible effects. Sleep problems were neither related to longitudinal change in episodic memory function nor to A{beta} accumulation, suggesting that sleep-related cortical changes were independent of AD neuropathology and cognitive decline.

ConclusionWorse self-reported sleep in later adulthood was associated with more cortical thinning in regions of high expression of genes related to oligodendrocytes and S1 pyramidal neurons, but not to A{beta} accumulation or memory decline. The relationship to cortical brain change suggests that self-reported sleep parameters are relevant in lifespan studies, but small effect sizes, except for a few restricted regions, indicate that self-reported sleep is not a good biomarker of general cortical degeneration in healthy older adults.
]]></description>
<dc:creator>Fjell, A.</dc:creator>
<dc:creator>Sorensen, O.</dc:creator>
<dc:creator>Amlien, I. K.</dc:creator>
<dc:creator>Bartres-Faz, D.</dc:creator>
<dc:creator>Brandmaier, A.</dc:creator>
<dc:creator>Macia, D.</dc:creator>
<dc:creator>Buchmann, N.</dc:creator>
<dc:creator>Demuth, I.</dc:creator>
<dc:creator>Drevon, C. A.</dc:creator>
<dc:creator>Duzel, S.</dc:creator>
<dc:creator>Ebmeier, K.</dc:creator>
<dc:creator>Ghisletta, P.</dc:creator>
<dc:creator>Idland, A.-V.</dc:creator>
<dc:creator>Kietzmann, T.</dc:creator>
<dc:creator>Kievit, R. A.</dc:creator>
<dc:creator>Kuhn, S. A.</dc:creator>
<dc:creator>Lindenberger, U.</dc:creator>
<dc:creator>Magnussen, F.</dc:creator>
<dc:creator>Mowinckel, A. M.</dc:creator>
<dc:creator>Nyberg, L.</dc:creator>
<dc:creator>Roe, J. M.</dc:creator>
<dc:creator>Sexton, C.</dc:creator>
<dc:creator>Sole-Padulles, C.</dc:creator>
<dc:creator>Pudas, S.</dc:creator>
<dc:creator>Vidal-Pineiro, D.</dc:creator>
<dc:creator>Sederevicius, D.</dc:creator>
<dc:creator>Suri, S.</dc:creator>
<dc:creator>Wagner, G.</dc:creator>
<dc:creator>Watne, L. O.</dc:creator>
<dc:creator>Westerhausen, R.</dc:creator>
<dc:creator>Zsoldos, E.</dc:creator>
<dc:creator>Walhovd, K. B.</dc:creator>
<dc:date>2020-04-28</dc:date>
<dc:identifier>doi:10.1101/2020.04.28.065474</dc:identifier>
<dc:title><![CDATA[Self-reported sleep problems are related to cortical thinning in aging but not memory decline and amyloid-β accumulation - results from the Lifebrain consortium]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-04-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.04.27.064634v1?rss=1">
<title>
<![CDATA[
Disrupted structural connectivity in ArcAβ mouse model of Aβ amyloidosis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.04.27.064634v1?rss=1"
</link>
<description><![CDATA[
Although amyloid beta (A{beta}) deposition is one of the major causes of white matter (WM) alterations in Alzheimers disease (AD), little is known about the underlying basis of WM damage and its association with global structural connectivity and network topology. We aimed to dissect the contributions of WM microstructure to structural connectivity and network properties in the ArcA{beta} mice model of A{beta} amyloidosis.

We acquired diffusion-weighted images (DWI) of wild type (WT) and ArcA{beta} transgenic (TG) mice using a 9.4 T MRI scanner. Fixel-based analysis (FBA) was performed to measure fiber tract-specific properties. We also performed three complementary experiments; to identify the global differences in structural connectivity, to compute network properties and to measure cellular basis of white matter alterations.

Transgenic mice displayed disrupted structural connectivity centered to the entorhinal cortex (EC) and a lower fiber density and fiber bundle cross-section. In addition, there was a reduced network efficiency and degree centrality in weighted structural connectivity in the transgenic mice. To further examine the underlying neuronal basis of connectivity and network deficits, we performed histology experiments. We found no alteration in myelination and an increased level of neurofilament light (NFL) in the brain regions with disrupted connectivity in the TG mice. Furthermore, TG mice had a reduced number of perineuronal nets (PNN) in the EC.

The observed FDC reductions may indicate a decrease in axonal diameter or axon count which would explain the basis of connectivity deficits and reduced network efficiency in TG mice. The increase in NFL suggests a breakdown of axonal integrity, which would reduce WM fiber health. Considering the pivotal role of the EC in AD, A{beta} deposition may primarily increase NFL release, damaging PNN in the entorhinal pathway, resulting in disrupted structural connectivity.
]]></description>
<dc:creator>Al-Amin, M. M.</dc:creator>
<dc:creator>Grandjean, J.</dc:creator>
<dc:creator>Klohs, J.</dc:creator>
<dc:creator>Kim, J.</dc:creator>
<dc:date>2020-04-28</dc:date>
<dc:identifier>doi:10.1101/2020.04.27.064634</dc:identifier>
<dc:title><![CDATA[Disrupted structural connectivity in ArcAβ mouse model of Aβ amyloidosis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-04-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.04.24.031138v1?rss=1">
<title>
<![CDATA[
Dynamics of Brain Structure and its Genetic Architecture over the Lifespan 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.04.24.031138v1?rss=1"
</link>
<description><![CDATA[
Human brain structure changes throughout our lives. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental, and neurodegenerative diseases. Here, we identified common genetic variants that affect rates of brain growth or atrophy, in the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal MRI data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene-set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and ageing.
]]></description>
<dc:creator>Brouwer, R. M.</dc:creator>
<dc:creator>Klein, M.</dc:creator>
<dc:creator>Grasby, K. L.</dc:creator>
<dc:creator>Schnack, H. G.</dc:creator>
<dc:creator>Jahanshad, N.</dc:creator>
<dc:creator>Teeuw, J.</dc:creator>
<dc:creator>Thomopoulos, S. I.</dc:creator>
<dc:creator>Sprooten, E.</dc:creator>
<dc:creator>Franz, C. E.</dc:creator>
<dc:creator>Gogtay, N.</dc:creator>
<dc:creator>Kremen, W.</dc:creator>
<dc:creator>Panizzon, M. S.</dc:creator>
<dc:creator>Olde Loohuis, L. M.</dc:creator>
<dc:creator>Whelan, C. D.</dc:creator>
<dc:creator>Aghajani, M.</dc:creator>
<dc:creator>Alloza, C.</dc:creator>
<dc:creator>Alnaes, D.</dc:creator>
<dc:creator>Artiges, E.</dc:creator>
<dc:creator>Ayesa-Arriola, R.</dc:creator>
<dc:creator>Barker, G. J.</dc:creator>
<dc:creator>Blok, E.</dc:creator>
<dc:creator>Boen, E.</dc:creator>
<dc:creator>Breukelaar, I. A.</dc:creator>
<dc:creator>Bright, J. K.</dc:creator>
<dc:creator>Buimer, E. E.</dc:creator>
<dc:creator>Bülow, R.</dc:creator>
<dc:creator>Cannon, D. M.</dc:creator>
<dc:creator>Ciufolini, S.</dc:creator>
<dc:creator>Crossley, N. A.</dc:creator>
<dc:creator>Damatac, C. G.</dc:creator>
<dc:creator>Dazzan, P.</dc:creator>
<dc:creator>de Mol, C. L.</dc:creator>
<dc:creator>de Zwarte, S. M.</dc:creator>
<dc:creator>Desrivieres, S.</dc:creator>
<dc:creator>Diaz-Caneja, C. M.</dc:creator>
<dc:creator>Doan, N. T.</dc:creator>
<dc:creator>Dohm, K.</dc:creator>
<dc:creator>Fröhner, J. H.</dc:creator>
<dc:creator>Goltermann, J.</dc:creator>
<dc:creator>Grigis, A.</dc:creator>
<dc:creator>Grotegerd, D</dc:creator>
<dc:date>2020-04-27</dc:date>
<dc:identifier>doi:10.1101/2020.04.24.031138</dc:identifier>
<dc:title><![CDATA[Dynamics of Brain Structure and its Genetic Architecture over the Lifespan]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-04-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/859637v1?rss=1">
<title>
<![CDATA[
Baseline dopamine predicts individual variation in methylphenidate's effects on cognitive motivation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/859637v1?rss=1"
</link>
<description><![CDATA[
The cognitive enhancing effects of methylphenidate are well established, but the mechanisms remain unclear. We recently demonstrated that methylphenidate boosts cognitive motivation by enhancing the weight on the benefits of a cognitive task in a manner that depended on striatal dopamine. Here we considered the complementary hypothesis that methylphenidate might also act by changing the weight on the opportunity cost of a cognitive task. To this end, fifty healthy participants (25 women) completed a novel cognitive effort discounting task that was sensitive to opportunity cost, and required choices between task and leisure. They were tested on methylphenidate, sulpiride or placebo and also underwent an [18F]DOPA PET scan to quantify baseline dopamine synthesis capacity. Methylphenidate boosted choices of cognitive effort over leisure across the group, and this effect was greatest in participants with more striatal dopamine at baseline. The effects of sulpiride did not reach significance. This study strengthens the motivational account of methylphenidates effects on cognition and suggests that methylphenidate reduces the cost of mental labor by increasing striatal dopamine.
]]></description>
<dc:creator>Hofmans, L.</dc:creator>
<dc:creator>Papadopetraki, D.</dc:creator>
<dc:creator>van den Bosch, R.</dc:creator>
<dc:creator>Määttä, J. I.</dc:creator>
<dc:creator>Froböse, M. I.</dc:creator>
<dc:creator>Zandbelt, B. B.</dc:creator>
<dc:creator>Westbrook, A.</dc:creator>
<dc:creator>Verkes, R.-J.</dc:creator>
<dc:creator>Cools, R.</dc:creator>
<dc:date>2019-11-29</dc:date>
<dc:identifier>doi:10.1101/859637</dc:identifier>
<dc:title><![CDATA[Baseline dopamine predicts individual variation in methylphenidate's effects on cognitive motivation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-11-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.04.09.035113v1?rss=1">
<title>
<![CDATA[
A new set of composite, non-redundant electroencephalogram measures of non-rapid eye movement sleep based on the power law scaling of the Fourier spectrum 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.04.09.035113v1?rss=1"
</link>
<description><![CDATA[
A novel method for deriving composite, non-redundant measures of non-rapid eye movement (NREM) sleep electroencephalogram (EEG) is developed on the basis of the power law scaling of the Fourier spectra. Measures derived are the spectral intercept, the slope (spectral exponent), as well as the maximal whitened spectral peak amplitude and frequency in the sleep spindle range. As a proof of concept, we apply these measures on a large sleep EEG dataset (N = 175; 81 females; age range: 17-60 years) with previously demonstrated effects of age, sex and intelligence. As predicted, aging is associated with decreased overall spectral slopes (increased exponents) and whitened spectral peak amplitudes in the spindle frequency range. In addition, age associates with decreased sleep spindle spectral peak frequencies in the frontal region. Women were characterized by higher spectral intercepts and higher spectral peak frequencies in the sleep spindle range. No sex differences in whitened spectral peak amplitudes of the sleep spindle range were found. Intelligence correlated positively with whitened spectral peak amplitudes of the spindle frequency range in women, but not in men. Last, age-related increases in spectral exponents did not differ in subjects with average and high intelligence. Our findings replicate and complete previous reports in the literature, indicating that the number of variables describing NREM sleep EEG can be effectively reduced in order to overcome redundancy and Type I statistical errors in future electrophysiological studies of sleep.

Author summaryGiven the tight reciprocal relationship between sleep and wakefulness, the objective description of the complex neural activity patterns characterizing human sleep is of utmost importance in understanding the several facets of brain function, like sex differences, aging and cognitive abilities. Current approaches are either exclusively based on visual impressions expressed in graded levels of sleep depth (W, N1, N2, N3, REM), whereas computerized quantitative methods provide an almost infinite number of potential metrics, suffering from significant redundancy and arbitrariness. Our current approach relies on the assumptions that the spontaneous human brain activity as reflected by the scalp-derived electroencephalogram (EEG) are characterized by coloured noise-like properties. That is, the contribution of different frequencies to the power spectrum of the signal are best described by power law functions with negative exponents. In addition, we assume, that stages N2-N3 are further characterized by additional non-random (non-noise like, sinusoidal) activity patterns, which are emerging at specific frequencies, called sleep spindles (9-18 Hz). By relying on these assumptions we were able to effectively reduce 191 spectral measures to 4: (1) the spectral intercept reflecting the overall amplitude of the signal, (2) the spectral slope reflecting the constant ratio of low over high frequency power, (3) the frequency of the maximal sleep spindle activity and (4) the amplitude of the sleep spindle spectral peak. These 4 measures were efficient in characterizing known age-effects, sex-differences and cognitive correlates of sleep EEG. Future clinical and basic studies are supposed to be significantly empowered by the efficient data reduction provided by our approach.
]]></description>
<dc:creator>Bodizs, R.</dc:creator>
<dc:creator>Szalardy, O.</dc:creator>
<dc:creator>Horvath, C.</dc:creator>
<dc:creator>Peter, U. P.</dc:creator>
<dc:creator>Gombos, F.</dc:creator>
<dc:creator>Simor, P.</dc:creator>
<dc:creator>Potari, A.</dc:creator>
<dc:creator>Zeising, M.</dc:creator>
<dc:creator>Steiger, A.</dc:creator>
<dc:creator>Dresler, M.</dc:creator>
<dc:date>2020-04-10</dc:date>
<dc:identifier>doi:10.1101/2020.04.09.035113</dc:identifier>
<dc:title><![CDATA[A new set of composite, non-redundant electroencephalogram measures of non-rapid eye movement sleep based on the power law scaling of the Fourier spectrum]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-04-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.04.17.046813v1?rss=1">
<title>
<![CDATA[
Exploiting Electrophysiological Measures of Semantic Processing for Auditory Attention Decoding 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.04.17.046813v1?rss=1"
</link>
<description><![CDATA[
In Auditory Attention Decoding, a users electrophysiological brain responses to certain features of speech are modelled and subsequently used to distinguish attended from unattended speech in multi-speaker contexts. Such approaches are frequently based on acoustic features of speech, such as the auditory envelope. A recent paper shows that the brains response to a semantic description (i.e., semantic dissimilarity) of narrative speech can also be modelled using such an approach. Here we use the (publicly available) data accompanying that study, in order to investigate whether combining this semantic dissimilarity feature with an auditory envelope approach improves decoding performance over using the envelope alone. We analyse data from their  Cocktail Party experiment in which 33 subjects attended to one of two simultaneously presented audiobook narrations, for 30 1-minute fragments. We find that the addition of the dissimilarity feature to an envelope-based approach significantly increases accuracy, though the increase is marginal (85.4% to 86.6%). However, we subsequently show that this dissimilarity feature, in which the degree of dissimilarity of the current word with regard to the previous context is tagged to the onsets of each content word, can be replaced with a binary content-word-onset feature, without significantly affecting the results (i.e., modelled responses or accuracy), putting in question the added value of the dissimilarity information for the approach introduced in this recent paper.
]]></description>
<dc:creator>Dijkstra, K.</dc:creator>
<dc:creator>Desain, P.</dc:creator>
<dc:creator>Farquhar, J.</dc:creator>
<dc:date>2020-04-18</dc:date>
<dc:identifier>doi:10.1101/2020.04.17.046813</dc:identifier>
<dc:title><![CDATA[Exploiting Electrophysiological Measures of Semantic Processing for Auditory Attention Decoding]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-04-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/854927v1?rss=1">
<title>
<![CDATA[
Genetic Association Study of Childhood Aggression across raters, instruments and age 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/854927v1?rss=1"
</link>
<description><![CDATA[
Childhood aggressive behavior (AGG) has a substantial heritability of around 50%. Here we present a genome-wide association meta-analysis (GWAMA) of childhood AGG, in which all phenotype measures across childhood ages from multiple assessors were included. We analyzed phenotype assessments for a total of 328 935 observations from 87 485 children aged between 1.5 and 18 years, while accounting for sample overlap. We also meta-analyzed within subsets of the data - i.e. within rater, instrument and age. SNP-heritability for the overall meta-analysis (AGGoverall) was 3.31% (SE=0.0038). We found no genome-wide significant SNPs for AGGoverall. The gene-based analysis returned three significant genes: ST3GAL3 (P=1.6E-06), PCDH7 (P=2.0E-06) and IPO13 (P=2.5E-06). All three genes have previously been associated with educational traits. Polygenic scores based on our GWAMA significantly predicted aggression in a holdout sample of children (variance explained = 0.44%) and in retrospectively assessed childhood aggression (variance explained = 0.20%). Genetic correlations (rg) among rater-specific assessment of AGG ranged from rg =0.46 between self- and teacher-assessment to rg =0.81 between mother- and teacher-assessment. We obtained moderate to strong rgs with selected phenotypes from multiple domains, but hardly with any of the classical biomarkers thought to be associated with AGG. Significant genetic correlations were observed with most psychiatric and psychological traits (range |rg| : 0.19 - 1.00), except for obsessive-compulsive disorder. Aggression had a negative genetic correlation (rg =~ -0.5) with cognitive traits and age at first birth. Aggression was strongly genetically correlated with smoking phenotypes (range |rg| : 0.46 - 0.60). The genetic correlations between aggression and psychiatric disorders were weaker for teacher-reported AGG than for mother- and self-reported AGG. The current GWAMA of childhood aggression provides a powerful tool to interrogate the rater-specific genetic etiology of AGG.
]]></description>
<dc:creator>Ip, H. F.</dc:creator>
<dc:creator>van der Laan, C. M.</dc:creator>
<dc:creator>Brikell, I.</dc:creator>
<dc:creator>Sanchez-Mora, C.</dc:creator>
<dc:creator>Nolte, I. M.</dc:creator>
<dc:creator>St Pourcain, B.</dc:creator>
<dc:creator>Bolhuis, K.</dc:creator>
<dc:creator>Palviainen, T.</dc:creator>
<dc:creator>Zafarmand, H.</dc:creator>
<dc:creator>Colodro-Conde, L.</dc:creator>
<dc:creator>Gordon, S.</dc:creator>
<dc:creator>Zayats, T.</dc:creator>
<dc:creator>Aliev, F.</dc:creator>
<dc:creator>Jiang, C.</dc:creator>
<dc:creator>Wang, C. A.</dc:creator>
<dc:creator>Saunders, G.</dc:creator>
<dc:creator>Karhunen, V.</dc:creator>
<dc:creator>Hammerschlag, A. R.</dc:creator>
<dc:creator>Adkins, D. E.</dc:creator>
<dc:creator>Border, R.</dc:creator>
<dc:creator>Peterson, R. E.</dc:creator>
<dc:creator>Prinz, J. A.</dc:creator>
<dc:creator>Thiering, E.</dc:creator>
<dc:creator>Seppälä, I.</dc:creator>
<dc:creator>Vilor-Tejedor, N.</dc:creator>
<dc:creator>Ahluwalia, T. S.</dc:creator>
<dc:creator>Day, F. R.</dc:creator>
<dc:creator>Hottenga, J.-J.</dc:creator>
<dc:creator>Allegrini, A. G.</dc:creator>
<dc:creator>Krapohl, E. M. L.</dc:creator>
<dc:creator>Rimfeld, K.</dc:creator>
<dc:creator>Chen, Q.</dc:creator>
<dc:creator>Lu, Y.</dc:creator>
<dc:creator>Martin, J.</dc:creator>
<dc:creator>Soler Artigas, M.</dc:creator>
<dc:creator>Rovira, P.</dc:creator>
<dc:creator>Bosch, R.</dc:creator>
<dc:creator>Espanol, G.</dc:creator>
<dc:creator>Ramos Quiroga, J. A.</dc:creator>
<dc:creator>Neumann, A.</dc:creator>
<dc:creator>Ensink, J.</dc:creator>
<dc:creator></dc:creator>
<dc:date>2019-11-29</dc:date>
<dc:identifier>doi:10.1101/854927</dc:identifier>
<dc:title><![CDATA[Genetic Association Study of Childhood Aggression across raters, instruments and age]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-11-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.04.14.031740v1?rss=1">
<title>
<![CDATA[
Longitudinal alterations in fronto-striatal glutamate are associated with functioning during inhibitory control in autism spectrum disorder and obsessive compulsive disorder 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.04.14.031740v1?rss=1"
</link>
<description><![CDATA[
BackgroundAutism spectrum disorder (ASD) and obsessive compulsive disorder (OCD) are neurodevelopmental disorders with overlapping symptomatology. Both show deficits in inhibitory control, which are associated with altered functioning and glutamate concentrations in the fronto-striatal circuitry. These parameters have never been examined together. Here we, for the first time, used a multi-center, longitudinal approach to investigate fronto-striatal functioning during an inhibitory control task and its association with fronto-striatal glutamate concentrations across these two disorders.

Methods74 adolescents with ASD (24) or OCD (15) and controls (35) aged 8-17 were recruited across three sites of the European TACTICS consortium. They underwent two magnetic resonance imaging (MRI) sessions with a one-year interval. This included proton magnetic resonance spectroscopy (1H-MRS; n=74) and functional MRI during an inhibitory control task (n=57). We used linear mixed effects models to investigate, over time, the relationship between fronto-striatal functioning and glutamate concentrations across these groups and continuous measures of overlapping compulsivity symptoms.

ResultsDuring failed inhibitory control, in OCD increased striatal glutamate was associated with increased neural activation of ACC, an effect that decreased over time. During successful inhibitory control, higher ACC glutamate was positively associated with striatal activation in OCD and compulsivity across time. ACC glutamate levels decreased over time in the ASD group compared to controls, while striatal glutamate decreased over time, independent of diagnosis.

ConclusionsSignificant differences in fronto-striatal glutamate were observed in ASD and OCD, affecting functional activity during failed- and successful inhibitory control differently, especially in OCD, with effects changing over time.
]]></description>
<dc:creator>Hollestein, V.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Brandeis, D.</dc:creator>
<dc:creator>Banaschewski, T.</dc:creator>
<dc:creator>Kaiser, A.</dc:creator>
<dc:creator>Hohmann, S.</dc:creator>
<dc:creator>Oranje, B.</dc:creator>
<dc:creator>Gooskens, B.</dc:creator>
<dc:creator>Durston, S.</dc:creator>
<dc:creator>Lythgoe, D. J.</dc:creator>
<dc:creator>Naaijen, J.</dc:creator>
<dc:date>2020-04-14</dc:date>
<dc:identifier>doi:10.1101/2020.04.14.031740</dc:identifier>
<dc:title><![CDATA[Longitudinal alterations in fronto-striatal glutamate are associated with functioning during inhibitory control in autism spectrum disorder and obsessive compulsive disorder]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-04-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.04.13.039024v1?rss=1">
<title>
<![CDATA[
Neurophysiological signatures in the retrieval of individual autobiographical memories of real-life episodic events 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.04.13.039024v1?rss=1"
</link>
<description><![CDATA[
Autobiographical memory (AM) refers to recollected events that belong to an individuals past. In a classical episodic retrieval experiment in a laboratory, the events to be remembered are words or pictures that have hardly any personal relevance. While such stimuli provide necessary experimental and controlled conditions helping to advance in the understanding of memory, they do not capture the whole complexity of real-world stimuli. Recently, the incorporation of wearable cameras has allowed us to study the cognitive and neural bases of AM retrieval without active participant involvement, and they have been demonstrated to elicit a strong sense of first-person episodic recollection enhancing ecological validity. Here, we provide a new approach to understanding the retrieval of personal events, implementing a convolution network-based algorithm for the selection of the stimuli while monitoring participants memory retrieval with scalp EEG recordings over three periods of time after encoding (1 week, 2 weeks, and 6 to 12 months). We also examined an individual with a condition termed Aphantasia that provided more insights into the sensitivity of our protocol in the investigation of individual AM using real-life sequences.
]]></description>
<dc:creator>Nicolas, B.</dc:creator>
<dc:creator>Wu, X.</dc:creator>
<dc:creator>Dimiccolli, M.</dc:creator>
<dc:creator>Sierpowska, J.</dc:creator>
<dc:creator>Saiz-Masvidal, C.</dc:creator>
<dc:creator>Soriano-Mas, C.</dc:creator>
<dc:creator>Radeva, P.</dc:creator>
<dc:creator>Fuentemilla, L.</dc:creator>
<dc:date>2020-04-14</dc:date>
<dc:identifier>doi:10.1101/2020.04.13.039024</dc:identifier>
<dc:title><![CDATA[Neurophysiological signatures in the retrieval of individual autobiographical memories of real-life episodic events]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-04-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/549832v1?rss=1">
<title>
<![CDATA[
External location of touch is constructed post-hoc based on limb choice 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/549832v1?rss=1"
</link>
<description><![CDATA[
When humans indicate on which hand a tactile stimulus occurred, they often err when their hands are crossed. This finding seemingly supports the view that the automatically determined touch location in external space affects limb assignment: the crossed right hand is localized in left space, and this conflict presumably provokes hand assignment errors. Here, participants judged on which hand the first of two stimuli, presented during a bimanual movement, had occurred, and then indicated its external location by a reach-to-point movement. When participants incorrectly chose the hand stimulated second, they pointed to where that hand had been at the correct, first time point, though no stimulus had occurred at that location. This behavior suggests that stimulus localization depended on hand assignment, not vice versa. It is, thus, incompatible with the notion of automatic computation of external stimulus location upon occurrence. Instead, humans construct external touch location post-hoc and on demand.
]]></description>
<dc:creator>Maij, F.</dc:creator>
<dc:creator>Medendorp, W. P.</dc:creator>
<dc:creator>Heed, T.</dc:creator>
<dc:date>2019-02-14</dc:date>
<dc:identifier>doi:10.1101/549832</dc:identifier>
<dc:title><![CDATA[External location of touch is constructed post-hoc based on limb choice]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-02-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.04.09.033696v1?rss=1">
<title>
<![CDATA[
The Development of Cognitive Control in Children with Autism Spectrum Disorders or Obsessive-Compulsive Disorder: A Longitudinal fMRI study 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.04.09.033696v1?rss=1"
</link>
<description><![CDATA[
Repetitive behavior is a core symptom of Autism Spectrum Disorder (ASD) and Obsessive-Compulsive Disorder (OCD), and has been associated with impairments in cognitive control. However, it is unclear how cognitive control and associated neural circuitry relate to the development of repetitive behavior in children with these disorders. In a multicenter, longitudinal study (TACTICS; Translational Adolescent and Childhood Therapeutic Interventions in Compulsive Syndromes), the development of cognitive control was assessed during late childhood using a longitudinal fMRI design with a modified stop-signal task in children with ASD or OCD, and typically developing (TD) children (baseline: N=122 (8-12y), follow-up: N=72 (10-14y), average interval: 1.2y). Stop-signal reaction time (SSRT) decreased over development, regardless of diagnosis. Repetitive behavior in children with ASD and OCD was not associated with performance on the stop-signal task. There were no whole-brain between-group differences in brain activity, but ROI-analyses showed increases in activity in right precentral gyrus over development for children with OCD. In sum, even though subtle differences were observed in the development of brain activity in children with OCD, the findings overall suggest that the development of cognitive control, as assessed by the stop signal task, is similar in children with and without ASD or OCD.
]]></description>
<dc:creator>Gooskens, B.</dc:creator>
<dc:creator>Bos, D. J.</dc:creator>
<dc:creator>Naaijen, J.</dc:creator>
<dc:creator>Akkermans, S. E. A.</dc:creator>
<dc:creator>Kaiser, A.</dc:creator>
<dc:creator>Hohmann, S.</dc:creator>
<dc:creator>Bruchhage, M. M. K.</dc:creator>
<dc:creator>Banaschewski, T.</dc:creator>
<dc:creator>Brandeis, D.</dc:creator>
<dc:creator>Williams, S. C. R.</dc:creator>
<dc:creator>Lythgoe, D. J.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Oranje, B.</dc:creator>
<dc:creator>Durston, S.</dc:creator>
<dc:creator>the TACTICS consortium,</dc:creator>
<dc:date>2020-04-11</dc:date>
<dc:identifier>doi:10.1101/2020.04.09.033696</dc:identifier>
<dc:title><![CDATA[The Development of Cognitive Control in Children with Autism Spectrum Disorders or Obsessive-Compulsive Disorder: A Longitudinal fMRI study]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-04-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.04.03.024109v1?rss=1">
<title>
<![CDATA[
Spike timing in the attention network predicts behavioral outcome prior to target selection 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.04.03.024109v1?rss=1"
</link>
<description><![CDATA[
There has been little evidence linking changes in spiking activity that occur prior to a spatially predictable target (i.e., prior to target selection) to behavioral outcomes, despite such preparatory changes being widely assumed to enhance the sensitivity of sensory processing. We simultaneously recorded from frontal and parietal nodes of the attention network, while macaques performed a spatial-cueing task. When anticipating a spatially predictable target, different patterns of coupling between spike timing and oscillatory phase in local field potentials--but not changes in spike rate--were predictive of different behavioral outcomes. These behaviorally relevant differences in local and between-region synchronization occurred among specific cell types that were defined based on their sensory and motor properties, providing insight into the mechanisms underlying enhanced sensory processing prior to target selection. We propose that these changes in neural synchronization reflect differential, anticipatory engagement of the network nodes and functional units that shape attention-related sampling.
]]></description>
<dc:creator>Fiebelkorn, I. C.</dc:creator>
<dc:creator>Kastner, S.</dc:creator>
<dc:date>2020-04-05</dc:date>
<dc:identifier>doi:10.1101/2020.04.03.024109</dc:identifier>
<dc:title><![CDATA[Spike timing in the attention network predicts behavioral outcome prior to target selection]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-04-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.04.03.022590v1?rss=1">
<title>
<![CDATA[
Local and global dichotomic dysfunction in resting and evoked functional connectivity precedes tauopathy 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.04.03.022590v1?rss=1"
</link>
<description><![CDATA[
Functional network activity alterations are one of the earliest hallmarks of Alzheimers disease (AD), detected prior to amyloidosis and tauopathy. Better understanding the neuronal underpinnings of such network alterations could offer mechanistic insight into AD progression. Here, we examined a mouse model (early-tauopathy 3xTgAD mice) recapitulating this early AD stage. We found resting functional connectivity loss within ventral networks, including the entorhinal cortex, aligning with the spatial distribution of tauopathy reported in humans. Unexpectedly, in contrast to decreased connectivity at rest, 3xTgAD mice show enhanced fMRI signal within several projection areas following optogenetic activation of the entorhinal cortex. We corroborate this finding by demonstrating neuronal facilitation within ventral networks and synaptic hyperexcitability in projection targets. 3xTgAD mice thus reveal a dichotomic hypo-connected resting/hyper-responsive active phenotype. The strong homotopy between the areas affected supports the translatability of this pathophysiological model to tau-related deficits in humans.
]]></description>
<dc:creator>Mandino, F.</dc:creator>
<dc:creator>Yeow, L. Y.</dc:creator>
<dc:creator>Bi, R.</dc:creator>
<dc:creator>Lee, S.</dc:creator>
<dc:creator>Bae, H. G.</dc:creator>
<dc:creator>Baek, S. H.</dc:creator>
<dc:creator>Lee, C. Y.</dc:creator>
<dc:creator>Mohammad, H.</dc:creator>
<dc:creator>Teoh, C. L.</dc:creator>
<dc:creator>Lee, J.</dc:creator>
<dc:creator>Lai, M. K. P.</dc:creator>
<dc:creator>Jung, S.</dc:creator>
<dc:creator>Yu, F.</dc:creator>
<dc:creator>Olivo, M.</dc:creator>
<dc:creator>Gigg, J.</dc:creator>
<dc:creator>Grandjean, J.</dc:creator>
<dc:date>2020-04-04</dc:date>
<dc:identifier>doi:10.1101/2020.04.03.022590</dc:identifier>
<dc:title><![CDATA[Local and global dichotomic dysfunction in resting and evoked functional connectivity precedes tauopathy]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-04-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/475178v1?rss=1">
<title>
<![CDATA[
Functional connectivity with short-term dynamics explains diverse patterns of excitatory spike transmission in vivo 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/475178v1?rss=1"
</link>
<description><![CDATA[
Information transmission in neural networks is influenced by both short-term synaptic plasticity (STP) as well as non-synaptic factors, such as after-hyperpolarization currents and changes in excitability. Although these effects have been widely characterized in vitro using intracellular recordings, how they interact in vivo is unclear. Here we develop a statistical model of the short-term dynamics of spike transmission that aims to disentangle the contributions of synaptic and non-synaptic effects based only on observed pre- and postsynaptic spiking. The model includes a dynamic functional connection with short-term plasticity as well as effects due to the recent history of postsynaptic spiking and slow changes in postsynaptic excitability. Using paired spike recordings, we find that the model accurately describes the short-term dynamics of in vivo spike transmission at a diverse set of identified and putative excitatory synapses, including a thalamothalamic connection in mouse, a thalamocortical connection in a female rabbit, and an auditory brainstem synapse in a female gerbil. We illustrate the utility of this modeling approach by showing how the spike transmission patterns captured by the model may be sufficient to account for stimulus-dependent differences in spike transmission in the auditory brainstem (endbulb of Held). Finally, we apply this model to large-scale multi-electrode recordings to illustrate how such an approach has the potential to reveal cell-type specific differences in spike transmission in vivo. Although short-term synaptic plasticity parameters estimated from ongoing pre- and postsynaptic spiking are highly uncertain, our results are partially consistent with previous intracellular observations in these synapses.

Significance StatementAlthough synaptic dynamics have been extensively studied and modeled using intracellular recordings of post-synaptic currents and potentials, inferring synaptic effects from extracellular spiking is challenging. Whether or not a synaptic current contributes to postsynaptic spiking depends not only on the amplitude of the current, but also on many other factors, including the activity of other, typically unobserved, synapses, the overall excitability of the postsynaptic neuron, and how recently the postsynaptic neuron has spiked. Here we developed a model that, using only observations of pre- and postsynaptic spiking, aims to describe the dynamics of in vivo spike transmission by modeling both short-term synaptic plasticity and non-synaptic effects. This approach may provide a novel description of fast, structured changes in spike transmission.
]]></description>
<dc:creator>Ghanbari, A.</dc:creator>
<dc:creator>Ren, N.</dc:creator>
<dc:creator>Keine, C.</dc:creator>
<dc:creator>Stoelzel, C.</dc:creator>
<dc:creator>Englitz, B.</dc:creator>
<dc:creator>Swadlow, H.</dc:creator>
<dc:creator>Stevenson, I.</dc:creator>
<dc:date>2018-11-23</dc:date>
<dc:identifier>doi:10.1101/475178</dc:identifier>
<dc:title><![CDATA[Functional connectivity with short-term dynamics explains diverse patterns of excitatory spike transmission in vivo]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-11-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/797787v1?rss=1">
<title>
<![CDATA[
Integrating healthcare and research genetic data empowers the discovery of 49 novel developmental disorders 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/797787v1?rss=1"
</link>
<description><![CDATA[
De novo mutations (DNMs) in protein-coding genes are a well-established cause of developmental disorders (DD). However, known DD-associated genes only account for a minority of the observed excess of such DNMs. To identify novel DD-associated genes, we integrated healthcare and research exome sequences on 31,058 DD parent-offspring trios, and developed a simulation-based statistical test to identify gene-specific enrichments of DNMs. We identified 285 significantly DD-associated genes, including 28 not previously robustly associated with DDs. Despite detecting more DD-associated genes than in any previous study, much of the excess of DNMs of protein-coding genes remains unaccounted for. Modelling suggests that over 1,000 novel DD-associated genes await discovery, many of which are likely to be less penetrant than the currently known genes. Research access to clinical diagnostic datasets will be critical for completing the map of dominant DDs.
]]></description>
<dc:creator>Kaplanis, J.</dc:creator>
<dc:creator>Samocha, K. E.</dc:creator>
<dc:creator>Wiel, L.</dc:creator>
<dc:creator>Zhang, Z.</dc:creator>
<dc:creator>Arvai, K.</dc:creator>
<dc:creator>Eberhardt, R.</dc:creator>
<dc:creator>Gallone, G.</dc:creator>
<dc:creator>Lelieveld, S. H.</dc:creator>
<dc:creator>Martin, H.</dc:creator>
<dc:creator>McRae, J.</dc:creator>
<dc:creator>Short, P.</dc:creator>
<dc:creator>Torene, R.</dc:creator>
<dc:creator>de Boer, E.</dc:creator>
<dc:creator>Danecek, P.</dc:creator>
<dc:creator>Gardner, E. J.</dc:creator>
<dc:creator>Huang, N.</dc:creator>
<dc:creator>Lord, J.</dc:creator>
<dc:creator>Martincorena, I.</dc:creator>
<dc:creator>Pfundt, R.</dc:creator>
<dc:creator>Reijnders, M.</dc:creator>
<dc:creator>Yeung, A.</dc:creator>
<dc:creator>Yntema, H.</dc:creator>
<dc:creator>DDD study,</dc:creator>
<dc:creator>Vissers, L.</dc:creator>
<dc:creator>Juusola, J.</dc:creator>
<dc:creator>Wright, C.</dc:creator>
<dc:creator>Brunner, H.</dc:creator>
<dc:creator>Firth, H. V.</dc:creator>
<dc:creator>Fitzpatrick, D. R.</dc:creator>
<dc:creator>Barrett, J. C.</dc:creator>
<dc:creator>Hurles, M. E.</dc:creator>
<dc:creator>Gilissen, C.</dc:creator>
<dc:creator>Retterer, K.</dc:creator>
<dc:date>2019-10-16</dc:date>
<dc:identifier>doi:10.1101/797787</dc:identifier>
<dc:title><![CDATA[Integrating healthcare and research genetic data empowers the discovery of 49 novel developmental disorders]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/746891v1?rss=1">
<title>
<![CDATA[
Spatial Patterns for Discriminative Estimation (SPADE) 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/746891v1?rss=1"
</link>
<description><![CDATA[
Functional connectivity between brain regions is modulated by cognitive states or experimental conditions. A multivariate methodology that can capture fMRI connectivity maps in light of different experimental conditions would be of primary importance to learn about the specific roles of the different brain areas involved in the observed connectivity variations. Here we detail, adapt, optimize and evaluate a supervised dimensionality reduction model to fMRI timeseries. We demonstrate the strength of such an approach for fMRI data using data from the Human Connectome Project to show that the model provides close to perfect discrimination between different fMRI tasks at low dimensionality. The straightforward interpretability and relevance of the model results is demonstrated by the obtained linear filters relating to anatomical areas well known to be involved on each considered task, and its robustness by testing discriminatory generalization and spatial reproducibility with respect to the number of subjects and fMRI time-points acquired. We additionally suggest how such approach can provide a complementary view to traditional task fMRI analyses by looking at changes in the covariance structure as a substitute to changes in the mean signal. We conclude that the presented methodology provides a robust tool to investigate brain connectivity alterations across induced cognitive changes and has the potential to be used in pathological or pharmacological cohort studies. A publicly available toolbox is provided to facilitate the end use and further development of this methodology to extract Spatial Patterns for Discriminative Estimation (SP{spadesuit}DE).
]]></description>
<dc:creator>Llera Arenas, A.</dc:creator>
<dc:creator>Chauvin, R.</dc:creator>
<dc:creator>Mulders, P. C.</dc:creator>
<dc:creator>Naaijen, J.</dc:creator>
<dc:creator>Mennes, M.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:date>2019-08-28</dc:date>
<dc:identifier>doi:10.1101/746891</dc:identifier>
<dc:title><![CDATA[Spatial Patterns for Discriminative Estimation (SPADE)]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-08-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.02.17.952010v1?rss=1">
<title>
<![CDATA[
Greater male than female variability in regional brain structure across the lifespan 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.02.17.952010v1?rss=1"
</link>
<description><![CDATA[
For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders.
]]></description>
<dc:creator>Wierenga, L. M.</dc:creator>
<dc:creator>Doucet, G.</dc:creator>
<dc:creator>Dima, D.</dc:creator>
<dc:creator>Agartz, I.</dc:creator>
<dc:creator>Aghajani, M.</dc:creator>
<dc:creator>Akudjedu, T.</dc:creator>
<dc:creator>Albajes-Eizagirre, A.</dc:creator>
<dc:creator>Alnaes, D.</dc:creator>
<dc:creator>Alpert, K.</dc:creator>
<dc:creator>Andreassen, O. A.</dc:creator>
<dc:creator>Anticevic, A.</dc:creator>
<dc:creator>Asherson, P.</dc:creator>
<dc:creator>Banaschewski, T.</dc:creator>
<dc:creator>Bargallo, N.</dc:creator>
<dc:creator>Baumeister, S.</dc:creator>
<dc:creator>Baur-Streubel, R.</dc:creator>
<dc:creator>Bertolino, A.</dc:creator>
<dc:creator>Bonvino, A.</dc:creator>
<dc:creator>Boomsma, D.</dc:creator>
<dc:creator>Borgwardt, S.</dc:creator>
<dc:creator>Bourque, J.</dc:creator>
<dc:creator>den Braber, A.</dc:creator>
<dc:creator>Brandeis, D.</dc:creator>
<dc:creator>Breier, A.</dc:creator>
<dc:creator>Brodaty, H.</dc:creator>
<dc:creator>Brouwer, R.</dc:creator>
<dc:creator>Busatto, G.</dc:creator>
<dc:creator>Calhoun, V.</dc:creator>
<dc:creator>Canales-Rodriguez, E.</dc:creator>
<dc:creator>Cannon, D.</dc:creator>
<dc:creator>Caseras, X.</dc:creator>
<dc:creator>Chaim-Avancini, T.</dc:creator>
<dc:creator>Ching, C.</dc:creator>
<dc:creator>Conrod, P.</dc:creator>
<dc:creator>Conzelmann, A.</dc:creator>
<dc:creator>Crivello, F.</dc:creator>
<dc:creator>Davey, C.</dc:creator>
<dc:creator>Dickie, E.</dc:creator>
<dc:creator>Ehrlich, S.</dc:creator>
<dc:creator>van 't Ent, D.</dc:creator>
<dc:creator>Fouche, J.-P.</dc:creator>
<dc:creator>Fuentes-</dc:creator>
<dc:date>2020-02-17</dc:date>
<dc:identifier>doi:10.1101/2020.02.17.952010</dc:identifier>
<dc:title><![CDATA[Greater male than female variability in regional brain structure across the lifespan]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-02-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/759217v1?rss=1">
<title>
<![CDATA[
Longitudinal Automatic Segmentation of Hippocampal Subfields (LASHiS) using Multi-Contrast MRI 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/759217v1?rss=1"
</link>
<description><![CDATA[
The volumetric and morphometric examination of hippocampus formation subfields in a longitudinal manner using in vivo MRI could lead to more sensitive biomarkers for neuropsychiatric disorders and diseases including Alzheimers disease, as the anatomical subregions are functionally specialised. Longitudinal processing allows for increased sensitivity due to reduced confounds of inter-subject variability and higher effect-sensitivity than cross-sectional designs. We examined the performance of a new longitudinal pipeline (Longitudinal Automatic Segmentation of Hippocampus Subfields [LASHiS]) against three freely available, published approaches. LASHiS automatically segments hippocampus formation subfields by propagating labels from cross-sectionally labelled time point scans using joint-label fusion to a non-linearly realigned  single subject template, where image segmentation occurs free of bias to any individual time point. Our pipeline measures tissue characteristics available in in vivo high-resolution MRI scans, at both clinical (3 Tesla) and ultra-high field strength (7 Tesla) and differs from previous longitudinal segmentation pipelines in that it leverages multi-contrast information in the segmentation process. LASHiS produces robust and reliable automatic multi-contrast segmentations of hippocampus formation subfields, as measured by higher volume similarity coefficients and Dice coefficients for test-retest reliability and robust longitudinal Bayesian Linear Mixed Effects results at 7 T, while showing sound results at 3 T. All code for this project including the automatic pipeline is available at https://github.com/CAIsr/LASHiS
]]></description>
<dc:creator>Shaw, T. B.</dc:creator>
<dc:creator>Bollmann, S.</dc:creator>
<dc:creator>York, A.</dc:creator>
<dc:creator>Ziaei, M.</dc:creator>
<dc:creator>Barth, M.</dc:creator>
<dc:date>2019-09-08</dc:date>
<dc:identifier>doi:10.1101/759217</dc:identifier>
<dc:title><![CDATA[Longitudinal Automatic Segmentation of Hippocampal Subfields (LASHiS) using Multi-Contrast MRI]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.03.26.010678v1?rss=1">
<title>
<![CDATA[
Gamma-rhythmic input causes spike output 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.03.26.010678v1?rss=1"
</link>
<description><![CDATA[
The gamma rhythm has been implicated in neuronal communication, but causal evidence remains indirect. We measured spike output of local neuronal networks and emulated their synaptic input through optogenetics. Opsins provide currents through somato-dendritic membranes, similar to synapses, yet under experimental control with high temporal precision. We expressed Channelrhodopsin-2 in excitatory neurons of cat visual cortex and recorded neuronal responses to light with different temporal characteristics. Sine waves of different frequencies entrained neuronal responses with a reliability that peaked for input frequencies in the gamma band. Crucially, we also presented white-noise sequences, because their temporal unpredictability enables analysis of causality. Neuronal spike output was caused specifically by the inputs gamma component. This gamma-specific transfer function is likely an emergent property of in-vivo networks with feedback inhibition. The method described here could reveal the transfer function between the input to any one and the output of any other neuronal group.
]]></description>
<dc:creator>Lewis, C. M.</dc:creator>
<dc:creator>Ni, J.</dc:creator>
<dc:creator>Wunderle, T.</dc:creator>
<dc:creator>Jendritza, P.</dc:creator>
<dc:creator>Diester, I.</dc:creator>
<dc:creator>Fries, P.</dc:creator>
<dc:date>2020-03-26</dc:date>
<dc:identifier>doi:10.1101/2020.03.26.010678</dc:identifier>
<dc:title><![CDATA[Gamma-rhythmic input causes spike output]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-03-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/735530v1?rss=1">
<title>
<![CDATA[
Analyzing combined eye-tracking/EEG experiments with (non)linear deconvolution models 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/735530v1?rss=1"
</link>
<description><![CDATA[
Fixation-related potentials (FRPs), neural responses aligned to saccade offsets, are a promising tool to study the dynamics of attention and cognition under natural viewing conditions. In the past, four methodological problems have complicated the analysis of such combined eye-tracking/EEG experiments: (i) the synchronization of data streams, (ii) the removal of ocular artifacts, (iii) the condition-specific temporal overlap between the brain responses evoked by consecutive fixations, (iv) and the fact that numerous low-level stimulus and saccade properties also influence the post-saccadic neural responses. While effective solutions exist for the first two problems, the latter ones are only beginning to be addressed. In the current paper, we present and review a unified framework for FRP analysis that allows us to deconvolve overlapping potentials and control for linear and nonlinear confounds on the FRPs. An open software implementation is provided for all procedures. We then demonstrate the advantages of this approach for data from three commonly studied paradigms: face perception, scene viewing, and natural sentence reading. First, for a traditional ERP face recognition experiment, we show how deconvolution can separate stimulus-ERPs from overlapping muscle and brain potentials produced by small (micro)saccades on the face. Second, in scene viewing, we isolate multiple non-linear influences of saccade parameters on the FRP. Finally, for a natural sentence reading experiment using the boundary paradigm, we show how it is possible to study the neural correlates of parafoveal preview after removing spurious overlap effects caused by the associated difference in average fixation time. Our results suggest a principal way of measuring reliable fixation-related brain potentials during natural vision.
]]></description>
<dc:creator>Dimigen, O.</dc:creator>
<dc:creator>Ehinger, B. V.</dc:creator>
<dc:date>2019-08-15</dc:date>
<dc:identifier>doi:10.1101/735530</dc:identifier>
<dc:title><![CDATA[Analyzing combined eye-tracking/EEG experiments with (non)linear deconvolution models]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-08-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/677237v1?rss=1">
<title>
<![CDATA[
Recurrent networks can recycle neural resources to flexibly trade speed for accuracy in visual recognition 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/677237v1?rss=1"
</link>
<description><![CDATA[
Deep feedforward neural network models of vision dominate in both computational neuroscience and engineering. The primate visual system, by contrast, contains abundant recurrent connections. Recurrent signal flow enables recycling of limited computational resources over time, and so might boost the performance of a physically finite brain or model. Here we show: (1) Recurrent convolutional neural network models outperform feedforward convolutional models matched in their number of parameters in large-scale visual recognition tasks on natural images. (2) Setting a confidence threshold, at which recurrent computations terminate and a decision is made, enables flexible trading of speed for accuracy. At a given confidence threshold, the model expends more time and energy on images that are harder to recognise, without requiring additional parameters for deeper computations. (3) The recurrent models reaction time for an image predicts the human reaction time for the same image better than several parameter-matched and state-of-the-art feedforward models. (4) Across confidence thresholds, the recurrent model emulates the behaviour of feedforward control models in that it achieves the same accuracy at approximately the same computational cost (mean number of floating-point operations). However, the recurrent model can be run longer (higher confidence threshold) and then outperforms parameter-matched feedforward comparison models. These results suggest that recurrent connectivity, a hallmark of biological visual systems, may be essential for understanding the accuracy, flexibility, and dynamics of human visual recognition.

Author summaryDeep neural networks provide the best current models of biological vision and achieve the highest performance in computer vision. Inspired by the primate brain, these models transform the image signals through a sequence of stages, leading to recognition. Unlike brains in which outputs of a given computation are fed back into the same computation, these models do not process signals recurrently. The ability to recycle limited neural resources by processing information recurrently could explain the accuracy and flexibility of biological visual systems, which computer vision systems cannot yet match. Here we report that recurrent processing can improve recognition performance compared to similarly complex feedforward networks. Recurrent processing also enabled models to behave more flexibly and trade off speed for accuracy. Like humans, the recurrent network models can compute longer when an object is hard to recognise, which boosts their accuracy. The models recognition times predicted human recognition times for the same images. The performance and flexibility of recurrent neural network models illustrates that modeling biological vision can help us improve computer vision.
]]></description>
<dc:creator>Spoerer, C. J.</dc:creator>
<dc:creator>Kietzmann, T. C.</dc:creator>
<dc:creator>Kriegeskorte, N.</dc:creator>
<dc:date>2019-06-20</dc:date>
<dc:identifier>doi:10.1101/677237</dc:identifier>
<dc:title><![CDATA[Recurrent networks can recycle neural resources to flexibly trade speed for accuracy in visual recognition]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-06-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.03.24.000349v1?rss=1">
<title>
<![CDATA[
Atypical brain asymmetry in autism - a candidate for clinically meaningful stratification 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.03.24.000349v1?rss=1"
</link>
<description><![CDATA[
BackgroundAutism Spectrum Disorder (henceforth  autism) is a highly heterogeneous neurodevelopmental condition with few effective treatments for core and associated features. To make progress we need to both identify and validate neural markers that help to parse heterogeneity to tailor therapies to specific neurobiological profiles. Atypical hemispheric lateralization is a stable feature across studies in autism, however its potential of lateralization as a neural stratification marker has not been widely examined.

MethodsIn order to dissect heterogeneity in lateralization in autism, we used the large EU-AIMS Longitudinal European Autism Project dataset comprising 352 individuals with autism and 233 neurotypical (NT) controls as well as a replication dataset from ABIDE (513 autism, 691 NT) using a promising approach that moves beyond mean-group comparisons. We derived grey matter voxelwise laterality values for each subject and modelled individual deviations from the normative pattern of brain laterality across age using normative modeling.

ResultsResults showed that individuals with autism had highly individualized patterns of both extreme right- and leftward deviations, particularly in language-, motor- and visuospatial regions, associated with symptom severity. Language delay (LD) explained most variance in extreme rightward patterns, whereas core autism symptom severity explained most variance in extreme leftward patterns. Follow-up analyses showed that a stepwise pattern emerged with individuals with autism with LD showing more pronounced rightward deviations than autism individuals without LD.

ConclusionOur analyses corroborate the need for novel (dimensional) approaches to delineate the heterogeneous neuroanatomy in autism, and indicate atypical lateralization may constitute a neurophenotype for clinically meaningful stratification in autism.
]]></description>
<dc:creator>Floris, D. L.</dc:creator>
<dc:creator>Wolfer, T.</dc:creator>
<dc:creator>Zabihi, M.</dc:creator>
<dc:creator>Holz, N. E.</dc:creator>
<dc:creator>Zwiers, M. P.</dc:creator>
<dc:creator>Charman, T.</dc:creator>
<dc:creator>Tillmann, J.</dc:creator>
<dc:creator>Ecker, C.</dc:creator>
<dc:creator>Dell'Acqua, F.</dc:creator>
<dc:creator>Banaschewski, T.</dc:creator>
<dc:creator>Moessnang, C.</dc:creator>
<dc:creator>Baron-Cohen, S.</dc:creator>
<dc:creator>Holt, R.</dc:creator>
<dc:creator>Durston, S.</dc:creator>
<dc:creator>Loth, E.</dc:creator>
<dc:creator>Murphy, D. G. M.</dc:creator>
<dc:creator>Marquand, A.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:date>2020-03-25</dc:date>
<dc:identifier>doi:10.1101/2020.03.24.000349</dc:identifier>
<dc:title><![CDATA[Atypical brain asymmetry in autism - a candidate for clinically meaningful stratification]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-03-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.03.22.002543v1?rss=1">
<title>
<![CDATA[
Three Essential Resources to Improve Differential Scanning Fluorimetry (DSF) Experiments 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.03.22.002543v1?rss=1"
</link>
<description><![CDATA[
Differential Scanning Fluorimetry (DSF) is a method that enables rapid determination of a proteins apparent melting temperature (Tma). Owing to its high throughput, DSF has found widespread application in fields ranging from structural biology to chemical screening. Yet DSF has developed two opposing reputations: one as an indispensable laboratory tool to probe protein stability, another as a frustrating platform that often fails. Here, we aim to reconcile these disparate reputations and help users perform more successful DSF experiments with three resources: an updated, interactive theoretical framework, practical tips, and online data analysis. We anticipate that these resources, made available online at DSFworld (https://gestwickilab.shinyapps.io/dsfworld/), will broaden the utility of DSF.
]]></description>
<dc:creator>Wu, T.</dc:creator>
<dc:creator>Yu, J.</dc:creator>
<dc:creator>Gale-Day, Z.</dc:creator>
<dc:creator>Woo, A.</dc:creator>
<dc:creator>Suresh, A.</dc:creator>
<dc:creator>Hornsby, M.</dc:creator>
<dc:creator>Gestwicki, J. E.</dc:creator>
<dc:date>2020-03-25</dc:date>
<dc:identifier>doi:10.1101/2020.03.22.002543</dc:identifier>
<dc:title><![CDATA[Three Essential Resources to Improve Differential Scanning Fluorimetry (DSF) Experiments]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-03-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/275818v1?rss=1">
<title>
<![CDATA[
Why not record from every channel with a CMOS scanning probe? 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/275818v1?rss=1"
</link>
<description><![CDATA[
It is an uninformative truism to state that the brain operates at multiple spatial and temporal scales, each with each own set of emergent phenomena. More worthy of attention is the point that our current understanding of it cannot clearly indicate which of these phenomenological scales are the significant contributors to the brains function and primary output (i.e. behaviour). Apart from the sheer complexity of the problem, a major contributing factor to this state of affairs is the lack of instrumentation that can simultaneously address these multiple scales without causing function altering damages to the underlying tissue. One important facet of this problem is that standard neural recording devices normally require one output connection per electrode. This limits the number of electrodes that can fit along the thin shafts of implantable probes generating a limiting balance between density and spread. Sharing a single output connection between multiple electrodes relaxes this constraint and permits designs of ultra-high density probes.

Here we report the design and in-vivo validation of such a device, a complementary metal-oxide-semiconductor (CMOS) scanning probe with 1344 electrodes; the outcome of the European research project NeuroSeeker. We show that this design targets both local and global spatial scales by allowing the simultaneous recording of more than 1000 neurons spanning 7 functional regions with a single shaft. The neurons show similar recording longevity and signal to noise ratio to passive probes of comparable size and no adverse effects in awake or anesthetized animals. Addressing the data management of this device we also present novel visualization and monitoring methods. Using the probe with freely moving animals we show how accessing a number of cortical and subcortical brain regions offers a novel perspective on how the brain operates around salient behavioural events. Finally, we compare this probe with lower density, non CMOS designs (which have to adhere to the one electrode per output line rule). We show that an increase in density results in capturing neural firing patterns, undetectable by lower density devices, which correlate to self-similar structures inherent in complex naturalistic behaviour.

To help design electrode configurations for future, even higher density, CMOS probes, recordings from many different brain regions were obtained with an ultra-dense passive probe.
]]></description>
<dc:creator>Dimitriadis, G.</dc:creator>
<dc:creator>Neto, J. P.</dc:creator>
<dc:creator>Aarts, A.</dc:creator>
<dc:creator>Alexandru, A.</dc:creator>
<dc:creator>Ballini, M.</dc:creator>
<dc:creator>Battaglia, F.</dc:creator>
<dc:creator>Calcaterra, L.</dc:creator>
<dc:creator>David, F.</dc:creator>
<dc:creator>Fiath, R.</dc:creator>
<dc:creator>Frazao, J.</dc:creator>
<dc:creator>Geerts, J.</dc:creator>
<dc:creator>Gentet, L. J.</dc:creator>
<dc:creator>Helleputte, N. V.</dc:creator>
<dc:creator>Holzhammer, T.</dc:creator>
<dc:creator>Hoof, C. v.</dc:creator>
<dc:creator>Horvath, D.</dc:creator>
<dc:creator>Lopes, G.</dc:creator>
<dc:creator>Maris, E.</dc:creator>
<dc:creator>Marques-Smith, A.</dc:creator>
<dc:creator>Marton, G.</dc:creator>
<dc:creator>Meszena, D.</dc:creator>
<dc:creator>Mitra, S.</dc:creator>
<dc:creator>Musa, S.</dc:creator>
<dc:creator>Neves, H.</dc:creator>
<dc:creator>Nogueira, J.</dc:creator>
<dc:creator>Orban, G. A.</dc:creator>
<dc:creator>Pothof, F.</dc:creator>
<dc:creator>Putzeys, J.</dc:creator>
<dc:creator>Raducanu, B.</dc:creator>
<dc:creator>Ruther, P.</dc:creator>
<dc:creator>Schroeder, T.</dc:creator>
<dc:creator>Singer, W.</dc:creator>
<dc:creator>Tiesinga, P.</dc:creator>
<dc:creator>Ulbert, I.</dc:creator>
<dc:creator>Wang, S.</dc:creator>
<dc:creator>Welkenhuysen, M.</dc:creator>
<dc:creator>Kampff, A. R.</dc:creator>
<dc:date>2018-03-03</dc:date>
<dc:identifier>doi:10.1101/275818</dc:identifier>
<dc:title><![CDATA[Why not record from every channel with a CMOS scanning probe?]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-03-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.03.23.003228v1?rss=1">
<title>
<![CDATA[
Cortico-motor control dynamics orchestrates visual sampling 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.03.23.003228v1?rss=1"
</link>
<description><![CDATA[
Movements overtly sample sensory information, making sensory analysis an active-sensing process. In this study, we show that visual information sampling is not just locked to the (overt) movement dynamics, but it is structured by the internal (covert) dynamics of cortico-motor control. We asked human participants to perform an isometric motor task - based on proprioceptive feedback - while detecting unrelated near-threshold visual stimuli. The motor output (Force) shows zero-lag coherence with brain activity (recorded via electroencephalography) in the beta-band, as previously reported. In contrast, cortical rhythms in the alpha-band systematically forerun the motor output by 200ms. Importantly, visual detection is facilitated when cortico-motor alpha (not beta) synchronization is enhanced immediately before stimulus onset, namely at the optimal phase relationship for sensorimotor communication. These findings demonstrate an automatic gating of visual inputs by the ongoing motor control processes, providing evidence of an internal and alpha-cycling visuomotor loop.
]]></description>
<dc:creator>Tomassini, A.</dc:creator>
<dc:creator>Maris, E.</dc:creator>
<dc:creator>Hilt, P.</dc:creator>
<dc:creator>Fadiga, L.</dc:creator>
<dc:creator>D'Ausilio, A.</dc:creator>
<dc:date>2020-03-23</dc:date>
<dc:identifier>doi:10.1101/2020.03.23.003228</dc:identifier>
<dc:title><![CDATA[Cortico-motor control dynamics orchestrates visual sampling]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-03-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.03.12.988402v1?rss=1">
<title>
<![CDATA[
Rapid changes in brain activity during learning of grapheme-phoneme associations in adults 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.03.12.988402v1?rss=1"
</link>
<description><![CDATA[
Learning to associate written letters with speech sounds is crucial for the initial phase of acquiring reading skills. However, little is known about the cortical reorganization for supporting letter-speech sound learning, particularly the brain dynamics during the learning of grapheme-phoneme associations. In the present study, we trained 30 Finnish participants (mean age: 24.33 years, SD: 3.50 years) to associate novel foreign letters with familiar Finnish speech sounds on two consecutive days (first day ~ 50 minutes; second day ~ 25 minutes), while neural activity was measured using magnetoencephalography (MEG). Two sets of audiovisual stimuli were used for the training in which the grapheme-phoneme association in one set (Learnable) could be learned based on the different learning cues provided, but not in the other set (Control). The learning progress was tracked at a trial-by-trial basis and used to segment different learning stages for the MEG source analysis. The learning-related changes were examined by comparing the brain responses to Learnable and Control uni/multi-sensory stimuli, as well as the brain responses to learning cues at different learning stages over the two days. We found dynamic changes in brain responses related to multi-sensory processing when grapheme-phoneme associations were learned. Further, changes were observed in the brain responses to the novel letters during the learning process. We also found that some of these learning effects were observed only after memory consolidation the following day. Overall, the learning process modulated the activity in a large network of brain regions, including the superior temporal cortex and the dorsal (parietal) pathway. Most interestingly, middle- and inferior-temporal regions were engaged during multi-sensory memory encoding after the cross-modal relationship was extracted from the learning cues. Our findings highlight the brain dynamics and plasticity related to the learning of letter-speech sound associations and provide a more refined model of grapheme-phoneme learning in reading acquisition.
]]></description>
<dc:creator>Xu, W.</dc:creator>
<dc:creator>Kolozsvari, O. B.</dc:creator>
<dc:creator>Oostenveld, R.</dc:creator>
<dc:creator>Hamalainen, J. A.</dc:creator>
<dc:date>2020-03-12</dc:date>
<dc:identifier>doi:10.1101/2020.03.12.988402</dc:identifier>
<dc:title><![CDATA[Rapid changes in brain activity during learning of grapheme-phoneme associations in adults]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-03-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.03.19.999656v1?rss=1">
<title>
<![CDATA[
The gut microbiota of rural and urban individuals is shaped by geography and lifestyle 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.03.19.999656v1?rss=1"
</link>
<description><![CDATA[
Understanding the structure and drivers of gut microbiota remains a major ecological endeavour. Recent studies have shown that several factors including diet, lifestyle and geography may substantially shape the human gut microbiota. However, most of these studies have focused on the more abundant bacterial component and comparatively less is known regarding fungi in the human gut. This knowledge deficit is especially true for rural and urban African populations. Therefore, we assessed the structure and drivers of rural and urban gut mycobiota. Our participants (n=100) were balanced by geography and sex. The mycobiota of these geographically separated cohorts was characterized using amplicon analysis of the Internal Transcribed Spacer (ITS) gene. We further assessed biomarker species specific to rural and urban cohorts. In addition to phyla which have been shown to be ubiquitous constituents of gut microbiota, Pichia were key constituents of the mycobiota. We found that several factors including geographic location and lifestyle factors such as the smoking status were major drivers of gut mycobiota. Linear discriminant and the linear discriminant analysis effect size analysis revealed several distinct urban and rural biomarkers. Together, our analysis reveals distinct community structure in urban and rural South African individuals. Geography and lifestyle related factors were shown to be key drivers of rural and urban gut microbiota.

ImportanceThe past decade has revealed substantial insights regarding the ecological patterns of gut microbiomes. These studies have shown clear differences between the microbiomes of individuals living in urban and rural locations. Yet, in contrast to bacteria we know substantially less regarding the fungal gut microbiota (mycobiome). Here we provide the first insights regarding the mycobiome of individuals from urban and rural locations. We show that these communities are geographically structured. Further we show that lifestyle factors, such as diet and smoking, are strong drivers explaining community variability.
]]></description>
<dc:creator>Kabwe, M. H.</dc:creator>
<dc:creator>Vikram, S.</dc:creator>
<dc:creator>Mulaudzi, K.</dc:creator>
<dc:creator>Jansson, J. K.</dc:creator>
<dc:creator>Makhalanyane, T. P.</dc:creator>
<dc:date>2020-03-20</dc:date>
<dc:identifier>doi:10.1101/2020.03.19.999656</dc:identifier>
<dc:title><![CDATA[The gut microbiota of rural and urban individuals is shaped by geography and lifestyle]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-03-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.03.14.991802v1?rss=1">
<title>
<![CDATA[
Semantic and syntactic composition of minimal adjective-noun phrases in Dutch: an MEG study 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.03.14.991802v1?rss=1"
</link>
<description><![CDATA[
The possibility to combine smaller units of meaning (e.g., words) to create new and more complex meanings (e.g., phrases and sentences) is a fundamental feature of human language. In the present project, we investigated how the brain supports the semantic and syntactic composition of two-word adjective-noun phrases in Dutch, using magnetoencephalography (MEG). The present investigation followed up on previous studies reporting a composition effect in the left anterior temporal lobe (LATL) when comparing neural activity at nouns combined with adjectives, as opposed to nouns in a non-compositional context. The first aim of the present study was to investigate whether this effect, as well as its modulation by noun specificity and adjective class, can also be observed in Dutch. A second aim was to investigate to what extent these effects may be driven by syntactic composition rather than primarily by semantic composition as was previously proposed. To this end, a novel condition was administered in which participants saw nouns combined with pseudowords lacking meaning but agreeing with the nouns in terms of grammatical gender, as real adjectives would. We failed to observe a composition effect or its modulation in both a confirmatory analysis (focused on the cortical region and time-window where it has previously been reported) and in exploratory analyses (where we tested multiple regions and an extended potential time-window of the effect). A syntactically driven composition effect was also not observed in our data. We do, however, successfully observe an independent, previously reported effect on single word processing in our data, confirming that our MEG data processing pipeline does meaningfully capture language processing activity by the brain. The failure to observe the composition effect in LATL is surprising given that it has been previously reported in multiple studies. Reviewing all previous studies investigating this effect, we propose that materials and a task involving imagery might be necessary for this effect to be observed. In addition, we identified substantial variability in the regions of interest analysed in previous studies, which warrants additional checks of robustness of the effect. Further research should identify limits and conditions under which this effect can be observed. The failure to observe specifically a syntactic composition effect in such minimal phrases is less surprising given that it has not been previously reported in MEG data.
]]></description>
<dc:creator>Kochari, A.</dc:creator>
<dc:creator>Lewis, A.</dc:creator>
<dc:creator>Schoffelen, J.-M.</dc:creator>
<dc:creator>Schriefers, H.</dc:creator>
<dc:date>2020-03-15</dc:date>
<dc:identifier>doi:10.1101/2020.03.14.991802</dc:identifier>
<dc:title><![CDATA[Semantic and syntactic composition of minimal adjective-noun phrases in Dutch: an MEG study]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-03-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/787713v1?rss=1">
<title>
<![CDATA[
Hyperactivity-impulsivity in ADHD is associated with white matter microstructure in the cingulum’s angular bundle 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/787713v1?rss=1"
</link>
<description><![CDATA[
BackgroundAttention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by age-inappropriate levels of inattention and/or hyperactivity-impulsivity (HI). ADHD has been related to differences in white matter (WM) microstructure. However, much remains unclear regarding the nature of these WM differences, and which clinical aspects of ADHD they reflect. We systematically investigated if FA is associated with current and/or lifetime categorical diagnosis, impairment in daily life, and continuous ADHD symptom measures.

MethodsDiffusion-weighted imaging (DWI) data were obtained from 654 participants (322 unaffected, 258 affected, 74 subthreshold; 7-29 years of age). We applied automated global probabilistic tractography on 18 major WM pathways. Linear mixed effects regression models were used to examine associations of clinical measures with overall brain and tract-specific fractional anisotropy (FA).

ResultsThere were significant interactions of tract with all ADHD variables on FA. There were no significant associations of FA with current or lifetime diagnosis, nor with impairment. Lower FA in the right cingulums angular bundle (rCAB) was associated with higher hyperactivity/impulsivity symptom severity (PFWE=0.045). There were no significant effects for other tracts.

ConclusionsThis is the first time global probabilistic tractography has been applied to an ADHD dataset of this size. We found no evidence for altered FA in association with ADHD diagnosis. Our findings indicate that associations of FA with ADHD are not uniformly distributed across WM tracts. Continuous symptom measures of ADHD may be more sensitive to FA than diagnostic categories. The rCAB in particular may play a role in symptoms of hyperactivity and impulsivity.
]]></description>
<dc:creator>Damatac, C. G.</dc:creator>
<dc:creator>Zwiers, M.</dc:creator>
<dc:creator>Chauvin, R. J. M.</dc:creator>
<dc:creator>van Rooij, D.</dc:creator>
<dc:creator>Akkermans, S. E. A.</dc:creator>
<dc:creator>Naaijen, J.</dc:creator>
<dc:creator>Hoekstra, P. J.</dc:creator>
<dc:creator>Hartman, C. A.</dc:creator>
<dc:creator>Oosterlaan, J.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>Sprooten, E.</dc:creator>
<dc:date>2019-09-30</dc:date>
<dc:identifier>doi:10.1101/787713</dc:identifier>
<dc:title><![CDATA[Hyperactivity-impulsivity in ADHD is associated with white matter microstructure in the cingulum’s angular bundle]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/622589v1?rss=1">
<title>
<![CDATA[
Previously reward-associated stimuli capture spatial attention in the absence of changes in the corresponding sensory representations as measured with MEG 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/622589v1?rss=1"
</link>
<description><![CDATA[
Studies of selective attention typically consider the role of task goals or physical salience, but recent work has shown that attention can also be captured by previously reward-associated stimuli, even if they are currently task-irrelevant. One theory underlying this value-driven attentional capture (VDAC) is that reward-associated stimulus representations may undergo plasticity in sensory cortex, thereby automatically capturing attention during early processing. To test this, we used magnetoencephalography to probe whether stimulus location and identity representations in sensory cortex are modulated by reward learning. We furthermore investigated the time-course of these neural effects, and their relationship to behavioural VDAC. Male and female human participants first learned stimulus-reward associations. Next, we measured VDAC in a separate task by presenting these stimuli in the absence of reward contingency, and probing their effects on the processing of separate target stimuli presented at different time lags. Using time-resolved multivariate pattern analysis, we found that learned value modulated the spatial selection of previously rewarded stimuli in posterior visual and parietal cortex from [~]260ms after stimulus onset. This value modulation was related to the strength of participants behavioural VDAC effect and persisted into subsequent target processing. Furthermore, we found a spatially invariant value signal from [~]340ms. Importantly, learned value did not influence cortical signatures of early processing (i.e., earlier than [~]200ms), nor did it influence the decodability of the identity of previously rewarded stimuli. Our results suggest that VDAC is underpinned by learned value signals which modulate spatial selection throughout posterior visual and parietal cortex. We further suggest that VDAC can occur in the absence of changes in early visual processing in cortex.

Significance statementAttention is our ability to focus on relevant information at the expense of irrelevant information. It can be affected by previously learned but currently irrelevant stimulus-reward associations, a phenomenon termed "value-driven attentional capture" (VDAC). The neural mechanisms underlying VDAC remain unclear. It has been speculated that reward learning induces visual cortical plasticity which modulates early visual processing to capture attention. Although we find that learned value modulates spatial signals in visual cortical areas, an effect which correlates with VDAC, we find no relevant signatures of changes in early visual processing in cortex.
]]></description>
<dc:creator>Tankelevitch, L.</dc:creator>
<dc:creator>Spaak, E.</dc:creator>
<dc:creator>Rushworth, M. F.</dc:creator>
<dc:creator>Stokes, M. G.</dc:creator>
<dc:date>2019-04-29</dc:date>
<dc:identifier>doi:10.1101/622589</dc:identifier>
<dc:title><![CDATA[Previously reward-associated stimuli capture spatial attention in the absence of changes in the corresponding sensory representations as measured with MEG]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-04-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.03.17.995035v1?rss=1">
<title>
<![CDATA[
Morphological and functional variability in central and subcentral motor cortex of the human brain 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.03.17.995035v1?rss=1"
</link>
<description><![CDATA[
There is a long-established link between anatomy and function in the somatomotor system in the mammalian cerebral cortex. The morphology of the central sulcus is predictive of the location of functional activation peaks relating to movement of different effectors in individuals. By contrast, morphological variation in the subcentral region and its relationship to function is, as yet, unknown. Investigating the subcentral region is particularly important in the context of speech, since control of the larynx during human speech production is related to activity in this region. Here, we examined the relationship between morphology in the central and subcentral region and the location of functional activity during movement of the hand, lips, tongue, and larynx at the individual participant level. We provide a systematic description of the sulcal patterns of the subcentral and adjacent opercular cortex, including the inter-individual variability in sulcal morphology. We show that, in the majority of participants, the anterior subcentral sulcus is not continuous, but consists of two distinct segments. A robust relationship between morphology of the central and subcentral sulcal segments and movement of different effectors is demonstrated. Inter-individual variability of underlying anatomy might thus explain previous inconsistent findings, in particular regarding the ventral larynx area in subcentral cortex. A surface registration based on sulcal labels indicated that such anatomical information can improve the alignment of functional data for group studies.
]]></description>
<dc:creator>Eichert, N.</dc:creator>
<dc:creator>Watkins, K. E.</dc:creator>
<dc:creator>Mars, R. B.</dc:creator>
<dc:creator>Petrides, M.</dc:creator>
<dc:date>2020-03-18</dc:date>
<dc:identifier>doi:10.1101/2020.03.17.995035</dc:identifier>
<dc:title><![CDATA[Morphological and functional variability in central and subcentral motor cortex of the human brain]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-03-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.03.14.990002v1?rss=1">
<title>
<![CDATA[
Hippocampal-medial prefrontal event segmentation and integration contribute to episodic memory formation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.03.14.990002v1?rss=1"
</link>
<description><![CDATA[
How do we encode our continuous life experiences for later retrieval? Theories of event segmentation and integration suggest that the hippocampus binds separately represented events into an ordered narrative. Using a functional Magnetic Resonance Imaging (fMRI) movie watching-recall dataset, we quantified two types of neural similarities (i.e., activation pattern similarity and within-region voxel-based connectivity pattern similarity) between separate events during movie watching and related them to subsequent retrieval of events as well as retrieval of sequential order. We demonstrated that compared to forgotten events, successfully remembered events were associated with distinct activation patterns in the hippocampus and medial prefrontal cortex. By contrast, similar connectivity patterns between events were associated with memory formation and were also relevant for retaining events in the correct order. We applied the same approaches to an independent movie watching fMRI dataset as validation and highlighted again the role of hippocampal activation pattern and connectivity pattern in memory formation. We propose that distinct activation patterns represent neural segmentation of events while similar connectivity patterns encode context information, and therefore integrate events into a narrative. Our results provide novel evidence for the role of hippocampal-medial prefrontal event segmentation and integration in episodic memory formation of real-life experience.
]]></description>
<dc:creator>Liu, W.</dc:creator>
<dc:creator>Shi, Y.</dc:creator>
<dc:creator>Cousins, J. N.</dc:creator>
<dc:creator>Kohn, N.</dc:creator>
<dc:creator>Fernandez, G.</dc:creator>
<dc:date>2020-03-15</dc:date>
<dc:identifier>doi:10.1101/2020.03.14.990002</dc:identifier>
<dc:title><![CDATA[Hippocampal-medial prefrontal event segmentation and integration contribute to episodic memory formation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-03-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.03.13.990929v1?rss=1">
<title>
<![CDATA[
Methylphenidate normalizes aberrant beta oscillations and reduces alpha power during retention in children with ADHD 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.03.13.990929v1?rss=1"
</link>
<description><![CDATA[
Attention Deficit-Hyperactivity Disorder (ADHD) has been intensively studied in neurodevelopmental research, with the aim to identify the neural substrates of the disorder. Prior studies have established that brain oscillations in specific frequency ranges associated with attention and motor tasks are altered in ADHD patients as compared to typically developing (TD) peers. We hypothesized that the behavioral improvement following medication in ADHD patients should be accompanied by a normalization in the modulation of such oscillations. We hence implemented a double-blind placebo-controlled crossover design, where boys diagnosed with ADHD underwent behavioral and MEG measurements during a spatial attention task while on and off stimulant medication (methylphenidate, MPH). Results were compared with an age/IQ-matched TD group performing the same task, to assess the effect of MPH on oscillatory activity in the alpha (7 - 13Hz) and beta (15 - 30Hz) bands. We observed that depression of beta band oscillation over motor cortex in preparation to the response in ADHD boys on placebo were significantly lower as compared to the TD group. Importantly MPH resulted in a normalization of the beta depression, which then reached the same levels as in the control subjects. Furthermore, alpha power increased during the preparation interval in the ADHD control group, supposedly reflecting working memory maintenance of the cue information. This increase was significantly reduced in the ADHD group on MPH, reflecting a reduced impact on working memory load. This is the first MEG study showing task related changes in brain oscillations with MPH in children with ADHD.

Significance statementBrain oscillations in the alpha (7-13Hz) and beta (15-30Hz) frequency bands are thought to underly different aspects of attentional processing and their aberrant modulation has been reported in ADHD. Here, we used a child-friendly adaptation of a Posner cueing paradigm to investigate such oscillations in children with and without a diagnosis of ADHD, and further examined the effects of methylphenidate (MPH) in the latter group. We showed that MPH restores aberrant patterns of beta desynchronization and reduces alpha power during retention in the ADHD group, concomitant to an improvement in behavioural performance.
]]></description>
<dc:creator>Mazzetti, C.</dc:creator>
<dc:creator>ter Huurne, N.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Jensen, O.</dc:creator>
<dc:date>2020-03-15</dc:date>
<dc:identifier>doi:10.1101/2020.03.13.990929</dc:identifier>
<dc:title><![CDATA[Methylphenidate normalizes aberrant beta oscillations and reduces alpha power during retention in children with ADHD]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-03-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/747329v1?rss=1">
<title>
<![CDATA[
Visual working memory representations in visual and parietal cortex do not remap after eye movements 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/747329v1?rss=1"
</link>
<description><![CDATA[
It has been suggested that our visual system does not only process stimuli that are directly available to our eyes, but also has a role in maintaining information in VWM over a period of seconds. It remains unclear however what happens to VWM representations in the visual system when we make saccades. Here, we tested the hypothesis that VWM representations are remapped within the visual system after making saccades. We directly compared the content of VWM for saccade and no-saccade conditions using MVPA of delay-related activity measured with fMRI. We found that when participants did not make a saccade, VWM representations were robustly present in contralateral early visual cortex. When making a saccade, VWM representations degraded in contralateral V1-V3 after the saccade shifted the location of the remembered grating to the opposite visual field. However, contrary to our hypothesis we found no evidence for the representations of the remembered grating at the saccadic target location in the opposite visual field, suggesting that there is no evidence for remapping of VWM in early visual cortex. Interestingly, IPS showed persistent VWM representations in both the saccade and no-saccade condition. Together, our results indicate that VWM representations in early visual cortex are not remapped across eye movements, potentially limiting the role of early visual cortex in VWM storage.

HighlightsO_LIVisual working memory (VWM) representations do not remap after making saccades
C_LIO_LIEye movement degrade VWM representations in early visual cortex, limiting the role of early visual cortex in VWM storage
C_LIO_LIParietal cortex shows persistent VWM representations across saccades
C_LI
]]></description>
<dc:creator>He, T.</dc:creator>
<dc:creator>Ekman, M.</dc:creator>
<dc:creator>Vandenbroucke, A. R. E.</dc:creator>
<dc:creator>de Lange, F.</dc:creator>
<dc:date>2019-08-28</dc:date>
<dc:identifier>doi:10.1101/747329</dc:identifier>
<dc:title><![CDATA[Visual working memory representations in visual and parietal cortex do not remap after eye movements]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-08-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/546671v1?rss=1">
<title>
<![CDATA[
Machine Learning Classification of Attention-Deficit/Hyperactivity Disorder Using Structural MRI Data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/546671v1?rss=1"
</link>
<description><![CDATA[
ADHD affects 5% of children world-wide. Of these, two-thirds continue to have impairing symptoms of ADHD into adulthood. Although a large literature implicates structural brain differences in the pathophysiology of the disorder, it is not clear if adults with ADHD have similar neuroanatomical impairments as those seen in children with recent reports from the large ENIGMA-ADHD consortium finding structural abnormalities for children but not for adults. This paper uses deep learning neural network classification models to determine if there are neuroanatomical changes in the brains of children with ADHD that are also observed for adult ADHD, and vice versa. We found that structural MRI data can significantly separate ADHD from control participants for both children and adults. Consistent with the prior reports from ENIGMA-ADHD, prediction performance and effect sizes were better for the child than the adult samples. The model trained on adult samples significantly predicted ADHD in the child sample, suggesting that our model learned anatomical features that common to ADHD in childhood and adulthood. These results support the continuity of ADHDs pathophysiology from childhood to adulthood. In addition, our work demonstrates a novel use of neural network classification models to test hypotheses about developmental continuity.
]]></description>
<dc:creator>Zhang-James, Y.</dc:creator>
<dc:creator>Helminen, E.</dc:creator>
<dc:creator>Liu, J.</dc:creator>
<dc:creator>the ENIGMA-ADHD working group,</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Hoogman, M.</dc:creator>
<dc:creator>Faraone, S.</dc:creator>
<dc:date>2019-02-11</dc:date>
<dc:identifier>doi:10.1101/546671</dc:identifier>
<dc:title><![CDATA[Machine Learning Classification of Attention-Deficit/Hyperactivity Disorder Using Structural MRI Data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-02-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.01.16.909812v1?rss=1">
<title>
<![CDATA[
Double-dissociation of frequency-specific contributions of dorso-lateral and dorso-medial prefrontal cortex to familiarity and recollective processes in the primate 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.01.16.909812v1?rss=1"
</link>
<description><![CDATA[
According to dual-process theories, recognition memory draws upon both familiarity and recollection. It remains unclear how primate prefrontal cortex (PFC) contributes to familiarity and recollection processes but frequency-specific neuronal activities are considered to play a key role. Here, non-human primate (NHP) electrophysiological local field potential (LFP) recordings first showed that a specific subregion of macaque PFC (i.e., dorsolateral PFC, dlPFC) was implicated in task performance at a specific frequency (i.e., increased beta power in the 10-15 Hz range observed in correct versus error trials) in a specific phase of a recognition memory task (i.e., during sample presentation). Then, to assess generalization to humans and causality we targeted left human dlPFC (BA 9/46) as well as left dorsomedial prefrontal cortex (BA 8/9) for comparison, and also vertex as a control, with transcranial magnetic stimulation at a frequency in the middle of the low-beta range observed in NHP (i.e. 12.5 Hz) and compared that to non-frequency-specific stimulation, and also to a no-stimulation control, during occasional sample presentations within a similar task. Hence we investigated hypotheses about the causal importance for human memory of a location-specific, frequency-specific, and task-epoch-specific intervention derived directly from the NHP electrophysiological observations. Using a dual-process signal detection (DPSD) model based on analysing receiver operating characteristics (ROC) curves, we showed beta-frequency TMS caused decreased recollection when targeted to human dlPFC, but enhanced familiarity when targeted to dorsomedial prefrontal cortex. Non-frequency-specific patterns of stimulation to all sites, and beta-frequency stimulation to vertex, were all without behavioural effect. This study provides causal evidence that PFC-mediated contributions to object recognition memory are modulated by beta-frequency activity; more broadly it provides translational evidence bridging NHPs and humans by emphasizing functional roles of beta-frequency activity in homologous brain regions in recognition memory.

HighlightsO_LIlow beta power in NHP dlPFC during stimulus encoding was related to behaviour
C_LIO_LIhuman rTMS study used parameters derived from NHP observations to test causality
C_LIO_LIlow beta rTMS to human dlPFC, but not dmPFC, impairs recollection
C_LIO_LIlow beta rTMS to human dmPFC, but not dlPFC, enhances familiarity
C_LIO_LIprovides cross-species validation of prefrontal beta power to primate recognition
C_LI
]]></description>
<dc:creator>Wu, Z.</dc:creator>
<dc:creator>Kavanova, M.</dc:creator>
<dc:creator>Hickman, L.</dc:creator>
<dc:creator>Lin, F.</dc:creator>
<dc:creator>Boschin, E.</dc:creator>
<dc:creator>Galeazzi, J. M.</dc:creator>
<dc:creator>Verhagen, L.</dc:creator>
<dc:creator>Buckley, M. J.</dc:creator>
<dc:date>2020-01-17</dc:date>
<dc:identifier>doi:10.1101/2020.01.16.909812</dc:identifier>
<dc:title><![CDATA[Double-dissociation of frequency-specific contributions of dorso-lateral and dorso-medial prefrontal cortex to familiarity and recollective processes in the primate]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-01-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.03.09.983205v1?rss=1">
<title>
<![CDATA[
A novel stimulus paradigm for simultaneous recording of monaural and binaural frequency following response for identification of binaural interaction component 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.03.09.983205v1?rss=1"
</link>
<description><![CDATA[
The objective of the study was to investigate whether monaural frequency following response (FFR) of right and left ear and binaural FFR could be obtained in the same recording using a novel stimulus presentation paradigm, for the purpose of identification the BIC. Twenty six young adults participated in the study. The FFR was recorded for 220 Hz pure-tone using a novel stimulus paradigm. The pure-tone was presented sequentially to two ears. Initially, the pure-tone was presented to the right ear, then to both ears, and finally to the left ear. The FFR could be elicited from all participants (all three responses: right ear, left ear, and both ears) in the same recording using the novel stimulus presentation paradigm used in the present study. The novel stimulus presentation paradigm used in the present study could be used for obtaining monaural and binaural FFRs in the same recording for identification of BIC.
]]></description>
<dc:creator>Bhagavan, S. G.</dc:creator>
<dc:creator>Kalaiah, M. K.</dc:creator>
<dc:date>2020-03-09</dc:date>
<dc:identifier>doi:10.1101/2020.03.09.983205</dc:identifier>
<dc:title><![CDATA[A novel stimulus paradigm for simultaneous recording of monaural and binaural frequency following response for identification of binaural interaction component]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-03-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.03.08.980995v1?rss=1">
<title>
<![CDATA[
Anatomically precise relationship between specific amygdala connections and selective markers of mental well-being in humans 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.03.08.980995v1?rss=1"
</link>
<description><![CDATA[
There has been increasing interest in using neuroimaging measures to predict psychiatric disorders. However, predictions usually rely on large numbers of brain connections and large disorder heterogeneity, thus lacking both anatomical and behavioural specificity, preventing the advancement of targeted interventions. Here, we address both challenges. First, using resting-state functional MRI, we parcellated the amygdala, a region implicated in mood disorders but difficult to image with high fidelity, into seven nuclei. Next, a questionnaire factor analysis provided four sub-clinical latent behaviours frequently found in anxious-depressive individuals, such as negative emotions and sleep problems. Finally, for each latent behaviour, we identified the most predictive connections between individual amygdala nuclei and highly specific regions of interest e.g. dorsal raphe nucleus in the brainstem or medial prefrontal cortical regions. A small number of distinct connections predicted behaviours, providing unprecedented levels of specificity, in humans, for relating mental well-being to precise anatomical connections.
]]></description>
<dc:creator>Klein-Flugge, M. C.</dc:creator>
<dc:creator>Jensen, D. E.</dc:creator>
<dc:creator>Takagi, Y.</dc:creator>
<dc:creator>Verhagen, L.</dc:creator>
<dc:creator>Smith, S. M.</dc:creator>
<dc:creator>Rushworth, M. F.</dc:creator>
<dc:date>2020-03-09</dc:date>
<dc:identifier>doi:10.1101/2020.03.08.980995</dc:identifier>
<dc:title><![CDATA[Anatomically precise relationship between specific amygdala connections and selective markers of mental well-being in humans]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-03-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.03.05.973172v1?rss=1">
<title>
<![CDATA[
Phenotype Discovery from Population Brain Imaging 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.03.05.973172v1?rss=1"
</link>
<description><![CDATA[
Neuroimaging allows for the non-invasive study of the brain in rich detail. Data-driven discovery of patterns of population variability in the brain has the potential to be extremely valuable for early disease diagnosis and understanding the brain. The resulting patterns can be used as imaging-derived phenotypes (IDPs), and may complement existing expert-curated IDPs. However, population datasets, comprising many different structural and functional imaging modalities from thousands of subjects, provide a computational challenge not previously addressed. Here, for the first time, a multimodal independent component analysis approach is presented that is scalable for data fusion of voxel-level neuroimaging data in the full UK Biobank (UKB) dataset, that will soon reach 100,000 imaged subjects. This new computational approach can estimate modes of population variability that enhance the ability to predict thousands of phenotypic and behavioural variables using data from UKB and the Human Connectome Project. A high-dimensional decomposition achieved improved predictive power compared with widely-used analysis strategies, single-modality decompositions and existing IDPs. In UKB data (14,503 subjects with 47 different data modalities), many interpretable associations with non-imaging phenotypes were identified, including multimodal spatial maps related to fluid intelligence, handedness and disease, in some cases where IDP-based approaches failed.
]]></description>
<dc:creator>Gong, W.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>Smith, S. M.</dc:creator>
<dc:date>2020-03-05</dc:date>
<dc:identifier>doi:10.1101/2020.03.05.973172</dc:identifier>
<dc:title><![CDATA[Phenotype Discovery from Population Brain Imaging]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-03-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.03.04.976860v1?rss=1">
<title>
<![CDATA[
Gradients of functional connectivity in the mouse cortex reflect neocortical evolution 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.03.04.976860v1?rss=1"
</link>
<description><![CDATA[
Understanding cortical organization is a fundamental goal of neuroscience that requires comparisons across species and modalities. Large-scale connectivity gradients have recently been introduced as a data-driven representation of the intrinsic organization of the cortex. We studied resting-state functional connectivity gradients in the mouse cortex and found robust spatial patterns across four data sets. The principal gradient of functional connectivity shows a striking overlap with an axis of neocortical evolution from two primordial origins. Additional gradients reflect sensory specialization and aspects of a sensory-to-transmodal hierarchy, and are associated with transcriptomic features. While some of these gradients strongly resemble observations in the human cortex, the overall pattern in the mouse cortex emphasizes the specialization of sensory areas over a global functional hierarchy.

HighlightsO_LIThe principal gradient of functional connectivity in the mouse cortex recapitulates an axis of neocortical evolution from archicortex and paleocortex.
C_LIO_LIAdditional gradients highlight sensory specialization and reflect aspects of a sensory-to-transmodal hierarchy.
C_LIO_LIFunctional connectivity gradients partly align with gene expression patterns.
C_LIO_LIMouse cortical gradients are stable across data sets.
C_LI
]]></description>
<dc:creator>Huntenburg, J. M.</dc:creator>
<dc:creator>Yeow, L. Y.</dc:creator>
<dc:creator>Mandino, F.</dc:creator>
<dc:creator>Grandjean, J.</dc:creator>
<dc:date>2020-03-05</dc:date>
<dc:identifier>doi:10.1101/2020.03.04.976860</dc:identifier>
<dc:title><![CDATA[Gradients of functional connectivity in the mouse cortex reflect neocortical evolution]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-03-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.03.03.974758v1?rss=1">
<title>
<![CDATA[
Analysis of structural brain asymmetries in Attention-Deficit/Hyperactivity Disorder in 39 datasets 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.03.03.974758v1?rss=1"
</link>
<description><![CDATA[
ObjectiveSome studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here we performed the largest-ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium.

MethodsWe analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,978 people with ADHD and unaffected 1,917 controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modelling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries.

ResultsThere was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t=2.4, P=0.019). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t=2.4, P=0.007) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohens d from -0.18 to 0.18) and would not survive study-wide correction for multiple testing.

ConclusionPrior studies of altered structural brain asymmetry in ADHD were likely underpowered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait.
]]></description>
<dc:creator>Postema, M. C.</dc:creator>
<dc:creator>Hoogman, M.</dc:creator>
<dc:creator>ENIGMA ADHD Working Group,</dc:creator>
<dc:creator>Glahn, D. C.</dc:creator>
<dc:creator>Jahanshad, N.</dc:creator>
<dc:creator>Medland, S.</dc:creator>
<dc:creator>Thompson, P. M.</dc:creator>
<dc:creator>Fisher, S. E.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Francks, C.</dc:creator>
<dc:date>2020-03-05</dc:date>
<dc:identifier>doi:10.1101/2020.03.03.974758</dc:identifier>
<dc:title><![CDATA[Analysis of structural brain asymmetries in Attention-Deficit/Hyperactivity Disorder in 39 datasets]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-03-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.03.03.974931v1?rss=1">
<title>
<![CDATA[
Predicting future drinking among young adults:using ensemble machine-learning to combine MRI with psychometrics and behaviour 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.03.03.974931v1?rss=1"
</link>
<description><![CDATA[
BackgroundWhile most research into predictors of problematic alcohol use has focused on adolescence, young adults are also at elevated risk, and differ from adolescents and adults in terms of exposure to alcohol and neurodevelopment. Here we examined predictors of alcohol use among young adults at a 1-year follow-up using a broad predictive modelling approach.

MethodsData in four modalities were included from 128 men aged between 18 and 25 years; functional MRI regions-of-interest from 1) a beer-incentive delay task, and 2) a social alcohol cue-exposure task, 3) grey matter data, and 4) non-neuroimaging data (i.e. psychometric and behavioural). These modalities were combined into an ensemble model to predict follow-up Alcohol Use Disorder Identification (AUDIT) scores, and were tested separately for their contribution. To reveal specificity for the prediction of future AUDIT scores, the same analyses were carried out for current AUDIT score.

ResultsThe ensemble resulted in a more accurate estimation of follow-up AUDIT score than any single modality. Only removal of the social alcohol cue-exposure task and of the non-neuroimaging data significantly worsened predictions. Reporting to need a drink in the morning to start the day was the strongest unique predictor of future drinking along with anterior cingulate cortex and cerebellar activity.

ConclusionsAlcohol-related task fMRI activity is a valuable predictor for future drinking among young adults alongside non-neuroimaging variables. Multi-modal prediction models best predict future drinking among young adults and may play an important part in the move towards individualized treatment and prevention efforts.
]]></description>
<dc:creator>Groefsema, M. M.</dc:creator>
<dc:creator>Luijten, M.</dc:creator>
<dc:creator>Engels, R. C. M. E.</dc:creator>
<dc:creator>Sescousse, G.</dc:creator>
<dc:creator>Jollans, L.</dc:creator>
<dc:date>2020-03-05</dc:date>
<dc:identifier>doi:10.1101/2020.03.03.974931</dc:identifier>
<dc:title><![CDATA[Predicting future drinking among young adults:using ensemble machine-learning to combine MRI with psychometrics and behaviour]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-03-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/441048v1?rss=1">
<title>
<![CDATA[
The Hex-Maze: A previous knowledge task for mice 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/441048v1?rss=1"
</link>
<description><![CDATA[
New information is rarely learned in isolation, instead most of what we experience can be incorporated into or uses previous knowledge networks in some form. However, most rodent laboratory tasks assume the animal to be naive with no previous experience influencing the results. Previous knowledge in form of a schema can facilitate knowledge acquisition and accelerate systems consolidation: memories become more rapidly hippocampal independent and instead rely more on the prefrontal cortex. Here, we developed a new spatial navigation task where food locations are learned in a large, gangway maze - the HexMaze. Analysing performance across sessions as well as on specific trials, we can show simple memory effects as well as multiple effects of previous knowledge accelerating both online learning and performance increases over offline periods. Importantly, we are the first to show that schema build-up is dependent on how much time passes, not how often the animal is trained.
]]></description>
<dc:creator>Bokeria, L.</dc:creator>
<dc:creator>Eichler, R.</dc:creator>
<dc:creator>Brincker, L.</dc:creator>
<dc:creator>Alonso, A.</dc:creator>
<dc:creator>Samanta, A.</dc:creator>
<dc:creator>Guardamagna, M.</dc:creator>
<dc:creator>Spooner, P.</dc:creator>
<dc:creator>Battaglia, F.</dc:creator>
<dc:creator>Genzel, L.</dc:creator>
<dc:date>2018-10-11</dc:date>
<dc:identifier>doi:10.1101/441048</dc:identifier>
<dc:title><![CDATA[The Hex-Maze: A previous knowledge task for mice]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-10-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/665398v1?rss=1">
<title>
<![CDATA[
Characterising group-level brain connectivity: a framework using Bayesian exponential random graph models 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/665398v1?rss=1"
</link>
<description><![CDATA[
The brain can be modelled as a network with nodes and edges derived from a range of imaging modalities: the nodes correspond to spatially distinct regions and the edges to the interactions between them. Whole-brain connectivity studies typically seek to determine how network properties change with a given categorical phenotype such as age-group, disease condition or mental state. To do so reliably, it is necessary to determine the features of the connectivity structure that are common across a group of brain scans. Given the complex interdependencies inherent in network data, this is not a straightforward task. Some studies construct a group-representative network (GRN), ignoring individual differences, while other studies analyse networks for each individual independently, ignoring information that is shared across individuals. We propose a Bayesian framework based on exponential random graph models (ERGM) extended to multiple networks to characterise the distribution of a entire population of networks. Using resting-state fMRI data from the Cam-CAN project, a study on healthy ageing, we demonstrate how our method can be used to characterise and compare the brains functional connectivity structure across a group of young individuals and a group of old individuals.
]]></description>
<dc:creator>Lehmann, B. C.</dc:creator>
<dc:creator>Henson, R. N.</dc:creator>
<dc:creator>Geerligs, L.</dc:creator>
<dc:creator>Cam-CAN,</dc:creator>
<dc:creator>White, S. R.</dc:creator>
<dc:date>2019-06-10</dc:date>
<dc:identifier>doi:10.1101/665398</dc:identifier>
<dc:title><![CDATA[Characterising group-level brain connectivity: a framework using Bayesian exponential random graph models]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-06-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.02.27.967463v1?rss=1">
<title>
<![CDATA[
Investigating the neuronal oscillatory correlates of the Gratton effect 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.02.27.967463v1?rss=1"
</link>
<description><![CDATA[
Rhythmic brain activity may provide a functional mechanism that facilitates dynamic interareal interactions and thereby give rise to complex behavior. It has been shown that low and high frequency oscillations propagate in opposite directions, but interactions between brain areas in various frequency bands are poorly understood. We investigated local and long-range synchrony in a brain-wide network and their relation to behavior, while human subjects executed a variant of the Simon task during MEG recording. We hypothesized that the behavioral difference for stimulus-response congruent (C) and incongruent (IC) trials is caused by differences in cortical synchrony, and that the relative behavioral benefit for trials following instances with the same stimulus-response contingency (i.e. the Gratton effect) is caused by contingency-induced changes in the state of the network. This would be achieved by temporarily upregulating the connectivity strength between behaviorally relevant network nodes. We identified regions-of-interest that differed in local synchrony during the response phase of the Simon task. Within this network, spectral power in none of the nodes in either of the studied frequencies was significantly different in the pre-cue window of the subsequent trial. Nor was there a significant difference in coherence between the task-relevant nodes that could explain the superior performance after compatible consecutive trials.
]]></description>
<dc:creator>van Es, M. W. J.</dc:creator>
<dc:creator>Gross, J.</dc:creator>
<dc:creator>Schoffelen, J.-M.</dc:creator>
<dc:date>2020-02-27</dc:date>
<dc:identifier>doi:10.1101/2020.02.27.967463</dc:identifier>
<dc:title><![CDATA[Investigating the neuronal oscillatory correlates of the Gratton effect]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-02-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.02.25.964932v1?rss=1">
<title>
<![CDATA[
The Drosophila FUS ortholog cabeza promotes adult founder myoblast selection by Xrp1-dependent regulation of FGF signaling 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.02.25.964932v1?rss=1"
</link>
<description><![CDATA[
The number of adult myofibers in Drosophila is determined by the number of founder myoblasts selected from a myoblast pool, a process governed by fibroblast growth factor (FGF) signaling. Here, we show that loss of cabeza (caz) function results in a reduced number of adult founder myoblasts, leading to a reduced number and misorientation of adult dorsal abdominal muscles. Genetic experiments revealed that loss of caz function in both adult myoblasts and neurons contributes to caz mutant muscle phenotypes. Selective overexpression of the FGF receptor Htl or the FGF receptor-specific signaling molecule Stumps in adult myoblasts partially rescued caz mutant muscle phenotypes, and Stumps levels were reduced in caz mutant founder myoblasts, indicating FGF pathway deregulation. In both adult myoblasts and neurons, caz mutant muscle phenotypes were mediated by increased expression levels of Xrp1, a DNA-binding protein involved in gene expression regulation. Xrp1-induced phenotypes were dependent on the DNA-binding capacity of its AT-hook motif, and increased Xrp1 levels in founder myoblasts reduced Stumps expression. Thus, control of Xrp1 expression by Caz is required for regulation of Stumps expression in founder myoblasts, resulting in correct founder myoblast selection.

Author SummarySkeletal muscles mediate movement, and therefore, proper structure and function of skeletal muscles is required for respiration, locomotion, and posture. Adult muscles arise from fusion of muscle precursor cells during development. In the fruit fly Drosophila melanogaster, muscle precursor cells come in two flavors: founder cells and fusion-competent cells. The number of founder cells selected during development corresponds to the number of adult muscles formed. Here, we report that inactivation of the Drosophila caz gene results in muscle developmental defects. Loss of caz function in both muscle precursor cells and the nerve cells that innervate muscles contributes to the muscle developmental defect. At the molecular level, loss of caz function leads to increased levels of Xrp1. Xrp1 regulates the expression of many other genes, including genes that produce components of the FGF signaling pathway, which is known to be involved in founder cell selection. In all, we uncovered a novel molecular mechanism that regulates founder cell selection during muscle development.
]]></description>
<dc:creator>Catinozzi, M.</dc:creator>
<dc:creator>Mallik, M.</dc:creator>
<dc:creator>Frickenhaus, M.</dc:creator>
<dc:creator>Been, M.</dc:creator>
<dc:creator>Sijlmans, C.</dc:creator>
<dc:creator>Kulshrestha, D.</dc:creator>
<dc:creator>Alexopoulos, I.</dc:creator>
<dc:creator>Weitkunat, M.</dc:creator>
<dc:creator>Schnorrer, F.</dc:creator>
<dc:creator>Storkebaum, E.</dc:creator>
<dc:date>2020-02-26</dc:date>
<dc:identifier>doi:10.1101/2020.02.25.964932</dc:identifier>
<dc:title><![CDATA[The Drosophila FUS ortholog cabeza promotes adult founder myoblast selection by Xrp1-dependent regulation of FGF signaling]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-02-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.02.24.963587v1?rss=1">
<title>
<![CDATA[
Mesoscopic-scale functional networks in the primate amygdala 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.02.24.963587v1?rss=1"
</link>
<description><![CDATA[
The primate amygdala performs multiple functions that may be related to the anatomical heterogeneity of its nuclei. At the level of single neurons, each function is reflected in stimulus- and task-specific responses. Given that neurons with a particular response profile are not clustered in any of the nuclei, single units may be too fine-grained to shed light on the mesoscale organization of the amygdala. We have extracted from local field potentials recorded simultaneously from multiple locations within the primate amygdala (Macaca mulatta) spatially defined and statistically separable responses to visual, tactile, and auditory stimuli. A generalized eigendecomposition-based method of source separation isolated coactivity patterns, or components, that in neurophysiological terms correspond to putative subnetworks. Some component spatial patterns mapped onto the anatomical organization of the amygdala, while other components reflected integration across nuclei. These components differentiated between visual, tactile, and auditory stimuli suggesting the presence of functionally distinct parallel subnetworks.
]]></description>
<dc:creator>Morrow, J. K.</dc:creator>
<dc:creator>Cohen, M. X.</dc:creator>
<dc:creator>Gothard, K. M.</dc:creator>
<dc:date>2020-02-26</dc:date>
<dc:identifier>doi:10.1101/2020.02.24.963587</dc:identifier>
<dc:title><![CDATA[Mesoscopic-scale functional networks in the primate amygdala]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-02-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.02.24.962761v1?rss=1">
<title>
<![CDATA[
Object selection by automatic spreading of top-down attentional signals in V1 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.02.24.962761v1?rss=1"
</link>
<description><![CDATA[
What is selected when attention is directed to a specific location of the visual field? Theories of object-based attention have suggested that when spatial attention is directed to part of an object, attention does not simply enhance the attended location but automatically spreads to enhance all locations that comprise the object. Here, we tested this hypothesis by reconstructing the distribution of attention from population neuronal activity patterns in V1 using functional magnetic resonance imaging (fMRI) and population-based receptive field mapping. We find that attention spreads from a spatially cued location to the underlying object - and enhances all spatial locations that comprise the object. Importantly, this spreading was also evident when the object was not task-relevant. These data suggest that attentional selection automatically operates at an object level, facilitating the reconstruction of coherent objects from fragmented representations in early visual cortex.
]]></description>
<dc:creator>Ekman, M.</dc:creator>
<dc:creator>Roelfsema, P.</dc:creator>
<dc:creator>de Lange, F.</dc:creator>
<dc:date>2020-02-25</dc:date>
<dc:identifier>doi:10.1101/2020.02.24.962761</dc:identifier>
<dc:title><![CDATA[Object selection by automatic spreading of top-down attentional signals in V1]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-02-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.01.31.928853v1?rss=1">
<title>
<![CDATA[
Effects of dopamine agonist treatment on resting-state network connectivity in Parkinson's disease 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.01.31.928853v1?rss=1"
</link>
<description><![CDATA[
Dopamine agonist (DA) medications commonly used to treat, or  normalise, motor symptoms of Parkinsons disease (PD) may lead to cognitive-neuropsychiatric side effects, such as increased impulsivity in decision-making. Subject-dependent variation in the neural response to dopamine modulation within cortico-basal ganglia circuitry is thought to play a key role in these latter, non-motor DA effects. This neuroimaging study combined resting-state functional magnetic resonance imaging (fMRI) with DA modification in patients with idiopathic PD, investigating whether brain  resting-state network (RSN) functional connectivity metrics identify disease-relevant effects of dopamine on systems-level neural processing. By comparing patients both  On and  Off their DA medications with age-matched, un-medicated healthy control subjects (HCs), we identified multiple non-normalising DA effects on frontal and basal ganglia RSN cortico-subcortical connectivity patterns in PD. Only a single isolated, potentially  normalising, DA effect on RSN connectivity in sensori-motor systems was observed, within cerebro-cerebellar neurocircuitry. Impulsivity in reward-based decision-making was positively correlated with ventral striatal connectivity within basal ganglia circuitry in HCs, but not in PD patients. Overall, we provide brain systems-level evidence for anomalous DA effects in PD on large-scale networks supporting cognition and motivated behaviour. Moreover, findings suggest that dysfunctional striatal and basal ganglia signalling patterns in PD are compensated for by increased recruitment of other cortico-subcortical and cerebro-cerebellar systems.
]]></description>
<dc:creator>Cole, D. M.</dc:creator>
<dc:creator>Mohammadi, B.</dc:creator>
<dc:creator>Milenkova, M.</dc:creator>
<dc:creator>Kollewe, K.</dc:creator>
<dc:creator>Schrader, C.</dc:creator>
<dc:creator>Samii, A.</dc:creator>
<dc:creator>Dengler, R.</dc:creator>
<dc:creator>Muente, T. F.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:date>2020-01-31</dc:date>
<dc:identifier>doi:10.1101/2020.01.31.928853</dc:identifier>
<dc:title><![CDATA[Effects of dopamine agonist treatment on resting-state network connectivity in Parkinson's disease]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-01-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.02.24.962779v1?rss=1">
<title>
<![CDATA[
The metabolite receptor SUCNR1 in oxidative stress-induced age-related macular degeneration 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.02.24.962779v1?rss=1"
</link>
<description><![CDATA[
Age-related macular degeneration (AMD) is the leading cause of vision impairment in elderly people. AMD is a multifactorial disease which is characterised by complex interactions between metabolic and environmental factors as well as multiple genetic susceptibility factors. The exact mechanism of the most prominent environmental factors, age and smoking, in combination with genetic susceptibility factors is little studied. Here, we set out to study the influence of age, smoking induced oxidative stress and the role of succinate receptor 1 (SUCNR1) in AMD development in mice.

Sucnr1 wild-type (WT), heterozygous (HT) and knock-out (KO) mice were exposed to smoking related oxidative stress by the addition of hydroquinone (HQ), the most abundant oxidant in cigarette smoke, to the drinking water of the mice. Using immunohistochemical staining, accumulation of oxidized LDL (oxLDL) in the mouse retina was assessed at 40 and 48 weeks of age.

At 40 weeks of age, a significant increase in oxLDL in the Sucnr1 KO mice treated with HQ was observed when compared to the WT and HT mice treated with HQ (p<0.01). However, at 48 weeks, no significant difference was observed between any of the groups. A second experiment analyzing the mice at 40 weeks of age was unable to confirm the observed results of the first experiment.

We identified oxLDL accumulations in Sucnr1 KO retinas exposed to HQ, but were unable to repeat this finding. Therefore, under the present conditions, the Sucnr1 KO mouse model is not a suitable model to study AMD development.
]]></description>
<dc:creator>Louer, E. M. M.</dc:creator>
<dc:creator>Deen, P. M. T.</dc:creator>
<dc:creator>Den Hollander, A. I.</dc:creator>
<dc:date>2020-02-25</dc:date>
<dc:identifier>doi:10.1101/2020.02.24.962779</dc:identifier>
<dc:title><![CDATA[The metabolite receptor SUCNR1 in oxidative stress-induced age-related macular degeneration]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-02-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.02.24.962282v1?rss=1">
<title>
<![CDATA[
A genetically encoded GRAB sensor for measuring serotonin dynamics in vivo 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.02.24.962282v1?rss=1"
</link>
<description><![CDATA[
Serotonin (5-HT) is a phylogenetically conserved monoamine neurotransmitter modulating a variety of processes in the brain. To directly visualize the dynamics of 5-HT, we developed a genetically encoded GPCR-Activation-Based 5-HT (GRAB5-HT) sensor with high sensitivity, selectivity, and spatiotemporal resolution. GRAB5-HT, detected 5-HT release in multiple physiological and pathological conditions in both flies and mice, and thus provides new insights into the dynamics and mechanisms of 5-HT signaling.
]]></description>
<dc:creator>Wan, J.</dc:creator>
<dc:creator>Peng, W.</dc:creator>
<dc:creator>Li, X.</dc:creator>
<dc:creator>Qian, T.</dc:creator>
<dc:creator>Song, K.</dc:creator>
<dc:creator>Zeng, J.</dc:creator>
<dc:creator>Deng, F.</dc:creator>
<dc:creator>Hao, S.</dc:creator>
<dc:creator>Feng, J.</dc:creator>
<dc:creator>Zhang, P.</dc:creator>
<dc:creator>Zhang, Y.</dc:creator>
<dc:creator>Zou, J.</dc:creator>
<dc:creator>Pan, S.</dc:creator>
<dc:creator>Zhu, J. J.</dc:creator>
<dc:creator>Jing, M.</dc:creator>
<dc:creator>Xu, M.</dc:creator>
<dc:creator>Li, Y.</dc:creator>
<dc:date>2020-02-25</dc:date>
<dc:identifier>doi:10.1101/2020.02.24.962282</dc:identifier>
<dc:title><![CDATA[A genetically encoded GRAB sensor for measuring serotonin dynamics in vivo]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-02-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.02.20.958314v1?rss=1">
<title>
<![CDATA[
Mapping human laryngeal motor cortex during vocalization 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.02.20.958314v1?rss=1"
</link>
<description><![CDATA[
The representations of the articulators involved in human speech production are organized somatotopically in primary motor cortex. The neural representation of the larynx, however, remains debated. Both a dorsal and a ventral larynx representation have been previously described. It is unknown, however, whether both representations are located in primary motor cortex. Here, we mapped the motor representations of the human larynx using fMRI and characterized the cortical microstructure underlying the activated regions. We isolated brain activity related to laryngeal activity during vocalization while controlling for breathing. We also mapped the articulators (the lips and tongue) and the hand area. We found two separate activations during vocalization - a dorsal and a ventral larynx representation. Structural and quantitative neuroimaging revealed that myelin content and cortical thickness underlying the dorsal, but not the ventral larynx representation, are similar to those of other primary motor representations. This finding confirms that the dorsal larynx representation is located in primary motor cortex and that the ventral one is not. We further speculate that the location of the ventral larynx representation is in premotor cortex, as seen in other primates. It remains unclear, however, whether and how these two representations differentially contribute to laryngeal motor control.
]]></description>
<dc:creator>Eichert, N.</dc:creator>
<dc:creator>Papp, D.</dc:creator>
<dc:creator>Mars, R. B.</dc:creator>
<dc:creator>Watkins, K. E.</dc:creator>
<dc:date>2020-02-21</dc:date>
<dc:identifier>doi:10.1101/2020.02.20.958314</dc:identifier>
<dc:title><![CDATA[Mapping human laryngeal motor cortex during vocalization]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-02-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.02.20.957506v1?rss=1">
<title>
<![CDATA[
Independent and sensitive gait parameters for objective evaluation in knee and hip osteoarthritis using wearable sensors 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.02.20.957506v1?rss=1"
</link>
<description><![CDATA[
ObjectiveTo identify non-redundant gait parameters sensitive to end-stage knee and hip osteoarthritis (OA), with a specific focus on turning, dual task performance, and upper body motion in addition to straight-ahead gait.

DesignGait was compared between individuals with unilateral, end-stage knee (n=25) or hip OA (n=26) scheduled for joint replacement, and healthy controls (n=27). For 2 minutes, subjects walked back-and-forth along a 6 meter trajectory making 180{degrees} turns, with and without a secondary cognitive task. Gait parameters were collected using 4 inertial measurement units on the feet and trunk. The dataset was reduced using factor analysis. One gait parameter from each factor was selected based on factor loading and effect size of the comparison between OA groups and healthy controls.

ResultsFour independent domains of gait were obtained: speed-spatial, speed-temporal, dual task cost, and upper body motion. Turning parameters did not constitute a separate domain. From these domains, stride length (speed-spatial) and cadence (speed-temporal) had the strongest factor loadings and effect sizes for both knee and hip OA, and lumbar sagittal range of motion (upper body motion) for hip OA only.

ConclusionsStride length, cadence, and lumbar sagittal range of motion were non-redundant and sensitive parameters, representing gait adaptations in individuals with knee or hip OA. Turning or dual task parameters had no additional value for evaluating gait in knee and hip OA. These findings hold promise for the objective evaluation of gait in the clinic. Future steps should include testing of responsiveness to interventions aiming to improve mobility.
]]></description>
<dc:creator>Boekesteijn, R. J.</dc:creator>
<dc:creator>Smolders, J. M. H.</dc:creator>
<dc:creator>Busch, V. J. J. F.</dc:creator>
<dc:creator>Geurts, A. C. H.</dc:creator>
<dc:creator>Smulders, K.</dc:creator>
<dc:date>2020-02-21</dc:date>
<dc:identifier>doi:10.1101/2020.02.20.957506</dc:identifier>
<dc:title><![CDATA[Independent and sensitive gait parameters for objective evaluation in knee and hip osteoarthritis using wearable sensors]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-02-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.02.20.957712v1?rss=1">
<title>
<![CDATA[
Two distinct types of eye-head coupling in freely moving mice 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.02.20.957712v1?rss=1"
</link>
<description><![CDATA[
Animals actively interact with their environment to gather sensory information. There is conflicting evidence about how mice use vision to sample their environment. During head restraint, mice make rapid eye movements strongly coupled between the eyes, similar to conjugate saccadic eye movements in humans. However, when mice are free to move their heads, eye movement patterns are more complex and often non-conjugate, with the eyes moving in opposite directions. Here, we combined eye tracking with head motion measurements in freely moving mice and found that both observations can be explained by the existence of two distinct types of coupling between eye and head movements. The first type comprised non-conjugate eye movements which systematically compensated for changes in head tilt to maintain approximately the same visual field relative to the horizontal ground plane. The second type of eye movements were conjugate and coupled to head yaw rotation to produce a "saccade and fixate" gaze pattern. During head initiated saccades, the eyes moved together in the same direction as the head, but during subsequent fixation moved in the opposite direction to the head to compensate for head rotation. This "saccade and fixate" pattern is similar to that seen in humans who use eye movements (with or without head movement) to rapidly shift gaze but in mice relies on combined eye and head movements. Indeed, the two types of eye movements very rarely occurred in the absence of head movements. Even in head-restrained mice, eye movements were invariably associated with attempted head motion. Both types of eye-head coupling were seen in freely moving mice during social interactions and a visually-guided object tracking task. Our results reveal that mice use a combination of head and eye movements to sample their environment and highlight the similarities and differences between eye movements in mice and humans.

HighlightsO_LITracking of eyes and head in freely moving mice reveals two types of eye-head coupling
C_LIO_LIEye/head tilt coupling aligns gaze to horizontal plane
C_LIO_LIRotational eye and head coupling produces a "saccade and fixate" gaze pattern with head leading the eye
C_LIO_LIBoth types of eye-head coupling are maintained during visually-guided behaviors
C_LIO_LIEye movements in head-restrained mice are related to attempted head movements
C_LI
]]></description>
<dc:creator>Meyer, A. F.</dc:creator>
<dc:creator>O'Keefe, J.</dc:creator>
<dc:creator>Poort, J.</dc:creator>
<dc:date>2020-02-20</dc:date>
<dc:identifier>doi:10.1101/2020.02.20.957712</dc:identifier>
<dc:title><![CDATA[Two distinct types of eye-head coupling in freely moving mice]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-02-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.02.18.954438v1?rss=1">
<title>
<![CDATA[
GADL1 is a multifunctional decarboxylase with tissue specific roles in β-alanine and carnosine production 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.02.18.954438v1?rss=1"
</link>
<description><![CDATA[
Carnosine and related {beta}-alanine-containing peptides are believed to be important antioxidants, pH-buffers and neuromodulators. However, their biosynthetic routes and therapeutic potential are still being debated. This study describes the first animal model lacking the enzyme glutamic acid decarboxylase-like 1 (GADL1). We show that Gadl1-/-mice are deficient in {beta}-alanine, carnosine and anserine, particularly in the olfactory bulb, cerebral cortex, and skeletal muscle. Gadl1-/-mice also exhibited decreased anxiety, increased levels of oxidative stress markers, alterations in energy and lipid metabolism, and age-related changes. Examination of the GADL1 active site indicated that the enzyme may have multiple physiological substrates, including aspartate and cysteine sulfinic acid, compatible with organ-specific functions. Human genetic studies show strong associations of the GADL1 locus with plasma levels of carnosine, subjective well-being, and muscle strength, also indicating a role for {beta}-alanine and its peptide derivatives in these traits. Together, this shows the multifaceted and organ specific roles of carnosine peptides and establishes Gadl1 knockout mice as a versatile model to explore carnosine biology and its therapeutic potential.
]]></description>
<dc:creator>Mahootchi, E.</dc:creator>
<dc:creator>Himaei, S. C.</dc:creator>
<dc:creator>Kleppe, R.</dc:creator>
<dc:creator>Winge, I.</dc:creator>
<dc:creator>Hegvik, T.-A.</dc:creator>
<dc:creator>Megias-Perez, R.</dc:creator>
<dc:creator>Totland, C.</dc:creator>
<dc:creator>Mogavero, F.</dc:creator>
<dc:creator>Baumann, A.</dc:creator>
<dc:creator>Glennon, J.</dc:creator>
<dc:creator>Miletic, H.</dc:creator>
<dc:creator>Kursula, P.</dc:creator>
<dc:creator>Haavik, J.</dc:creator>
<dc:date>2020-02-18</dc:date>
<dc:identifier>doi:10.1101/2020.02.18.954438</dc:identifier>
<dc:title><![CDATA[GADL1 is a multifunctional decarboxylase with tissue specific roles in β-alanine and carnosine production]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-02-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.02.14.948992v1?rss=1">
<title>
<![CDATA[
Visual Attention Through Uncertainty Minimization in Recurrent Generative Models 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.02.14.948992v1?rss=1"
</link>
<description><![CDATA[
Allocating visual attention through saccadic eye movements is a key ability of intelligent agents. Attention is both influenced through bottom-up stimulus properties as well as top-down task demands. The interaction of these two attention mechanisms is not yet fully understood. A parsimonious reconciliation posits that both processes serve the minimization of predictive uncertainty. We propose a recurrent generative neural network model that predicts a visual scene based on foveated glimpses. The model shifts its attention in order to minimize the uncertainty in its predictions. We show that the proposed model produces naturalistic eye movements focusing on informative stimulus regions. Introducing additional tasks modulates the saccade patterns towards task-relevant stimulus regions. The models saccade characteristics correspond well with previous experimental data in humans, providing evidence that uncertainty minimization could be a fundamental mechanisms for the allocation of visual attention.
]]></description>
<dc:creator>Standvoss, K.</dc:creator>
<dc:creator>Quax, S. C.</dc:creator>
<dc:creator>van Gerven, M. A. J.</dc:creator>
<dc:date>2020-02-14</dc:date>
<dc:identifier>doi:10.1101/2020.02.14.948992</dc:identifier>
<dc:title><![CDATA[Visual Attention Through Uncertainty Minimization in Recurrent Generative Models]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-02-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.02.14.948919v1?rss=1">
<title>
<![CDATA[
Opposite effects of choice history and stimulus history resolve a paradox of sequential choice bias 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.02.14.948919v1?rss=1"
</link>
<description><![CDATA[
Perceptual decisions are biased towards previous decisions. Previous research suggests that this choice repetition bias is increased after previous decisions of high confidence, as inferred from response time measures (Urai et al., 2017), but also when previous decisions were based on weak sensory evidence (Akaishi et al., 2014). As weak sensory evidence is typically associated with low confidence, these previous findings appear conflicting. To resolve this conflict, we set out to investigate the effect of decision confidence on choice repetition more directly by measuring explicit confidence ratings in a motion coherence discrimination task. Moreover, we explored how choice and stimulus history jointly affect subsequent perceptual choices. We found that participants were more likely to repeat previous choices of high subjective confidence, as well as previous fast choices, confirming the boost of choice repetition with decision confidence. Furthermore, we discovered that current choices were biased away from the previous evidence direction, not previous choice, and that this effect grew with previous evidence strength. These findings point towards simultaneous biases of choice repetition, modulated by decision confidence, and adaptation, modulated by the strength of evidence, which bias current perceptual decisions in opposite directions.
]]></description>
<dc:creator>Bosch, E.</dc:creator>
<dc:creator>Fritsche, M.</dc:creator>
<dc:creator>Ehinger, B. V.</dc:creator>
<dc:creator>de Lange, F. P.</dc:creator>
<dc:date>2020-02-14</dc:date>
<dc:identifier>doi:10.1101/2020.02.14.948919</dc:identifier>
<dc:title><![CDATA[Opposite effects of choice history and stimulus history resolve a paradox of sequential choice bias]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-02-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.02.05.935676v1?rss=1">
<title>
<![CDATA[
Structure and meaning organize neural oscillations into a content-specific hierarchy 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.02.05.935676v1?rss=1"
</link>
<description><![CDATA[
Neural oscillations track linguistic information during speech comprehension (e.g., Ding et al., 2016; Keitel et al., 2018), and are known to be modulated by acoustic landmarks and speech intelligibility (e.g., Zoefel & VanRullen, 2015). But, it is unclear what information (e.g., timing, rhythm, or content) the brain utilizes to generate linguistic structure and meaning beyond the information that is present in the physical stimulus. We used electroencephalography (EEG) to investigate whether oscillations are modulated by linguistic content over and above the speech stimulus rhythmicity and temporal distribution. We manipulated the presence of semantic and syntactic information apart from the timescale of their occurrence, and controlled for the acoustic-prosodic and lexical-semantic information in the signal. EEG was recorded while 29 adult native speakers of all genders listened to naturally-spoken Dutch sentences, jabberwocky controls with a sentence-like prosodic rhythm and morphemes, word lists with lexical content but no phrase structure, and backwards acoustically-matched controls. Mutual information (MI) analysis revealed sensitivity to linguistic content: Phase MI was highest for sentences at the phrasal (0.8-1.1 Hz) and lexical timescale (1.9-2.8 Hz), suggesting that the delta-band is modulated by lexically-driven combinatorial processing beyond prosody, and that linguistic content (i.e., structure and meaning) organizes the phase of neural oscillations beyond the timescale and rhythmicity of the stimulus. This pattern is consistent with neurophysiologically-inspired models of language comprehension (Martin, 2016, 2020; Martin & Doumas, 2017) where oscillations encode endogenously-generated linguistic content over and above exogenous or stimulus-driven timing and rhythm information.

Significance StatementBiological systems like the brain encode their environment not only by reacting in a series of stimulus-driven responses, but by combining stimulus-driven information with endogenous, internally-generated, inferential knowledge and meaning. Understanding language from speech is the human benchmark for this. Much research focusses on the purely stimulus-driven response, but here, we focus on the goal of language behavior: conveying structure and meaning. To that end, we use naturalistic stimuli that contrast acoustic-prosodic and lexical-semantic information to show that, during spoken language comprehension, oscillatory modulations reflect computations related to inferring structure and meaning from the acoustic signal. Our experiment provides the first evidence to date that compositional structure and meaning organize the oscillatory response, above and beyond acoustic and lexical controls.
]]></description>
<dc:creator>Kaufeld, G.</dc:creator>
<dc:creator>Bosker, H. R.</dc:creator>
<dc:creator>Alday, P. M.</dc:creator>
<dc:creator>Meyer, A. S.</dc:creator>
<dc:creator>Martin, A. E.</dc:creator>
<dc:date>2020-02-07</dc:date>
<dc:identifier>doi:10.1101/2020.02.05.935676</dc:identifier>
<dc:title><![CDATA[Structure and meaning organize neural oscillations into a content-specific hierarchy]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-02-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.02.09.940841v1?rss=1">
<title>
<![CDATA[
Cortical network mechanisms of response inhibition 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.02.09.940841v1?rss=1"
</link>
<description><![CDATA[
Both the right inferior frontal gyrus (rIFG) and the pre-supplementary motor area (pre-SMA) are crucial for successful response inhibition. However, the particular functional roles of those two regions have been controversially debated for more than a decade now. It is unclear whether the rIFG directly initiates stopping or serves an attentional function, whereas the stopping is triggered by the pre-SMA. The current multimodal MEG/fMRI study sought to clarify the role and temporal activation order of both regions in response inhibition using a selective stopping task. This task dissociates inhibitory from attentional processes. Our results reliably reveal a temporal precedence of rIFG over pre-SMA. Moreover, connectivity during response inhibition is directed from rIFG to pre-SMA and predicts stopping performance. Response inhibition is implemented via beta-band oscillations. Our findings support the hypothesis that response inhibition is initiated by the rIFG as a form of attention-independent top-down control.
]]></description>
<dc:creator>Schaum, M.</dc:creator>
<dc:creator>Pinzuti, E.</dc:creator>
<dc:creator>Sebastian, A.</dc:creator>
<dc:creator>Lieb, K.</dc:creator>
<dc:creator>Fries, P.</dc:creator>
<dc:creator>Mobascher, A.</dc:creator>
<dc:creator>Jung, P.</dc:creator>
<dc:creator>Wibral, M.</dc:creator>
<dc:creator>Tuescher, O.</dc:creator>
<dc:date>2020-02-10</dc:date>
<dc:identifier>doi:10.1101/2020.02.09.940841</dc:identifier>
<dc:title><![CDATA[Cortical network mechanisms of response inhibition]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-02-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/803718v1?rss=1">
<title>
<![CDATA[
Probing the neural dynamics of mnemonic representations in humans 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/803718v1?rss=1"
</link>
<description><![CDATA[
Memories are not stored as static engrams, but as dynamic representations affected by processes occurring after initial encoding. Previous studies revealed changes in activity and mnemonic representations in visual processing areas, parietal lobe, and hippocampus underlying repeated retrieval and suppression. However, these neural changes are usually induced by memory modulation immediately after memory formation. Here, we investigated 27 healthy participants with a two-day functional Magnetic Resonance Imaging design to probe how established memories are dynamically modulated by retrieval and suppression 24 hours after learning. Behaviorally, we demonstrated that established memories can still be strengthened by repeated retrieval. By contrast, repeated suppression had a modest negative effect, and suppression-induced forgetting was associated with individual suppression efficacy. Neurally, we demonstrated item-specific pattern reinstatements in visual processing areas, parietal lobe, and hippocampus. Then, we showed that repeated retrieval reduced activity amplitude in the ventral visual cortex and hippocampus, but enhanced the distinctiveness of activity patterns in the ventral visual cortex and parietal lobe. Critically, reduced activity was associated with enhanced representation of idiosyncratic memory traces in ventral visual cortex and precuneus. In contrast, repeated memory suppression was associated with the reduced lateral prefrontal activity, but relative intact mnemonic representations. Our results replicated most of the neural changes induced by memory retrieval and suppression immediately after learning and extended those findings to established memories after initial consolidation. Active retrieval seems to promote episode-unique mnemonic representations in the neocortex after initial encoding but also consolidation.

HighlightsO_LIRepeated retrieval strengthened consolidated memories, while repeated suppression had a modest negative effect.
C_LIO_LIPattern reinstatements of individual memories were detected in the visual area, parietal lobe, and hippocampus after 24 hours.
C_LIO_LIAfter repeated retrieval, reduced activity amplitude was associated with increased distinctiveness of activity patterns in the ventral visual cortex and right precuneus.
C_LIO_LIRepeated suppression was associated with the reduced lateral prefrontal activity, but unchanged mnemonic representations.
C_LI
]]></description>
<dc:creator>Liu, W.</dc:creator>
<dc:creator>Kohn, N.</dc:creator>
<dc:creator>Fernandez, G.</dc:creator>
<dc:date>2019-10-15</dc:date>
<dc:identifier>doi:10.1101/803718</dc:identifier>
<dc:title><![CDATA[Probing the neural dynamics of mnemonic representations in humans]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.02.07.939504v1?rss=1">
<title>
<![CDATA[
A fast genetically encoded fluorescent sensor for faithful in vivo acetylcholine detection in mice, fish, worms and flies 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.02.07.939504v1?rss=1"
</link>
<description><![CDATA[
Here we design and optimize a genetically encoded fluorescent indicator, iAChSnFR, for the ubiquitous neurotransmitter acetylcholine, based on a bacterial periplasmic binding protein. iAChSnFR shows large fluorescence changes, rapid rise and decay kinetics, and insensitivity to most cholinergic drugs. iAChSnFR revealed large transients in a variety of slice and in vivo preparations in mouse, fish, fly and worm. iAChSnFR will be useful for the study of acetylcholine in all animals.
]]></description>
<dc:creator>Borden, P. M.</dc:creator>
<dc:creator>Zhang, P.</dc:creator>
<dc:creator>Shivange, A. V.</dc:creator>
<dc:creator>Marvin, J. S.</dc:creator>
<dc:creator>Cichon, J.</dc:creator>
<dc:creator>Dan, C.</dc:creator>
<dc:creator>Podgorski, K.</dc:creator>
<dc:creator>Figueiredo, A.</dc:creator>
<dc:creator>Novak, O.</dc:creator>
<dc:creator>Tanimoto, M.</dc:creator>
<dc:creator>Shigetomi, E.</dc:creator>
<dc:creator>Lobas, M. A.</dc:creator>
<dc:creator>Kim, H.</dc:creator>
<dc:creator>Zhu, P. K.</dc:creator>
<dc:creator>Zhang, Y.</dc:creator>
<dc:creator>Zheng, W. S.</dc:creator>
<dc:creator>Fan, C.</dc:creator>
<dc:creator>Wang, G.</dc:creator>
<dc:creator>Xiang, B.</dc:creator>
<dc:creator>Gan, L.</dc:creator>
<dc:creator>Zhang, G.-X.</dc:creator>
<dc:creator>Guo, K.</dc:creator>
<dc:creator>Lin, L.</dc:creator>
<dc:creator>Cai, Y.</dc:creator>
<dc:creator>Yee, A.</dc:creator>
<dc:creator>Aggarwal, A.</dc:creator>
<dc:creator>Ford, C. P.</dc:creator>
<dc:creator>Rees, D. C.</dc:creator>
<dc:creator>Dietrich, D.</dc:creator>
<dc:creator>KHAKH, B. S.</dc:creator>
<dc:creator>Dittman, J. S.</dc:creator>
<dc:creator>Gan, W.-B.</dc:creator>
<dc:creator>Koyama, M. S.</dc:creator>
<dc:creator>Jayaraman, V.</dc:creator>
<dc:creator>Cheer, J. F.</dc:creator>
<dc:creator>Lester, H. A.</dc:creator>
<dc:creator>Zhu, J. J.</dc:creator>
<dc:creator>Looger, L. L.</dc:creator>
<dc:date>2020-02-08</dc:date>
<dc:identifier>doi:10.1101/2020.02.07.939504</dc:identifier>
<dc:title><![CDATA[A fast genetically encoded fluorescent sensor for faithful in vivo acetylcholine detection in mice, fish, worms and flies]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-02-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.02.04.933606v1?rss=1">
<title>
<![CDATA[
Mindfulness meditation experience is associated with increased ability to monitor covert somatosensory attention 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.02.04.933606v1?rss=1"
</link>
<description><![CDATA[
The distinguishing practice of mindfulness meditation is the intentional regulation of attention towards the present moment. Mindfulness meditation therefore emphasizes metacognitive functions, in particular the ability to monitor the attentional focus on a moment-by-moment basis. In this study we set out to test whether mindfulness meditation experience is associated with an increased ability to monitor moment-by-moment fluctuation in the attentional state. In response to auditory cues, participants maintained somatosensory attention to either their left or right hand. At random moments, trials were terminated by a probe sound to which participants reported their level of attention at that moment. MEG was recorded during the attention interval preceding probe onset. Using a beamformer approach, alpha activity in contralateral primary somatosensory regions was quantified. Alpha activity for self-reported high versus low attention trials was compared both within and between groups of either highly experienced experienced mindfulness meditators, novice meditators or meditation-naive participants (controls). As predicted, generally contralateral alpha power was associated with self-reported attention. Novice meditators (< 1000 h of meditation) showed temporal profiles similar to controls, displaying a correspondence between self-report and alpha power preceding probe onset. Expert meditators (>> 1000 h) showed a strikingly different pattern, however. Their self-reported attentional state corresponded with alpha power during a more extended time interval preceding those of controls and novice meditators. In addition, self-reported low attention trials showed a distinctive alpha suppression preceding probe onset, suggesting that the ability for moment-by-moment monitoring of the attentional state permitted greater attentional control.
]]></description>
<dc:creator>Whitmarsh, S.</dc:creator>
<dc:creator>Jensen, O.</dc:creator>
<dc:creator>Barendregt, H.</dc:creator>
<dc:date>2020-02-04</dc:date>
<dc:identifier>doi:10.1101/2020.02.04.933606</dc:identifier>
<dc:title><![CDATA[Mindfulness meditation experience is associated with increased ability to monitor covert somatosensory attention]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-02-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.02.04.933382v1?rss=1">
<title>
<![CDATA[
Prestimulus alpha power is related to the strength of stimulus representation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.02.04.933382v1?rss=1"
</link>
<description><![CDATA[
Spatial attention can modulate behavioural performance and is associated with several electrophysiological markers. In this study, we used multivariate pattern analysis in electrophysiology data to investigate the effects of covert spatial attention on the quality of stimulus processing and underlying mechanisms. Our results show that covert spatial attention led to (i) an anticipatory alpha power desynchronization; (ii) enhanced stimuli identity information. Moreover, we found that alpha power fluctuations in anticipation of the relevant stimuli boosted and prolonged the coding of stimulus identity.
]]></description>
<dc:creator>Barne, L. C.</dc:creator>
<dc:creator>de Lange, F.</dc:creator>
<dc:creator>Cravo, A. M.</dc:creator>
<dc:date>2020-02-04</dc:date>
<dc:identifier>doi:10.1101/2020.02.04.933382</dc:identifier>
<dc:title><![CDATA[Prestimulus alpha power is related to the strength of stimulus representation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-02-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/685560v1?rss=1">
<title>
<![CDATA[
Enlarging the Scope of Randomization and Permutation Tests in Neuroimaging and Neuroscience 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/685560v1?rss=1"
</link>
<description><![CDATA[
Especially for the high-dimensional data collected in neuroscience, nonparametric statistical tests are an excellent alternative for parametric statistical tests. Because of the freedom to use any function of the data as a test statistic, nonparametric tests have the potential for a drastic increase in sensitivity by making a biologically-informed choice for a test statistic. In a companion paper (Geerligs & Maris, 2020), we demonstrate that such a drastic increase is actually possible. This increase in sensitivity is only useful if, at the same time, the false alarm (FA) rate can be controlled. However, for some study types (e.g., within-participant studies), nonparametric tests do not control the FA rate (see Eklund, Nichols, & Knutsson, 2016). In the present paper, we present a family of nonparametric randomization and permutation tests of which we prove exact FA rate control. Crucially, these proofs hold for a much larger family of study types than before, and they include both within-participant studies and studies in which the explanatory variable is not under experimental control. The crucial element of this statistical innovation is the adoption of a novel but highly relevant null hypothesis: statistical independence between the biological and the explanatory variable.
]]></description>
<dc:creator>Maris, E.</dc:creator>
<dc:date>2019-06-28</dc:date>
<dc:identifier>doi:10.1101/685560</dc:identifier>
<dc:title><![CDATA[Enlarging the Scope of Randomization and Permutation Tests in Neuroimaging and Neuroscience]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-06-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.01.27.921619v1?rss=1">
<title>
<![CDATA[
Evaluation of DNA extraction protocols from liquid-based cytology specimens for studying cervical microbiota 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.01.27.921619v1?rss=1"
</link>
<description><![CDATA[
Cervical microbiota (CM) are considered an important factor affecting the progression of cervical intraepithelial neoplasia (CIN) and are implicated in the persistence of human papillomavirus (HPV). Collection of liquid-based cytology (LBC) samples is routine for cervical cancer screening and HPV genotyping and can be used for long-term cytological biobanking. We sought to determine whether it is possible to access microbial DNA from LBC specimens, and compared the performance of four different extraction protocols: (ZymoBIOMICS DNA Miniprep Kit; QIAamp PowerFecal Pro DNA Kit; QIAamp DNA Mini Kit; and IndiSpin Pathogen Kit) and their ability to capture the diversity of CM from LBC specimens. LBC specimens from 20 patients (stored for 716 {+/-} 105 days) with CIN values of 2 or 3 were each aliquoted for each of the four kits. Loss of microbial diversity due to long-term LBC storage could not be assessed due to lack of fresh LBC samples. Comparisons with other types of cervical sampling were not performed. We observed that all DNA extraction kits provided equivalent accessibility to the cervical microbial DNA within stored LBC samples. Approximately 80% microbial genera were shared among all DNA extraction protocols. Potential kit contaminants were observed as well. Variation between individuals was a significantly greater influence on the observed microbial composition than was the method of DNA extraction. We also observed that HPV16 was significantly associated with community types that were not dominated by Lactobacillus iners.
]]></description>
<dc:creator>Shibata, T.</dc:creator>
<dc:creator>Nakagawa, M.</dc:creator>
<dc:creator>Coleman, H. N.</dc:creator>
<dc:creator>Owens, S. M.</dc:creator>
<dc:creator>Greenfield, W. W.</dc:creator>
<dc:creator>Sasagawa, T.</dc:creator>
<dc:creator>Robeson, M. S.</dc:creator>
<dc:date>2020-01-28</dc:date>
<dc:identifier>doi:10.1101/2020.01.27.921619</dc:identifier>
<dc:title><![CDATA[Evaluation of DNA extraction protocols from liquid-based cytology specimens for studying cervical microbiota]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-01-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/839969v1?rss=1">
<title>
<![CDATA[
Patterns of socio-cognitive stratification and perinatal risk in the child brain 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/839969v1?rss=1"
</link>
<description><![CDATA[
The expanding behavioral repertoire of the developing brain during childhood and adolescence is shaped by complex brain-environment interactions and flavored by unique life experiences. The transition into young adulthood offer opportunities for adaptation and growth, but also increased susceptibility to environmental perturbations, such as the characteristics of social relationships, family environment, quality of schools and activities, financial security, urbanization and pollution, drugs, cultural practices, and values, that all act in concert with our genetic architecture and biology. Our multivariate brain-behavior mapping in 7,577 children aged 9-11 years across 585 brain imaging phenotypes, and 617 cognitive, behavioral, psychosocial and socioeconomic measures revealed three population modes of brain co-variation, which were robust as assessed by cross-validation and permutation testing, taking into account siblings and twins, identified using genetic data. The first mode revealed traces of perinatal complications, including pre-term and twin-birth, eclampsia and toxemia, shorter period of breast feeding and lower cognitive scores, with higher cortical thickness and lower cortical areas and volumes. The second mode reflected a pattern of socio-cognitive stratification, linking lower cognitive ability and socioeconomic status to lower cortical thickness, area and volumes. The third mote captured a pattern related to urbanicity, with particulate matter pollution (PM25) inversely related to home value, walkability and population density, associated with diffusion properties of white matter tracts. These results underscore the importance of a multidimensional and interdisciplinary understanding, integrating social, psychological and biological sciences, to map the constituents of healthy development and to identify factors that may precede maladjustment and mental illness.
]]></description>
<dc:creator>Alnaes, D.</dc:creator>
<dc:creator>Kaufmann, T.</dc:creator>
<dc:creator>Marquand, A. F.</dc:creator>
<dc:creator>Smith, S. M.</dc:creator>
<dc:creator>Westlye, L. T.</dc:creator>
<dc:date>2019-11-13</dc:date>
<dc:identifier>doi:10.1101/839969</dc:identifier>
<dc:title><![CDATA[Patterns of socio-cognitive stratification and perinatal risk in the child brain]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-11-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.01.24.918516v1?rss=1">
<title>
<![CDATA[
A comprehensive atlas of white matter tracts in the chimpanzee 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.01.24.918516v1?rss=1"
</link>
<description><![CDATA[
Chimpanzees (Pan troglodytes) are, along with bonobos, humans closest living relatives. The advent of diffusion MRI tractography in recent years has allowed a resurgence of comparative neuroanatomical studies in humans and other primate species. Here we offer, in comparative perspective, the first chimpanzee white matter atlas, constructed from in vivo chimpanzee diffusion-weighted scans. Comparative white matter atlases provide a useful tool for identifying neuroanatomical differences and similarities between humans and other primate species. Until now, comprehensive fascicular atlases have been created for humans (Homo sapiens), rhesus macaques (Macaca mulatta), and several other nonhuman primate species, but never in a nonhuman ape. Information on chimpanzee neuroanatomy is essential for understanding the anatomical specializations of white matter organization that are unique to the human lineage.
]]></description>
<dc:creator>Bryant, K. L.</dc:creator>
<dc:creator>Li, L.</dc:creator>
<dc:creator>Mars, R. B.</dc:creator>
<dc:date>2020-01-25</dc:date>
<dc:identifier>doi:10.1101/2020.01.24.918516</dc:identifier>
<dc:title><![CDATA[A comprehensive atlas of white matter tracts in the chimpanzee]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-01-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/782649v1?rss=1">
<title>
<![CDATA[
New insights on the ventral attention network: Inhibition and recruitment during a bimodal task 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/782649v1?rss=1"
</link>
<description><![CDATA[
Reorienting attention to unexpected events is essential in daily life. fMRI studies have revealed the involvement of the ventral attention network (VAN), including the temporo-parietal junction (TPJ), in such process. In this MEG study with 34 participants (17 women) we used a bimodal (visual/auditory) attention task to determine the neuronal dynamics associated with suppression of the activity of the VAN during top-down attention and its recruitment when information from the unattended sensory modality is involuntarily integrated. We observed an anticipatory power increase of alpha/beta (12-20 Hz) oscillations in the VAN following a cue indicating the modality to attend. Stronger VAN power increases predicted better task performance, suggesting that the VAN suppression prevents shifting attention to distractors. Moreover, the TPJ was synchronized with the frontal eye field in that frequency band, suggesting that the dorsal attention network (DAN) might participate in such suppression. Furthermore, we found a 12-20 Hz power decrease, in both the VAN and DAN, when information of both sensory modalities was congruent, suggesting an involvement of these networks for attention capture. Our results show that effective multimodal attentional reorientation includes the modulation of the VAN and DAN through upper-alpha/beta oscillations. Altogether these results indicate that the suppressing role of alpha/beta oscillations might operate beyond sensory regions.

SIGNIFICANCE STATEMENTReorienting attention to unexpected events from multiple sensory sources is essential in daily life. We explored the dynamics of the ventral attention network (VAN), a set of brain regions related to attentional reorienting, when relevant information was anticipated (i.e. during top-down attention) and when unexpected congruent information from another sensory modality was presented (involuntary attentional capture). We report that activity in the alpha/beta range (12-20 Hz) within the VAN indexed both top-down and attentional capture processes. Also, the VAN was synchronized with the dorsal attention network in this frequency band, suggesting an integrated role of both networks for attentional regulation. Our results shed light on the neurophysiological mechanisms that the brain carry out for reorienting attention to relevant environmental stimuli.
]]></description>
<dc:creator>Solis-Vivanco, R.</dc:creator>
<dc:creator>Jensen, O.</dc:creator>
<dc:creator>Bonnefond, M.</dc:creator>
<dc:date>2019-09-26</dc:date>
<dc:identifier>doi:10.1101/782649</dc:identifier>
<dc:title><![CDATA[New insights on the ventral attention network: Inhibition and recruitment during a bimodal task]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.01.22.915553v1?rss=1">
<title>
<![CDATA[
A Bayesian and efficient observer model explains concurrent attractive and repulsive history biases in visual perception 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.01.22.915553v1?rss=1"
</link>
<description><![CDATA[
Perceptual decisions can be repelled away from (repulsive adaptation) or attracted towards recent visual experience (attractive serial dependence). It is currently unclear whether and how these repulsive and attractive biases interact during visual processing and what computational principles may underlie these history dependencies. In the current study, we disentangle repulsive and attractive biases by exploring the respective timescales over which current visual processing is influenced by previous experience. Across four experiments, we find that perceptual decisions about stimulus orientation are concurrently attracted towards the short-term perceptual history and repelled from stimuli experienced up to minutes into the past. We show that the temporal pattern of short-term attraction and long-term repulsion cannot be captured by an ideal Bayesian observer model alone. Instead, it is well captured by an ideal observer model with efficient encoding and Bayesian decoding of visual information in a slowly changing environment. Concurrent attractive and repulsive history biases in perceptual decisions may thus be the consequence of the need for visual processing to simultaneously satisfy constraints of both efficiency and stability.
]]></description>
<dc:creator>Fritsche, M.</dc:creator>
<dc:creator>Spaak, E.</dc:creator>
<dc:creator>de Lange, F. P.</dc:creator>
<dc:date>2020-01-23</dc:date>
<dc:identifier>doi:10.1101/2020.01.22.915553</dc:identifier>
<dc:title><![CDATA[A Bayesian and efficient observer model explains concurrent attractive and repulsive history biases in visual perception]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-01-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/778134v1?rss=1">
<title>
<![CDATA[
Dopamine Promotes Cognitive Effort by Biasing the Benefits Versus Costs of Cognitive Work 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/778134v1?rss=1"
</link>
<description><![CDATA[
Stimulants like methylphenidate are increasingly used for cognitive enhancement, but precise mechanisms are unknown. We found that methylphenidate boosts willingness to expend cognitive effort by altering the benefit-to-cost ratio of cognitive work. Willingness to expend effort was greater for participants with higher striatal dopamine synthesis capacity, while methylphenidate and sulpiride - a selective D2 receptor antagonist - increased cognitive motivation more for participants with lower synthesis capacity. A sequential sampling model informed by momentary gaze revealed that decisions to expend effort are related to amplification of benefit-versus-cost information attended early in the decision process, while the effect of benefits is strengthened with higher synthesis capacity and by methylphenidate. These findings demonstrate that methylphenidate boosts the perceived benefits-versus-costs of cognitive effort by modulating striatal dopamine signaling.

One Sentence SummaryStriatal dopamine increases cognitive effort by respectively amplifying and attenuating the subjective benefits and costs of cognitive control.
]]></description>
<dc:creator>Westbrook, A.</dc:creator>
<dc:creator>van den Bosch, R.</dc:creator>
<dc:creator>Määttä, J.</dc:creator>
<dc:creator>Hofmans, L.</dc:creator>
<dc:creator>Papadopetraki, D.</dc:creator>
<dc:creator>Cools, R.</dc:creator>
<dc:creator>Frank, M. J.</dc:creator>
<dc:date>2019-09-23</dc:date>
<dc:identifier>doi:10.1101/778134</dc:identifier>
<dc:title><![CDATA[Dopamine Promotes Cognitive Effort by Biasing the Benefits Versus Costs of Cognitive Work]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.01.13.904532v1?rss=1">
<title>
<![CDATA[
Distraction attenuates goal-directed neural responses for food rewards 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.01.13.904532v1?rss=1"
</link>
<description><![CDATA[
Distracted eating can lead to increased food intake, but it is unclear how. We hypothesized that distraction affects the change in motivated responses for food reward after satiation. To investigate this, 38 healthy normal-weight participants (28F, 10M) performed a detection task varying in attentional load (high or low distraction) during fMRI. Simultaneously, they exerted effort for food rewards (sweet or savory) by repeated button presses. Two fMRI runs were separated by outcome devaluation (satiation) of one of the reward outcomes, to assess outcome-sensitive, i.e. goal-directed, responses. Behavioral results showed no effect of distraction on effort for food reward following outcome devaluation. At an uncorrected threshold (p<0.001), distraction decreased goal-directed responses (devalued versus valued) in the right inferior frontal gyrus (rIFG). Importantly, these distraction-sensitive rIFG responses correlated negatively (r = - 0.40, p = 0.014) with the effect of distraction on the number of button presses. Specifically, decreased rIFG responses due to distraction related to increased button presses for food reward after satiation, in line with the rIFGs established role in response inhibition. Furthermore, distraction decreased functional connectivity between the rIFG (seed) and left putamen for valued versus devalued food rewards (pFWE(cluster)<0.05). Our results suggest that distraction attenuates the ability to inhibit responses for food reward after satiation by affecting the rIFG. Furthermore, distraction attenuated connectivity between two regions involved in response inhibition - rIFG and putamen - after outcome devaluation. These results may explain why distraction can lead to overeating in our current, distracting, environment. The study was preregistered at: https://osf.io/ad2qk.
]]></description>
<dc:creator>Duif, I.</dc:creator>
<dc:creator>Wegman, J.</dc:creator>
<dc:creator>de Graaf, K.</dc:creator>
<dc:creator>Smeets, P. A. M.</dc:creator>
<dc:creator>Aarts, E.</dc:creator>
<dc:date>2020-01-14</dc:date>
<dc:identifier>doi:10.1101/2020.01.13.904532</dc:identifier>
<dc:title><![CDATA[Distraction attenuates goal-directed neural responses for food rewards]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-01-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.01.12.903112v1?rss=1">
<title>
<![CDATA[
Modeling human age-associated increase in Gadd45γ expression leads to spatial recognition memory impairments in young adult mice 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.01.12.903112v1?rss=1"
</link>
<description><![CDATA[
Aging is associated with the progressive decay of cognitive function. Hippocampus-dependent processes, such as the formation of spatial memory, are particularly vulnerable to aging. Currently, the molecular mechanisms responsible for age-dependent cognitive decline are largely unknown. Here, we investigated the expression and function of the growth arrest DNA damage gamma (Gadd45{gamma}) during aging and cognition. We report that Gadd45{gamma} expression is increased in the hippocampus of aged humans and that Gadd45{gamma} overexpression in the young adult mouse hippocampus compromises cognition. Moreover, Gadd45{gamma} overexpression in hippocampal neurons disrupted CREB signaling and the expression of well-established activity-regulated genes. This work shows that Gadd45{gamma} expression is tightly controlled in the hippocampus and its disruption may be a mechanism contributing to age-related cognitive impairments observed in humans.
]]></description>
<dc:creator>Brito, D. V.</dc:creator>
<dc:creator>Gulmez Karaca, K.</dc:creator>
<dc:creator>Kupke, J.</dc:creator>
<dc:creator>Mudlaff, F.</dc:creator>
<dc:creator>Zeuch, B.</dc:creator>
<dc:creator>Gomes, R.</dc:creator>
<dc:creator>Lopes, L. V.</dc:creator>
<dc:creator>Oliveira, A. M. M.</dc:creator>
<dc:date>2020-01-14</dc:date>
<dc:identifier>doi:10.1101/2020.01.12.903112</dc:identifier>
<dc:title><![CDATA[Modeling human age-associated increase in Gadd45γ expression leads to spatial recognition memory impairments in young adult mice]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-01-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.01.12.903088v1?rss=1">
<title>
<![CDATA[
Engram reactivation during memory retrieval predicts long-term memory performance in aged mice 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.01.12.903088v1?rss=1"
</link>
<description><![CDATA[
Age-related cognitive decline preferentially targets long-lasting episodic memories that require intact hippocampal function. Memory traces (or engrams) are believed to be encoded within the neurons activated during learning (neuronal ensembles), and recalled by reactivation of the same population. However, whether engram reactivation dictates memory performance late in life is not known. Here, we labelled neuronal ensembles formed during object location recognition learning in the dentate gyrus, and analyzed the reactivation of this population by long-term memory recall in young adult, cognitively impaired-and unimpaired-aged mice. We found that reactivation of memory-encoding neuronal ensembles at long-term memory recall was disrupted in impaired but not unimpaired-aged mice. Furthermore, we showed that the memory performance in the aged population correlated with the degree of engram reactivation at long-term memory recall. Overall, our data implicates recall-induced engram reactivation as a prediction factor of memory performance in aging. Moreover, our findings suggest impairments in neuronal ensemble stabilization and/or reactivation as an underlying mechanism in age-dependent cognitive decline.
]]></description>
<dc:creator>Gulmez Karaca, K.</dc:creator>
<dc:creator>Brito, D. V.</dc:creator>
<dc:creator>Zeuch, B.</dc:creator>
<dc:creator>Oliveira, A. M. M.</dc:creator>
<dc:date>2020-01-14</dc:date>
<dc:identifier>doi:10.1101/2020.01.12.903088</dc:identifier>
<dc:title><![CDATA[Engram reactivation during memory retrieval predicts long-term memory performance in aged mice]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-01-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.01.08.898288v1?rss=1">
<title>
<![CDATA[
Individual differences among deep neural network models 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.01.08.898288v1?rss=1"
</link>
<description><![CDATA[
Deep neural networks (DNNs) excel at visual recognition tasks and are increasingly used as a modelling framework for neural computations in the primate brain. However, each DNN instance, just like each individual brain, has a unique connectivity and representational profile. Here, we investigate individual differences among DNN instances that arise from varying only the random initialization of the network weights. Using representational similarity analysis, we demonstrate that this minimal change in initial conditions prior to training leads to substantial differences in intermediate and higher-level network representations, despite achieving indistinguishable network-level classification performance. We locate the origins of the effects in an under-constrained alignment of category exemplars, rather than a misalignment of category centroids. Furthermore, while network regularization can increase the consistency of learned representations, considerable differences remain. These results suggest that computational neuroscientists working with DNNs should base their inferences on multiple networks instances instead of single off-the-shelf networks.
]]></description>
<dc:creator>Mehrer, J.</dc:creator>
<dc:creator>Spoerer, C. J.</dc:creator>
<dc:creator>Kriegeskorte, N.</dc:creator>
<dc:creator>Kietzmann, T. C.</dc:creator>
<dc:date>2020-01-09</dc:date>
<dc:identifier>doi:10.1101/2020.01.08.898288</dc:identifier>
<dc:title><![CDATA[Individual differences among deep neural network models]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-01-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.01.06.896167v1?rss=1">
<title>
<![CDATA[
Improving the sensitivity of cluster-based statistics for fMRI data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.01.06.896167v1?rss=1"
</link>
<description><![CDATA[
Because of the high dimensionality of neuroimaging data, identifying a statistical test that is both valid and maximally sensitive is an important challenge. Here, we present a combination of two approaches for fMRI data analysis that together result in substantial improvements of the sensitivity of cluster-based statistics. The first approach is to create novel cluster definitions that are sensitive to physiologically plausible effect patterns. The second is to adopt a new approach to combine test statistics with different sensitivity profiles, which we call the min(p) method. These innovations are made possible by using the randomization inference framework. In this paper, we report on a set of simulations that demonstrate (1) that the proposed methods control the false-alarm rate, (2) that the sensitivity profiles of cluster-based test statistics vary depending on the cluster defining thresholds and cluster definitions, and (3) that the min(p) method for combining these test statistics results in a drastic increase of sensitivity (up to five-fold), compared to existing fMRI analysis methods. This increase in sensitivity is not at the expense of the spatial specificity of the inference.
]]></description>
<dc:creator>Geerligs, L.</dc:creator>
<dc:creator>Maris, E.</dc:creator>
<dc:date>2020-01-07</dc:date>
<dc:identifier>doi:10.1101/2020.01.06.896167</dc:identifier>
<dc:title><![CDATA[Improving the sensitivity of cluster-based statistics for fMRI data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-01-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/694364v1?rss=1">
<title>
<![CDATA[
Analysis of task-based functional MRI data preprocessed with fMRIPrep 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/694364v1?rss=1"
</link>
<description><![CDATA[
Functional magnetic resonance imaging (fMRI) is a standard tool to investigate the neural correlates of cognition. fMRI noninvasively measures brain activity, allowing identification of patterns evoked by tasks performed during scanning. Despite the long history of this technique, the idiosyncrasies of each dataset have led to the use of ad-hoc preprocessing protocols customized for nearly every different study. This approach is time-consuming, error-prone, and unsuitable for combining datasets from many sources. Here we showcase fMRIPrep (http://fmriprep.org), a robust tool to prepare human fMRI data for statistical analysis. This software instrument addresses the reproducibility concerns of the established protocols for fMRI preprocessing. By leveraging the Brain Imaging Data Structure (BIDS) to standardize both the input datasets --MRI data as stored by the scanner-- and the outputs --data ready for modeling and analysis--, fMRIPrep is capable of preprocessing a diversity of datasets without manual intervention. In support of the growing popularity of fMRIPrep, this protocol describes how to integrate the tool in a task-based fMRI investigation workflow.
]]></description>
<dc:creator>Esteban, O.</dc:creator>
<dc:creator>Ciric, R.</dc:creator>
<dc:creator>Finc, K.</dc:creator>
<dc:creator>Blair, R. W.</dc:creator>
<dc:creator>Markiewicz, C. J.</dc:creator>
<dc:creator>Moodie, C. A.</dc:creator>
<dc:creator>Kent, J. D.</dc:creator>
<dc:creator>Goncalves, M.</dc:creator>
<dc:creator>DuPre, E.</dc:creator>
<dc:creator>Gomez, D. E.</dc:creator>
<dc:creator>Ye, Z.</dc:creator>
<dc:creator>Salo, T.</dc:creator>
<dc:creator>Valabregue, R.</dc:creator>
<dc:creator>Amlien, I. K.</dc:creator>
<dc:creator>Liem, F.</dc:creator>
<dc:creator>Jacoby, N.</dc:creator>
<dc:creator>Stojic, H.</dc:creator>
<dc:creator>Cieslak, M.</dc:creator>
<dc:creator>Urchs, S.</dc:creator>
<dc:creator>Halchenko, Y. O.</dc:creator>
<dc:creator>Ghosh, S. S.</dc:creator>
<dc:creator>de la Vega, A.</dc:creator>
<dc:creator>Yarkoni, T.</dc:creator>
<dc:creator>Wright, J. A.</dc:creator>
<dc:creator>Thompson, W. H.</dc:creator>
<dc:creator>Poldrack, R. A.</dc:creator>
<dc:creator>Gorgolewski, K. J.</dc:creator>
<dc:date>2019-07-08</dc:date>
<dc:identifier>doi:10.1101/694364</dc:identifier>
<dc:title><![CDATA[Analysis of task-based functional MRI data preprocessed with fMRIPrep]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-07-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/166306v1?rss=1">
<title>
<![CDATA[
Optimal decision making using grid cells under spatial uncertainty 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/166306v1?rss=1"
</link>
<description><![CDATA[
Minimizing spatial uncertainty is essential for navigation, but the neural mechanisms remain elusive. Here we combine predictions of a simulated grid cell system with behavioural and fMRI measures in humans during virtual navigation. First, we showed that polarising cues produce anisotropy in motion parallax. Secondly, we simulated entorhinal grid cells in an environment with anisotropic information and found that self-location is decoded best when grid-patterns are aligned with the axis of greatest information. Thirdly, when exposing human participants to polarised virtual reality environments, we found that navigation performance is anisotropic, in line with the use of parallax. Eye movements showed that participants preferentially viewed polarising cues, which correlated with navigation performance. Finally, using fMRI we found that the orientation of grid-cell-like representations in entorhinal cortex anchored to the environmental axis of greatest parallax information, orthogonal to the polarisation axis. In sum, we demonstrate a crucial role of the entorhinal grid system in reducing uncertainty in representations of self-location and find evidence for adaptive spatial computations underlying entorhinal representations in service of optimal navigation.
]]></description>
<dc:creator>Navarro Schroeder, T.</dc:creator>
<dc:creator>Towse, B. W.</dc:creator>
<dc:creator>Burgess, N.</dc:creator>
<dc:creator>Barry, C.</dc:creator>
<dc:creator>Doeller, C. F.</dc:creator>
<dc:date>2017-07-20</dc:date>
<dc:identifier>doi:10.1101/166306</dc:identifier>
<dc:title><![CDATA[Optimal decision making using grid cells under spatial uncertainty]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/847921v1?rss=1">
<title>
<![CDATA[
Spatial attention and expectations rely on modality-specific and multisensory mechanisms 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/847921v1?rss=1"
</link>
<description><![CDATA[
In our natural environment, the brain needs to combine signals from multiple sensory modalities into a coherent percept. While spatial attention guides perceptual decisions by prioritizing processing of signals that are task-relevant, spatial expectations encode the probability of signals over space. Previous studies have shown that behavioral effects of spatial attention generalize across sensory modalities. However, because they manipulated spatial attention as signal probability over space, these studies could not dissociate attention and expectation or assess their interaction.

In two experiments, we orthogonally manipulated spatial attention (i.e., task-relevance) and expectation (i.e., signal probability) selectively in one sensory modality (i.e., primary modality) (experiment 1: audition, experiment 2: vision) and assessed their effects on primary and secondary sensory modalities in which attention and expectation were held constant.

Our results show behavioral effects of spatial attention that are comparable for audition and vision as primary modalities; yet, signal probabilities were learnt more slowly in audition, so that spatial expectations were formed later in audition than vision. Critically, when these differences in learning between audition and vision were accounted for, both spatial attention and expectation affected responses more strongly in the primary modality in which they were manipulated, and generalized to the secondary modality only in an attenuated fashion. Collectively, our results suggest that both spatial attention and expectation rely on modality-specific and multisensory mechanisms.
]]></description>
<dc:creator>Zuanazzi, A.</dc:creator>
<dc:creator>Noppeney, U.</dc:creator>
<dc:date>2019-11-20</dc:date>
<dc:identifier>doi:10.1101/847921</dc:identifier>
<dc:title><![CDATA[Spatial attention and expectations rely on modality-specific and multisensory mechanisms]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-11-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2019.12.20.884726v1?rss=1">
<title>
<![CDATA[
A RIPOR2 in-frame deletion is a frequent and highly penetrant cause of adult-onset hearing loss 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2019.12.20.884726v1?rss=1"
</link>
<description><![CDATA[
Hearing loss is one of the most prevalent disabilities worldwide, and has a significant impact on quality of life. The adult-onset type of the condition is highly heritable but the genetic causes are largely unknown, which is in contrast to childhood-onset hearing loss. We identified an in-frame deletion of 12 nucleotides in RIPOR2 as a highly penetrant cause of adult-onset progressive hearing loss that segregated as an autosomal dominant trait in 12 families from the Netherlands. Hearing loss associated with the deletion in 63 subjects displayed variable audiometric characteristics and an average age of onset of 30.6 years (SD 14.9 years, range 0-70 years). A functional effect of the RIPOR2 variant was demonstrated by aberrant localization of the mutant RIPOR2 in the stereocilia of cochlear hair cells and failure to rescue morphological defects in RIPOR2-deficient hair cells, in contrast to the wildtype protein. Strikingly, the RIPOR2 variant is present in 18 of 22,952 individuals not selected for hearing loss in the Southeast Netherlands. Collectively, these data demonstrate that an inherited form of adult-onset hearing loss is relatively common, with potentially thousands of individuals at risk in the Netherlands and beyond, which makes it an attractive target for developing a (genetic) therapy.
]]></description>
<dc:creator>de Bruijn, S. E.</dc:creator>
<dc:creator>Smits, J. J.</dc:creator>
<dc:creator>Liu, C.</dc:creator>
<dc:creator>Lanting, C. P.</dc:creator>
<dc:creator>Beynon, A. J.</dc:creator>
<dc:creator>Blankevoort, j.</dc:creator>
<dc:creator>Oostrik, J.</dc:creator>
<dc:creator>Koole, W.</dc:creator>
<dc:creator>de Vrieze, E.</dc:creator>
<dc:creator>DOOFNL consortium,</dc:creator>
<dc:creator>Cremers, C. W.</dc:creator>
<dc:creator>Cremers, F. P.</dc:creator>
<dc:creator>Roosing, S.</dc:creator>
<dc:creator>Yntema, H. G.</dc:creator>
<dc:creator>Kunst, H. P.</dc:creator>
<dc:creator>Zhao, B.</dc:creator>
<dc:creator>Pennings, R. J.</dc:creator>
<dc:creator>Kremer, H.</dc:creator>
<dc:date>2019-12-23</dc:date>
<dc:identifier>doi:10.1101/2019.12.20.884726</dc:identifier>
<dc:title><![CDATA[A RIPOR2 in-frame deletion is a frequent and highly penetrant cause of adult-onset hearing loss]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-12-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/548933v1?rss=1">
<title>
<![CDATA[
Resolving multisensory and attentional influences across cortical depth in sensory cortices 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/548933v1?rss=1"
</link>
<description><![CDATA[
In our environment our senses are bombarded with a myriad of signals, only a subset of which is relevant for our goals. Using sub-millimeter-resolution fMRI at 7T we resolved BOLD-response and activation patterns across cortical depth in early sensory cortices to auditory, visual and audiovisual stimuli under auditory or visual attention. In visual cortices, auditory stimulation induced widespread inhibition irrespective of attention, whereas auditory relative to visual attention suppressed mainly central visual field representations. In auditory cortices, visual stimulation suppressed activations, but amplified responses to concurrent auditory stimuli, in a patchy topography. Critically, multisensory interactions in auditory cortices were stronger in deeper laminae, while attentional influences were greatest at the surface. These distinct depth-dependent profiles suggest that multisensory and attentional mechanisms regulate sensory processing via partly distinct circuitries. Our findings are crucial for understanding how the brain regulates information flow across senses to interact with our complex multisensory world.
]]></description>
<dc:creator>Gau, R.</dc:creator>
<dc:creator>Bazin, P.-L.</dc:creator>
<dc:creator>Trampel, R.</dc:creator>
<dc:creator>Turner, R.</dc:creator>
<dc:creator>Noppeney, U.</dc:creator>
<dc:date>2019-03-15</dc:date>
<dc:identifier>doi:10.1101/548933</dc:identifier>
<dc:title><![CDATA[Resolving multisensory and attentional influences across cortical depth in sensory cortices]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-03-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2019.12.17.879346v1?rss=1">
<title>
<![CDATA[
Accurate brain age prediction with lightweight deep neural networks 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2019.12.17.879346v1?rss=1"
</link>
<description><![CDATA[
Deep learning has huge potential for accurate disease prediction with neuroimaging data, but the prediction performance is often limited by training-dataset size and computing memory requirements. To address this, we propose a deep convolutional neural network model, Simple Fully Convolutional Network (SFCN), for accurate prediction of brain age using T1-weighted structural MRI data. Compared with other popular deep network architectures, SFCN has fewer parameters, so is more compatible with small dataset size and 3D volume data. The network architecture was combined with several techniques for boosting performance, including data augmentation, pre-training, model regularization, model ensemble and prediction bias correction. We compared our overall SFCN approach with several widely-used machine learning models. It achieved state-of-the-art performance in UK Biobank data (N = 14,503), with mean absolute error (MAE) = 2.14y in brain age prediction and 99.5% in sex classification. SFCN also won (both parts of) the 2019 Predictive Analysis Challenge for brain age prediction, involving 79 competing teams (N = 2,638, MAE = 2.90y). We describe here the details of our approach, and its optimisation and validation. Our approach can easily be generalised to other tasks using different image modalities, and is released on GitHub.

HighlightsO_LIA lightweight deep learning model, Simple Fully Convolutional Network (SFCN), is presented, achieving state-of-the-art brain age prediction and sex classification performance in UK Biobank MRI brain imaging data.
C_LIO_LIEven with limited number of training subjects (e.g., 50), SFCN performs better than widely-used regression models.
C_LIO_LIA semi-multimodal ensemble strategy is proposed and achieved first place in the PAC 2019 brain age prediction challenge.
C_LIO_LILinear regression can remove brain age prediction bias (even on unlabelled data) while maintaining state-of-the-art performance.
C_LI
]]></description>
<dc:creator>Peng, H.</dc:creator>
<dc:creator>Gong, W.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>Vedaldi, A.</dc:creator>
<dc:creator>Smith, S. M.</dc:creator>
<dc:date>2019-12-18</dc:date>
<dc:identifier>doi:10.1101/2019.12.17.879346</dc:identifier>
<dc:title><![CDATA[Accurate brain age prediction with lightweight deep neural networks]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-12-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2019.12.17.879189v1?rss=1">
<title>
<![CDATA[
Characterization of SETD1A haploinsufficiency in humans and Drosophila defines a novel neurodevelopmental syndrome. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2019.12.17.879189v1?rss=1"
</link>
<description><![CDATA[
Defects in histone methyltransferases (HMTs) are major contributing factors in neurodevelopmental disorders (NDDs). Heterozygous variants of SETD1A involved in histone H3 lysine 4 (H3K4) methylation were previously identified in individuals with schizophrenia. Here, we define the clinical features of the Mendelian syndrome associated with haploinsufficiency of SETD1A by investigating 15 predominantly pediatric individuals who all have de novo SETD1A variants. These individuals present with a core set of symptoms comprising global developmental delay and/or intellectual disability, subtle facial dysmorphisms, behavioral and psychiatric problems. We examined cellular phenotypes in three patient derived lymphoblastoid cell lines with three variants: p.Gly535Alafs*12, c.4582-2_4582delAG, and p.Tyr1499Asp. These patient cell lines displayed DNA damage repair defects that were comparable to previously observed RNAi-mediated depletion of SETD1A. This suggested that these variants, including the p.Tyr1499Asp in the catalytic SET domain, behave as Loss-of-Function (LoF) alleles. Previous studies demonstrated a role for SETD1A in cell cycle control and differentiation. However, individuals with SETD1A variants do not show major structural brain defects or severe microcephaly, suggesting that defective proliferation and differentiation of neural progenitors is unlikely the single underlying cause of the disorder. We show here that the Drosophila Melanogaster SETD1A orthologue is required in postmitotic neurons of the fly brain for normal memory, suggesting a role in post development neuronal function. Together, this study defines a neurodevelopmental disorder caused by dominant de novo LoF variants in SETD1A and further supports a role for H3K4 methyltransferases in the regulation of neuronal processes underlying normal cognitive functioning.
]]></description>
<dc:creator>Kummeling, J.</dc:creator>
<dc:creator>Stremmelaar, D. E.</dc:creator>
<dc:creator>Raun, N.</dc:creator>
<dc:creator>Reijnders, M. R.</dc:creator>
<dc:creator>Willemsen, M. H.</dc:creator>
<dc:creator>Ruiterkamp-Versteeg, M.</dc:creator>
<dc:creator>Schepens, M.</dc:creator>
<dc:creator>Man, C. C.</dc:creator>
<dc:creator>Gilissen, C.</dc:creator>
<dc:creator>Cho, M. T.</dc:creator>
<dc:creator>McWalter, K.</dc:creator>
<dc:creator>Sinnema, M.</dc:creator>
<dc:creator>Wheless, J. W.</dc:creator>
<dc:creator>Simon, M. E.</dc:creator>
<dc:creator>Genetti, C. A.</dc:creator>
<dc:creator>Casey, A. M.</dc:creator>
<dc:creator>Terhal, P. A.</dc:creator>
<dc:creator>van der Smagt, J. `J</dc:creator>
<dc:creator>van Gassen, K. L.</dc:creator>
<dc:creator>Joset, P.</dc:creator>
<dc:creator>Bahr, A.</dc:creator>
<dc:creator>Steindl, K.</dc:creator>
<dc:creator>Rauch, A.</dc:creator>
<dc:creator>Keller, E.</dc:creator>
<dc:creator>Raas-Rothschild, A.</dc:creator>
<dc:creator>Koolen, D. A.</dc:creator>
<dc:creator>Agrawal, P. B.</dc:creator>
<dc:creator>Hoffman, T. L.</dc:creator>
<dc:creator>Powell-Hamilton, N. N.</dc:creator>
<dc:creator>Thiffault, I.</dc:creator>
<dc:creator>Engleman, K.</dc:creator>
<dc:creator>Zhou, D.</dc:creator>
<dc:creator>Bodamer, O.</dc:creator>
<dc:creator>Hoefele, J.</dc:creator>
<dc:creator>Riedhammer, K. M.</dc:creator>
<dc:creator>Schwaibold, E. M.</dc:creator>
<dc:creator>Tasic, V.</dc:creator>
<dc:creator>Schubert, D.</dc:creator>
<dc:creator>Top, D.</dc:creator>
<dc:creator>Pfundt, R.</dc:creator>
<dc:creator>H</dc:creator>
<dc:date>2019-12-18</dc:date>
<dc:identifier>doi:10.1101/2019.12.17.879189</dc:identifier>
<dc:title><![CDATA[Characterization of SETD1A haploinsufficiency in humans and Drosophila defines a novel neurodevelopmental syndrome.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-12-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/439984v1?rss=1">
<title>
<![CDATA[
Gene Expression Correlates of the Cortical Network Underlying Sentence Processing 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/439984v1?rss=1"
</link>
<description><![CDATA[
A pivotal question in modern neuroscience is which genes regulate brain circuits that underlie cognitive functions. However, the field is still in its infancy. Here we report an integrated investigation of the high-level language network (i.e., sentence processing network) in the human cerebral cortex, combining regional gene expression profiles, task fMRI, large-scale neuroimaging meta-analysis, and resting-state functional network approaches. We revealed reliable gene expression-functional network correlations using three different network definition strategies, and identified a consensus set of genes related to connectivity within the sentence-processing network. The genes involved showed enrichment for neural development and actin-related functions, as well as association signals with autism, which can involve disrupted language functioning. Our findings help elucidate the molecular basis of the brains infrastructure for language. The integrative approach described here will be useful to study other complex cognitive traits.
]]></description>
<dc:creator>Kong, X.-Z.</dc:creator>
<dc:creator>Tzourio-Mazoyer, N.</dc:creator>
<dc:creator>Joliot, M.</dc:creator>
<dc:creator>Fedorenko, E.</dc:creator>
<dc:creator>Liu, J.</dc:creator>
<dc:creator>Fisher, S. E.</dc:creator>
<dc:creator>Francks, C.</dc:creator>
<dc:date>2018-10-11</dc:date>
<dc:identifier>doi:10.1101/439984</dc:identifier>
<dc:title><![CDATA[Gene Expression Correlates of the Cortical Network Underlying Sentence Processing]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-10-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2019.12.15.876847v1?rss=1">
<title>
<![CDATA[
Susceptibility to auditory closed-loop stimulation of sleep slow oscillations changes with age 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2019.12.15.876847v1?rss=1"
</link>
<description><![CDATA[
BackgroundCortical slow oscillations (SOs) and thalamo-cortical sleep spindles hallmark slow wave sleep and facilitate sleep-dependent memory consolidation. Experiments utilising auditory closed-loop stimulation to enhance these oscillations have shown great potential in young and older subjects. However, the magnitude of responses has yet to be compared between these age groups.

ObjectiveWe examined the possibility of enhancing SOs and performance on different memory tasks in a healthy older population using auditory closed-loop stimulation and contrast effects to a young adult cohort.

MethodsIn a within-subject design, subjects (n = 17, 55.7 {+/-} 1.0 years, 9 female) received auditory click stimulation in synchrony with SO up-states, which was compared to a no-stimulation sham condition. Overnight memory consolidation was assessed for declarative word-pairs and procedural finger-tapping skill. Post-sleep encoding capabilities were tested with a picture recognition task. Electrophysiological effects of stimulation were compared to those reported previously in a younger cohort (n = 11, 24.2 {+/-} 0.9 years, 8 female).

ResultsOvernight retention and post-sleep encoding performance of the older cohort revealed no beneficial effect of stimulation, which contrasts with the enhancing effect the same stimulation protocol had in our younger cohort. Auditory stimulation prolonged endogenous SO trains and induced sleep spindles phase-locked to SO up-states in the older population. However, responses were markedly reduced compared to younger subjects. Additionally, the temporal dynamics of stimulation effects on SOs and spindles differed between age groups.

ConclusionsOur findings suggest that the susceptibility to auditory stimulation during sleep drastically changes with age and reveal the difficulties of translating a functional protocol from younger to older populations.

HighlightsO_LIAuditory closed-loop stimulation induced SOs and sleep spindles in older subjects
C_LIO_LIStimulation effects were reduced and overall susceptibility diminished with age
C_LIO_LISlow oscillation and sleep spindle dynamics deviated from those in younger subjects
C_LIO_LIStimulation shows no evidence for memory effect in older subjects
C_LI
]]></description>
<dc:creator>Schneider, J.</dc:creator>
<dc:creator>Lewis, P. A.</dc:creator>
<dc:creator>Koester, D.</dc:creator>
<dc:creator>Born, J.</dc:creator>
<dc:creator>Ngo, H.-V. V.</dc:creator>
<dc:date>2019-12-15</dc:date>
<dc:identifier>doi:10.1101/2019.12.15.876847</dc:identifier>
<dc:title><![CDATA[Susceptibility to auditory closed-loop stimulation of sleep slow oscillations changes with age]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-12-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/258723v1?rss=1">
<title>
<![CDATA[
Mutational origins and pathogenic consequences of multinucleotide mutations in 6,688 trios with developmental disorders 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/258723v1?rss=1"
</link>
<description><![CDATA[
De novo mutations (DNMs) in protein-coding genes are a well-established cause of developmental disorders (DD). However, known DD-associated genes only account for a minority of the observed excess of such DNMs. To identify novel DD-associated genes, we integrated healthcare and research exome sequences on 31,058 DD parent-offspring trios, and developed a simulation-based statistical test to identify gene-specific enrichments of DNMs. We identified 299 significantly DD-associated genes, including 49 not previously robustly associated with DDs. Despite detecting more DD-associated genes than in any previous study, much of the excess of DNMs of protein-coding genes remains unaccounted for. Modelling suggests that over 500 novel DD-associated genes await discovery, many of which are likely to be less penetrant than the currently known genes. Research access to clinical diagnostic datasets will be critical for completing the map of dominant DDs.
]]></description>
<dc:creator>Kaplanis, J.</dc:creator>
<dc:creator>Akawi, N.</dc:creator>
<dc:creator>Gallone, G.</dc:creator>
<dc:creator>McRae, J. F.</dc:creator>
<dc:creator>Prigmore, E.</dc:creator>
<dc:creator>Wright, C. F.</dc:creator>
<dc:creator>Fitzpatrick, D. R.</dc:creator>
<dc:creator>Firth, H. V.</dc:creator>
<dc:creator>Barrett, J. C.</dc:creator>
<dc:creator>Hurles, M. E.</dc:creator>
<dc:creator>on behalf of the Deciphering Developmental Disorders Study,</dc:creator>
<dc:date>2018-02-02</dc:date>
<dc:identifier>doi:10.1101/258723</dc:identifier>
<dc:title><![CDATA[Mutational origins and pathogenic consequences of multinucleotide mutations in 6,688 trios with developmental disorders]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-02-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/868414v1?rss=1">
<title>
<![CDATA[
Characterizing neuroanatomic heterogeneity in people with and without ADHD based on subcortical brain volumes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/868414v1?rss=1"
</link>
<description><![CDATA[
BackgroundAttention-Deficit/Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder in children and adults. Neuroanatomic heterogeneity limits our understanding of the etiology of ADHD. This study aimed to parse neuroanatomic heterogeneity of ADHD, and to determine whether subgroups could be discerned in patients based on subcortical volumes.

MethodsUsing the dataset from the ENIGMA-ADHD Working Group, we applied exploratory factor analysis (EFA) to subcortical volumes of 993 boys with and without ADHD, and to subsamples of 653 adult men, 400 girls, and 447 women. Factor scores derived from the EFA were used to build networks. A community detection (CD) algorithm clustered participants into subgroups based on the networks.

ResultsThree factors (basal ganglia, limbic system, and thalamus) were found in boys and men with and without ADHD. The factor structures for girls and women differed from those in males. Given sample size considerations, we concentrated subsequent analyses on males. Male participants could be separated into four communities, though Community 3 was absent in healthy men. Significantly case-control differences of subcortical volumes were observed within communities in boys with increased effect sizes, but not in men. While we found no significant differences in ADHD symptom severity between communities in boys or men; affected men in Community 1 and 4 presented comorbidities more frequently than those in other communities.

ConclusionOur results indicate that neuroanatomic heterogeneity in subcortical volumes exists, irrespective of ADHD diagnosis. Effect sizes of case-control differences appear more pronounced at least in some of the subgroups.
]]></description>
<dc:creator>Li, T.</dc:creator>
<dc:creator>Rooij, D. v.</dc:creator>
<dc:creator>Mota, N. R.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>the ENIGMA ADHD Working Group,</dc:creator>
<dc:creator>Hoogman, M.</dc:creator>
<dc:creator>Vasquez, A. A.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:date>2019-12-08</dc:date>
<dc:identifier>doi:10.1101/868414</dc:identifier>
<dc:title><![CDATA[Characterizing neuroanatomic heterogeneity in people with and without ADHD based on subcortical brain volumes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-12-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/868265v1?rss=1">
<title>
<![CDATA[
Perinatal selective serotonin reuptake inhibitor exposure and behavioral outcomes: a systematic review and meta-analyses of animal studies 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/868265v1?rss=1"
</link>
<description><![CDATA[
In the Western world, 2-5% of pregnant women use selective serotonin reuptake inhibitor (SSRI) antidepressants. There is no consensus on the potential long-term neurodevelopmental outcomes of early SSRI exposure. Our aim was to determine whether there is an overall effect of perinatal SSRI exposure in animals on a spectrum of behavioral domains. After a comprehensive database search in PubMed, PsycINFO, and Web of Science, we included 99 publications. We performed nine meta-analyses and two qualitative syntheses corresponding to different behavioral categories, aggregating data from thousands of animals. We found evidence for reduced activity and exploration behavior (standardized mean difference (SMD) -0.28 [-0.38, -0.18]), more passive stress coping (SMD -0.37 [-0.52, -0.23]), and less efficient sensory processing (SMD -0.37 [-0.69, -0.06]) in SSRI-versus vehicle-exposed animals. No differences were found for anxiety (p=0.06), social behavior, learning and memory, ingestive- and reward behavior, motoric behavior, or reflex and pain sensitivity. Exposure in the period equivalent to the human third trimester was associated with the strongest effects.

HighlightsO_LIPerinatal SSRI exposure in rodents alters outcomes in three behavioral domains.
C_LIO_LIIt leads to reduced activity, passive stress coping, and weaker sensory processing.
C_LIO_LIFemales are understudied but seem to be less vulnerable than males.
C_LIO_LIEarly postnatal exposure in rodents leads to the largest effects on behavior.
C_LIO_LIThis is equivalent to the third trimester of pregnancy in humans.
C_LI
]]></description>
<dc:creator>Ramsteijn, A. S.</dc:creator>
<dc:creator>Van de Wijer, L.</dc:creator>
<dc:creator>Rando, J.</dc:creator>
<dc:creator>van Luijk, J.</dc:creator>
<dc:creator>Homberg, J. R.</dc:creator>
<dc:creator>Olivier, J. D. A.</dc:creator>
<dc:date>2019-12-06</dc:date>
<dc:identifier>doi:10.1101/868265</dc:identifier>
<dc:title><![CDATA[Perinatal selective serotonin reuptake inhibitor exposure and behavioral outcomes: a systematic review and meta-analyses of animal studies]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-12-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/584896v1?rss=1">
<title>
<![CDATA[
Human lateral Frontal Pole contributes to control over social-emotional behaviour 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/584896v1?rss=1"
</link>
<description><![CDATA[
Regulation of emotional behavior is essential for human social interactions. Recent work has exposed its cognitive complexity, as well as its unexpected reliance on portions of the anterior prefrontal cortex (aPFC) also involved in exploration, relational reasoning, and counterfactual choice, rather than on dorsolateral and medial prefrontal areas involved in several forms of cognitive control. This study anatomically qualifies the contribution of aPFC territories to the regulation of social-emotional actions, and explores a possible structural pathway through which emotional regulation might be implemented.

We provide converging evidence from task-based fMRI, diffusion-weighted imaging, and functional connectivity fingerprints for a novel neural element in emotional regulation. Task-based fMRI in human male participants (N = 40) performing a social-emotional approach-avoidance task identified aPFC territories involved in the regulation of social-emotional actions. Connectivity fingerprints, based on diffusion-weighted imaging and resting-state connectivity, localized those task-defined frontal regions to the lateral frontal pole (FPl), an anatomically-defined portion of the aPFC that lacks a homologous counterpart in macaque brains. Probabilistic tractography indicated that 10-20% of inter-individual variation in social-emotional regulation abilities is accounted for by the strength of structural connectivity between FPl and amygdala. Evidence from an independent replication sample (N = 50; 10 females) further substantiated this result. These findings provide novel neuroanatomical evidence for incorporating FPl in models of control over human social-emotional behavior.

Significance statementSuccessful regulation of emotional behaviors is a prerequisite for successful participation in human society, as is evidenced by the social isolation and loss of occupational opportunities often encountered by people suffering from emotion-regulation disorders such as social-anxiety disorder and psychopathy. Knowledge about the precise cortical regions and connections supporting this control is crucial for understanding both the nature of computations needed to successfully traverse the space of possible actions in social situations, and the potential interventions that might result in efficient treatment of social-emotional disorders. This study provides evidence for a precise cortical region (FPl) and a structural pathway (the ventral amygdalofugal bundle) through which a cognitively complex form of emotional action regulation might be implemented in the human brain.
]]></description>
<dc:creator>Bramson, B.</dc:creator>
<dc:creator>Folloni, D.</dc:creator>
<dc:creator>Verhagen, L.</dc:creator>
<dc:creator>Hartogsveld, B.</dc:creator>
<dc:creator>Mars, R. B.</dc:creator>
<dc:creator>Toni, I.</dc:creator>
<dc:creator>Roelofs, K.</dc:creator>
<dc:date>2019-03-25</dc:date>
<dc:identifier>doi:10.1101/584896</dc:identifier>
<dc:title><![CDATA[Human lateral Frontal Pole contributes to control over social-emotional behaviour]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-03-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/866301v1?rss=1">
<title>
<![CDATA[
An illustration of reproducibility in neuroscience research in the absence of selective reporting 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/866301v1?rss=1"
</link>
<description><![CDATA[
The problem of poor reproducibility of scientific findings has received much attention over recent years, in a variety of fields including psychology and neuroscience. The problem has been partly attributed to publication bias and unwanted practices such as p-hacking. Low statistical power in individual studies is also understood to be an important factor. In a recent multi-site collaborative study, we mapped brain anatomical left-right asymmetries for regional measures of surface area and cortical thickness, in 99 MRI datasets from around the world, for a total of over 17,000 participants. In the present study, we re-visited these hemispheric effects from the perspective of reproducibility. Within each dataset, we considered that an effect had been reproduced when it matched the meta-analytic effect from the 98 other datasets, in terms of effect direction and uncorrected significance at p<0.05. In this sense, the results within each dataset were viewed as coming from separate studies in an  ideal publishing environment, i.e. free from selective reporting and p hacking. We found an average reproducibility rate per dataset, over all effects, of 63.2% (SD = 22.9%, min = 22.2%, max = 97.0%). As expected, reproducibility was higher for larger effects and in larger datasets. There is clearly substantial room to improve reproducibility in brain MRI research through increasing statistical power. These findings constitute an empirical illustration of reproducibility in the absence of publication bias or p hacking, when assessing realistic biological effects in heterogeneous neuroscience data, and given typically-used sample sizes.
]]></description>
<dc:creator>Kong, X.-Z.</dc:creator>
<dc:creator>ENIGMA Laterality Working Group,</dc:creator>
<dc:creator>Francks, C.</dc:creator>
<dc:date>2019-12-06</dc:date>
<dc:identifier>doi:10.1101/866301</dc:identifier>
<dc:title><![CDATA[An illustration of reproducibility in neuroscience research in the absence of selective reporting]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-12-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/863605v1?rss=1">
<title>
<![CDATA[
Structural Brain Alterations and Their Association with Cognitive Function and Symptoms in Attention-Deficit/Hyperactivity Disorder Families 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/863605v1?rss=1"
</link>
<description><![CDATA[
Gray matter disruptions have been found consistently in Attention-deficit/Hyperactivity Disorder (ADHD). The organization of these alterations into brain structural networks remains largely unexplored. We investigated 508 participants (281 males) with ADHD (N = 210), their unaffected siblings (N = 108), individuals with subthreshold ADHD (N = 49), and unrelated healthy controls (N = 141) with an age range from 7 - 18 years old from 336 families in the Dutch NeuroIMAGE project. Source based morphometry was used to examine structural brain network alterations and their association with symptoms and cognitive performance. Two networks showed significant reductions in individuals with ADHD compared to unrelated healthy controls after False Discovery Rate correction. Component A, mainly located in bilateral Crus I, showed a case/control difference with sub-clinical cases being intermediate between cases and controls. The unaffected siblings were similar to controls. After correcting for IQ and medication status, component A showed a negative correlation with inattention symptoms across the entire sample. Component B included a maximum cluster in the bilateral insula, where unaffected siblings, similar to cases, showed significantly reduced loadings compared to controls; but no relationship with individual symptoms or cognitive measures was found for component B. This multivariate approach suggests that areas reflecting genetic liability within ADHD are partly separate from those areas modulating symptom severity.
]]></description>
<dc:creator>Jiang, W.</dc:creator>
<dc:creator>Duan, K.</dc:creator>
<dc:creator>Rootes-Murdy, K.</dc:creator>
<dc:creator>Hoekstra, P. J.</dc:creator>
<dc:creator>Hartman, C.</dc:creator>
<dc:creator>Oosterlaan, J.</dc:creator>
<dc:creator>Heslenfeld, D.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Buitelaar, J.</dc:creator>
<dc:creator>Arias-Vasquez, A.</dc:creator>
<dc:creator>Liu, J.</dc:creator>
<dc:creator>Turner, J.</dc:creator>
<dc:date>2019-12-04</dc:date>
<dc:identifier>doi:10.1101/863605</dc:identifier>
<dc:title><![CDATA[Structural Brain Alterations and Their Association with Cognitive Function and Symptoms in Attention-Deficit/Hyperactivity Disorder Families]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-12-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/863118v1?rss=1">
<title>
<![CDATA[
The amplification of genetic factors for early vocabulary during children's language and literacy development 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/863118v1?rss=1"
</link>
<description><![CDATA[
The heritability of language and literacy skills increases during development. The underlying mechanisms are little understood, and may involve (i) the amplification of early genetic influences and/or (ii) the emergence of novel genetic factors (innovation). Here, we use multivariate structural equation models to quantify these processes, as captured by genome-wide genetic markers. Studying expressive and receptive vocabulary at 38 months and subsequent language, literacy and cognitive skills (7-13 years) in unrelated children (ALSPAC: N[&le;]6,092), we found little support for genetic innovation during mid-childhood and adolescence. Instead, genetic factors for early vocabulary, especially those unique to receptive skills, were amplified. Explaining as little as 3.9%(SE=1.8%) variation in early language, the same genetic influences accounted for 25.7%(SE=6.4%) to 45.1%(SE=7.6%) variation in verbal intelligence and literacy skills, but also performance intelligence, capturing the majority of SNP-heritability ([&le;]99%). This suggests that complex verbal and non-verbal cognitive skills originate developmentaly in early receptive language.
]]></description>
<dc:creator>Verhoef, E.</dc:creator>
<dc:creator>Shapland, C. Y.</dc:creator>
<dc:creator>Fisher, S. E.</dc:creator>
<dc:creator>Dale, P. S.</dc:creator>
<dc:creator>St Pourcain, B.</dc:creator>
<dc:date>2019-12-03</dc:date>
<dc:identifier>doi:10.1101/863118</dc:identifier>
<dc:title><![CDATA[The amplification of genetic factors for early vocabulary during children's language and literacy development]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-12-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/857656v1?rss=1">
<title>
<![CDATA[
The frequency gradient of human resting-state brain oscillations follows cortical hierarchies 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/857656v1?rss=1"
</link>
<description><![CDATA[
The human cortex is characterized by local morphological features such as cortical thickness, myelin content and gene expression that change along the posterior-anterior axis. We investigated if these structural gradients are associated with a similar gradient in a prominent feature of brain activity - namely the frequency of brain oscillations. In resting-state MEG recordings from healthy participants (N=187), we found that the strongest peak frequency in a brain area decreases significantly, gradually and robustly along the posterior-anterior axis following the global hierarchy from early sensory to higher-order areas. This spatial gradient of peak frequency was significantly anticorrelated with the cortical thickness of corresponding areas representing a proxy of the cortical hierarchical level. This result indicates that the intrinsic  resonance frequency decreases systematically from early sensory to higher-order areas and establishes a new structure-function relationship pertaining to brain oscillations as a core organizational principle that may underlie hierarchical specialization in the brain.
]]></description>
<dc:creator>Mahjoory, K.</dc:creator>
<dc:creator>Schoffelen, J.-M.</dc:creator>
<dc:creator>Keitel, A.</dc:creator>
<dc:creator>Gross, J.</dc:creator>
<dc:date>2019-11-27</dc:date>
<dc:identifier>doi:10.1101/857656</dc:identifier>
<dc:title><![CDATA[The frequency gradient of human resting-state brain oscillations follows cortical hierarchies]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-11-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/573808v1?rss=1">
<title>
<![CDATA[
Cross-disorder genetic analyses implicate dopaminergic signaling as a biological link between Attention-Deficit/Hyperactivity Disorder and obesity measures 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/573808v1?rss=1"
</link>
<description><![CDATA[
Attention-Deficit/Hyperactivity Disorder (ADHD) and obesity are frequently comorbid, genetically correlated, and share brain substrates. The biological mechanisms driving this association are unclear, but candidate systems, like dopaminergic neurotransmission and circadian rhythm, have been suggested. Our aim was to identify the biological mechanisms underpinning the genetic link between ADHD and obesity measures and investigate associations of overlapping genes with brain volumes. We tested the association of dopaminergic and circadian rhythm gene sets with ADHD, body mass index (BMI), and obesity (using GWAS data of N=53,293, N=681,275, and N=98,697, respectively). We then conducted genome-wide ADHD-BMI and ADHD-obesity gene-based meta-analyses, followed by pathway enrichment analyses. Finally, we tested the association of ADHD-BMI overlapping genes with brain volumes (primary GWAS data N=10,720-10,928; replication data N=9,428). The dopaminergic gene set was associated with both ADHD (P=5.81x10-3) and BMI (P=1.63x10-5), the circadian rhythm was associated with BMI (P=1.28x10-3). The genome-wide approach also implicated the dopaminergic system, as the Dopamine-DARPP32 Feedback in cAMP Signaling pathway was enriched in both ADHD-BMI and ADHD-obesity results. The ADHD-BMI overlapping genes were associated with putamen volume (P=7.7x10-3; replication data P=3.9x10-2) - a brain region with volumetric reductions in ADHD and BMI and linked to inhibitory control. Our findings suggest that dopaminergic neurotransmission, partially through DARPP-32-dependent signaling and involving the putamen, is a key player underlying the genetic overlap between ADHD and obesity measures. Uncovering shared etiological factors underlying the frequently observed ADHD-obesity comorbidity may have important implications in terms of prevention and/or efficient treatment of these conditions.
]]></description>
<dc:creator>Mota, N. R.</dc:creator>
<dc:creator>Poelmans, G.</dc:creator>
<dc:creator>Klein, M.</dc:creator>
<dc:creator>Torrico, B.</dc:creator>
<dc:creator>Fernandez-Castillo, N.</dc:creator>
<dc:creator>Cormand, B.</dc:creator>
<dc:creator>Reif, A.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Arias-Vasquez, A.</dc:creator>
<dc:date>2019-03-11</dc:date>
<dc:identifier>doi:10.1101/573808</dc:identifier>
<dc:title><![CDATA[Cross-disorder genetic analyses implicate dopaminergic signaling as a biological link between Attention-Deficit/Hyperactivity Disorder and obesity measures]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-03-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/849570v1?rss=1">
<title>
<![CDATA[
Tensor Image Registration Library: Automated Non-Linear Registration of Sparsely Sampled Histological Specimens to Post-Mortem MRI of the Whole Human Brain 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/849570v1?rss=1"
</link>
<description><![CDATA[
There is a need to understand the histopathological basis of MRI signal characteristics in complex biological matter. Microstructural imaging holds promise for sensitive and specific indicators of the early stages of human neurodegeneration but requires validation against traditional histological markers before it can be reliably applied in the clinical setting. Validation relies on a precise and preferably automatic method to align MRI and histological images of the same tissue, which poses unique challenges compared to more conventional MRI-to-MRI registration.

A customisable open-source platform, Tensor Image Registration Library (TIRL) is presented. Based on TIRL, a fully automated pipeline was implemented to align small stained histological images with dissection photographs of corresponding tissue blocks and coronal brain slices, and further with high-resolution (0.5 mm) whole-brain post-mortem MRI data. The pipeline performed three separate deformable registrations to achieve accurate mapping between whole-brain MRI and small-slide histology coordinates. The robustness and accuracy of the individual registration steps were evaluated using both simulated data and real-life images from 6 different anatomical locations of one post-mortem human brain.

The automated registration method demonstrated sub-millimetre accuracy in all steps, robustness against tissue damage, and good reproducibility between experiments. The method also outperformed manual landmark-based slice-to-volume registration, also correcting for curvatures in the slicing plane. Due to the customisability of TIRL, the pipeline can be conveniently adapted for other research needs and is therefore suitable for the large-scale comparison of routinely collected histology and MRI data.

HighlightsO_LITIRL: new framework for prototyping bespoke image registration pipelines
C_LIO_LIPipeline for automated registration of small-slide histology to whole-brain MRI
C_LIO_LISlice-to-volume registration accounting for through-plane deformations
C_LIO_LINo need for serial histological sampling
C_LI
]]></description>
<dc:creator>Huszar, I. N.</dc:creator>
<dc:creator>Pallebage-Gamarallage, M.</dc:creator>
<dc:creator>Foxley, S.</dc:creator>
<dc:creator>Tendler, B. C.</dc:creator>
<dc:creator>Leonte, A.</dc:creator>
<dc:creator>Hiemstra, M.</dc:creator>
<dc:creator>Mollink, J.</dc:creator>
<dc:creator>Smart, A.</dc:creator>
<dc:creator>Bangerter-Christensen, S.</dc:creator>
<dc:creator>Brooks, H.</dc:creator>
<dc:creator>Turner, M. R.</dc:creator>
<dc:creator>Ansorge, O.</dc:creator>
<dc:creator>Miller, K. L.</dc:creator>
<dc:creator>Jenkinson, M.</dc:creator>
<dc:date>2019-11-26</dc:date>
<dc:identifier>doi:10.1101/849570</dc:identifier>
<dc:title><![CDATA[Tensor Image Registration Library: Automated Non-Linear Registration of Sparsely Sampled Histological Specimens to Post-Mortem MRI of the Whole Human Brain]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-11-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/850875v1?rss=1">
<title>
<![CDATA[
A one-step biofunctionalization strategy of electrospun scaffolds enables spatially selective presentation of biological cues 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/850875v1?rss=1"
</link>
<description><![CDATA[
To recapitulate the heterogeneous complexity of tissues in our body with synthetic mimics of the extracellular matrix (ECM), it is important to develop methods that can easily allow the selective functionalization of defined spatial domains. Here, we introduce a facile method to functionalize microfibrillar meshes with different reactive groups able to bind biological moieties in a one-step reaction. The resulting scaffolds proved to selectively support a differential neurite growth after being seeded with dorsal root ganglia. Considering the general principles behind the method developed, this is a promising strategy to realize enhanced biomimicry of native ECM for different regenerative medicine applications.
]]></description>
<dc:creator>Wieringa, P.</dc:creator>
<dc:creator>Girao, A.</dc:creator>
<dc:creator>Truckenmuller, R.</dc:creator>
<dc:creator>Welle, A.</dc:creator>
<dc:creator>Micera, S.</dc:creator>
<dc:creator>van Wezel, R.</dc:creator>
<dc:creator>Moroni, L.</dc:creator>
<dc:date>2019-11-25</dc:date>
<dc:identifier>doi:10.1101/850875</dc:identifier>
<dc:title><![CDATA[A one-step biofunctionalization strategy of electrospun scaffolds enables spatially selective presentation of biological cues]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-11-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/831321v1?rss=1">
<title>
<![CDATA[
Genome-wide association study identifies 49 common genetic variants associated with handedness. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/831321v1?rss=1"
</link>
<description><![CDATA[
Handedness, a consistent asymmetry in skill or use of the hands, has been studied extensively because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and 32 studies from the International Handedness Consortium, we conducted the worlds largest genome-wide association study of handedness (1,534,836 right-handed, 194,198 (11.0%) left-handed and 37,637 (2.1%) ambidextrous individuals). We found 41 genetic loci associated with left-handedness and seven associated with ambidexterity at genome-wide levels of significance (P < 5x10-8). Tissue enrichment analysis implicated the central nervous system and brain tissues including the hippocampus and cerebrum in the etiology of left-handedness. Pathways including regulation of microtubules, neurogenesis, axonogenesis and hippocampus morphology were also highlighted. We found suggestive positive genetic correlations between being left-handed and some neuropsychiatric traits including schizophrenia and bipolar disorder. SNP heritability analyses indicated that additive genetic effects of genotyped variants explained 5.9% (95% CI = 5.8% - 6.0%) of the underlying liability of being left-handed, while the narrow sense heritability was estimated at 12% (95% CI = 7.2% - 17.7%). Further, we show that genetic correlation between left-handedness and ambidexterity is low (rg = 0.26; 95% CI = 0.08 - 0.43) implying that these traits are largely influenced by different genetic mechanisms. In conclusion, our findings suggest that handedness, like many other complex traits is highly polygenic, and that the genetic variants that predispose to left-handedness may underlie part of the association with some psychiatric disorders that has been observed in multiple observational studies.
]]></description>
<dc:creator>Cuellar Partida, G.</dc:creator>
<dc:creator>Tung, J. Y.</dc:creator>
<dc:creator>Eriksson, N.</dc:creator>
<dc:creator>Albrecht, E.</dc:creator>
<dc:creator>Aliev, F.</dc:creator>
<dc:creator>Andreassen, O. A.</dc:creator>
<dc:creator>Barroso, I.</dc:creator>
<dc:creator>Beckmann, J. S.</dc:creator>
<dc:creator>Boks, M. P.</dc:creator>
<dc:creator>Boomsma, D. I.</dc:creator>
<dc:creator>Boyd, H. A.</dc:creator>
<dc:creator>Breteler, M. M.</dc:creator>
<dc:creator>Campbell, H.</dc:creator>
<dc:creator>Chasman, D. I.</dc:creator>
<dc:creator>Cherkas, L. F.</dc:creator>
<dc:creator>Davies, G.</dc:creator>
<dc:creator>de Geus, E. J.</dc:creator>
<dc:creator>Deary, I. J.</dc:creator>
<dc:creator>Deloukas, P.</dc:creator>
<dc:creator>Dick, D. M.</dc:creator>
<dc:creator>Duffy, D. L.</dc:creator>
<dc:creator>Eriksson, J. G.</dc:creator>
<dc:creator>Esko, T.</dc:creator>
<dc:creator>Feenstra, B.</dc:creator>
<dc:creator>Geller, F.</dc:creator>
<dc:creator>Gieger, C.</dc:creator>
<dc:creator>Giegling, I.</dc:creator>
<dc:creator>Gordon, S. D.</dc:creator>
<dc:creator>Han, J.</dc:creator>
<dc:creator>Hansen, T. F.</dc:creator>
<dc:creator>Hartmann, A. M.</dc:creator>
<dc:creator>Heikkila, K.</dc:creator>
<dc:creator>Hicks, A. A.</dc:creator>
<dc:creator>Hayward, C.</dc:creator>
<dc:creator>Hirschhorn, J. N.</dc:creator>
<dc:creator>Hottenga, J.-J.</dc:creator>
<dc:creator>Huffman, J. E.</dc:creator>
<dc:creator>Hwang, L.-D.</dc:creator>
<dc:creator>Ikram, M. A.</dc:creator>
<dc:creator>Kaprio, J.</dc:creator>
<dc:creator>Kemp, J. P.</dc:creator>
<dc:creator>Khaw, K.-</dc:creator>
<dc:date>2019-11-07</dc:date>
<dc:identifier>doi:10.1101/831321</dc:identifier>
<dc:title><![CDATA[Genome-wide association study identifies 49 common genetic variants associated with handedness.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-11-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/845842v1?rss=1">
<title>
<![CDATA[
ExploreASL: an image processing pipeline for multi-center ASL perfusion MRI studies 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/845842v1?rss=1"
</link>
<description><![CDATA[
Arterial spin labeling (ASL) has undergone significant development since its inception, with a focus on improving standardization and reproducibility of its acquisition and quantification. In a community-wide effort towards robust and reproducible clinical ASL image processing, we developed the software package ExploreASL, allowing standardized analyses across centers and scanners.

The procedures used in ExploreASL capitalize on published image processing advancements and address the challenges of multi-center datasets with scanner-specific processing and artifact reduction to limit patient exclusion. ExploreASL is self-contained, written in MATLAB and based on Statistical Parameter Mapping (SPM) and runs on multiple operating systems. The toolbox adheres to previously defined international standards for data structure, provenance, and best analysis practice.

ExploreASL was iteratively refined and tested in the analysis of >10,000 ASL scans using different pulse-sequences in a variety of clinical populations, resulting in four processing modules: Import, Structural, ASL, and Population that perform tasks, respectively, for data curation, structural and ASL image processing and quality control, and finally preparing the results for statistical analyses on both single-subject and group level. We illustrate ExploreASL processing results from three cohorts: perinatally HIV-infected children, healthy adults, and elderly at risk for neurodegenerative disease. We show the reproducibility for each cohort when processed at different centers with different operating systems and MATLAB versions, and its effects on the quantification of gray matter cerebral blood flow.

ExploreASL facilitates the standardization of image processing and quality control, allowing the pooling of cohorts to increase statistical power and discover between-group perfusion differences. Ultimately, this workflow may advance ASL for wider adoption in clinical studies, trials, and practice.
]]></description>
<dc:creator>Mutsaerts, H. J.</dc:creator>
<dc:creator>Petr, J. H.</dc:creator>
<dc:creator>Groot, P. F.</dc:creator>
<dc:creator>van de Maele, P.</dc:creator>
<dc:creator>Ingala, S.</dc:creator>
<dc:creator>Robertson, A. D.</dc:creator>
<dc:creator>Vaclavu, L.</dc:creator>
<dc:creator>Groote, I.</dc:creator>
<dc:creator>Kuijf, H.</dc:creator>
<dc:creator>Zelaya, F.</dc:creator>
<dc:creator>O'Daly, O.</dc:creator>
<dc:creator>Hilal, S.</dc:creator>
<dc:creator>Wink, A. M.</dc:creator>
<dc:creator>Kant, I.</dc:creator>
<dc:creator>Caan, M.</dc:creator>
<dc:creator>Morgan, C.</dc:creator>
<dc:creator>de Bresser, J.</dc:creator>
<dc:creator>Lysvik, E.</dc:creator>
<dc:creator>Schrantee, A.</dc:creator>
<dc:creator>Bjornebekk, A.</dc:creator>
<dc:creator>Clement, P.</dc:creator>
<dc:creator>Shirzadi, Z.</dc:creator>
<dc:creator>Kuijer, J.</dc:creator>
<dc:creator>Anazodo, U.</dc:creator>
<dc:creator>Pajkrt, D.</dc:creator>
<dc:creator>Richard, E.</dc:creator>
<dc:creator>Bokkers, R.</dc:creator>
<dc:creator>Reneman, L.</dc:creator>
<dc:creator>Masellis, M.</dc:creator>
<dc:creator>Guenther, M.</dc:creator>
<dc:creator>MacIntosh, B.</dc:creator>
<dc:creator>Achten, E.</dc:creator>
<dc:creator>Chappell, M.</dc:creator>
<dc:creator>van Osch, M.</dc:creator>
<dc:creator>Golay, X.</dc:creator>
<dc:creator>Thomas, D.</dc:creator>
<dc:creator>de Vita, E.</dc:creator>
<dc:creator>Bjornerud, A.</dc:creator>
<dc:creator>Nederveen, A.</dc:creator>
<dc:creator>Hendrikse, J.</dc:creator>
<dc:creator>Asllani, I.</dc:creator>
<dc:creator>Barkhof, F.</dc:creator>
<dc:date>2019-11-17</dc:date>
<dc:identifier>doi:10.1101/845842</dc:identifier>
<dc:title><![CDATA[ExploreASL: an image processing pipeline for multi-center ASL perfusion MRI studies]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-11-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/842906v1?rss=1">
<title>
<![CDATA[
Meso-scale multi-material fabrication of a Synthetic ECM Mimic for In vivo-like Peripheral Nerve Regeneration 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/842906v1?rss=1"
</link>
<description><![CDATA[
A growing focus and continuing challenge for biological sciences is creating representative in vitro environments to study and influence cell behavior. Here, we describe the synthetic recreation of the highly ordered extracellular matrix (ECM) of the peripheral nervous system (PNS) in terms of structure and scale, providing a versatile 3D culturing platform that achieves some of the highest in vitro neurite growth rates so far reported. By combining electrospinning technology with a unique multi-material processing sequence that harnesses intrinsic material properties, a hydrogel construct is realized that incorporates oriented 6 m-diameter microchannels decorated with topographical nanofibers. We show that this mimics the native PNS ECM architecture and promotes extensive growth from primary neurons; through controlled variation in design, we show that the open lumens of the microchannels directing rapid axon invasion of the hydrogel while the nanofibers provide essential cues for cell adhesion and topographical guidance. Furthermore, these microstructural and nanofibrillar elements enabled a typically bioinert hydrogel (PEGDA) to achieve similar neurite extension when compared to a biocompatible collagen hydrogel, with PEGDA-based devices approaching neurite growth rates similar to what is observed in vivo. Through the accessible fabrication approach developed here, multi-material scaffolds were designed with cell-relevant architectures ranging from meso-to nanoscale and shown to support nerve growth to mimic PNS regeneration, with potential for regenerative medicine and neural engineering applications.
]]></description>
<dc:creator>Wieringa, P.</dc:creator>
<dc:creator>Goncalves de Pinho, A. R.</dc:creator>
<dc:creator>Truckenmueller, R.</dc:creator>
<dc:creator>Micera, S.</dc:creator>
<dc:creator>van Wezel, R.</dc:creator>
<dc:creator>Moroni, L.</dc:creator>
<dc:date>2019-11-15</dc:date>
<dc:identifier>doi:10.1101/842906</dc:identifier>
<dc:title><![CDATA[Meso-scale multi-material fabrication of a Synthetic ECM Mimic for In vivo-like Peripheral Nerve Regeneration]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-11-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/835652v1?rss=1">
<title>
<![CDATA[
Conjunctive Representations that Integrate Stimuli, Responses, and Rules are Critical for Action Selection 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/835652v1?rss=1"
</link>
<description><![CDATA[
People can use abstract rules to flexibly configure and select actions for specific situations. Yet how exactly rules shape actions towards specific sensory and/or motor requirements remains unclear. One possibility is that rules become integrated with sensory/response features in a non-linear, conjunctive manner (e.g., event files; Hommel, 1998) to drive rule-guided action selection. To dynamically track such conjunctive representations during action selection, we applied a time-resolved representational similarity analysis to the spectral-temporal profiles of the EEG signal, while participants selected actions based on varying rules. Across two experiments, we found that action selection engages conjunctive representations binding action rules to specific sensory/motor settings throughout the entire selection period. The strength of conjunctions was the most important predictor of trial-by-trial variability in response times (RTs) and was closely, and selectively, related to an important behavioral indicator of event files--the partial-overlap priming pattern. Thus, conjunctive representations were functionally dissociated from their constituent action features and play a critical role during flexible selection of action.
]]></description>
<dc:creator>Kikumoto, A.</dc:creator>
<dc:creator>Mayr, U.</dc:creator>
<dc:date>2019-11-08</dc:date>
<dc:identifier>doi:10.1101/835652</dc:identifier>
<dc:title><![CDATA[Conjunctive Representations that Integrate Stimuli, Responses, and Rules are Critical for Action Selection]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-11-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/837443v1?rss=1">
<title>
<![CDATA[
Sleep time, social jetlag and intelligence: biology or work timing? 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/837443v1?rss=1"
</link>
<description><![CDATA[
Sleep-wake patterns show substantial biological determination, but they are also subject to individual choice and societal pressure. Some evidence suggests that high IQ is associated with later sleep patterns. However, t is therefore unclear whether the relationship between IQ and later sleep is due to biological or social effects, such as timing and flexibility of working hours. We investigated the association between habitual sleep timing during work days and work-free days, working time and intelligence in a sample of 1,172 adults. We found no difference in chronotype, and the later sleep timing of high-IQ individuals on work days was fully accounted for by later work start times.

Our results indicate that later sleep timing in those with higher IQs is not due to physiological differences, but rather due to later or more flexible work schedules. Later working times and the resulting lower social jetlag may be one of the reasons why higher IQ is associated with lower prospective morbidity and mortality.

Statement of significanceSome evidence shows that higher intelligence is associated with sleep characteristics, but it is unclear if this is because of biological or social mechanisms. We provide evidence for a social mechanism. We found that high IQ individuals indeed sleep later, but only on working days, and this difference is fully accounted for by later work timing. Our evidence is consistent with a view that highly intelligent individuals sleep later because they can afford to, consequently experience lower social jetlag, and this may partially account for better health outcomes.
]]></description>
<dc:creator>Ujma, P. P.</dc:creator>
<dc:creator>Baudson, T.</dc:creator>
<dc:creator>Bodizs, R.</dc:creator>
<dc:creator>Dresler, M.</dc:creator>
<dc:date>2019-11-11</dc:date>
<dc:identifier>doi:10.1101/837443</dc:identifier>
<dc:title><![CDATA[Sleep time, social jetlag and intelligence: biology or work timing?]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-11-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/836874v1?rss=1">
<title>
<![CDATA[
Six new reference-quality bat genomes illuminate the molecular basis and evolution of bat adaptations 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/836874v1?rss=1"
</link>
<description><![CDATA[
Bats account for ~20% of all extant mammal species and are considered exceptional given their extraordinary adaptations, including biosonar, true flight, extreme longevity, and unparalleled immune systems. To understand these adaptations, we generated reference-quality genomes of six species representing the key divergent lineages. We assembled these genomes with a novel pipeline incorporating state-of-the-art long-read and long-range sequencing and assembly techniques. The genomes were annotated using a maximal evidence approach, de novo predictions, protein/mRNA alignments, Iso-seq long read and RNA-seq short read transcripts, and gene projections from our new TOGA pipeline, retrieving virtually all (>99%) mammalian BUSCO genes. Phylogenetic analyses of 12,931 protein coding-genes and 10,857 conserved non-coding elements identified across 48 mammalian genomes helped to resolve bats closest extant relatives within Laurasiatheria, supporting a basal position for bats within Scrotifera. Genome-wide screens along the bat ancestral branch revealed (a) selection on hearing-involved genes (e.g LRP2, SERPINB6, TJP2), which suggest that laryngeal echolocation is a shared ancestral trait of bats; (b) selection (e.g INAVA, CXCL13, NPSR1) and loss of immunity related proteins (e.g. LRRC70, IL36G), including pro-inflammatory NF-kB signalling; and (c) expansion of the APOBEC family, associated with restricting viral infection, transposon activity and interferon signalling. We also identified unique integrated viruses, indicating that bats have a history of tolerating viral pathogens, lethal to other mammal species. Non-coding RNA analyses identified variant and novel microRNAs, revealing regulatory relationships that may contribute to phenotypic diversity in bats. Together, our reference-quality genomes, high-quality annotations, genome-wide screens and in-vitro tests revealed previously unknown genomic adaptations in bats that may explain their extraordinary traits.
]]></description>
<dc:creator>Jebb, D.</dc:creator>
<dc:creator>Huang, Z.</dc:creator>
<dc:creator>Pippel, M.</dc:creator>
<dc:creator>Hughes, G. M.</dc:creator>
<dc:creator>Lavrichenko, K.</dc:creator>
<dc:creator>Devanna, P.</dc:creator>
<dc:creator>Winkler, S.</dc:creator>
<dc:creator>Jermiin, L. S.</dc:creator>
<dc:creator>Skirmuntt, E. C.</dc:creator>
<dc:creator>Katzourakis, A.</dc:creator>
<dc:creator>Burkitt-Gray, L.</dc:creator>
<dc:creator>Ray, D. A.</dc:creator>
<dc:creator>Sullivan, K. A.</dc:creator>
<dc:creator>Roscito, J. G.</dc:creator>
<dc:creator>Kirilenko, B. M.</dc:creator>
<dc:creator>Davalos, L. M.</dc:creator>
<dc:creator>Corthals, A. P.</dc:creator>
<dc:creator>Power, M.</dc:creator>
<dc:creator>Jones, G.</dc:creator>
<dc:creator>Ransome, R. D.</dc:creator>
<dc:creator>Dechmann, D.</dc:creator>
<dc:creator>Locatelli, A. G.</dc:creator>
<dc:creator>Puechmaille, S. J.</dc:creator>
<dc:creator>Fedrigo, O.</dc:creator>
<dc:creator>Jarvis, E. D.</dc:creator>
<dc:creator>Springer, M. S.</dc:creator>
<dc:creator>Hiller, M.</dc:creator>
<dc:creator>Vernes, S. C.</dc:creator>
<dc:creator>Myers, E. W.</dc:creator>
<dc:creator>Teeling, E. C.</dc:creator>
<dc:date>2019-11-09</dc:date>
<dc:identifier>doi:10.1101/836874</dc:identifier>
<dc:title><![CDATA[Six new reference-quality bat genomes illuminate the molecular basis and evolution of bat adaptations]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-11-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/834481v1?rss=1">
<title>
<![CDATA[
Primate homologs of mouse cortico-striatal circuits 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/834481v1?rss=1"
</link>
<description><![CDATA[
With the increasing necessity of animal models in biomedical research, there is a vital need to harmonise findings across species by establishing similarities and differences in rodent and primate neuroanatomy. Using a connectivity fingerprint matching approach, we compared cortico-striatal circuits across humans, non-human primates, and mice using resting state fMRI data in all species. Our results suggest that the connectivity patterns for both the nucleus accumbens and cortico-striatal motor circuits (posterior/lateral putamen) were conserved across species, making them reliable targets for cross-species comparisons. However, a large number of human and macaque striatal voxels were not matched to any mouse cortico-striatal circuit (mouse->human: 85% unassigned; mouse->macaque 69% unassigned; macaque->human; 31% unassigned). These unassigned voxels were largely localised to the caudate nucleus and anterior putamen, overlapping with executive function and social/language regions of the striatum, and connected to prefrontal-projecting cerebellar lobules and anterior prefrontal cortex, forming circuits that seem to be unique for non-human primates and humans. Our results demonstrate the potential of connectivity fingerprint matching to bridge the gap between rodent and primate neuroanatomy.
]]></description>
<dc:creator>Balsters, J. H.</dc:creator>
<dc:creator>Zerbi, V.</dc:creator>
<dc:creator>Sallet, J.</dc:creator>
<dc:creator>Wenderoth, N.</dc:creator>
<dc:creator>Mars, R. B.</dc:creator>
<dc:date>2019-11-08</dc:date>
<dc:identifier>doi:10.1101/834481</dc:identifier>
<dc:title><![CDATA[Primate homologs of mouse cortico-striatal circuits]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-11-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/830950v1?rss=1">
<title>
<![CDATA[
Tandem electrospinning for heterogeneous nanofiber patterns 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/830950v1?rss=1"
</link>
<description><![CDATA[
Smart nanofibrillar constructs can be a promising technological solution for many emerging and established fields, facilitating the potential impact of nano-scale strategies to address relevant technological challenges. As a fabrication technique, electrospinning (ESP) is relatively well-known, accessible, economic, and fast, though until now has shown limitation over control and design of the fibrillar constructs which can be produced. Here, we introduce "Tandem Electrospinning" (T-ESP), a novel technique able to create increasingly complex patterns of fibrous polymeric constructs on a micro and nano-scale. Modifying a standard ESP configuration results in a focusing electric field that is able to spatially define the deposition pattern of multiple polymer jets simultaneously. Additional spatially defined heterogeneity is achieved by tuning polymer solution properties to obtain a gradient of fiber alignment. Heterogeneous fibrous meshes are created with either random, aligned, or a divergent fiber patterns. This approach holds potential for many fields, with application examples shown for Tissue Engineering and Separation Technologies. The technique outlined here provides a rapid, versatile, and accessible method for polymeric nanofabrication of patterned heterogeneous fibrous constructs. Polymer properties are also shown to dictate fiber alignment, providing further insight into the mechanisms involved in the electrospinning fabrication process.
]]></description>
<dc:creator>Wieringa, P.</dc:creator>
<dc:creator>Truckenmuerller, R.</dc:creator>
<dc:creator>Micera, S.</dc:creator>
<dc:creator>van Wezel, R.</dc:creator>
<dc:creator>Moroni, L.</dc:creator>
<dc:date>2019-11-06</dc:date>
<dc:identifier>doi:10.1101/830950</dc:identifier>
<dc:title><![CDATA[Tandem electrospinning for heterogeneous nanofiber patterns]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-11-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/502716v1?rss=1">
<title>
<![CDATA[
Midfrontal theta phase coordinates behaviorally relevant brain computations during response conflict 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/502716v1?rss=1"
</link>
<description><![CDATA[
Neural oscillations are thought to provide a cyclic time frame for orchestrating brain computations. Following this assumption, midfrontal theta oscillations have recently been proposed to temporally organize brain computations during conflict processing. Using a multivariate analysis approach, we show that brain-behavior relationships during conflict tasks are modulated according to the phase of ongoing endogenous midfrontal theta oscillations recorded by scalp EEG. We found reproducible results in two independent datasets, using two different conflict tasks: brain-behavior relationships (correlation between reaction time and theta power) were theta phase-dependent in a subject-specific manner, and these "behaviorally optimal" theta phases were also associated with fronto-parietal cross-frequency dynamics emerging as theta phase-locked beta power bursts. These effects were present regardless of the strength of conflict. Thus, these results provide empirical evidence that midfrontal theta oscillations are involved in cyclically orchestrating brain computations likely related to response execution during the tasks rather than purely related to conflict processing. More generally, this study supports the hypothesis that phase-based computation is an important mechanism giving rise to cognitive processing.
]]></description>
<dc:creator>Duprez, J.</dc:creator>
<dc:creator>Gulbinaite, R.</dc:creator>
<dc:creator>Cohen, M. X.</dc:creator>
<dc:date>2018-12-20</dc:date>
<dc:identifier>doi:10.1101/502716</dc:identifier>
<dc:title><![CDATA[Midfrontal theta phase coordinates behaviorally relevant brain computations during response conflict]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-12-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/645234v1?rss=1">
<title>
<![CDATA[
Cross-species cortical alignment identifies different types of neuroanatomical reorganization in higher primates 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/645234v1?rss=1"
</link>
<description><![CDATA[
Evolutionary modifications of the temporo-parietal cortex are considered to be a critical adaptation of the human brain. Cortical adaptations, however, can affect different aspects of brain architecture, including areal expansion or changes in connectivity profiles. We propose to distinguishing different types of brain reorganization using a computational neuroanatomy approach. We investigate the extent to which between-species alignment based on cortical myelin can predict changes in connectivity patterns across macaque, chimpanzee and human. We show that expansion and relocation of brain areas are sufficient to predict terminations of several white matter tracts in temporo-parietal cortex, including the middle and superior longitudinal fasciculus, but not of the arcuate fasciculus. This demonstrates that the arcuate fasciculus underwent additional evolutionary modifications affecting the connectivity pattern of the temporal lobe. The presented approach can flexibly be extended to include other features of cortical organization and other species, allowing direct tests of comparative hypotheses of brain organization.
]]></description>
<dc:creator>Eichert, N.</dc:creator>
<dc:creator>Robinson, E. C.</dc:creator>
<dc:creator>Bryant, K. L.</dc:creator>
<dc:creator>Jbabdi, S.</dc:creator>
<dc:creator>Jenkinson, M.</dc:creator>
<dc:creator>Li, L.</dc:creator>
<dc:creator>Krug, K.</dc:creator>
<dc:creator>Watkins, K. E.</dc:creator>
<dc:creator>Mars, R. B.</dc:creator>
<dc:date>2019-05-22</dc:date>
<dc:identifier>doi:10.1101/645234</dc:identifier>
<dc:title><![CDATA[Cross-species cortical alignment identifies different types of neuroanatomical reorganization in higher primates]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-05-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/530121v1?rss=1">
<title>
<![CDATA[
Oscillatory Mechanisms of Successful Memory Formation in Younger and Older Adults Are Related to Structural Integrity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/530121v1?rss=1"
</link>
<description><![CDATA[
We studied oscillatory mechanisms of successful memory formation in 47 younger and 52 older adults in an intentional associative memory task with cued recall. While older adults showed reduced memory performance, we found subsequent memory effects (SME) in alpha/beta and theta frequency bands in both age groups. Using logistic mixed effect models, we then investigated whether interindividual differences in structural integrity of memory regions that were functionally linked to oscillatory dynamics in previous studies (Hanslmayr et al., 2011) could account for interindividual differences in the strength of the SME. Structural integrity of inferior frontal gyrus (IFG) and hippocampus (HC) was reduced in older adults. SME in the alpha/beta band were indeed modulated by the cortical thickness of inferior frontal gyrus (IFG), in line with its hypothesized role for deep semantic elaboration. Importantly, this structure-function relationship did not differ by age group. However, older adults were more frequently represented among the participants with low cortical thickness and consequently weaker SME in the alpha band. Thus, our results suggest that differences in the structural integrity of the IFG are the basis not only for interindividual, but also for age differences in memory formation.
]]></description>
<dc:creator>Sander, M. C.</dc:creator>
<dc:creator>Fandakova, Y.</dc:creator>
<dc:creator>Grandy, T. H.</dc:creator>
<dc:creator>Shing, Y. L.</dc:creator>
<dc:creator>Werkle-Bergner, M.</dc:creator>
<dc:date>2019-01-24</dc:date>
<dc:identifier>doi:10.1101/530121</dc:identifier>
<dc:title><![CDATA[Oscillatory Mechanisms of Successful Memory Formation in Younger and Older Adults Are Related to Structural Integrity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-01-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/822700v1?rss=1">
<title>
<![CDATA[
Recurrent interactions in local cortical circuits 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/822700v1?rss=1"
</link>
<description><![CDATA[
The majority of cortical synapses are local and excitatory. Local recurrent circuits could implement amplification, allowing for pattern completion and other computations1. Cortical circuits contain subnetworks, consisting of neurons with similar receptive fields and elevated connectivity relative to the network average2,3. Understanding the computations performed by these subnetworks during behavior has been hampered by the fact that cortical neurons encoding different types of information are spatially intermingled and distributed over large brain volumes 4,5. We used computational modeling, optical recordings and manipulations to probe the function of recurrent coupling in layer (L) 2/3 of the somatosensory cortex during tactile discrimination. A model of L2/3 dynamics revealed that recurrent excitation enhances sensory signals via amplification, but only for subnetwork with elevated connectivity. Networks with high amplification were sensitive to damage: loss of a few subnetwork members degraded stimulus encoding. We tested this prediction experimentally by mapping neuronal selectivity5 and photoablating6,7 neurons with specific selectivity. In L2/3 of the somatosensory cortex, ablating a small proportion (10-20, < 5 % of the total) of neurons representing touch dramatically reduced responses in the spared touch representation, but not other representations. Network models further predicted that degradation following ablation should be greatest among spared neurons with stimulus responses that were most similar to the ablated population. Consistent with this prediction, ablations most strongly impacted neurons with selectivity similar to the ablated population. Our data shows that recurrence among cortical neurons with similar selectivity can drive input-specific amplification during behavior.
]]></description>
<dc:creator>Peron, S. P.</dc:creator>
<dc:creator>Voelcker, B.</dc:creator>
<dc:creator>Pancholi, R.</dc:creator>
<dc:creator>Wittenbach, J.</dc:creator>
<dc:creator>Olafsdottir, H. F.</dc:creator>
<dc:creator>Freeman, J.</dc:creator>
<dc:creator>Svoboda, K.</dc:creator>
<dc:date>2019-10-29</dc:date>
<dc:identifier>doi:10.1101/822700</dc:identifier>
<dc:title><![CDATA[Recurrent interactions in local cortical circuits]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/825083v1?rss=1">
<title>
<![CDATA[
The Role of Gene Encoding Variation of DRD4 in the Relationship between Inattention and Seasonal Daylight 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/825083v1?rss=1"
</link>
<description><![CDATA[
Daylight is the strongest synchronizer of human circadian rhythms. The circadian pathway hypothesis posits that synchrony between daylight and the circadian system relates to (in)attention. The dopamine neurotransmitter system is implicated in regulating the circadian system as well as in (attention)-deficit hyperactivity disorder [ADHD]. We studied the role of functional genetic variation in the gene encoding of dopamine-receptor-D4 (DRD4) in the relationship between inattention and seasonal daylight (changes). Gene-by-environment (GxE) mega-analyses were performed across eight studies including 3757 adult participants (with and without ADHD). We tested 1) the Spring-focus hypothesis, in which attention in 7R-carriers normalizes with increasing daylight levels preceding measurement, 2) the Summer-born ADHD hypothesis, in which 7R-carriers report more inattention when born in spring/summer than in autumn/winter, 3) the Winter-born ADHD hypothesis, opposing the second hypothesis. The Spring-focus hypothesis was upheld (1386 ADHD, 760 controls; d=-0.16 between periods); 7R-carriers reported even less inattention than 7R-non-carriers after winter solstice (d=0.27 between genotype-groups). Results were diagnosis-independent. Sensitivity analyses at individual study level confirmed the circannual patterns for 7R-carriers. Incorporating geographic changes into the independent measure, we also calculated changes in sunlight levels. This approach likewise showed that inattention correlated negatively with increasing light levels in 7R-carriers (r=-.135). Results emphasize peripheral effects of dopamine and the effects of (seasonal) daylight changes on cognition.
]]></description>
<dc:creator>Vollebregt, M.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Arnold, L. E.</dc:creator>
<dc:creator>Faraone, S.</dc:creator>
<dc:creator>Grevet, E. H.</dc:creator>
<dc:creator>Reif, A.</dc:creator>
<dc:creator>Zayats, T.</dc:creator>
<dc:creator>Bralten, J.</dc:creator>
<dc:creator>Bau, C. H.</dc:creator>
<dc:creator>Haavik, J.</dc:creator>
<dc:creator>Kuntsi, J.</dc:creator>
<dc:creator>Cupertino, R.</dc:creator>
<dc:creator>Loo, S.</dc:creator>
<dc:creator>Lundervold, A. J.</dc:creator>
<dc:creator>Ribases, M.</dc:creator>
<dc:creator>Sanchez-Mora, C.</dc:creator>
<dc:creator>Ramos-Quiroga, J. A.</dc:creator>
<dc:creator>Asherson, P.</dc:creator>
<dc:creator>Swanson, J. M.</dc:creator>
<dc:creator>Arns, M.</dc:creator>
<dc:date>2019-10-31</dc:date>
<dc:identifier>doi:10.1101/825083</dc:identifier>
<dc:title><![CDATA[The Role of Gene Encoding Variation of DRD4 in the Relationship between Inattention and Seasonal Daylight]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/820571v1?rss=1">
<title>
<![CDATA[
Adaptive Spike-Artifact Removal from Local Field Potentials Uncovers Prominent Beta and Gamma Band Neuronal Synchronization 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/820571v1?rss=1"
</link>
<description><![CDATA[
BackgroundMany neurons synchronize their action potentials to the phase of local field potential (LFP) fluctuations in one or more frequency bands. Analyzing this spike-to-LFP synchronization is challenging, however, when neural spikes and LFP are generated in the same local circuit, because the spikes action potential waveform leak into the LFP and distort phase synchrony estimates. Existing approaches to address this spike bleed-through artifact relied on removing the average action potential waveforms of neurons, but this leaves artifacts in the LFP and distorts synchrony estimates.nnNew MethodWe describe a spike-removal method that surpasses these limitations by decomposing individual action potentials into their frequency components before their removal from the LFP. The adaptively estimated frequency components allow for variable spread, strength and temporal variation of the spike artifact.nnResultsThis adaptive approach effectively removes spike bleed-through artifacts in synthetic data with known ground truth, and in single neuron and LFP recordings in nonhuman primate striatum. For a large population of neurons with both narrow and broad action potential waveforms, the use of adaptive artifact removal uncovered 20-35 Hz beta and 35-45 Hz gamma band spike-LFP synchronization that would have remained contaminated otherwise.nnComparison with Existing MethodsWe demonstrate that adaptive spike-artifact removal cleans LFP data that remained contaminated when applying existing Bayesian and non-Bayesian methods of average spike-artifact removal.nnConclusionsApplying adaptive spike-removal from field potentials allows to estimate the phase at which neurons synchronize and the consistency of their phase-locked firing for both beta and low gamma frequencies. These metrics may prove essential to understand cell-to-circuit neuronal interactions in multiple brain systems.
]]></description>
<dc:creator>Banaie Boroujeni, K.</dc:creator>
<dc:creator>Tiesinga, P.</dc:creator>
<dc:creator>Womelsdorf, T.</dc:creator>
<dc:date>2019-10-28</dc:date>
<dc:identifier>doi:10.1101/820571</dc:identifier>
<dc:title><![CDATA[Adaptive Spike-Artifact Removal from Local Field Potentials Uncovers Prominent Beta and Gamma Band Neuronal Synchronization]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/817767v1?rss=1">
<title>
<![CDATA[
Resolving the dark matter of ABCA4 for 1,054 Stargardt disease probands through integrated genomics and transcriptomics 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/817767v1?rss=1"
</link>
<description><![CDATA[
Missing heritability in human diseases represents a major challenge. Although whole-genome sequencing enables the analysis of coding and non-coding sequences, substantial costs and data storage requirements hamper its large-scale use to (re)sequence genes in genetically unsolved cases. The ABCA4 gene implicated in Stargardt disease (STGD1) has been studied extensively for 22 years, but thousands of cases remained unsolved. Therefore, single molecule molecular inversion probes were designed that enabled an automated and cost-effective sequence analysis of the complete 128-kb ABCA4 gene. Analysis of 1,054 unsolved STGD and STGD-like probands resulted in bi-allelic variations in 448 probands. Twenty-seven different causal deep-intronic variants were identified in 117 alleles. Based on in vitro splice assays, the 13 novel causal deep-intronic variants were found to result in pseudo-exon (PE) insertions (n=10) or exon elongations (n=3). Intriguingly, intron 13 variants c.1938-621G>A and c.1938-514G>A resulted in dual PE insertions consisting of the same upstream, but different downstream PEs. The intron 44 variant c.6148-84A>T resulted in two PE insertions that were accompanied by flanking exon deletions. Structural variant analysis revealed 11 distinct deletions, two of which contained small inverted segments. Uniparental isodisomy of chromosome 1 was identified in one proband. Integrated complete gene sequencing combined with transcript analysis, identified pathogenic deep-intronic and structural variants in 26% of bi-allelic cases not solved previously by sequencing of coding regions. This strategy serves as a model study that can be applied to other inherited diseases in which only one or a few genes are involved in the majority of cases.
]]></description>
<dc:creator>Khan, M.</dc:creator>
<dc:creator>Cornelis, S. S.</dc:creator>
<dc:creator>Pozo-Valero, M. d.</dc:creator>
<dc:creator>Whelan, L.</dc:creator>
<dc:creator>Runhart, E. H.</dc:creator>
<dc:creator>Mishra, K.</dc:creator>
<dc:creator>Bults, F.</dc:creator>
<dc:creator>AlSwaiti, Y.</dc:creator>
<dc:creator>AlTabishi, A.</dc:creator>
<dc:creator>Baere, E. D.</dc:creator>
<dc:creator>Banfi, S.</dc:creator>
<dc:creator>Banin, E.</dc:creator>
<dc:creator>Bauwens, M.</dc:creator>
<dc:creator>Ben-Yosef, T.</dc:creator>
<dc:creator>Boon, C. J. F.</dc:creator>
<dc:creator>Born, L. I. v. d.</dc:creator>
<dc:creator>Defoort, S.</dc:creator>
<dc:creator>Devos, A.</dc:creator>
<dc:creator>Dockery, A.</dc:creator>
<dc:creator>Dudakova, L.</dc:creator>
<dc:creator>Fakin, A.</dc:creator>
<dc:creator>Farrar, G. J.</dc:creator>
<dc:creator>Ferraz Sallum, J. M.</dc:creator>
<dc:creator>Fujinami, K.</dc:creator>
<dc:creator>Gilissen, C.</dc:creator>
<dc:creator>Glavac, D.</dc:creator>
<dc:creator>Gorin, M. B.</dc:creator>
<dc:creator>Greenberg, J.</dc:creator>
<dc:creator>Hayashi, T.</dc:creator>
<dc:creator>Hettinga, Y.</dc:creator>
<dc:creator>Hoischen, A.</dc:creator>
<dc:creator>Hoyng, C. B.</dc:creator>
<dc:creator>Hufendiek, K.</dc:creator>
<dc:creator>Jagle, H.</dc:creator>
<dc:creator>Kamakari, S.</dc:creator>
<dc:creator>Karali, M.</dc:creator>
<dc:creator>Kellner, U.</dc:creator>
<dc:creator>Klaver, C. C. W.</dc:creator>
<dc:creator>Kousal, B.</dc:creator>
<dc:creator>Lamey, T.</dc:creator>
<dc:creator>MacDonald, I. M.</dc:creator>
<dc:creator>Matynia, A.</dc:creator>
<dc:creator>McLaren, T.</dc:creator>
<dc:creator>M</dc:creator>
<dc:date>2019-10-25</dc:date>
<dc:identifier>doi:10.1101/817767</dc:identifier>
<dc:title><![CDATA[Resolving the dark matter of ABCA4 for 1,054 Stargardt disease probands through integrated genomics and transcriptomics]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/809582v1?rss=1">
<title>
<![CDATA[
Structural Brain Imaging Studies Offer Clues about the Effects of the Shared Genetic Etiology among Neuropsychiatric Disorders 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/809582v1?rss=1"
</link>
<description><![CDATA[
BackgroundGenomewide association studies have found significant genetic correlations among many neuropsychiatric disorders. In contrast, we know much less about the degree to which structural brain alterations are similar among disorders and, if so, the degree to which such similarities have a genetic etiology.

MethodsFrom the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium, we acquired standardized mean differences (SMDs) in regional brain volume and cortical thickness between cases and controls. We had data on 41 brain regions for: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), epilepsy, major depressive disorder (MDD), obsessive compulsive disorder (OCD) and schizophrenia (SCZ). These data had been derived from 24,360 patients and 37,425 controls.

ResultsThe SMDs were significantly correlated between SCZ and BD, OCD, MDD, and ASD. MDD was positively correlated with BD and OCD. BD was positively correlated with OCD and negatively correlated with ADHD. These pairwise correlations among disorders were correlated with the corresponding pairwise correlations among disorders derived from genomewide association studies (r = 0.49).

ConclusionsOur results show substantial similarities in sMRI phenotypes among neuropsychiatric disorders and suggest that these similarities are accounted for, in part, by corresponding similarities in common genetic variant architectures.
]]></description>
<dc:creator>Radonjic, N. V.</dc:creator>
<dc:creator>Hess, J. L.</dc:creator>
<dc:creator>Rovira, P.</dc:creator>
<dc:creator>Andreassen, O.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Ching, C. R. K.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Hoogman, M.</dc:creator>
<dc:creator>Jahanshad, N.</dc:creator>
<dc:creator>McDonald, C.</dc:creator>
<dc:creator>Schmaal, L.</dc:creator>
<dc:creator>Sisodiya, S. M.</dc:creator>
<dc:creator>Stein, D. J.</dc:creator>
<dc:creator>van den Heuvel, O. A.</dc:creator>
<dc:creator>van Erp, T. G. M.</dc:creator>
<dc:creator>van Rooij, D.</dc:creator>
<dc:creator>Veltman, D. J.</dc:creator>
<dc:creator>Thompson, P.</dc:creator>
<dc:creator>Faraone, S. V.</dc:creator>
<dc:date>2019-10-17</dc:date>
<dc:identifier>doi:10.1101/809582</dc:identifier>
<dc:title><![CDATA[Structural Brain Imaging Studies Offer Clues about the Effects of the Shared Genetic Etiology among Neuropsychiatric Disorders]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/781195v1?rss=1">
<title>
<![CDATA[
Genetic underpinnings of sociability in the UK Biobank 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/781195v1?rss=1"
</link>
<description><![CDATA[
Difficulties with sociability include a tendency to avoid social contacts and activities, and to prefer being alone rather than being with others. While sociability is a continuously distributed trait in the population, decreased sociability represent a common early manifestation of multiple neuropsychiatric disorders such as Schizophrenia (SCZ), Bipolar Disorder (BP), Major Depressive Disorder (MDD), Autism Spectrum Disorders (ASDs), and Alzheimers disease (AD). We aimed to investigate the genetic underpinnings of sociability as a continuous trait in the general population. In this respect, we performed a genome-wide association study (GWAS) using a sociability score based on 4 social functioning-related self-report questions in the UK Biobank sample (n=342,461) to test the effect of individual genetic variants. This was followed by LD score analyses to investigate the genetic correlation with psychiatric disorders (SCZ, BP, MDD, ASDs) and a neurological disorder (AD) as well as related phenotypes (Loneliness and Social Anxiety). The phenotypic data indeed showed that the sociability score was decreased in individuals with ASD, (probable) MDD, BP and SCZ, but not in individuals with AD. Our GWAS showed 604 genome-wide significant SNPs, coming from 18 independent loci (SNP-based h2=0.06). Genetic correlation analyses showed significant correlations with SCZ (rg=0.15, p=9.8e-23), MDD (rg=0.68, p=6.6e-248) and ASDs (rg=0.27, p=4.5e-28), but no correlation with BP (rg=0.01, p=0.45) or AD (rg=0.04, p=0.55). Our sociability trait was also genetically correlated with Loneliness (rg=0.45, p=2.4e-8) and Social Anxiety (rg=0.48, p=0.002). Our study shows that there is a significant genetic component to variation in population levels of sociability, which is relevant to some psychiatric disorders (SCZ, MDD, ASDs), but not to BP and AD.
]]></description>
<dc:creator>Bralten, J.</dc:creator>
<dc:creator>Klemann, C. J. H. M.</dc:creator>
<dc:creator>Mota, N. R.</dc:creator>
<dc:creator>de Witte, W.</dc:creator>
<dc:creator>Arango, C.</dc:creator>
<dc:creator>Fabbri, C.</dc:creator>
<dc:creator>Kas, M. J.</dc:creator>
<dc:creator>van der Wee, N.</dc:creator>
<dc:creator>Penninx, B. W. J. H.</dc:creator>
<dc:creator>Serretti, A.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Poelmans, G.</dc:creator>
<dc:date>2019-09-25</dc:date>
<dc:identifier>doi:10.1101/781195</dc:identifier>
<dc:title><![CDATA[Genetic underpinnings of sociability in the UK Biobank]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/811711v1?rss=1">
<title>
<![CDATA[
The genetic architecture of human brainstem structures and their involvement in common brain disorders 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/811711v1?rss=1"
</link>
<description><![CDATA[
Brainstem regions support critical bodily functions, yet their genetic architectures and involvement in brain disorders remain understudied. Here, we examined volumes of brainstem structures using magnetic resonance imaging in 43,353 individuals. In 27,034 genotyped healthy participants, we identified 16 genetic loci associated with whole brainstem volume and 10, 23, 3, and 9 loci associated with volumes of the midbrain, pons, superior cerebellar peduncle, and medulla oblongata, respectively. These loci were mapped to 305 genes, including genes linked to brainstem development and common brain disorders. We detected genetic overlap between the brainstem volumes and eight psychiatric and neurological disorders. Using imaging data from 16,319 additional individuals, we observed differential volume alterations in schizophrenia, bipolar disorder, multiple sclerosis, mild cognitive impairment, dementia, and Parkinsons disease. Together, our results provide new insights into the genetic underpinnings of brainstem structures and support their involvement in common brain disorders.
]]></description>
<dc:creator>Elvsashagen, T.</dc:creator>
<dc:creator>Bahrami, S.</dc:creator>
<dc:creator>van der Meer, D.</dc:creator>
<dc:creator>Agartz, I.</dc:creator>
<dc:creator>Alnaes, D.</dc:creator>
<dc:creator>Barch, D. M.</dc:creator>
<dc:creator>Baur-Streubel, R.</dc:creator>
<dc:creator>Bertolino, A.</dc:creator>
<dc:creator>Beyer, M. K.</dc:creator>
<dc:creator>Blasi, G.</dc:creator>
<dc:creator>Borgwardt, S.</dc:creator>
<dc:creator>Boye, B.</dc:creator>
<dc:creator>Buitelaar, J.</dc:creator>
<dc:creator>Boen, E.</dc:creator>
<dc:creator>Celius, E. G.</dc:creator>
<dc:creator>Cervenka, S.</dc:creator>
<dc:creator>Conzelmann, A.</dc:creator>
<dc:creator>Coynel, D.</dc:creator>
<dc:creator>Di Carlo, P.</dc:creator>
<dc:creator>Djurovic, S.</dc:creator>
<dc:creator>Eisenacher, S.</dc:creator>
<dc:creator>Espeseth, T.</dc:creator>
<dc:creator>Fatouros-Bergman, H.</dc:creator>
<dc:creator>Flyckt, L.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Frei, O.</dc:creator>
<dc:creator>Gelao, B.</dc:creator>
<dc:creator>Harbo, H. F.</dc:creator>
<dc:creator>Hartman, C. A.</dc:creator>
<dc:creator>Haberg, A.</dc:creator>
<dc:creator>Heslenfeld, D.</dc:creator>
<dc:creator>Hoekstra, P.</dc:creator>
<dc:creator>Hogestol, E. A.</dc:creator>
<dc:creator>Jonassen, R.</dc:creator>
<dc:creator>Jonsson, E. G.</dc:creator>
<dc:creator>Kirsch, P.</dc:creator>
<dc:creator>Kloszewska, I.</dc:creator>
<dc:creator>Lagerberg, T. V.</dc:creator>
<dc:creator>Landro, N. I.</dc:creator>
<dc:creator>Le Hellard, S.</dc:creator>
<dc:creator>Lesch, K.-P.</dc:creator>
<dc:creator>Maglanoc, L.</dc:creator>
<dc:date>2019-10-21</dc:date>
<dc:identifier>doi:10.1101/811711</dc:identifier>
<dc:title><![CDATA[The genetic architecture of human brainstem structures and their involvement in common brain disorders]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/791160v1?rss=1">
<title>
<![CDATA[
Identification of risk variants and characterization of the polygenic architecture of disruptive behavior disorders in the context of ADHD 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/791160v1?rss=1"
</link>
<description><![CDATA[
Attention-Deficit/Hyperactivity Disorder (ADHD) is a childhood psychiatric disorder often comorbid with disruptive behavior disorders (DBDs). ADHD comorbid with DBDs (ADHD+DBDs) is a complex phenotype with a risk component that can be attributed to common genetic variants. Here we report a large GWAS meta-analysis of ADHD+DBDs based on seven cohorts in total including 3,802 cases and 31,305 controls. Three genome-wide significant loci were identified on chromosomes 1, 7, and 11. A GWAS meta-analysis including a Chinese cohort supported the locus on chromosome 11 to be a strong risk locus for ADHD+DBDs across European and Chinese ancestries (rs7118422, P=3.15x10-10, OR=1.17). This locus was not associated with ADHD without DBDs in a secondary GWAS of 13,583 ADHD cases and 22,314 controls, suggesting that the locus is a specific risk locus for the comorbid phenotype.nnWe found a higher SNP heritability for ADHD+DBDs (h2SNP =0.34) when compared to ADHD without DBDs (h2SNP =0.20). Genetic correlations of ADHD+DBDs with aggressive (rg =0.81) and anti-social behaviors (rg=0.82) were high, and polygenic risk score analyses revealed a significant increased burden of variants associated with ADHD and aggression in individuals with ADHD+DBDs compared to ADHD without DBDs. Our results suggests that ADHD+DBDs represent a more severe phenotype with respect to the genetic risk load than ADHD without DBDs, in line with previous studies, and that the risk load to some extent can be explained by variants associated with aggressive behavior.
]]></description>
<dc:creator>Demontis, D.</dc:creator>
<dc:creator>Walters, R. K.</dc:creator>
<dc:creator>Rajagopal, V. M.</dc:creator>
<dc:creator>Waldman, I. D.</dc:creator>
<dc:creator>Grove, J.</dc:creator>
<dc:creator>Als, T. D.</dc:creator>
<dc:creator>Dalsgaard, S.</dc:creator>
<dc:creator>Ribases, M.</dc:creator>
<dc:creator>Bybjerg-Grauholm, J.</dc:creator>
<dc:creator>Baekvad-Hansen, M.</dc:creator>
<dc:creator>Werge, T.</dc:creator>
<dc:creator>Nordentoft, M.</dc:creator>
<dc:creator>Mors, O.</dc:creator>
<dc:creator>Mortensen, P. B.</dc:creator>
<dc:creator>ADHD Working Group of the Psychiatric Genomics Consortium (PGC),</dc:creator>
<dc:creator>Hougaard, D. M.</dc:creator>
<dc:creator>Neale, B.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Faraone, S. V.</dc:creator>
<dc:creator>Borglum, A. D.</dc:creator>
<dc:date>2019-10-02</dc:date>
<dc:identifier>doi:10.1101/791160</dc:identifier>
<dc:title><![CDATA[Identification of risk variants and characterization of the polygenic architecture of disruptive behavior disorders in the context of ADHD]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/804864v1?rss=1">
<title>
<![CDATA[
Efficient and robust coding in heterogeneous recurrent networks 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/804864v1?rss=1"
</link>
<description><![CDATA[
Cortical networks show a large heterogeneity of neuronal properties. However, traditional coding models have focused on homogeneous populations of excitatory and inhibitory neurons. Here, we analytically derive a class of recurrent networks of spiking neurons that close to optimally track a continuously varying input online, based on two assumptions: 1) every spike is decoded linearly and 2) the network aims to reduce the mean-squared error between the input and the estimate. From this we derive a class of predictive coding networks, that unifies encoding and decoding and in which we can investigate the difference between homogeneous networks and heterogeneous networks, in which each neurons represents different features and has different spike-generating properties. We find that in this framework,  type 1 and  type 2 neurons arise naturally and networks consisting of a heterogeneous population of different neuron types are both more efficient and more robust against correlated noise. We make two experimental predictions: 1) we predict that integrators show strong correlations with other integrators and resonators are correlated with resonators, whereas the correlations are much weaker between neurons with different coding properties and 2) that  type 2 neurons are more coherent with the overall network activity than  type 1 neurons.
]]></description>
<dc:creator>Zeldenrust, F.</dc:creator>
<dc:creator>Gutkin, B.</dc:creator>
<dc:creator>Deneve, S.</dc:creator>
<dc:date>2019-10-16</dc:date>
<dc:identifier>doi:10.1101/804864</dc:identifier>
<dc:title><![CDATA[Efficient and robust coding in heterogeneous recurrent networks]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/800540v1?rss=1">
<title>
<![CDATA[
Adaptive time scales in recurrent neural networks 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/800540v1?rss=1"
</link>
<description><![CDATA[
Recurrent neural network models have become widely used in computational neuroscience to model the dynamics of neural populations as well as in machine learning applications to model data with temporal dependencies. The different variants of RNNs commonly used in these scientific fields can be derived as discrete time approximations of the instantaneous firing rate of a population of neurons. The time constants of the neuronal process are generally ignored in these approximations, while learning these time constants could possibly inform us about the time scales underlying temporal processes and enhance the expressive capacity of the network. To investigate the potential of adaptive time constants, we compare the standard Elman approximation to a more lenient one that still accounts for the time scales at which processes unfold. We show that such a model with adaptive time scales performs better on predicting temporal data, increasing the memory capacity of recurrent neural networks, and allows recovery of the time scales at which the underlying processes unfold.
]]></description>
<dc:creator>Quax, S. C.</dc:creator>
<dc:creator>D'Asaro, M.</dc:creator>
<dc:creator>van Gerven, M. A. J.</dc:creator>
<dc:date>2019-10-10</dc:date>
<dc:identifier>doi:10.1101/800540</dc:identifier>
<dc:title><![CDATA[Adaptive time scales in recurrent neural networks]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/795799v1?rss=1">
<title>
<![CDATA[
Comparison of beamformer implementations for MEG source localization 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/795799v1?rss=1"
</link>
<description><![CDATA[
Beamformers are applied for estimating spatiotemporal characteristics of neuronal sources underlying measured MEG/EEG signals. Several MEG analysis toolboxes include an implementation of a linearly constrained minimum-variance (LCMV) beamformer. However, differences in implementations and in their results complicate the selection and application of beamformers and may hinder their wider adoption in research and clinical use. Additionally, combinations of different MEG sensor types (such as magnetometers and planar gradiometers) and application of preprocessing methods for interference suppression, such as signal space separation (SSS), can affect the results in different ways for different implementations. So far, a systematic evaluation of the different implementations has not been performed. Here, we compared the localization performance of the LCMV beamformer pipelines in four widely used open-source toolboxes (FieldTrip, SPM12, Brainstorm, and MNE-Python) using datasets both with and without SSS interference suppression.nnWe analyzed MEG data that were i) simulated, ii) recorded from a static and moving phantom, and iii) recorded from a healthy volunteer receiving auditory, visual, and somatosensory stimulation. We also investigated the effects of SSS and the combination of the magnetometer and gradiometer signals. We quantified how localization error and point-spread volume vary with SNR in all four toolboxes.nnWhen applied carefully to MEG data with a typical SNR (3-15 dB), all four toolboxes localized the sources reliably; however, they differed in their sensitivity to preprocessing parameters. As expected, localizations were highly unreliable at very low SNR, but we found high localization error also at very high SNRs. We also found that the SNR improvement offered by SSS led to more accurate localization.
]]></description>
<dc:creator>Jaiswal, A. K.</dc:creator>
<dc:creator>Nenonen, J.</dc:creator>
<dc:creator>Stenroos, M.</dc:creator>
<dc:creator>Gramfort, A.</dc:creator>
<dc:creator>Dalal, S. S.</dc:creator>
<dc:creator>Westner, B. U.</dc:creator>
<dc:creator>Litvak, V.</dc:creator>
<dc:creator>Mosher, J. C.</dc:creator>
<dc:creator>Schoffelen, J. M.</dc:creator>
<dc:creator>Witton, C.</dc:creator>
<dc:creator>Oostenveld, R.</dc:creator>
<dc:creator>Parkkonen, L.</dc:creator>
<dc:date>2019-10-07</dc:date>
<dc:identifier>doi:10.1101/795799</dc:identifier>
<dc:title><![CDATA[Comparison of beamformer implementations for MEG source localization]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/795567v1?rss=1">
<title>
<![CDATA[
Brain rhythms shift and deploy attention 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/795567v1?rss=1"
</link>
<description><![CDATA[
One of the most central cognitive functions is attention. Its neuronal underpinnings have primarily been studied during conditions of sustained attention. Much less is known about the neuronal dynamics underlying the processes of shifting attention in space, as compared to maintaining it on one stimulus, and of deploying it to a particular stimulus. Here, we use ECoG to investigate four rhythms across large parts of the left hemisphere of two macaque monkeys during a task that allows investigation of deployment and shifting. Shifting involved a strong transient enhancement of power in a 2-7 Hz theta band in frontal, pre-motor and visual areas, and reductions of power in an 11-20 Hz beta band in a fronto-centro-parietal network and in a 29-36 Hz high-beta band in premotor cortex. Deployment of attention to the contralateral hemifield involved an enhancement of beta power in parietal areas, a concomitant reduction of high-beta power in pre-motor areas and an enhancement of power in a 60-76 Hz gamma band in extra-striate cortex. Effects due to shifting occurred earlier than effects due to deployment. These results demonstrate that the four investigated rhythms are involved in attentional allocation, with striking differences between shifting and deployment between different brain areas.nnSignificanceWe are often confronted by many visual stimuli, and attentional mechanisms select one stimulus for in-depth processing. This involves that attention is shifted between stimuli and deployed to one stimulus at a time. Prior studies have revealed that these processes are subserved by several brain rhythms. Therefore, we recorded brain activity in macaque monkeys with many electrodes distributed over large parts of their left hemisphere, while they performed a task that involved shifting and deploying attention. We found four dominant rhythms: theta (2-7 Hz), beta (11-20 Hz), high-beta (29-36 Hz) and gamma (60-76 Hz). Attentional shifting and deployment involved dynamic modulations in the strength of those rhythms with high specificity in space and time.
]]></description>
<dc:creator>Richter, C. G.</dc:creator>
<dc:creator>Bosman, C. A.</dc:creator>
<dc:creator>Vezoli, J.</dc:creator>
<dc:creator>Schoffelen, J.-M.</dc:creator>
<dc:creator>Fries, P.</dc:creator>
<dc:date>2019-10-07</dc:date>
<dc:identifier>doi:10.1101/795567</dc:identifier>
<dc:title><![CDATA[Brain rhythms shift and deploy attention]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/790204v1?rss=1">
<title>
<![CDATA[
Reduced fronto-striatal volume in ADHD in two cohorts across the lifespan 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/790204v1?rss=1"
</link>
<description><![CDATA[
ObjectiveNeuroimaging studies have associated Attention-Deficit/Hyperactivity Disorder (ADHD) with altered brain anatomy. However, small and heterogeneous study samples, and the use of region-of-interest and tissue-specific analyses have limited the consistency and replicability of these effects. The present study uses a fully data-driven multivariate approach to investigate alterations in both gray and white matter simultaneously, and capture neuroanatomical features associated with ADHD in two large, independent, demographically different cohorts.nnMethodsThe study comprised two ADHD cohorts with structural magnetic resonance imaging data: the Dutch NeuroIMAGE cohort (n=890, average age 17.2 years, discovery sample) and the Brazilian IMpACT cohort (n=180, average age 44.2 years, cross validation sample). Using independent component analysis of whole-brain morphometry images in the NeuroIMAGE cohort, 375 independent components of neuroanatomical variations were extracted and assessed their association with ADHD. Afterwards, ADHD-associated components were cross validated in the Brazilian IMpACT cohort.nnResultsIn both discovery (corrected- p=0.020) and validation (p=0.033) cohorts, ADHD diagnosis was significantly associated with reduced brain volume in a component mapping to frontal lobes, striatum, and their interconnecting white-matter tracts. The most pronounced case-control differences were localized in white matter adjacent to the orbitofrontal cortex.nnConclusionIndependent component analysis is a sensitive approach to uncover neuroanatomical alterations in ADHD and avoid bias attributable to a priori region-of-interest based methods. Current results provide further evidence for the role of the fronto-striatal circuit in ADHD. The fact that the two cohorts are from different continents and comprising different age ranges highlights the robustness of the findings.
]]></description>
<dc:creator>Cupertino, R. B.</dc:creator>
<dc:creator>Soheili-Nezhad, S.</dc:creator>
<dc:creator>Grevet, E. H.</dc:creator>
<dc:creator>Bandeira, C. E.</dc:creator>
<dc:creator>Picon, F. A.</dc:creator>
<dc:creator>Tavares, M. E.</dc:creator>
<dc:creator>Naaijen, J.</dc:creator>
<dc:creator>van Rooij, D.</dc:creator>
<dc:creator>Akkermans, S.</dc:creator>
<dc:creator>Vitola, E. S.</dc:creator>
<dc:creator>Zwiers, M. P.</dc:creator>
<dc:creator>Hoekstra, P. J.</dc:creator>
<dc:creator>Breda, V.</dc:creator>
<dc:creator>Oosterlaan, J.</dc:creator>
<dc:creator>Hartman, C. A.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Dotto Bau, C. H.</dc:creator>
<dc:creator>Sprooten, E.</dc:creator>
<dc:date>2019-10-02</dc:date>
<dc:identifier>doi:10.1101/790204</dc:identifier>
<dc:title><![CDATA[Reduced fronto-striatal volume in ADHD in two cohorts across the lifespan]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-10-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/782581v1?rss=1">
<title>
<![CDATA[
Say what I mean - Expectancy effects in the EEG during joint and spontaneous word-by-word sentence production 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/782581v1?rss=1"
</link>
<description><![CDATA[
Our aim in the present study is to measure neural correlates during spontaneous interactive sentence production. We present a novel approach using the word-by-word technique from improvisational theatre, in which two speakers jointly produce one sentence. This paradigm allows the assessment of behavioural aspects, such as turn-times, and electrophysiological responses, such as event-related-potentials (ERPs). Twenty-five participants constructed a cued but spontaneous four-word German sentence together with a confederate, taking turns for each word of the sentence. In 30% of the trials, an unexpected gender-marked article was uttered by the confederate. To complete the sentence in a meaningful way, the participant had to detect the violation, (possibly) inhibit a prepared response, and retrieve and utter a new fitting response. We found significant increases in response times after unexpected words and - despite allowing unscripted language production and naturally varying speech material - successfully detected significant N400 and P600 ERP effects for the unexpected word. The N400 EEG activity further significantly predicted the response time of the subsequent turn. Our results show that combining behavioural and neuroscientific measures of verbal interactions while retaining sufficient experimental control is possible, and that this combination provides promising insights into the mechanisms of spontaneous spoken dialogue.
]]></description>
<dc:creator>Goregliad Fjaellingsdal, T.</dc:creator>
<dc:creator>Schwenke, D.</dc:creator>
<dc:creator>Scherbaum, S.</dc:creator>
<dc:creator>Kuhlen, A. K.</dc:creator>
<dc:creator>Boegels, S.</dc:creator>
<dc:creator>Meekes, J.</dc:creator>
<dc:creator>Bleichner, M. G.</dc:creator>
<dc:date>2019-09-26</dc:date>
<dc:identifier>doi:10.1101/782581</dc:identifier>
<dc:title><![CDATA[Say what I mean - Expectancy effects in the EEG during joint and spontaneous word-by-word sentence production]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/553255v1?rss=1">
<title>
<![CDATA[
Neural System Identification with Cortical Information Flow 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/553255v1?rss=1"
</link>
<description><![CDATA[
Cortical information flow (CIF) is a new framework for system identification in neuroscience. CIF models represent neural systems as coupled brain regions that each embody neural computations. These brain regions are coupled to observed data specific to that region. Neural computations are estimated via stochastic gradient descent. We show using a large-scale fMRI dataset that, in this manner, we can estimate models that learn meaningful neural computations. Our framework is general in the sense that it can be used in conjunction with any (combination of) neural recording techniques. It is also scalable, providing neuroscientists with a principled approach to make sense of the high-dimensional neural datasets.
]]></description>
<dc:creator>Ambrogioni, L.</dc:creator>
<dc:creator>Seeliger, K.</dc:creator>
<dc:creator>Guclu, U.</dc:creator>
<dc:creator>van Gerven, M.</dc:creator>
<dc:date>2019-02-18</dc:date>
<dc:identifier>doi:10.1101/553255</dc:identifier>
<dc:title><![CDATA[Neural System Identification with Cortical Information Flow]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-02-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/781054v1?rss=1">
<title>
<![CDATA[
The Object Space Task reveals a dissociation between semantic-like and episodic-like memory in a mouse model of Kleefstra Syndrome 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/781054v1?rss=1"
</link>
<description><![CDATA[
Kleefstra syndrome is a disorder caused by a mutation in the EHMT1 gene characterized in humans by general developmental delay, mild to severe intellectual disability and autism. Here, we characterized semantic- and episodic-like memory in the Ehmt1+/- mouse model using the Object Space Task. We combined conventional behavioral analysis with automated analysis by deep-learning networks, a session-based computational learning model and a trial-based classifier. Ehmt1 +/- mice showed more anxiety-like features and generally explored objects less, but the difference decreased over time. Interestingly, when analyzing memory-specific exploration, Ehmt1 +/- show increased expression of semantic-like memory, but a deficit in episodic-like memory. A similar dissociation of semantic and episodic memory performance has been previously reported in humans with autism. Using our automatic classifier to differentiate between genotypes, we found that semantic-like memory features are better suited for classification than general exploration differences. Thus, detailed behavioral classification with the Object Space Task produced a more detailed behavioral phenotype of the Ehmt1 +/- mouse model.nnOne Sentence SummaryEhmt1 +/- mice show decreased exploration and episodic-like memory but increased semantic-like memory In the Object Space Task. (143 of 150)
]]></description>
<dc:creator>Schut, E. H. S.</dc:creator>
<dc:creator>Alonso, A.</dc:creator>
<dc:creator>Smits, S.</dc:creator>
<dc:creator>Khamassi, M.</dc:creator>
<dc:creator>Samanta, A.</dc:creator>
<dc:creator>Negwer, M.</dc:creator>
<dc:creator>Nadif Kasri, N.</dc:creator>
<dc:creator>Navarro Lobato, I.</dc:creator>
<dc:creator>Genzel, L.</dc:creator>
<dc:date>2019-09-25</dc:date>
<dc:identifier>doi:10.1101/781054</dc:identifier>
<dc:title><![CDATA[The Object Space Task reveals a dissociation between semantic-like and episodic-like memory in a mouse model of Kleefstra Syndrome]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/781294v1?rss=1">
<title>
<![CDATA[
Neural dynamics of perceptual inference and its reversal during imagery 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/781294v1?rss=1"
</link>
<description><![CDATA[
After the presentation of a visual stimulus, cortical visual processing cascades from low-level sensory features in primary visual areas to increasingly abstract representations in higher-level areas. It is often hypothesized that the reverse process underpins the human ability to generate mental images. Under this hypothesis, visual information feeds back from high-level areas as abstract representations are used to construct the sensory representation in primary visual cortices. Such reversals of information flow are also hypothesized to play a central role in later stages of perception. According to predictive processing theories, ambiguous sensory information is resolved using abstract representations coming from high-level areas through oscillatory rebounds between different levels of the visual hierarchy. However, despite the elegance of these theoretical models, to this day there is no direct experimental evidence of the reversion of visual information flow during mental imagery and perception. In the first part of this paper, we provide direct evidence in humans for a reverse order of activation of the visual hierarchy during imagery. Specifically, we show that classification machine learning models trained on brain data at different time points during the early feedforward phase of perception are reactivated in reverse order during mental imagery. In the second part of the paper, we report an 11Hz oscillatory pattern of feedforward and reversed visual processing phases during perception. Together, these results are in line with the idea that during perception, the high-level cause of sensory input is inferred through recurrent hypothesis updating, whereas during imagery, this learned forward mapping is reversed to generate sensory signals given abstract representations.
]]></description>
<dc:creator>Dijkstra, N.</dc:creator>
<dc:creator>Ambrogioni, L.</dc:creator>
<dc:creator>van Gerven, M.</dc:creator>
<dc:date>2019-09-24</dc:date>
<dc:identifier>doi:10.1101/781294</dc:identifier>
<dc:title><![CDATA[Neural dynamics of perceptual inference and its reversal during imagery]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/779736v1?rss=1">
<title>
<![CDATA[
Behavioural relevance of spontaneous, transient brain network interactions in fMRI 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/779736v1?rss=1"
</link>
<description><![CDATA[
How spontaneously fluctuating functional magnetic resonance imaging (fMRI) signals in different brain regions relate to behaviour has been an open question for decades. Correlations in these signals, known as functional connectivity, can be averaged over several minutes of data to provide a stable representation of the functional network architecture for an individual. However, associations between these stable features and behavioural traits have been shown to be dominated by individual differences in anatomy. Here, using kernel learning tools, we propose methods to assess and compare the relation between time-varying functional connectivity, time-averaged functional connectivity, structural brain data, and non-imaging subject behavioural traits. We applied these methods on Human Connectome Project resting-state fMRI data to show that time-varying fMRI functional connectivity, detected at time-scales of a few seconds, has associations with some behavioural traits that are not dominated by anatomy. Despite time-averaged functional connectivity accounting for the largest proportion of variability in the fMRI signal between individuals, we found that some aspects of intelligence could only be explained by time-varying functional connectivity. The finding that time-varying fMRI functional connectivity has a unique relationship to population behavioural variability suggests that it might reflect transient neuronal communication fluctuating around a stable neural architecture.

Significance statementComplex cognition is dynamic and emerges from the interaction between multiple areas across the whole brain, i.e. from brain networks. Hence, the utility of functional MRI to investigate brain activity depends on how well it can capture time-varying network interactions. Here, we develop methods to predict behavioural traits of individuals from either time-varying functional connectivity, time-averaged functional connectivity, or structural brain data. We use these to show that the time-varying nature of functional brain networks in fMRI can be reliably measured and can explain aspects of behaviour not captured by structural data or time-averaged functional connectivity. These results provide important insights to the question of how the brain represents information and how these representations can be measured with fMRI.
]]></description>
<dc:creator>Vidaurre, D.</dc:creator>
<dc:creator>Llera Arenas, A.</dc:creator>
<dc:creator>Smith, S. M.</dc:creator>
<dc:creator>Woolrich, M. W.</dc:creator>
<dc:date>2019-09-24</dc:date>
<dc:identifier>doi:10.1101/779736</dc:identifier>
<dc:title><![CDATA[Behavioural relevance of spontaneous, transient brain network interactions in fMRI]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/775494v1?rss=1">
<title>
<![CDATA[
Reduction of spontaneous cortical beta bursts in Parkinson’s disease is linked to symptom severity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/775494v1?rss=1"
</link>
<description><![CDATA[
Parkinsons disease is characterized by a gradual loss of dopaminergic neurons, which are associated with altered neuronal activity in the beta band (13-30 Hz). Assessing beta band activity typically involves transforming the time-series to get the power of the signal in the frequency-domain. Such transformation assumes that the time-series can be reduced to a combination of steady-state sine-and cosine waves. However, recent studies have suggested that this approach masks relevant biophysical features in the beta band activity--for example, that the beta band exhibits transient bursts of high-amplitude activity.nnIn an exploratory study we used magnetoencephalography (MEG) to record cortical beta band activity to characterize how spontaneous cortical beta bursts manifest in Parkinsons patients ON and OFF dopaminergic medication, and compare this to matched healthy controls. From three minutes of MEG data, we extracted the time-course of beta band activity from the sensorimotor cortex and characterized high-amplitude epochs in the signal to test if they exhibited burst like properties. We then compared the rate, duration, inter-burst interval, and peak amplitude of the high-amplitude epochs between the Parkinsons patients and healthy controls.nnOur results show that Parkinsons patients OFF medication had a 6-17% lower beta bursts rate compared to healthy controls, while both the duration and the amplitude of the bursts were the same for Parkinsons patients and healthy controls and medicated state of the Parkinsons patients. These data thus support the view that beta bursts are fundamental underlying features of beta band activity, and show that changes in cortical beta band power in PD can be explained primarily by changes in the underlying burst rate. Importantly, our results also revealed a relationship between beta bursts rate and motor symptom severity in PD: a lower burst rate scaled with increased in severity of bradykinesia and postural/kinetic tremor. Beta burst rate might thus serve as neuromarker for Parkinsons disease that can help in the assessment of symptom severity in Parkinsons disease or evaluate treatment effectiveness.
]]></description>
<dc:creator>Vinding, M. C.</dc:creator>
<dc:creator>Tsitsi, P.</dc:creator>
<dc:creator>Waldthaler, J.</dc:creator>
<dc:creator>Oostenveld, R.</dc:creator>
<dc:creator>Ingvar, M.</dc:creator>
<dc:creator>Svenningsson, P.</dc:creator>
<dc:creator>Lundqvist, D.</dc:creator>
<dc:date>2019-09-22</dc:date>
<dc:identifier>doi:10.1101/775494</dc:identifier>
<dc:title><![CDATA[Reduction of spontaneous cortical beta bursts in Parkinson’s disease is linked to symptom severity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/762419v1?rss=1">
<title>
<![CDATA[
From rare Copy Number Variations to biological processes in ADHD 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/762419v1?rss=1"
</link>
<description><![CDATA[
AimAttention-deficit/hyperactivity disorder (ADHD) is a highly heritable psychiatric disorder. The objective of this study was to define ADHD-associated candidate genes, and their associated molecular modules and biological themes, based on the analysis of rare genetic variants.nnMethodsWe combined data from 11 published copy number variation (CNV) studies in 6176 individuals with ADHD and 25026 controls and prioritized genes by applying an integrative strategy based on criteria including recurrence in ADHD individuals, absence in controls, complete coverage in copy number gains, and presence in the minimal region common to overlapping CNVs, as well as on protein-protein interactions and information from cross-species genotype-phenotype annotation.nnResultsWe localized 2241 eligible genes in the 1532 reported CNVs, of which we classified 432 as high-priority ADHD candidate genes. The high-priority ADHD candidate genes were significantly co-expressed in the brain. A network of 66 genes was supported by ADHD-relevant phenotypes in the cross-species database. In addition, four significantly interconnected protein modules were found among the high-priority ADHD genes. A total of 26 genes were observed across all applied bioinformatic methods. Look-up in the latest genome-wide association study for ADHD showed that among those 26, POLR3C and RBFOX1 were also supported by common genetic variants.nnConclusionsIntegration of a stringent filtering procedure in CNV studies with suitable bioinformatics approaches can identify ADHD candidate genes at increased levels of credibility. Our pipeline provides additional insight in the molecular mechanisms underlying ADHD and allows prioritization of genes for functional validation in validated model organisms.
]]></description>
<dc:creator>Harich, B.</dc:creator>
<dc:creator>van der Voet, M.</dc:creator>
<dc:creator>Klein, M.</dc:creator>
<dc:creator>Fenckova, M.</dc:creator>
<dc:creator>Cizek, P.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Schenck, A.</dc:creator>
<dc:date>2019-09-16</dc:date>
<dc:identifier>doi:10.1101/762419</dc:identifier>
<dc:title><![CDATA[From rare Copy Number Variations to biological processes in ADHD]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/770222v1?rss=1">
<title>
<![CDATA[
Cross-disorder GWAS meta-analysis for Attention Deficit/Hyperactivity Disorder, Autism Spectrum Disorder, Obsessive Compulsive Disorder, and Tourette Syndrome 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/770222v1?rss=1"
</link>
<description><![CDATA[
Attention Deficit/Hyperactivity Disorder (ADHD), Autism Spectrum Disorder (ASD), Obsessive-Compulsive Disorder (OCD), and Tourette Syndrome (TS) are among the most prevalent neurodevelopmental psychiatric disorders of childhood and adolescence. High comorbidity rates across these four disorders point toward a common etiological thread that could be connecting them across the repetitive behaviors-impulsivity-compulsivity continuum. Aiming to uncover the shared genetic basis across ADHD, ASD, OCD, and TS, we undertake a systematic cross-disorder meta-analysis, integrating summary statistics from all currently available genome-wide association studies (GWAS) for these disorders, as made available by the Psychiatric Genomics Consortium (PGC) and the Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH). We present analysis of a combined dataset of 93,294 individuals, across 6,788,510 markers and investigate associations on the single-nucleotide polymorphism (SNP), gene and pathway levels across all four disorders but also pairwise. In the ADHD-ASD-OCD-TS cross disorder GWAS meta-analysis, we uncover in total 297 genomewide significant variants from six LD (linkage disequilibrium) -independent genomic risk regions. Out of these genomewide significant association results, 199 SNPs, that map onto four genomic regions, show high posterior probability for association with at least three of the studied disorders (m-value>0.9). Gene-based GWAS meta-analysis across ADHD, ASD, OCD, and TS identified 21 genes significantly associated under Bonferroni correction. Out of those, 15 could not be identified as significantly associated based on the individual disorder GWAS dataset, indicating increased power in the cross-disorder comparisons. Cross-disorder tissue-specificity analysis implicates the Hypothalamus-Pituitary-Adrenal axis (stress response) as possibly underlying shared pathophysiology across ADHD, ASD, OCD, and TS. Our work highlights genetic variants and genes that may contribute to overlapping neurobiology across the four studied disorders and highlights the value of re-defining the framework for the study across this spectrum of highly comorbid disorders, by using transdiagnostic approaches.
]]></description>
<dc:creator>Yang, Z.</dc:creator>
<dc:creator>Wu, H.</dc:creator>
<dc:creator>Lee, P. H.</dc:creator>
<dc:creator>Tsetsos, F.</dc:creator>
<dc:creator>Davis, L. K.</dc:creator>
<dc:creator>Yu, D.</dc:creator>
<dc:creator>Lee, S. H.</dc:creator>
<dc:creator>Dalsgaard, S. D.</dc:creator>
<dc:creator>Haavik, J.</dc:creator>
<dc:creator>Barta, C.</dc:creator>
<dc:creator>Zayats, T.</dc:creator>
<dc:creator>Eapen, V.</dc:creator>
<dc:creator>Wray, N. R.</dc:creator>
<dc:creator>Devlin, B.</dc:creator>
<dc:creator>Daly, M.</dc:creator>
<dc:creator>Neale, B.</dc:creator>
<dc:creator>Borglum, A.</dc:creator>
<dc:creator>Crowley, J. J.</dc:creator>
<dc:creator>Scharf, J.</dc:creator>
<dc:creator>Mathews, C. A.</dc:creator>
<dc:creator>Faraone, S. V.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Mattheisen, M.</dc:creator>
<dc:creator>Smoller, J. W.</dc:creator>
<dc:creator>Paschou, P.</dc:creator>
<dc:date>2019-09-16</dc:date>
<dc:identifier>doi:10.1101/770222</dc:identifier>
<dc:title><![CDATA[Cross-disorder GWAS meta-analysis for Attention Deficit/Hyperactivity Disorder, Autism Spectrum Disorder, Obsessive Compulsive Disorder, and Tourette Syndrome]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/769372v1?rss=1">
<title>
<![CDATA[
Dissociable neural effects of temporal expectations due to passage of time and contextual probability 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/769372v1?rss=1"
</link>
<description><![CDATA[
The human brain is equipped with complex mechanisms to track the changing probability of events in time. While the passage of time itself usually leads to a mounting expectation, context can provide additional information about when events are likely to happen. In this study we dissociate these two sources of temporal expectation in terms of their neural correlates and underlying brain connectivity patterns. We analysed magnetoencephalographic (MEG) data acquired from N=24 healthy participants listening to auditory stimuli. These stimuli could be presented at different temporal intervals but occurred most often at intermediate intervals, forming a contextual probability distribution. Evoked MEG response amplitude was sensitive to both passage of time and contextual probability, albeit at different latencies: the effects of passage of time were observed earlier than the effects of context. The underlying sources of MEG activity were also different across the two types of temporal prediction: the effects of passage of time were localised to early auditory regions and superior temporal gyri, while context was additionally linked to activity in inferior parietal cortices. Finally, these differences were modelled using biophysical (dynamic causal) modelling: passage of time was explained in terms of widespread gain modulation and decreased prediction error signalling at lower levels of the hierarchy, while contextual expectation led to more localised gain modulation and decreased prediction error signalling at higher levels of the hierarchy. These results present a comprehensive account of how independent sources of temporal prediction may be differentially expressed in cortical circuits.nnHIGHLIGHTS- Predictability of tone onset times affects auditory network connectivityn- Foreperiod and distribution of events in time have dissociable neural substratesn- Decreased prediction error at different levels of cortical hierarchy
]]></description>
<dc:creator>Todorovic, A.</dc:creator>
<dc:creator>Auksztulewicz, R.</dc:creator>
<dc:date>2019-09-14</dc:date>
<dc:identifier>doi:10.1101/769372</dc:identifier>
<dc:title><![CDATA[Dissociable neural effects of temporal expectations due to passage of time and contextual probability]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/765149v1?rss=1">
<title>
<![CDATA[
Experience-dependent changes to cortico-hippocampal networks during NREM sleep 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/765149v1?rss=1"
</link>
<description><![CDATA[
Memory reactivation during NonREM-ripples is thought to communicate new information to a systems-wide network. Cortical high frequency events have also been described that co-occur with ripples. Focusing on NonREM sleep after different behaviors, both hippocampal ripples and parietal high frequency oscillations were detected. A bimodal frequency distribution was observed in the parietal high frequency events, faster and slower, with increases in prefrontal directionality measured by Granger causality analysis specifically seen during the fast parietal oscillations. Furthermore, fast events activated prefrontal-parietal cortex whereas slow events activated hippocampal-parietal areas. Finally, there was a learning-induced increase in both number and size of fast high frequency events. These patterns were not seen after novelty exposure or foraging, but occurred after the learning of a new goal location in a maze. Disruption of either sleep or hippocampal ripples impaired long-term memory consistent with these having a role in memory consolidation.
]]></description>
<dc:creator>Aleman Zapata, A.</dc:creator>
<dc:creator>Morris, R. G.</dc:creator>
<dc:creator>Battaglia, F. P.</dc:creator>
<dc:creator>Genzel, L.</dc:creator>
<dc:date>2019-09-11</dc:date>
<dc:identifier>doi:10.1101/765149</dc:identifier>
<dc:title><![CDATA[Experience-dependent changes to cortico-hippocampal networks during NREM sleep]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/765180v1?rss=1">
<title>
<![CDATA[
From competing motor plans to a single action within a single trial on the human motor periphery 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/765180v1?rss=1"
</link>
<description><![CDATA[
Contemporary motor control theories propose competition between multiple motor plans before the winning command is executed. While most competitions are completed prior to movement onset, movements are often initiated before the competition has been resolved. An example of this is saccadic averaging, wherein the eyes land at an intermediate location between two visual targets. Behavioral and neurophysiological signatures of competing motor commands have also been reported for reaching movements, but debate remains about whether such signatures attest to an unresolved competition, arise from averaging across many trials, or reflect a strategy to optimize behavior given task constraints. Here, we recorded electromyographic activity from an upper limb muscle (m. pectoralis) while twelve (8 female) participants performed an immediate response reach task, freely choosing between one of two identical and suddenly presented visual targets. On each trial, muscle recruitment showed two distinct phases of directionally-tuned activity. In the first wave, time-locked ~100 ms of target presentation, muscle activity was clearly influenced by the non-chosen target, reflecting a competition between reach commands that was biased in favor of the ultimately chosen target. This resulted in an initial movement intermediate between the two targets. In contrast, the second wave, time-locked to voluntary reach onset, was not biased toward the non-chosen target, showing that the competition between targets was resolved. Instead, this wave of activity compensated for the averaging induced by the first wave. Thus, single-trial analysis reveals an evolution in how the non-chosen target differentially influences the first and second wave of muscle activity.

SIGNIFICANCE STATEMENTContemporary theories of motor control suggest that multiple motor plans compete for selection before the winning command is executed. Evidence for this is found in intermediate reach movements towards two potential target locations, but recent findings have challenged this notion by arguing that intermediate reaching movements reflect an optimal response strategy. By examining upper limb muscle recruitment during a free-choice reach task, we show early recruitment of a sub-optimal averaged motor command to the two targets that subsequently transitions to a single motor command that compensates for the initially averaged motor command. Recording limb muscle activity permits single-trial resolution of the dynamic influence of the non-chosen target through time.
]]></description>
<dc:creator>Gu, C.</dc:creator>
<dc:creator>Corneil, B. D.</dc:creator>
<dc:creator>Medendorp, P. W.</dc:creator>
<dc:creator>Selen, L. P. J.</dc:creator>
<dc:date>2019-09-11</dc:date>
<dc:identifier>doi:10.1101/765180</dc:identifier>
<dc:title><![CDATA[From competing motor plans to a single action within a single trial on the human motor periphery]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/762534v1?rss=1">
<title>
<![CDATA[
Serotonergic development of active sensing 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/762534v1?rss=1"
</link>
<description><![CDATA[
Active sensing requires adaptive motor (positional) control of sensory organs based on contextual, sensory and task requirements, and develops postnatally after the maturation of intracortical circuits. Alterations in sensorimotor network connectivity during this period are likely to impact sensorimotor computation also in adulthood. Serotonin is among the cardinal developmental regulators of network formation, thus changing the serotonergic drive might have consequences for the emergence and maturation of sensorimotor control. Here we tested this hypothesis on an object localization task by quantifying the motor control dynamics of whiskers during tactile navigation. The results showed that sustained alterations in serotonergic signaling in serotonin transporter knockout rats, or the transient pharmacological inactivation of the transporter during early postnatal development, impairs the emergence of adaptive motor control of whisker position based on recent sensory information. A direct outcome of this altered motor control is that the mechanical force transmitted to whisker follicles upon contact is reduced, suggesting that increased excitability observed upon altered serotonergic signaling is not due to increased synaptic drive originating from the periphery upon whisker contact. These results argue that postnatal development of adaptive motor control requires intact serotonergic signaling and that even its transient dysregulation during early postnatal development causes lasting sensorimotor impairments in adulthood.
]]></description>
<dc:creator>Azarfar, A.</dc:creator>
<dc:creator>Zhang, Y.</dc:creator>
<dc:creator>Alishbayli, A.</dc:creator>
<dc:creator>Schubert, D.</dc:creator>
<dc:creator>Homberg, J. R.</dc:creator>
<dc:creator>Celikel, T.</dc:creator>
<dc:date>2019-09-08</dc:date>
<dc:identifier>doi:10.1101/762534</dc:identifier>
<dc:title><![CDATA[Serotonergic development of active sensing]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/763078v1?rss=1">
<title>
<![CDATA[
Temporal tuning of repetition suppression across the visual cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/763078v1?rss=1"
</link>
<description><![CDATA[
The visual system adapts to its recent history. A phenomenon related to this is repetition suppression (RS) - a reduction in neural responses to repeated compared to non-repeated visual input. An intriguing hypothesis is that the timescale over which RS occurs across the visual hierarchy is tuned to the temporal statistics of visual input features, which change rapidly in low-level areas but are more stable in higher-level areas. Here, we tested this hypothesis by studying the influence of the temporal lag between successive visual stimuli on RS throughout the visual system using fMRI. Twelve human volunteers engaged in four fMRI sessions in which we characterized the BOLD response to pairs of repeated and non-repeated natural images with inter-stimulus intervals (ISI) ranging from 50 to 1000 milliseconds to quantify the temporal tuning of RS along the posterior-anterior axis of the visual system. As expected, RS was maximal for short ISIs and decayed with increasing ISI. Furthermore, the overall magnitude of RS gradually increased from posterior to anterior visual areas. Crucially, however, and against our hypothesis, RS decayed at a similar rate in early and late visual areas. This finding challenges the prevailing view that the timescale of RS increases along the posterior-anterior axis of the visual system and suggests that RS is not tuned to temporal input regularities.
]]></description>
<dc:creator>Fritsche, M.</dc:creator>
<dc:creator>Lawrence, S. J. D.</dc:creator>
<dc:creator>de Lange, F. P.</dc:creator>
<dc:date>2019-09-09</dc:date>
<dc:identifier>doi:10.1101/763078</dc:identifier>
<dc:title><![CDATA[Temporal tuning of repetition suppression across the visual cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/762559v1?rss=1">
<title>
<![CDATA[
Assessing the utility of MAGNETO to control neuronal excitability in the somatosensory cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/762559v1?rss=1"
</link>
<description><![CDATA[
Magnetic neuromodulation has outstanding promise for the development of novel neural interfaces without direct physical intervention with the brain. Here we tested the utility of Magneto in the adult somatosensory cortex by performing whole-cell intracellular recordings in vitro and extracellular recordings in freely moving mice. Results show that magnetic stimulation does not alter subthreshold membrane excitability or contribute to the generation of action potentials in virally transduced neurons expressing Magneto.
]]></description>
<dc:creator>Kole, K.</dc:creator>
<dc:creator>Zhang, Y.</dc:creator>
<dc:creator>Jansen, E. J. R.</dc:creator>
<dc:creator>Brouns, T.</dc:creator>
<dc:creator>Bijlsma, A.</dc:creator>
<dc:creator>Calcini, N.</dc:creator>
<dc:creator>Yan, X.</dc:creator>
<dc:creator>da Silva Lantyer, A.</dc:creator>
<dc:creator>Celikel, T.</dc:creator>
<dc:date>2019-09-09</dc:date>
<dc:identifier>doi:10.1101/762559</dc:identifier>
<dc:title><![CDATA[Assessing the utility of MAGNETO to control neuronal excitability in the somatosensory cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/762443v1?rss=1">
<title>
<![CDATA[
Development of adaptive motor control for tactile navigation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/762443v1?rss=1"
</link>
<description><![CDATA[
Navigation is a result of complex sensorimotor computation which requires integration of sensory information in allocentric and egocentric coordinates as the brain computes a motor plan to drive navigation. In this active sensing process, motor commands are adaptively regulated based on prior sensory information. In the darkness, rodents commonly rely on their tactile senses, in particular to their whiskers, to gather the necessary sensory information and instruct navigation. Previous research has shown that rodents can process whisker input to guide mobility even prior to whisking onset by the end of the second postnatal week, however, when and how adaptive sensorimotor control of whisker position matures is still not known. Here, we addressed this question in rats longitudinally as animals searched for a stationary target in darkness. The results showed that juvenile rats perform object localization by controlling their body, but not whisker position, based on the expected location of the target. Adaptive, closed-loop, control of whisker position matures only after the third postnatal week. Computational modeling of the active whisking showed the emergence of the closed-loop control of whisker position and reactive retraction, i.e. whisker retraction that ensures the constancy of duration of tactile sampling, facilitate the maturation of sensorimotor exploration strategies during active sensing. These results argue that adaptive motor control of body and whiskers develop sequentially, and sensorimotor control of whisker position emerges later in postnatal development upon the maturation of intracortical sensorimotor circuits.
]]></description>
<dc:creator>Azarfar, A.</dc:creator>
<dc:creator>Celikel, T.</dc:creator>
<dc:date>2019-09-08</dc:date>
<dc:identifier>doi:10.1101/762443</dc:identifier>
<dc:title><![CDATA[Development of adaptive motor control for tactile navigation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/755447v1?rss=1">
<title>
<![CDATA[
Neurovegetative symptom subtypes in young people with major depressive disorder and their structural brain correlates 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/755447v1?rss=1"
</link>
<description><![CDATA[
BackgroundDepression is a leading cause of burden of disease among young people. Current treatments are not uniformly effective, in part due to the heterogeneous nature of major depressive disorder (MDD). Refining MDD into more homogeneous subtypes is an important step towards identifying underlying pathophysiological mechanisms and improving treatment of young people. In adults, symptom-based subtypes of depression identified using data-driven methods mainly differed in patterns of neurovegetative symptoms (sleep and appetite/weight). These subtypes have been associated with differential biological mechanisms, including immuno-metabolic markers, genetics and brain alterations (mainly in the ventral striatum and insular cortex).nnMethodsK-means clustering was applied to individual depressive symptoms from the Quick Inventory of Depressive Symptoms (QIDS) in 275 young people (15-25 years old) with MDD to identify symptom-based subtypes, and in 244 young people from an independent dataset (a subsample of the STAR*D dataset). Insula surface area and thickness and ventral striatum volume were compared between the subtypes using structural MRI.nnResultsThree subtypes were identified in the discovery dataset and replicated in the independent dataset; severe depression with increased appetite, severe depression with decreased appetite and severe insomnia, and moderate depression. The severe increased appetite subtype showed lower surface area in the anterior insula compared to both healthy controls and the moderate subtype.nnConclusionsOur findings in young people replicate the previously identified symptom-based depression subtypes in adults. The structural alterations of the anterior insular cortex add to the existing evidence of different pathophysiological mechanisms involved in this subtype.
]]></description>
<dc:creator>Toenders, Y. J.</dc:creator>
<dc:creator>Schmaal, L.</dc:creator>
<dc:creator>Harrison, B. J.</dc:creator>
<dc:creator>Dinga, R.</dc:creator>
<dc:creator>Berk, M.</dc:creator>
<dc:creator>Davey, C.</dc:creator>
<dc:date>2019-09-05</dc:date>
<dc:identifier>doi:10.1101/755447</dc:identifier>
<dc:title><![CDATA[Neurovegetative symptom subtypes in young people with major depressive disorder and their structural brain correlates]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/756395v1?rss=1">
<title>
<![CDATA[
Handedness and Other Variables Associated with Human Brain Asymmetrical Skew 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/756395v1?rss=1"
</link>
<description><![CDATA[
The human cerebral hemispheres show a left-right asymmetrical torque pattern, which has been claimed to be absent in chimpanzees. The functional significance and developmental mechanisms are unknown. Here we carried out the largest-ever analysis of global brain shape asymmetry in magnetic resonance imaging data. Three population datasets were used, the UK Biobank (N = 39,678), Human Connectome Project (N = 1,113) and BIL&GIN (N = 453). At the population level, there was an anterior and dorsal skew of the right hemisphere, relative to the left. Both skews were associated independently with handedness, and various regional grey and white matter metrics oppositely in the two hemispheres, as well as other variables related to cognitive functions, sociodemographic factors, and physical and mental health. The two skews showed SNP-based heritabilities of 4-13%, but also substantial polygenicity in causal mixture model analysis, and no individually significant loci were found in GWAS for either skew. There was evidence for a significant genetic correlation (rg=-0.40, p=0.0075) between horizontal brain skew and Autism Spectrum Disorder. These results provide the first large-scale description of population-average brain skews and their inter-individual variations, their replicable associations with handedness, and insights into biological and other factors which associate with human brain asymmetry.
]]></description>
<dc:creator>Kong, X.</dc:creator>
<dc:creator>Postema, M. C.</dc:creator>
<dc:creator>Carrion Castillo, A.</dc:creator>
<dc:creator>Pepe, A.</dc:creator>
<dc:creator>Crivello, F.</dc:creator>
<dc:creator>Joliot, M.</dc:creator>
<dc:creator>Mazoyer, B.</dc:creator>
<dc:creator>Fisher, S. E.</dc:creator>
<dc:creator>Francks, C.</dc:creator>
<dc:date>2019-09-05</dc:date>
<dc:identifier>doi:10.1101/756395</dc:identifier>
<dc:title><![CDATA[Handedness and Other Variables Associated with Human Brain Asymmetrical Skew]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/580365v1?rss=1">
<title>
<![CDATA[
Shared polygenetic variation between ASD and ADHD exerts opposite association patterns with educational attainment 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/580365v1?rss=1"
</link>
<description><![CDATA[
Insight into shared polygenetic architectures affects our understanding of neurodevelopmental disorders. Here, we investigate evidence for pleiotropic mechanisms that may explain the comorbidity between Autism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD). These complex neurodevelopmental conditions often co-occur, but differ in their polygenetic association patterns, especially with educational attainment (EA), showing discordant association effects. Using multivariable regression analyses and existing genome-wide summary statistics based on 10,610 to 766,345 individuals, we demonstrate that EA-related polygenic variation is shared between ASD and ADHD. We show that different combinations of the same ASD and ADHD risk-increasing alleles can simultaneously re-capture known ASD-related positive and ADHD-related negative associations with EA. Such patterns, although to a lesser degree, were also present for combinations of other psychiatric disorders. These findings suggest pleiotropic mechanisms, where the same polygenic sites can encode multiple independent, even discordant, association patterns without involving distinct loci, and have implications for cross-disorder investigations.
]]></description>
<dc:creator>Verhoef, E.</dc:creator>
<dc:creator>Grove, J.</dc:creator>
<dc:creator>Shapland, C. Y.</dc:creator>
<dc:creator>Demontis, D.</dc:creator>
<dc:creator>Burgess, S.</dc:creator>
<dc:creator>Rai, D.</dc:creator>
<dc:creator>Borglum, A. D.</dc:creator>
<dc:creator>St Pourcain, B.</dc:creator>
<dc:date>2019-03-17</dc:date>
<dc:identifier>doi:10.1101/580365</dc:identifier>
<dc:title><![CDATA[Shared polygenetic variation between ASD and ADHD exerts opposite association patterns with educational attainment]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-03-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/751255v1?rss=1">
<title>
<![CDATA[
Psilocybin exerts distinct effects on resting state networks associated with serotonin and dopamine in mice 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/751255v1?rss=1"
</link>
<description><![CDATA[
Hallucinogenic agents have been proposed as potent antidepressants; this includes the serotonin (5-HT) receptor 2A agonist psilocybin. In human subjects, psilocybin alters functional connectivity (FC) within the default-mode network (DMN), a constellation of inter-connected regions that is involved in self-reference and displays altered FC in depressive disorders. In this study we investigated the effects of psilocybin on FC in the analogue of the DMN in mouse, with a view to establishing an experimental animal model to investigate underlying mechanisms. Psilocybin effects were investigated in lightly-anaesthetized mice using resting-state fMRI. Dual-regression analysis identified reduced FC within the ventral striatum in psilocybin-relative to vehicle-treated mice. Refinement of the analysis using spatial references derived from both gene expression maps and viral tracer projection fields revealed two distinct effects of psilocybin: it increased FC between 5-HT-associated networks and elements of the murine DMN, thalamus, and midbrain; it decreased FC within dopamine (DA)-associated striatal networks. These results suggest that interaction between 5-HT- and DA-regulated neural networks contributes to the neural and therefore psychological effects of psilocybin. Furthermore, they highlight how information on molecular expression patterns and structural connectivity can assist in the interpretation of pharmaco-fMRI findings.
]]></description>
<dc:creator>Grandjean, J.</dc:creator>
<dc:creator>Buehlmann, D.</dc:creator>
<dc:creator>Buerge, M.</dc:creator>
<dc:creator>Sigrist, H.</dc:creator>
<dc:creator>Seifritz, E.</dc:creator>
<dc:creator>Vollenweider, F. X.</dc:creator>
<dc:creator>Pryce, C. R.</dc:creator>
<dc:creator>Rudin, M.</dc:creator>
<dc:date>2019-09-01</dc:date>
<dc:identifier>doi:10.1101/751255</dc:identifier>
<dc:title><![CDATA[Psilocybin exerts distinct effects on resting state networks associated with serotonin and dopamine in mice]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-09-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/750091v1?rss=1">
<title>
<![CDATA[
Localizing regions in the genome contributing to ADHD, aggressive and antisocial behavior 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/750091v1?rss=1"
</link>
<description><![CDATA[
Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder, which in some cases occurs comorbid with aggressive and antisocial behavior (AGG; ASB). The three externalizing behaviors are moderately to highly heritable and are genetically correlated. However, the genomic regions underlying this correlation are unknown. In this study, we aimed to localize genetic loci shared between ADHD, AGG, and ASB, using two complementary approaches.

GWAS summary statistics for ADHD, AGG, and ASB were used for (1) cross-trait gene-based meta-analysis association analyses and (2) local genetic correlation analyses to identify shared genetic loci. Results of both complementary methods were combined to retrieve overlapping genes. Biological functionality of prioritized genes was assessed by exploring gene expression patterns in brain tissues and testing for gene-based association with (subcortical) brain regions.

We confirmed previous findings that ADHD, AGG, and ASB were positively genetically correlated at a global level. We identified eleven significant genes in cross-trait gene-based meta-analyses, 31 loci shared between traits; 34 genes were identified when both approaches were combined.

This study emphasizes the complex genetic architecture underlying global genetic correlations at the locus level. Converging evidence from these cross-trait analyses highlights novel candidate genes underlying biological mechanisms shared by ADHD, AGG, and ASB.
]]></description>
<dc:creator>Rodriguez Lopez, M. L.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Klein, M.</dc:creator>
<dc:date>2019-08-29</dc:date>
<dc:identifier>doi:10.1101/750091</dc:identifier>
<dc:title><![CDATA[Localizing regions in the genome contributing to ADHD, aggressive and antisocial behavior]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-08-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/743120v1?rss=1">
<title>
<![CDATA[
Quantifying the cost of cognitive stability and flexibility 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/743120v1?rss=1"
</link>
<description><![CDATA[
Exerting cognitive control is known to carry a subjective effort cost and people are generally biased to avoid it. Recent theorizing suggests that the cost of cognitive effort serves as a motivational signal to bias people away from excessive focusing and towards more cognitive flexibility. We asked whether the effort cost of stable distractor resistance is higher than that of flexible updating of working memory representations. We tested this prediction by using (i) a delayed response paradigm in which we manipulate demands for distractor resistance and flexible updating, as well as (ii) a subsequent cognitive effort discounting paradigm that allows us to quantify subjective effort costs. We demonstrate, in two different samples (28 and 62 participants) that participants discount tasks both high in distractor resistance and flexible updating when comparing with taking a break. As predicted, when directly contrasting distractor resistance and flexible updating the subjective cost of performing a task requiring distractor resistance is higher than that requiring flexible updating.
]]></description>
<dc:creator>Papadopetraki, D.</dc:creator>
<dc:creator>Froboese, M. I.</dc:creator>
<dc:creator>Westbrook, A.</dc:creator>
<dc:creator>Zandbelt, B. B.</dc:creator>
<dc:creator>Cools, R.</dc:creator>
<dc:date>2019-08-29</dc:date>
<dc:identifier>doi:10.1101/743120</dc:identifier>
<dc:title><![CDATA[Quantifying the cost of cognitive stability and flexibility]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-08-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/747352v1?rss=1">
<title>
<![CDATA[
Generating Templates and Growth Charts for School-Aged Brain Development 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/747352v1?rss=1"
</link>
<description><![CDATA[
Standard brain templates and growth charts provide an invaluable resource for basic science research, with the eventual goal of contributing to the clinical care of neuropsychiatric conditions. Here, we report on a protocol to generate MRI brain templates in children and adolescents at one-year intervals from 6-to-18 years of age, with their corresponding growth charts, using a large-scale neuroimaging data resource (948 brain images from China and United States). To assure that the brain templates and growth charts are reliable and accurate, we developed a refined pipeline consisting of template construction, image registration, brain area labeling and growth chart modeling. The pipeline comprises multiple modular workflows that can be used for multiple applications. In our approach, population- and age-specific templates were first constructed to avoid systemic bias in registration. Brain areas were then labeled based on the appropriate templates, and their morphological metrics were extracted for modeling associated growth curves. We implemented warp cost as a function of age differences between individual brains and template brains. A strong U-shaped cost function was revealed, indicating larger age differences are associated with greater registration errors. This validates the necessity of age-specific reference templates in pediatric brain imaging studies. Growth chart analyses revealed preferential shape differences between Chinese and US samples in lateral frontal and parietal areas, aspects of cortex which are most variable across individuals with regard to structure and function as well as associated behavioral performance. This growth distinction is largely driven by neurodevelopmental differences between Chinese and US age-specific brain templates. The pipeline together with the brain templates and charts are publicly available and integrated into the Connectome Computation System.
]]></description>
<dc:creator>Dong, H.-M.</dc:creator>
<dc:creator>Castellanos, F. X.</dc:creator>
<dc:creator>Yang, N.</dc:creator>
<dc:creator>Zhang, Z.</dc:creator>
<dc:creator>He, Y.</dc:creator>
<dc:creator>Zhang, L.</dc:creator>
<dc:creator>Xu, T.</dc:creator>
<dc:creator>Holmes, A.</dc:creator>
<dc:creator>Yeo, B. T. T.</dc:creator>
<dc:creator>Chen, F.</dc:creator>
<dc:creator>Wang, B.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>White, T. H.</dc:creator>
<dc:creator>Sporns, O.</dc:creator>
<dc:creator>Qiu, J.</dc:creator>
<dc:creator>Feng, T.</dc:creator>
<dc:creator>Chen, A.</dc:creator>
<dc:creator>Liu, X.</dc:creator>
<dc:creator>Chen, X.</dc:creator>
<dc:creator>Weng, X.</dc:creator>
<dc:creator>Milham, M.</dc:creator>
<dc:creator>Zuo, X.-N.</dc:creator>
<dc:date>2019-08-28</dc:date>
<dc:identifier>doi:10.1101/747352</dc:identifier>
<dc:title><![CDATA[Generating Templates and Growth Charts for School-Aged Brain Development]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-08-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/743138v1?rss=1">
<title>
<![CDATA[
Beyond accuracy: Measures for assessing machine learning models, pitfalls and guidelines 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/743138v1?rss=1"
</link>
<description><![CDATA[
Pattern recognition predictive models have become an important tool for analysis of neuroimaging data and answering important questions from clinical and cognitive neuroscience. Regardless of the application, the most commonly used method to quantify model performance is to calculate prediction accuracy, i.e. the proportion of correctly classified samples. While simple and intuitive, other performance measures are often more appropriate with respect to many common goals of neuroimaging pattern recognition studies. In this paper, we will review alternative performance measures and focus on their interpretation and practical aspects of model evaluation. Specifically, we will focus on 4 families of performance measures: 1) categorical performance measures such as accuracy, 2) rank based performance measures such as the area under the curve, 3) probabilistic performance measures based on quadratic error such as Brier score, and 4) probabilistic performance measures based on information criteria such as logarithmic score. We will examine their statistical properties in various settings using simulated data and real neuroimaging data derived from public datasets. Results showed that accuracy had the worst performance with respect to statistical power, detecting model improvement, selecting informative features and reliability of results. Therefore in most cases, it should not be used to make statistical inference about model performance. Accuracy should also be avoided for evaluating utility of clinical models, because it does not take into account clinically relevant information, such as relative cost of false-positive and false-negative misclassification or calibration of probabilistic predictions. We recommend alternative evaluation criteria with respect to the goals of a specific machine learning model.
]]></description>
<dc:creator>Dinga, R.</dc:creator>
<dc:creator>Penninx, B. W. J. H.</dc:creator>
<dc:creator>Veltman, D. J.</dc:creator>
<dc:creator>Schmaal, L.</dc:creator>
<dc:creator>Marquand, A. F.</dc:creator>
<dc:date>2019-08-22</dc:date>
<dc:identifier>doi:10.1101/743138</dc:identifier>
<dc:title><![CDATA[Beyond accuracy: Measures for assessing machine learning models, pitfalls and guidelines]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-08-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/739094v1?rss=1">
<title>
<![CDATA[
Hippocampal subfield volumes are uniquely affected in PTSD and depression: International analysis of 31 cohorts from the PGC-ENIGMA PTSD Working Group 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/739094v1?rss=1"
</link>
<description><![CDATA[
BackgroundPTSD and depression commonly co-occur and have been associated with smaller hippocampal volumes compared to healthy and trauma-exposed controls. However, the hippocampus is heterogeneous, with subregions that may be uniquely affected in individuals with PTSD and depression.nnMethodsWe used random effects regressions and a harmonized neuroimaging protocol based on FreeSurfer (v6.0) to identify sub-structural hippocampal markers of current PTSD (C-PTSD), depression, and the interaction of these conditions across 31 cohorts worldwide (N=3,115; Mage=38.9{+/-}13.9 years). Secondary analyses tested these associations by sex and after modeling the simultaneous effects of remitted PTSD, childhood trauma, mild traumatic brain injury, and alcohol use disorder.nnResultsA significant negative main effect of depression (n=800, vs. no depression, n=1456) was observed in the hippocampal tail ({beta}=-0.13) and CA1 ({beta}=-0.09) after adjusting for covariates and multiple testing (adjusted ps (q)=0.028). A main effect of C-PTSD (n=1042 vs. control, n=1359) was not significant, but an interaction between C-PTSD and depression was significant in the CA1 ({beta}=-0.24, q=0.044). Pairwise comparisons revealed significantly smaller CA1 volumes in individuals with C-PTSD+Depression than controls ({beta}=-0.12, q=0.012), C-PTSD-only ({beta}=-0.17, q=0.001), and Depression-only ({beta}=-0.18, q=0.023). Follow-up analyses revealed sex effects in the hippocampal tail of depressed females, and an interaction effect of C-PTSD and depression in the fimbria of males.nnConclusionsCollectively our results suggest that depression is a stronger predictor of hippocampal volumetry than PTSD, particularly in the CA1, and provide compelling evidence of more pronounced hippocampal phenotypes in comorbid PTSD and depression compared to either condition alone.
]]></description>
<dc:creator>Salminen, L. E.</dc:creator>
<dc:creator>Sämann, P. G.</dc:creator>
<dc:creator>Zheng, Y.</dc:creator>
<dc:creator>Dennis, E. L.</dc:creator>
<dc:creator>Clarke, E. K.</dc:creator>
<dc:creator>Jahanshad, N.</dc:creator>
<dc:creator>Iglesias, J. E.</dc:creator>
<dc:creator>Whelan, C. D.</dc:creator>
<dc:creator>Bruce, S. E.</dc:creator>
<dc:creator>Hayes, J. P.</dc:creator>
<dc:creator>Seedat, S.</dc:creator>
<dc:creator>Averill, C. L.</dc:creator>
<dc:creator>Baugh, L. A.</dc:creator>
<dc:creator>Bomyea, J.</dc:creator>
<dc:creator>Bright, J.</dc:creator>
<dc:creator>Buckle, C. J.</dc:creator>
<dc:creator>Choi, K.</dc:creator>
<dc:creator>Davenport, N. D.</dc:creator>
<dc:creator>Davidson, R. J.</dc:creator>
<dc:creator>Densmore, M.</dc:creator>
<dc:creator>Disner, S. G.</dc:creator>
<dc:creator>du Plessis, S.</dc:creator>
<dc:creator>Elman, J. A.</dc:creator>
<dc:creator>Fani, N.</dc:creator>
<dc:creator>Forster, G. L.</dc:creator>
<dc:creator>Franz, C. E.</dc:creator>
<dc:creator>Frijling, J. L.</dc:creator>
<dc:creator>Gonenc, A.</dc:creator>
<dc:creator>Gruber, S. A.</dc:creator>
<dc:creator>Grupe, D. W.</dc:creator>
<dc:creator>Guenette, J. P.</dc:creator>
<dc:creator>Haswell, C. C.</dc:creator>
<dc:creator>Hofmann, D.</dc:creator>
<dc:creator>Hollifield, M.</dc:creator>
<dc:creator>Hosseini, B.</dc:creator>
<dc:creator>Hudson, A. R.</dc:creator>
<dc:creator>Ipser, J.</dc:creator>
<dc:creator>Jovanovic, T.</dc:creator>
<dc:creator>Kennedy-Krage, A.</dc:creator>
<dc:creator>Kennis, M.</dc:creator>
<dc:creator>King, A.</dc:creator>
<dc:creator>Kinzel, P.</dc:creator>
<dc:date>2019-08-21</dc:date>
<dc:identifier>doi:10.1101/739094</dc:identifier>
<dc:title><![CDATA[Hippocampal subfield volumes are uniquely affected in PTSD and depression: International analysis of 31 cohorts from the PGC-ENIGMA PTSD Working Group]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-08-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/741108v1?rss=1">
<title>
<![CDATA[
Brunner syndrome associated MAOA dysfunction in human iPSC derived dopaminergic neurons results in dysregulated NMDAR expression and increased network activity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/741108v1?rss=1"
</link>
<description><![CDATA[
Monoamine oxidase A (MAOA) is an enzyme that catalyzes the degradation of dopamine, noradrenaline, and serotonin. Regulation of monoamine neurotransmitter abundance through MAOA activity strongly affects motor control, emotion, and cognitive function. Mutations in MAOA cause Brunner Syndrome, which is characterized by impulsive aggressive behavior and mild intellectual disability (ID). The impaired MAOA activity in Brunner Syndrome patients results in bioamine aberration, but it is currently unknown how this affects neuronal function. MAOA is highly expressed in serotonergic and dopaminergic neurons, and dysfunction of both neurotransmission systems is associated with aggressive behavior in mice and humans. Research has so far mainly focused on the serotonergic system. Here, we generated human induced pluripotent stem cell-derived induced dopaminergic neurons (iDANs) from individuals with known MAOA mutations, to investigate MAOA-dependent effects on dopamine neuronal function in the context of Brunner Syndrome. We assessed iDAN lines from three patients and combined data from morphological analysis, gene expression, single-cell electrophysiology, and network analysis using micro-electrode arrays (MEAs). We observed mutation-dependent functional effects as well as overlapping changes in iDAN morphology. The most striking effect was a clear increase in N-methyl-D-aspartate (NMDA) receptor mRNA expression in all patient lines. A marked increase was also seen in coordinated network activity (network bursts) on the MEA in all patient lines, while single-cell intrinsic properties and spontaneous excitatory postsynaptic currents activity appeared normal. Together, our data indicate that dysfunction of MAOA leads to increased coordinated network activity in iDANs, possibly caused by increased synaptic NMDA receptor expression.
]]></description>
<dc:creator>Shi, Y.</dc:creator>
<dc:creator>van Rhijn, J.-R.</dc:creator>
<dc:creator>Bormann, M.</dc:creator>
<dc:creator>Mossink, B.</dc:creator>
<dc:creator>Frega, M.</dc:creator>
<dc:creator>Hakobjan, M.</dc:creator>
<dc:creator>Kittel-Schneider, S.</dc:creator>
<dc:creator>Schubert, D.</dc:creator>
<dc:creator>Brunner, H.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Nadif Kasri, N.</dc:creator>
<dc:date>2019-08-21</dc:date>
<dc:identifier>doi:10.1101/741108</dc:identifier>
<dc:title><![CDATA[Brunner syndrome associated MAOA dysfunction in human iPSC derived dopaminergic neurons results in dysregulated NMDAR expression and increased network activity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-08-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/739409v1?rss=1">
<title>
<![CDATA[
PASER for automated analysis of neural signals recorded in pulsating magnetic fields 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/739409v1?rss=1"
</link>
<description><![CDATA[
Thanks to the advancements in multichannel intracranial neural recordings, magnetic neuroimaging and magnetic neurostimulation techniques (including magnetogenetics), it is now possible to perform large-scale high-throughput neural recordings while imaging or controlling neural activity in a magnetic field. Analysis of neural recordings performed in a switching magnetic field, however, is not a trivial task as gradient and pulse artefacts interfere with the unit isolation. Here we introduce a toolbox called PASER, Processing and Analysis Schemes for Extracellular Recordings, that performs automated denoising, artefact removal, quality control of electrical recordings, unit classification and visualization. PASER is written in MATLAB and modular by design. The current version integrates with third party applications to provide additional functionality, including data import, spike sorting and the analysis of local field potentials. After the description of the toolbox, we evaluate 9 different spike sorting algorithms based on computational cost, unit yield, unit quality and clustering reliability across varying conditions including self-blurring and noise-reversal. Implementation of the best performing spike sorting algorithm (KiloSort) in the default version of the PASER provides the end user with a fully automated pipeline for quantitative analysis of broadband extracellular signals. PASER can be integrated with any established pipeline that sample neural activity with intracranial electrodes. Unlike the existing algorithmic solutions, PASER provides an end-to-end solution for neural recordings made in switching magnetic fields independent from the number of electrodes and the duration of recordings, thus enables high-throughput analysis of neural activity in a wide range of electro-magnetic recording conditions.
]]></description>
<dc:creator>Brouns, T.</dc:creator>
<dc:creator>Celikel, T.</dc:creator>
<dc:date>2019-08-19</dc:date>
<dc:identifier>doi:10.1101/739409</dc:identifier>
<dc:title><![CDATA[PASER for automated analysis of neural signals recorded in pulsating magnetic fields]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-08-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/739912v1?rss=1">
<title>
<![CDATA[
Reduced firing rates of pyramidal cells in frontal cortex of APP/PS1 can be restored by acute treatment with levetiracetam 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/739912v1?rss=1"
</link>
<description><![CDATA[
In recent years aberrant neural oscillations in various cortical areas have emerged as a common physiological hallmark across mouse models of amyloid pathology and patients with Alzheimers disease. However, much less is known about the underlying effect of amyloid pathology on single cell activity. Here, we used high density silicon probe recordings from frontal cortex area of 9 months old APP/PS1 mice to show that resting state Local Field Potential (LFP) power in the theta and beta band is increased in transgenic animals, while single cell firing rates, specifically of putative pyramidal cells, are significantly reduced. At the same time, these sparsely firing pyramidal cells phase-lock their spiking activity more strongly to the ongoing theta and beta rhythms. Furthermore, we demonstrated that the anti-epileptic drug, levetiracetam, can restore principal cell firing rates back to control levels. Overall, our results highlight reduced firing rates of cortical pyramidal cells as a symptom of amyloid pathology and indicate that lifting cortical inhibition might contribute to the beneficial effects of levetiracetam on AD patients.nnO_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY
]]></description>
<dc:creator>Klee, J. L.</dc:creator>
<dc:creator>Kiliaan, A. J.</dc:creator>
<dc:creator>Lipponen, A.</dc:creator>
<dc:creator>Battaglia, F. P.</dc:creator>
<dc:date>2019-08-19</dc:date>
<dc:identifier>doi:10.1101/739912</dc:identifier>
<dc:title><![CDATA[Reduced firing rates of pyramidal cells in frontal cortex of APP/PS1 can be restored by acute treatment with levetiracetam]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-08-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/736520v1?rss=1">
<title>
<![CDATA[
Prediction of a cell-type specific mouse mesoconnectome using gene expression data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/736520v1?rss=1"
</link>
<description><![CDATA[
Reconstructing brain connectivity at sufficient resolution for computational models designed to study the biophysical mechanisms underlying cognitive processes is extremely challenging. For such a purpose, a mesoconnectome that includes laminar and cell-type specificity would be a major step forward. We analysed the ability of gene expression patterns to predict cell-type and laminar specific projection patterns and analyzed the biological context of the most predictive groups of genes. To achieve our goal, we used publicly available volumetric gene expression and connectivity data and pre-processed it for prediction by averaging across brain regions, imputing missing values and rescaling. Afterwards, we predicted the strength of axonal projections and their binary form using expression patterns of individual genes and co-expression patterns of spatial gene modules.nnFor predicting projection strength, we found that ridge (L2-regularized) regression had the highest cross-validated accuracy with a median r2 score of 0.54 which corresponded for binarized predictions to a median area under the ROC value of 0.89. Next, we identified 200 spatial gene modules using the dictionary learning and sparse coding approach. We found that these modules yielded predictions of comparable accuracy, with a median r2 score of 0.51. Finally, a gene ontology enrichment analysis of the most predictive gene groups resulted in significant annotations related to postsynaptic function.nnTaken together, we have demonstrated a prediction pipeline that can be used to perform multimodal data integration to improve the accuracy of the predicted mesoconnectome and support other neuroscience use cases.
]]></description>
<dc:creator>Timonidis, N.</dc:creator>
<dc:creator>Bakker, R.</dc:creator>
<dc:creator>Tiesinga, P.</dc:creator>
<dc:date>2019-08-15</dc:date>
<dc:identifier>doi:10.1101/736520</dc:identifier>
<dc:title><![CDATA[Prediction of a cell-type specific mouse mesoconnectome using gene expression data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-08-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/303016v1?rss=1">
<title>
<![CDATA[
Hemispheric Asymmetry of Globus Pallidus Explains Reward-related Posterior Alpha Modulation in Humans 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/303016v1?rss=1"
</link>
<description><![CDATA[
While subcortical structures like the basal ganglia have been widely explored in relation to motor control, recent evidence suggests that their mechanisms extend to the domain of attentional switching. We here investigated the subcortical involvement in reward related top-down control of visual alpha-band oscillations (8 - 13 Hz), which have been consistently linked to mechanisms supporting the allocation of visuo-spatial attention. Given that items associated with contextual saliency (e.g. monetary reward or loss) attract attention, it is not surprising that the acquired salience of visual items further modulates. The executive networks controlling such reward-dependent modulations of oscillatory brain activity have yet to be fully elucidated. Although such networks have been explored in terms of cortico-cortical interactions, subcortical regions are likely to be involved. To uncover this, we combined MRI and MEG data from 17 male and 11 female participants, investigating whether derived measures of subcortical structural asymmetries predict interhemispheric modulation of alpha power during a spatial attention task. We show that volumetric hemispheric lateralization of globus pallidus (GP) and thalamus (Th) explains individual hemispheric biases in the ability to modulate posterior alpha power. Importantly, for the GP, this effect became stronger when the value-saliency parings in the task increased. Our findings suggest that the GP and Th in humans are part of a subcortical executive control network, differentially involved in modulating posterior alpha activity in the presence of saliency. Further investigation aimed at uncovering the interaction between subcortical and neocortical attentional networks would provide useful insight in future studies.nnSignificance statementWhile the involvement of subcortical regions into higher level cognitive processing, such as attention and reward attribution, has been already indicated in previous studies, little is known about its relationship with the functional oscillatory underpinnings of said processes. In particular, interhemispheric modulation of alpha band (8-13Hz) oscillations, as recorded with magnetoencephalography (MEG), has been previously shown to vary as a function of salience (i.e. monetary reward/loss) in a spatial attention task. We here provide novel insights into the link between subcortical and cortical control of visual attention. Using the same reward-related spatial attention paradigm, we show that the volumetric lateralization of subcortical structures (specifically Globus Pallidus and Thalamus) explains individual biases in the modulation of visual alpha activity.
]]></description>
<dc:creator>Mazzetti, C.</dc:creator>
<dc:creator>Staudigl, T.</dc:creator>
<dc:creator>Marshall, T. R.</dc:creator>
<dc:creator>Fallon, S. J.</dc:creator>
<dc:creator>Zumer, J. M.</dc:creator>
<dc:creator>Jensen, O.</dc:creator>
<dc:date>2018-04-17</dc:date>
<dc:identifier>doi:10.1101/303016</dc:identifier>
<dc:title><![CDATA[Hemispheric Asymmetry of Globus Pallidus Explains Reward-related Posterior Alpha Modulation in Humans]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-04-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/732735v1?rss=1">
<title>
<![CDATA[
Theta power and theta-gamma coupling support spatial memory retrieval 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/732735v1?rss=1"
</link>
<description><![CDATA[
Hippocampal theta oscillations have been implicated in spatial memory function in both rodents and humans. What is less clear is how hippocampal theta interacts with higher frequency oscillations during spatial memory function, and how this relates to subsequent behaviour. Here we asked ten human epilepsy patients undergoing intracranial EEG recording to perform a desk-top virtual reality spatial memory task, and found that increased theta power in two discrete bands ( low 2-5Hz and  high 6-9Hz) during cued retrieval was associated with improved task performance. Similarly, increased coupling between  low theta phase and gamma amplitude during the same period was associated with improved task performance. These results support a role of theta oscillations and theta-gamma phase-amplitude coupling in human spatial memory function.
]]></description>
<dc:creator>Vivekananda, U.</dc:creator>
<dc:creator>Bush, D.</dc:creator>
<dc:creator>Bisby, J. A.</dc:creator>
<dc:creator>Baxendale, S.</dc:creator>
<dc:creator>Rodionov, R.</dc:creator>
<dc:creator>Diehl, B.</dc:creator>
<dc:creator>Chowdhury, F. A.</dc:creator>
<dc:creator>McEvoy, A. W.</dc:creator>
<dc:creator>Miserocchi, A.</dc:creator>
<dc:creator>Walker, M.</dc:creator>
<dc:creator>Burgess, N.</dc:creator>
<dc:date>2019-08-12</dc:date>
<dc:identifier>doi:10.1101/732735</dc:identifier>
<dc:title><![CDATA[Theta power and theta-gamma coupling support spatial memory retrieval]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-08-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/725937v1?rss=1">
<title>
<![CDATA[
Intellectual Disability-related genes increase ADHD risk and locomotor activity in Drosophila 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/725937v1?rss=1"
</link>
<description><![CDATA[
ObjectiveAttention-Deficit/Hyperactivity Disorder (ADHD) is a common, highly heritable neuropsychiatric disorder. ADHD often co-occurs with Intellectual Disability (ID), and shared overlapping genetics have been suggested. This study aimed to identify novel ADHD genes by investigating whether genes carrying rare mutations linked to ID contribute to ADHD risk through common genetic variants. Validation and characterization of candidates were performed using Drosophila melanogaster.nnMethodCommon genetic variants in a diagnostic gene panel of 396 autosomal ID genes were tested for association with ADHD risk, through gene-set and gene-wide analyses, using ADHD meta-analytic data of the Psychiatric Genomics Consortium (n=19,210) for discovery and iPSYCH ADHD data for replication (n=37,076). The significant genes were functionally validated and characterized in Drosophila by assessing locomotor activity and sleep upon knockdown of those genes in brain circuits.nnResultsThe ID gene-set was significantly associated with ADHD risk in the discovery and replication data-sets. The three genes most consistently associated were MEF2C, ST3GAL3, and TRAPPC9. Performing functional characterization of the two evolutionary conserved genes in Drosophila melanogaster, we found their knockdown in dopaminergic (dMEF2) and circadian neurons (dTRAPPC9) to result in increased locomotor activity and reduced sleep, concordant with the human phenotype.nnConclusionsThis study reveals that a large set of ID-related genes contributes to ADHD risk through effects of common alleles. Utilizing this continuity, we identified TRAPPC9, MEF2C, and ST3GAL3 as novel ADHD candidate genes. Characterization in Drosophila suggests that TRAPPC9 and MEF2C contribute to ADHD-related behavior through distinct neural substrates.
]]></description>
<dc:creator>Klein, M.</dc:creator>
<dc:creator>Singgih, E.</dc:creator>
<dc:creator>van Rens, A.</dc:creator>
<dc:creator>Demontis, D.</dc:creator>
<dc:creator>Borglum, A.</dc:creator>
<dc:creator>Roth Mota, N.</dc:creator>
<dc:creator>Castells-Nobau, A.</dc:creator>
<dc:creator>Kiemeney, L.</dc:creator>
<dc:creator>Brunner, H.</dc:creator>
<dc:creator>Arias-Vasquez, A.</dc:creator>
<dc:creator>Schenck, A.</dc:creator>
<dc:creator>van der Voet, M.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:date>2019-08-05</dc:date>
<dc:identifier>doi:10.1101/725937</dc:identifier>
<dc:title><![CDATA[Intellectual Disability-related genes increase ADHD risk and locomotor activity in Drosophila]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-08-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/723643v1?rss=1">
<title>
<![CDATA[
Discovering the shared biology of cognitive traits determined by genetic overlap 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/723643v1?rss=1"
</link>
<description><![CDATA[
Investigating the contribution of biology to human cognition has assumed a bottom-up causal cascade where genes influence brain systems that activate, communicate, and ultimately drive behavior. Yet few studies have directly tested whether cognitive traits with overlapping genetic underpinnings also rely on overlapping brain systems. Here, we report a step-wise exploratory analysis of genetic and functional imaging overlaps among cognitive traits. We used twin-based genetic analyses in the human connectome project (HCP) dataset (N=486), in which we quantified the heritability of measures of cognitive functions, and tested whether they were driven by common genetic factors using pairwise genetic correlations. Subsequently, we derived activation maps associated with cognitive tasks via functional imaging meta-analysis in BrainMap (N=4484), and tested whether cognitive traits that shared genetic variation also exhibited overlapping brain activation. Our genetic analysis determined that six cognitive measures (card sorting, no-go continuous performance, fluid intelligence, processing speed, reading decoding and vocabulary comprehension) were heritable (0.3<h2<0.5), and genetically correlated with at least one other heritable cognitive measure (0.2<{rho}g<0.35). The meta-analysis showed that two genetically-correlated traits, card sorting and fluid intelligence ({rho}g=0.24), also had a significant brain activation overlap ({rho}perm=0.29). These findings indicate that fluid intelligence and executive functioning rely on overlapping biological features, both at the neural systems level and at the molecular level. The cross-disciplinary approach we introduce provides a concrete framework for data-driven quantification of biological convergence between genetics, brain function, and behavior in health and disease.
]]></description>
<dc:creator>Guimaraes, J. P.</dc:creator>
<dc:creator>Bralten, J.</dc:creator>
<dc:creator>Greven, C. U.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Sprooten, E.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:date>2019-08-02</dc:date>
<dc:identifier>doi:10.1101/723643</dc:identifier>
<dc:title><![CDATA[Discovering the shared biology of cognitive traits determined by genetic overlap]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-08-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/720227v1?rss=1">
<title>
<![CDATA[
Mitochondrial dysfunction impairs human neuronal development and reduces neuronal network activity and synchronicity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/720227v1?rss=1"
</link>
<description><![CDATA[
Epilepsy, intellectual and cortical sensory deficits and psychiatric manifestations are among the most frequent manifestations of mitochondrial diseases. Yet, how mitochondrial dysfunction affects neural structure and function remains largely elusive. This is mostly due to the lack of a proper in vitro translational neuronal model system(s) with impaired energy metabolism. Leveraging the induced pluripotent stem cell technology, from a cohort of patients with the common pathogenic m.3243A>G variant of mitochondrial encephalomyopathy, lactic acidosis and stroke-like episodes (MELAS), we differentiated excitatory cortical neurons (iNeurons) with normal (low heteroplasmy) and impaired (high heteroplasmy) mitochondrial function on an isogenic nuclear DNA background. iNeurons with high levels of heteroplasmy exhibited mitochondrial dysfunction, delayed neural maturation, reduced dendritic complexity and fewer functional excitatory synapses. Micro-electrode array recordings of neuronal networks with high heteroplasmy displayed reduced network activity and decreased synchronous network bursting. The impaired neural energy metabolism of iNeurons compromising the structural and functional integrity of neurons and neural networks, could be the primary driver of increased susceptibility to neuropsychiatric manifestations of mitochondrial disease.
]]></description>
<dc:creator>Klein Gunnewiek, T. M.</dc:creator>
<dc:creator>van Hugte, E. J. H.</dc:creator>
<dc:creator>Frega, M.</dc:creator>
<dc:creator>Guardia, G. S.</dc:creator>
<dc:creator>Foreman, K. B.</dc:creator>
<dc:creator>Panneman, D.</dc:creator>
<dc:creator>Mossink, B.</dc:creator>
<dc:creator>Linda, K.</dc:creator>
<dc:creator>Keller, J. M.</dc:creator>
<dc:creator>Schubert, D.</dc:creator>
<dc:creator>Cassiman, D.</dc:creator>
<dc:creator>Morava, E.</dc:creator>
<dc:creator>Rodenburg, R.</dc:creator>
<dc:creator>Perales-Clemente, E.</dc:creator>
<dc:creator>Nelson, T. J.</dc:creator>
<dc:creator>Nadif Kasri, N.</dc:creator>
<dc:creator>Kozicz, T.</dc:creator>
<dc:date>2019-07-30</dc:date>
<dc:identifier>doi:10.1101/720227</dc:identifier>
<dc:title><![CDATA[Mitochondrial dysfunction impairs human neuronal development and reduces neuronal network activity and synchronicity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-07-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/636241v1?rss=1">
<title>
<![CDATA[
Electrocorticographic dissociation of alpha and beta rhythmic activity in the human sensorimotor system 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/636241v1?rss=1"
</link>
<description><![CDATA[
This study uses electrocorticography in humans to assess how alpha- and beta-band rhythms modulate excitability of the sensorimotor cortex during movement selection, as indexed through a psychophysically-controlled movement imagery task. Both rhythms displayed effector-specific modulations, tracked spectral markers of action potentials in the local neuronal population, and showed spatially systematic phase relationships (traveling waves). Yet, alpha- and beta-band rhythms differed in their anatomical and functional properties, were weakly correlated, and traveled along opposite directions across the sensorimotor cortex. Increased alpha-band power in the somatosensory cortex ipsilateral to the selected arm was associated with spatially-unspecific inhibition. Decreased beta-band power over contralateral motor cortex was associated with a focal shift from relative inhibition to excitation. These observations indicate the relevance of both inhibition and disinhibition mechanisms for precise spatiotemporal coordination of neuronal populations during movement selection. Those mechanisms are implemented through the substantially different neurophysiological properties of sensorimotor alpha- and beta-band rhythms.
]]></description>
<dc:creator>Stolk, A.</dc:creator>
<dc:creator>Brinkman, L.</dc:creator>
<dc:creator>Vansteensel, M. J.</dc:creator>
<dc:creator>Aarnoutse, E.</dc:creator>
<dc:creator>Leijten, F. S. S.</dc:creator>
<dc:creator>Dijkerman, C. H.</dc:creator>
<dc:creator>Knight, R. T.</dc:creator>
<dc:creator>de Lange, F. P.</dc:creator>
<dc:creator>Toni, I.</dc:creator>
<dc:date>2019-05-12</dc:date>
<dc:identifier>doi:10.1101/636241</dc:identifier>
<dc:title><![CDATA[Electrocorticographic dissociation of alpha and beta rhythmic activity in the human sensorimotor system]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-05-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/196410v1?rss=1">
<title>
<![CDATA[
Amygdalar atrophy as the genetically mediated hub of limbic degeneration in Alzheimer’s disease 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/196410v1?rss=1"
</link>
<description><![CDATA[
Pharmacological progress, basic science and medical practice can benefit from objective biomarkers that assist in early diagnosis and prognostic stratification of diseases. In the field of Alzheimers disease (AD), the clinical presentation of early stage dementia may not fulfill any diagnostic criteria for years, and quantifying structural brain changes by magnetic resonance imaging (MRI) has shown promise in the discovery of sensitive biomarkers. Although hippocampal atrophy is often used as an in vivo measure of AD, data-driven neuroimaging has revealed complex patterns of regional brain vulnerability that may not perfectly map to anatomical boundaries. In addition to aiding diagnosis, decoding genetic influences on neuroimaging measures of the disease can enlighten molecular mechanisms of the underlying pathology in living patients and guide the therapeutic design.nnHere, we aimed to extract a data-driven MRI feature of brain atrophy in AD by decomposing structural neuroimages using independent component analysis (ICA), a method for performing unbiased computational search in high dimensional data spaces. Our study of the AD Neuroimaging Initiative dataset (n=1,100 subjects) revealed a disease-vulnerable feature with a network-like topology, comprising amygdala, hippocampus, fornix and the inter-connecting white-matter tracts of the limbic system. Whole-genome sequencing identified a nonsynonymous variant (rs34173062) in SHARPIN, a gene coding for a synaptic protein, as a significant modifier of this new MRI feature (p=2.1x10-10). The risk variant was brought to replication in the UK Biobank dataset (n=8,428 subjects), where it was associated with reduced cortical thickness in areas co-localizing with those of the discovery sample (left entorhinal cortex p=0.002, right entorhinal cortex p=8.6x10-4; same direction), as well as with the history of AD in both parents (p=2.3x10-6; same direction).nnIn conclusion, our study shows that ICA can transform voxel-wise volumetric measures of the brain into a data-driven feature of neurodegeneration in AD. Structure of the limbic system, as the most vulnerable focus of brain atrophy in AD, is affected by genetic variability of SHARPIN. The elevated risk of dementia in carriers of the minor allele supports engagement of SHARPIN in the disease pathways, and its role in neurotransmitter receptor scaffolding and integrin signaling may inform on new molecular mechanisms of AD pathophysiology.nnAbbreviationsAlzheimers disease (AD), genome-wide association study (GWAS), independent component analysis (ICA), mild cognitive impairment (MCI), medial temporal circuit (MTC), single-nucleotide polymorphism (SNP), tensor-based morphometry (TBM)
]]></description>
<dc:creator>Soheili-Nezhad, S.</dc:creator>
<dc:creator>Jahanshad, N.</dc:creator>
<dc:creator>Tajer, A.</dc:creator>
<dc:creator>Guelfi, S.</dc:creator>
<dc:creator>Khosrowabadi, R.</dc:creator>
<dc:creator>Pouretemad, H.</dc:creator>
<dc:creator>Saykin, A. J.</dc:creator>
<dc:creator>Thompson, P. M.</dc:creator>
<dc:creator>Zarei, M.</dc:creator>
<dc:date>2017-09-30</dc:date>
<dc:identifier>doi:10.1101/196410</dc:identifier>
<dc:title><![CDATA[Amygdalar atrophy as the genetically mediated hub of limbic degeneration in Alzheimer’s disease]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/228254v1?rss=1">
<title>
<![CDATA[
Systemizing is genetically correlated with autism and is genetically distinct from social autistic traits 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/228254v1?rss=1"
</link>
<description><![CDATA[
The core diagnostic criteria for autism comprise two symptom domains - social and communication difficulties, and unusually repetitive and restricted behaviour, interests and activities. There is some evidence to suggest that these two domains are dissociable, yet, this hypothesis has not been tested using molecular genetics. We test this using a GWAS of a non-social autistic trait, systemizing (N = 51,564), defined as the drive to analyse and build systems. We demonstrate that systemizing is heritable and genetically correlated with autism. In contrast, we do not identify significant genetic correlations between social autistic traits and systemizing. Supporting this, polygenic scores for systemizing are significantly positively associated with restricted and repetitive behaviour but not with social difficulties in autistic individuals. These findings strongly suggest that the two core domains of autism are genetically dissociable, and point at how to fractionate the genetics of autism.
]]></description>
<dc:creator>Warrier, V.</dc:creator>
<dc:creator>Toro, R.</dc:creator>
<dc:creator>Chakrabarti, B.</dc:creator>
<dc:creator>iPSYCH-Broad Autism Group,</dc:creator>
<dc:creator>Borglum, A.</dc:creator>
<dc:creator>Grove, J.</dc:creator>
<dc:creator>the 23andMe Research Team,</dc:creator>
<dc:creator>Hinds, D.</dc:creator>
<dc:creator>Bourgeron, T.</dc:creator>
<dc:creator>Baron-Cohen, S.</dc:creator>
<dc:date>2017-12-03</dc:date>
<dc:identifier>doi:10.1101/228254</dc:identifier>
<dc:title><![CDATA[Systemizing is genetically correlated with autism and is genetically distinct from social autistic traits]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-12-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/399402v1?rss=1">
<title>
<![CDATA[
The genetic architecture of the human cerebral cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/399402v1?rss=1"
</link>
<description><![CDATA[
The cerebral cortex underlies our complex cognitive capabilities, yet we know little about the specific genetic loci influencing human cortical structure. To identify genetic variants, including structural variants, impacting cortical structure, we conducted a genome-wide association meta-analysis of brain MRI data from 51,662 individuals. We analysed the surface area and average thickness of the whole cortex and 34 regions with known functional specialisations. We identified 255 nominally significant loci (P [&le;] 5 x 10-8); 199 survived multiple testing correction (P [&le;] 8.3 x 10-10; 187 surface area; 12 thickness). We found significant enrichment for loci influencing total surface area within regulatory elements active during prenatal cortical development, supporting the radial unit hypothesis. Loci impacting regional surface area cluster near genes in Wnt signalling pathways, known to influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinsons disease, insomnia, depression and ADHD.nnOne Sentence SummaryCommon genetic variation is associated with inter-individual variation in the structure of the human cortex, both globally and within specific regions, and is shared with genetic risk factors for some neuropsychiatric disorders.
]]></description>
<dc:creator>Grasby, K. L.</dc:creator>
<dc:creator>Jahanshad, N.</dc:creator>
<dc:creator>Painter, J. N.</dc:creator>
<dc:creator>Colodro-Conde, L.</dc:creator>
<dc:creator>Bralten, J.</dc:creator>
<dc:creator>Hibar, D. P.</dc:creator>
<dc:creator>Lind, P. A.</dc:creator>
<dc:creator>Pizzagalli, F.</dc:creator>
<dc:creator>Ching, C. R.</dc:creator>
<dc:creator>McMahon, M. A.</dc:creator>
<dc:creator>Shatokhina, N.</dc:creator>
<dc:creator>Zsembik, L. C. P.</dc:creator>
<dc:creator>Agartz, I.</dc:creator>
<dc:creator>Alhusaini, S.</dc:creator>
<dc:creator>Almeida, M. A.</dc:creator>
<dc:creator>Alnaes, D.</dc:creator>
<dc:creator>Amlien, I. K.</dc:creator>
<dc:creator>Andersson, M.</dc:creator>
<dc:creator>Ard, T.</dc:creator>
<dc:creator>Armstrong, N. J.</dc:creator>
<dc:creator>Ashley-Koch, A.</dc:creator>
<dc:creator>Bernard, M.</dc:creator>
<dc:creator>Brouwer, R. M.</dc:creator>
<dc:creator>Buimer, E. E.</dc:creator>
<dc:creator>Bülow, R.</dc:creator>
<dc:creator>Bürger, C.</dc:creator>
<dc:creator>Cannon, D. M.</dc:creator>
<dc:creator>Chakravarty, M.</dc:creator>
<dc:creator>Chen, Q.</dc:creator>
<dc:creator>Cheung, J. W.</dc:creator>
<dc:creator>Couvy-Duchesne, B.</dc:creator>
<dc:creator>Dale, A. M.</dc:creator>
<dc:creator>Dalvie, S.</dc:creator>
<dc:creator>de Araujo, T. K.</dc:creator>
<dc:creator>de Zubicaray, G. I.</dc:creator>
<dc:creator>de Zwarte, S. M.</dc:creator>
<dc:creator>den Braber, A.</dc:creator>
<dc:creator>Doan, N. T.</dc:creator>
<dc:creator>Dohm, K.</dc:creator>
<dc:creator>Ehrlich, S.</dc:creator>
<dc:creator>Engel</dc:creator>
<dc:date>2018-09-03</dc:date>
<dc:identifier>doi:10.1101/399402</dc:identifier>
<dc:title><![CDATA[The genetic architecture of the human cerebral cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/706051v1?rss=1">
<title>
<![CDATA[
Medial prefrontal decoupling from the default mode network benefits memory 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/706051v1?rss=1"
</link>
<description><![CDATA[
In the last few years the involvement of the medial prefrontal cortex (mPFC) in memory processing has received increased attention. It is centrally involved when we use prior knowledge (schemas) to improve learning of new material. With the mPFC also being one of the core hubs of the default mode network (DMN) and the DMNs role in memory retrieval, we decided to investigate whether the mPFC in a schema paradigm acts independently of the DMN. We tested this with data from a cross-sectional developmental study. During retrieval of schema items, the mPFC decoupled from the DMN with the degree of decoupling predicting memory performance. This finding suggests that a demand specific reconfiguration of the DMN supports schema memory. Additionally, we found that in the control condition, which relied on episodic memory, activity in the parahippocampal gyrus was positively related to memory performance. We interpret these results as a demand specific network reconfiguration of the DMN: a decoupling of the mPFC to support schema memory and a decoupling of the parahippocampal gyrus facilitating episodic memory. This supports the notion of dynamic reconfiguration of brain networks in response to task demands in the sense of process specific alliances.
]]></description>
<dc:creator>Mueller, N. C.</dc:creator>
<dc:creator>Dresler, M.</dc:creator>
<dc:creator>Janzen, G.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>Fernandez, G.</dc:creator>
<dc:creator>Kohn, N.</dc:creator>
<dc:date>2019-07-18</dc:date>
<dc:identifier>doi:10.1101/706051</dc:identifier>
<dc:title><![CDATA[Medial prefrontal decoupling from the default mode network benefits memory]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-07-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/703793v1?rss=1">
<title>
<![CDATA[
The Evolutionary History of Common Genetic Variants Influencing Human Cortical Surface Area 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/703793v1?rss=1"
</link>
<description><![CDATA[
Structural brain changes along the lineage that led to modern Homo sapiens have contributed to our unique cognitive and social abilities. However, the evolutionarily relevant molecular variants impacting key aspects of neuroanatomy are largely unknown. Here, we integrate evolutionary annotations of the genome at diverse timescales with common variant associations from large-scale neuroimaging genetic screens in living humans, to reveal how selective pressures have shaped neocortical surface area. We show that variation within human gained enhancers active in the developing brain is associated with global surface area as well as that of specific regions. Moreover, we find evidence of recent polygenic selection over the past 2,000 years influencing surface area of multiple cortical regions, including those involved in spoken language and visual processing.
]]></description>
<dc:creator>Tilot, A. L.</dc:creator>
<dc:creator>Khramtsova, E. A.</dc:creator>
<dc:creator>Grasby, K.</dc:creator>
<dc:creator>Jahanshad, N.</dc:creator>
<dc:creator>Painter, J.</dc:creator>
<dc:creator>Colodro Conde, L.</dc:creator>
<dc:creator>Bralten, J.</dc:creator>
<dc:creator>Hibar, D. P.</dc:creator>
<dc:creator>Lind, P.</dc:creator>
<dc:creator>Liu, S.</dc:creator>
<dc:creator>Brotman, S. M.</dc:creator>
<dc:creator>Thompson, P. M.</dc:creator>
<dc:creator>Medland, S. E.</dc:creator>
<dc:creator>Macciardi, F.</dc:creator>
<dc:creator>Stranger, B. E.</dc:creator>
<dc:creator>Davis, L. K.</dc:creator>
<dc:creator>Fisher, S. E.</dc:creator>
<dc:creator>Stein, J.</dc:creator>
<dc:date>2019-07-16</dc:date>
<dc:identifier>doi:10.1101/703793</dc:identifier>
<dc:title><![CDATA[The Evolutionary History of Common Genetic Variants Influencing Human Cortical Surface Area]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-07-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/458133v1?rss=1">
<title>
<![CDATA[
Structuring Time in Human Lateral Entorhinal Cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/458133v1?rss=1"
</link>
<description><![CDATA[
Remembering event sequences is central to episodic memory and thought to be supported by the hippocampal-entorhinal region. We previously demonstrated that the hippocampus maps spatial and temporal distances between events encountered along a fixed route through a virtual city (Deuker et al., 2016), but the content of entorhinal mnemonic representations remains unclear. Here, we demonstrate that, after learning, multi-voxel representations in the anterior-lateral entorhinal cortex (alEC) specifically reflect the temporal event structure. Holistic representations of the temporal structure related to memory recall and the temporal event structure could be reconstructed from entorhinal multi-voxel patterns. Our findings demonstrate representations of temporal structure in the alEC in line with temporal information carried by population signals in the lateral entorhinal cortex of navigating rodents and activations of its human homologue during temporal memory retrieval. Our results provide novel evidence for the role of the human alEC in representing time for episodic memory.
]]></description>
<dc:creator>Bellmund, J. L. S.</dc:creator>
<dc:creator>Deuker, L.</dc:creator>
<dc:creator>Doeller, C. F.</dc:creator>
<dc:date>2018-11-01</dc:date>
<dc:identifier>doi:10.1101/458133</dc:identifier>
<dc:title><![CDATA[Structuring Time in Human Lateral Entorhinal Cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-11-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/495697v1?rss=1">
<title>
<![CDATA[
The Cost of Appearing Suspicious? Information Gathering Costs in Trust Decisions 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/495697v1?rss=1"
</link>
<description><![CDATA[
Trust decisions are inherently uncertain, as people have incomplete information about the trustworthiness of the other prior to their decision. Therefore, it is beneficial to gather information about a trustees past behaviour before deciding whether or not to trust them. However, elaborate inquiries about a trustees behavior may change the trustees willingness to reciprocate, causing either a decrease due to the investor appearing suspicious, or an increase because the investor appears to be highly betrayal-averse. Such a change could cause the investor to gather less or more information, respectively. We examine how information acquisition is modulated by social context, monetary cost, and the trustees trustworthiness. Participants had the opportunity to sequentially sample information about a trustees reciprocation history before they decided whether or not to invest. On some trials, we induced a social context by telling the participant that the trustee would later learn how much the participant sampled ("overt sampling"). Participants sampled less when there was a monetary cost and when the reciprocation history was more conclusive. Crucially, when sampling was free and overt, participants sampled less, suggesting negative consequences of appearing suspicious. In post-experiment questionnaires, participants indeed reported a belief that the reciprocation probability would decrease when information was overtly sampled. The findings replicated in a second experiment and were well accounted for by a utility-maximizing model in which overt sampling induces a decrease in reciprocation probability. This study opens the door to broader applications of the tools and models of information sampling to social decision-making.nnSignificance StatementTrust and reciprocity are essential for establishing and maintaining beneficial cooperative interactions. However, not everyone can be trusted. Here, we focus on a fundamental question in the study of social interaction: how people gather and use information to make a decision to trust or not trust. While more information seems better, participants gathered less information about trustworthiness when the trustee would learn about the inquiries, as if they avoided appearing suspicious. Indeed, participants reported that they believed that sampling elaborately would make the trustee less willing to reciprocate trust. Using a mathematical model of information gathering, we show that this belief indeed reduces the value of information. Our findings contribute to a deeper understanding of information gathering in social contexts.
]]></description>
<dc:creator>Ma, I.</dc:creator>
<dc:creator>Sanfey, A. G.</dc:creator>
<dc:creator>Ma, W. J.</dc:creator>
<dc:date>2018-12-17</dc:date>
<dc:identifier>doi:10.1101/495697</dc:identifier>
<dc:title><![CDATA[The Cost of Appearing Suspicious? Information Gathering Costs in Trust Decisions]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-12-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/693895v1?rss=1">
<title>
<![CDATA[
Differences in strategic abilities but not associative processes explain memory development 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/693895v1?rss=1"
</link>
<description><![CDATA[
Childrens learning capabilities change while growing up. One framework that describes the cognitive and neural development of childrens growing learning abilities is the two-component model. It distinguishes processes that integrate separate features into a coherent memory representation (associative component) and executive abilities, such as elaboration, evaluation and monitoring, that support memory processing (strategic component). In an fMRI study using an object-location association paradigm, we investigated how the two components influence memory performance across development. We tested children (10-12 yrs., n=31), late adolescents (18 yrs., n=29) and adults (25+ yrs., n=30) of either sex. For studying the associative component, we also probed how the utilisation of prior knowledge (schemas) facilitates memory across age groups. Children had overall lower retrieval performance, while adolescents and adults did not differ from each other. All groups benefitted from schemas, but this effect did not differ between groups. Performance differences between groups were associated with deactivation of the dorsal medial prefrontal cortex (dmPFC), which in turn was linked to executive functioning. These patterns were stronger in adolescents and adults and seemed absent in children. This pattern of results suggests the childrens executive system, the strategic component, is not as mature and thus cannot facilitate memory performance in the same way as in adolescents/adults. In contrast, we did not find age-related differences in the associative component; with activity in the angular gyrus predicting memory performance systematically across groups. Overall our results suggest that differences of executive rather than associative abilities explain memory differences between children, adolescents and adults.
]]></description>
<dc:creator>Mueller, N.</dc:creator>
<dc:creator>Kohn, N.</dc:creator>
<dc:creator>van Buuren, M.</dc:creator>
<dc:creator>Klijn, N.</dc:creator>
<dc:creator>Emmen, H.</dc:creator>
<dc:creator>Berkers, R. M.</dc:creator>
<dc:creator>Dresler, M.</dc:creator>
<dc:creator>Janzen, G.</dc:creator>
<dc:creator>Fernandez, G.</dc:creator>
<dc:date>2019-07-05</dc:date>
<dc:identifier>doi:10.1101/693895</dc:identifier>
<dc:title><![CDATA[Differences in strategic abilities but not associative processes explain memory development]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-07-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/693754v1?rss=1">
<title>
<![CDATA[
Effects of distraction on taste-related neural processing 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/693754v1?rss=1"
</link>
<description><![CDATA[
Distracted eating is associated with increased food intake and overweight. However, the underlying neurocognitive mechanisms are unknown. To elucidate these mechanisms, 41 healthy normal-weight participants received sips of high- and low-sweet isocaloric chocolate milk, while performing a high- or low-distracting detection task during fMRI on two test days. Subsequently, we measured ad libitum food intake. As expected, a region in the primary taste cortex - located in the insula - responded more to the sweeter drink. Distraction did not affect this right insula sweetness response across the group, but did weaken sweetness-related connectivity of this region to a secondary taste region in the right orbitofrontal cortex. Moreover, distraction-related attenuation of taste processing in the insula predicted increased subsequent ad libitum food intake after distraction between subjects. These results reveal a previously unknown mechanism explaining how distraction during consumption attenuates neural taste processing and increases food intake. The study was preregistered at https://osf.io/vxdhg/register/5771ca429ad5a1020de2872e?view_only=e3207cd6567f41f0a1505e343a64b5aa.
]]></description>
<dc:creator>Duif, I.</dc:creator>
<dc:creator>Wegman, J. B.</dc:creator>
<dc:creator>Mars, M. M.</dc:creator>
<dc:creator>de Graaf, K.</dc:creator>
<dc:creator>Smeets, P. A.</dc:creator>
<dc:creator>Aarts, E.</dc:creator>
<dc:date>2019-07-05</dc:date>
<dc:identifier>doi:10.1101/693754</dc:identifier>
<dc:title><![CDATA[Effects of distraction on taste-related neural processing]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-07-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/692772v1?rss=1">
<title>
<![CDATA[
Reconciling Dimensional and Categorical Models of Autism Heterogeneity: a Brain Connectomics & Behavioral Study 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/692772v1?rss=1"
</link>
<description><![CDATA[
BackgroundHeterogeneity in autism spectrum disorder (ASD) has hindered the development of biomarkers, thus motivating subtyping efforts. Most subtyping studies divide ASD individuals into non-overlapping (categorical) subgroups. However, continuous inter-individual variation in ASD suggests the need for a dimensional approach.nnMethodsA Bayesian model was employed to decompose resting-state functional connectivity (RSFC) of ASD individuals into multiple abnormal RSFC patterns, i.e., categorical subtypes henceforth referred to as "factors". Importantly, the model allowed each individual to express one or more factors to varying degrees (dimensional subtyping). The model was applied to 306 ASD individuals (age 5.2-57 years) from two multisite repositories. Posthoc analyses associated factors with symptoms and demographics.nnResultsAnalyses yielded three factors with dissociable whole-brain hypo/hyper RSFC patterns. Most participants expressed multiple (categorical) factors, suggestive of a mosaic of subtypes within individuals. All factors shared abnormal RSFC involving the default network, but the directionality (hypo/hyper RSFC) differed across factors. Factor 1 was associated with core ASD symptoms, while factor 2 was associated with comorbid symptoms. Older males preferentially expressed factor 3. Factors were robust across multiple control analyses and not associated with IQ, nor head motion.nnConclusionsThere exist at least three ASD factors with dissociable patterns of whole-brain RSFC, behaviors and demographics. Heterogeneous default network hypo/hyper RSFC across the factors might explain previously reported inconsistencies. The factors differentiated between core ASD and comorbid symptoms - a less appreciated domain of heterogeneity in ASD. These factors are co-expressed in ASD individuals with different degrees, thus reconciling categorical and dimensional perspectives of ASD heterogeneity.
]]></description>
<dc:creator>Tang, S.</dc:creator>
<dc:creator>Sun, N.</dc:creator>
<dc:creator>Floris, D. L.</dc:creator>
<dc:creator>Zhang, X.</dc:creator>
<dc:creator>Di Martino, A.</dc:creator>
<dc:creator>Yeo, B. T. T.</dc:creator>
<dc:date>2019-07-04</dc:date>
<dc:identifier>doi:10.1101/692772</dc:identifier>
<dc:title><![CDATA[Reconciling Dimensional and Categorical Models of Autism Heterogeneity: a Brain Connectomics & Behavioral Study]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-07-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/368001v1?rss=1">
<title>
<![CDATA[
Prediction and final temporal errors are used for trial-to-trial motor corrections 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/368001v1?rss=1"
</link>
<description><![CDATA[
Many daily life situations (e.g. dodging an approaching object or hitting a moving target) require people to correct planning of future movements based on previous temporal errors. However, the actual temporal error can be difficult to perceive: imagine a baseball batter that swings and misses a fastball. Here we show that in such situations people can use an internal error signal to make corrections in the next trial. This signal is based on the discrepancy between the actual and the planned action onset time: the prediction error. In this study, we used three interception tasks: reaching movements, saccadic eye movements and a button press that released a cursor moving ballistically for a fixed time. We found that action onset depended on the previous temporal error in the arm movement experiment only and not in the saccadic and button press experiments. However, this dependency was modulated by the movement time: faster arm movements depended less on the previous actual temporal error. An analysis using a Kalman filter confirmed that people used the prediction error rather than the previous temporal error for trial-by-trial corrections in fast arm movements, saccades and button press.
]]></description>
<dc:creator>Lopez-Moliner, J.</dc:creator>
<dc:creator>Vullings, C.</dc:creator>
<dc:creator>Madelain, L.</dc:creator>
<dc:creator>van Beers, R. J.</dc:creator>
<dc:date>2018-07-12</dc:date>
<dc:identifier>doi:10.1101/368001</dc:identifier>
<dc:title><![CDATA[Prediction and final temporal errors are used for trial-to-trial motor corrections]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/687681v1?rss=1">
<title>
<![CDATA[
A large single-participant fMRI dataset for probing brain responses to naturalistic stimuli in space and time 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/687681v1?rss=1"
</link>
<description><![CDATA[
Visual and auditory representations in the human brain have been studied with encoding, decoding and reconstruction models. Representations from convolutional neural networks have been used as explanatory models for these stimulus-induced hierarchical brain activations. However, none of the fMRI datasets currently available has adequate amounts of data for sufficiently sampling their representations. We recorded a densely sampled large fMRI dataset (TR=700 ms) in a single individual exposed to spatiotemporal visual and auditory naturalistic stimuli (30 episodes of BBCs Doctor Who). The data consists of 120.830 whole-brain volumes (approx. 23 h) of single-presentation data (full episodes, training set) and 1.178 volumes (11 min) of repeated narrative short episodes (test set, 22 repetitions), recorded with fixation over a period of six months. This rich dataset can be used widely to study the way the brain represents audiovisual input across its sensory hierarchies.
]]></description>
<dc:creator>Seeliger, K.</dc:creator>
<dc:creator>Sommers, R. P.</dc:creator>
<dc:creator>Güclü, U.</dc:creator>
<dc:creator>Bosch, S. E.</dc:creator>
<dc:creator>van Gerven, M. A. J.</dc:creator>
<dc:date>2019-07-02</dc:date>
<dc:identifier>doi:10.1101/687681</dc:identifier>
<dc:title><![CDATA[A large single-participant fMRI dataset for probing brain responses to naturalistic stimuli in space and time]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-07-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/688630v1?rss=1">
<title>
<![CDATA[
Population codes of prior knowledge learned through environmental regularities 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/688630v1?rss=1"
</link>
<description><![CDATA[
How the brain makes correct inferences about its environment based on noisy and ambiguous observations, is one of the fundamental questions in Neuroscience. Prior knowledge about the probability with which certain events occur in the environment plays an important role in this process. Humans are able to incorporate such prior knowledge in an efficient, Bayes optimal, way in many situations, but it remains an open question how the brain acquires and represents this prior knowledge. The long time spans over which prior knowledge is acquired make it a challenging question to investigate experimentally. In order to guide future experiments with clear empirical predictions, we used a neural network model to learn two commonly used tasks in the experimental literature (i.e. orientation classification and orientation estimation) where the prior probability of observing a certain stimulus is manipulated. We show that a population of neurons learns to correctly represent and incorporate prior knowledge, by only receiving feedback about the accuracy of their inference from trial-to-trial and without any probabilistic feedback. We identify different factors that can influence the neural responses to unexpected or expected stimuli, and find a novel mechanism that changes the activation threshold of neurons, depending on the prior probability of the encoded stimulus. In a task where estimating the exact stimulus value is important, more likely stimuli also led to denser tuning curve distributions and narrower tuning curves, allocating computational resources such that information processing is enhanced for more likely stimuli. These results can explain several different experimental findings and clarify why some contradicting observations concerning the neural responses to expected versus unexpected stimuli have been reported and pose some clear and testable predictions about the neural representation of prior knowledge that can guide future experiments.
]]></description>
<dc:creator>Quax, S. C.</dc:creator>
<dc:creator>Bosch, S.</dc:creator>
<dc:creator>van Gerven, M.</dc:creator>
<dc:creator>Peelen, M.</dc:creator>
<dc:date>2019-07-01</dc:date>
<dc:identifier>doi:10.1101/688630</dc:identifier>
<dc:title><![CDATA[Population codes of prior knowledge learned through environmental regularities]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-07-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/682898v1?rss=1">
<title>
<![CDATA[
Cue-reactivity and approach bias to social alcohol cues and their association with drinking in a social setting in young adults 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/682898v1?rss=1"
</link>
<description><![CDATA[
Alcohol is mainly consumed in social settings, in which people often adapt their drinking behavior to that of others, also called imitation of drinking. Yet, it remains unclear what drives this drinking in a social setting. In this study, we expected to see stronger brain and behavioral responses to social compared to non-social alcohol cues, that would be associated with actual drinking in a social setting. The sample consisted of 153 beer-drinking males, aged 18-25 years. Brain responses to social alcohol cues were measured during an alcohol cue exposure task in the scanner. Behavioral responses to social alcohol cues were measured using a stimulus-response compatibility task, providing an index of approach bias towards these cues. Drinking in a social setting was measured in a Bar-Lab setting. Specific brain responses to social alcohol cues were observed in the bilateral superior temporal sulcus and the left inferior parietal lobe. There was no approach bias towards social alcohol cues specifically, however, we did find an approach bias towards alcohol (versus soda) cues in general. Brain responses and approach bias towards social alcohol cues were unrelated and not associated with drinking, measured in the Bar-Lab. Thus, we found no support for a relation between drinking in a social setting on the one hand, and brain cue-reactivity or behavioral approach biases to social alcohol cues on the other hand. This suggests that, in contrast to our hypothesis, drinking in a social setting may not be driven by brain or behavioral responses to social alcohol cues.
]]></description>
<dc:creator>Groefsema, M. M.</dc:creator>
<dc:creator>Mies, G. W.</dc:creator>
<dc:creator>Cousijn, J.</dc:creator>
<dc:creator>Engels, R. C. M. E.</dc:creator>
<dc:creator>Sescousse, G.</dc:creator>
<dc:creator>Luijten, M.</dc:creator>
<dc:date>2019-06-27</dc:date>
<dc:identifier>doi:10.1101/682898</dc:identifier>
<dc:title><![CDATA[Cue-reactivity and approach bias to social alcohol cues and their association with drinking in a social setting in young adults]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-06-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/677153v1?rss=1">
<title>
<![CDATA[
Altered White Matter Microstructural Organization in Post-Traumatic Stress Disorder across 3,049 Adults: Results from the PGC-ENIGMA PTSD Consortium 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/677153v1?rss=1"
</link>
<description><![CDATA[
A growing number of studies have examined alterations in white matter organization in people with posttraumatic stress disorder (PTSD) using diffusion MRI (dMRI), but the results have been mixed, which may be partially due to relatively small sample sizes among studies. Altered structural connectivity may be both a neurobiological vulnerability for, and a result of, PTSD. In an effort to find reliable effects, we present a multi-cohort analysis of dMRI metrics across 3,049 individuals from 28 cohorts currently participating in the PGC-ENIGMA PTSD working group (a joint partnership between the Psychiatric Genomics Consortium and the Enhancing NeuroImaging Genetics through Meta-Analysis consortium). Comparing regional white matter metrics across the full brain in 1,446 individuals with PTSD and 1,603 controls (2152 males/897 females) between ages 18-83, 92% of whom were trauma-exposed, we report associations between PTSD and disrupted white matter organization measured by lower fractional anisotropy (FA) in the tapetum region of the corpus callosum (Cohens d=-0.12, p=0.0021). The tapetum connects the left and right hippocampus, structures for which structure and function have been consistently implicated in PTSD. Results remained significant/similar after accounting for the effects of multiple potentially confounding variables: childhood trauma exposure, comorbid depression, history of traumatic brain injury, current alcohol abuse or dependence, and current use of psychotropic medications. Our results show that PTSD may be associated with alterations in the broader hippocampal network.
]]></description>
<dc:creator>Dennis, E.</dc:creator>
<dc:creator>Disner, S. E.</dc:creator>
<dc:creator>Fani, N.</dc:creator>
<dc:creator>Salminen, L. E.</dc:creator>
<dc:creator>Logue, M.</dc:creator>
<dc:creator>Clarke-Rubright, E. K.</dc:creator>
<dc:creator>Haswell, C. C.</dc:creator>
<dc:creator>Averill, C.</dc:creator>
<dc:creator>Baugh, L. A.</dc:creator>
<dc:creator>Bomyea, J.</dc:creator>
<dc:creator>Bruce, S. E.</dc:creator>
<dc:creator>Cha, J.</dc:creator>
<dc:creator>Choi, K.</dc:creator>
<dc:creator>Davenport, N. D.</dc:creator>
<dc:creator>Densmore, M.</dc:creator>
<dc:creator>du Plessis, S.</dc:creator>
<dc:creator>Forster, G. L.</dc:creator>
<dc:creator>Frijling, J. L.</dc:creator>
<dc:creator>Gonenc, A.</dc:creator>
<dc:creator>Gruber, S.</dc:creator>
<dc:creator>Grupe, D. W.</dc:creator>
<dc:creator>Guenette, J. P.</dc:creator>
<dc:creator>Hayes, J.</dc:creator>
<dc:creator>Hofmann, D.</dc:creator>
<dc:creator>Ipser, J.</dc:creator>
<dc:creator>Jovanovic, T.</dc:creator>
<dc:creator>Kelly, S.</dc:creator>
<dc:creator>Kennis, M.</dc:creator>
<dc:creator>Kinzel, P.</dc:creator>
<dc:creator>Koch, S. B.</dc:creator>
<dc:creator>Koerte, I.</dc:creator>
<dc:creator>Koopowitz, S.</dc:creator>
<dc:creator>Korgaonkar, M.</dc:creator>
<dc:creator>Krystal, J.</dc:creator>
<dc:creator>Lebois, L. A.</dc:creator>
<dc:creator>Li, G.</dc:creator>
<dc:creator>Magnotta, V. A.</dc:creator>
<dc:creator>Manthey, A.</dc:creator>
<dc:creator>May, G. J.</dc:creator>
<dc:creator>Menefee, D. S.</dc:creator>
<dc:creator>Nawijn, L.</dc:creator>
<dc:creator>Nelson, S. M.</dc:creator>
<dc:creator>Neufeld, R. W.</dc:creator>
<dc:creator>Nitschke,</dc:creator>
<dc:date>2019-06-20</dc:date>
<dc:identifier>doi:10.1101/677153</dc:identifier>
<dc:title><![CDATA[Altered White Matter Microstructural Organization in Post-Traumatic Stress Disorder across 3,049 Adults: Results from the PGC-ENIGMA PTSD Consortium]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-06-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/675264v1?rss=1">
<title>
<![CDATA[
Does alpha phase modulate visual target detection? Three experiments with tACS phase-based stimulus presentation. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/675264v1?rss=1"
</link>
<description><![CDATA[
In recent years the influence of alpha (7-13 Hz) phase on visual processing has received a lot of attention. Magneto-/encephalography (M/EEG) studies showed that alpha phase indexes visual excitability and task performance. If occipital alpha phase is functionally relevant, the phase of occipital alpha-frequency transcranial alternating current stimulation (tACS) could modulate visual processing. Visual stimuli presented at different pre-determined, experimentally controlled, phases of the entraining tACS signal should then result in an oscillatory pattern of visual performance. We studied this in a series of experiments. In experiment one, we applied 10 Hz tACS to right occipital cortex (O2) and used independent psychophysical staircases to obtain contrast thresholds for detection of visual gratings in left or right hemifield, in six equidistant tACS phase conditions. In experiments two and three, tACS was at EEG-based individual peak alpha frequency. In experiment two, we measured detection rates for gratings with (pseudo-)fixed contrast levels. In experiment three, participants detected brief luminance changes in a custom-built LED device, at eight equidistant alpha phases. In none of the experiments did the primary outcome measure over phase conditions consistently reflect a one-cycle sinusoid as predicted. However, post-hoc analyses of reaction times (RT) suggested that tACS alpha phase did modulate RT in both experiments 1 and 2 (not measured in experiment 3). This observation is in line with the idea that alpha phase causally gates visual inputs through cortical excitability modulation.
]]></description>
<dc:creator>de Graaf, T. A.</dc:creator>
<dc:creator>Thomson, A.</dc:creator>
<dc:creator>Janssens, S. E. W.</dc:creator>
<dc:creator>van Bree, S.</dc:creator>
<dc:creator>ten Oever, S.</dc:creator>
<dc:creator>Sack, A. T.</dc:creator>
<dc:date>2019-06-20</dc:date>
<dc:identifier>doi:10.1101/675264</dc:identifier>
<dc:title><![CDATA[Does alpha phase modulate visual target detection? Three experiments with tACS phase-based stimulus presentation.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-06-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/409649v1?rss=1">
<title>
<![CDATA[
Genetic Determinants of Cortical Structure (Thickness, Surface Area and Volumes) among Disease Free Adults in the CHARGE Consortium 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/409649v1?rss=1"
</link>
<description><![CDATA[
Cortical thickness, surface area and volumes (MRI cortical measures) vary with age and cognitive function, and in neurological and psychiatric diseases. We examined heritability, genetic correlations and genome-wide associations of cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprised 22,822 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the United Kingdom Biobank. Significant associations were replicated in the Enhancing Neuroimaging Genetics through Meta-analysis (ENIGMA) consortium, and their biological implications explored using bioinformatic annotation and pathway analyses. We identified genetic heterogeneity between cortical measures and brain regions, and 161 genome-wide significant associations pointing to wnt/{beta}-catenin, TGF-{beta} and sonic hedgehog pathways. There was enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging.
]]></description>
<dc:creator>Hofer, E.</dc:creator>
<dc:creator>Roshchupkin, G. V.</dc:creator>
<dc:creator>Adams, H.</dc:creator>
<dc:creator>Knol, M.</dc:creator>
<dc:creator>Lin, H.</dc:creator>
<dc:creator>Li, S.</dc:creator>
<dc:creator>Zare, H.</dc:creator>
<dc:creator>Ahmad, S.</dc:creator>
<dc:creator>Armstrong, N.</dc:creator>
<dc:creator>Satizabal, C.</dc:creator>
<dc:creator>Bernard, M.</dc:creator>
<dc:creator>Bis, J.</dc:creator>
<dc:creator>Gillespie, N.</dc:creator>
<dc:creator>Luciano, M.</dc:creator>
<dc:creator>Mishra, A.</dc:creator>
<dc:creator>Scholz, M.</dc:creator>
<dc:creator>Teumer, A.</dc:creator>
<dc:creator>Xia, R.</dc:creator>
<dc:creator>Jian, X.</dc:creator>
<dc:creator>Mosley, T.</dc:creator>
<dc:creator>Saba, Y.</dc:creator>
<dc:creator>Pirpamer, L.</dc:creator>
<dc:creator>Seiler, S.</dc:creator>
<dc:creator>Becker, J.</dc:creator>
<dc:creator>Carmichael, O.</dc:creator>
<dc:creator>Rotter, J.</dc:creator>
<dc:creator>Psaty, B.</dc:creator>
<dc:creator>Lopez, O.</dc:creator>
<dc:creator>Amin, N.</dc:creator>
<dc:creator>Lee, S.</dc:creator>
<dc:creator>Yang, Q.</dc:creator>
<dc:creator>Himali, J.</dc:creator>
<dc:creator>Maillard, P.</dc:creator>
<dc:creator>Beiser, A.</dc:creator>
<dc:creator>DeCarli, C.</dc:creator>
<dc:creator>Karama, S.</dc:creator>
<dc:creator>Lewis, L.</dc:creator>
<dc:creator>Bastin, M.</dc:creator>
<dc:creator>Harris, M.</dc:creator>
<dc:creator>Deary, I.</dc:creator>
<dc:creator>Witte, V.</dc:creator>
<dc:creator>Beyer, F.</dc:creator>
<dc:creator>Loeffler, M.</dc:creator>
<dc:creator>Mather, K.</dc:creator>
<dc:creator>Schofield, P.</dc:creator>
<dc:creator>Thalamuthu, A.</dc:creator>
<dc:creator>Kwok, J.</dc:creator>
<dc:creator>Wright, M.</dc:creator>
<dc:creator>Ames, D.</dc:creator>
<dc:creator>Trollor, J.</dc:creator>
<dc:creator>Jia</dc:creator>
<dc:date>2018-09-09</dc:date>
<dc:identifier>doi:10.1101/409649</dc:identifier>
<dc:title><![CDATA[Genetic Determinants of Cortical Structure (Thickness, Surface Area and Volumes) among Disease Free Adults in the CHARGE Consortium]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/391201v1?rss=1">
<title>
<![CDATA[
Deforming the metric of cognitive maps distorts memory 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/391201v1?rss=1"
</link>
<description><![CDATA[
Environmental boundaries anchor cognitive maps that support memory. However, trapezoidal boundary geometry distorts the regular firing patterns of entorhinal grid cells proposedly providing a metric for cognitive maps. Here, we test the impact of trapezoidal boundary geometry on human spatial memory using immersive virtual reality. Consistent with reduced regularity of grid patterns in rodents and a grid-cell model based on the eigenvectors of the successor representation, human positional memory was degraded in a trapezoid compared to a square environment; an effect particularly pronounced in the trapezoids narrow part. Congruent with spatial frequency changes of eigenvector grid patterns, distance estimates between remembered positions were persistently biased; revealing distorted memory maps that explained behavior better than the objective maps. Our findings demonstrate that environmental geometry affects human spatial memory similarly to rodent grid cell activity -- thus strengthening the putative link between grid cells and behavior along with their cognitive functions beyond navigation.
]]></description>
<dc:creator>Bellmund, J. L. S.</dc:creator>
<dc:creator>Ruiter, T. A.</dc:creator>
<dc:creator>Nau, M.</dc:creator>
<dc:creator>Barry, C.</dc:creator>
<dc:creator>Doeller, C. F.</dc:creator>
<dc:date>2018-08-14</dc:date>
<dc:identifier>doi:10.1101/391201</dc:identifier>
<dc:title><![CDATA[Deforming the metric of cognitive maps distorts memory]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/671958v1?rss=1">
<title>
<![CDATA[
Probabilistic representation in human visual cortex reflects uncertainty in serial decisions 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/671958v1?rss=1"
</link>
<description><![CDATA[
How does the brain represent the reliability of its sensory evidence? Here, we test whether sensory uncertainty is encoded in cortical population activity as the width of a probability distribution - a hypothesis that lies at the heart of Bayesian models of neural coding. We probe the neural representation of uncertainty by capitalizing on a well-known behavioral bias called serial dependence. Human observers of either sex reported the orientation of stimuli presented in sequence, while activity in visual cortex was measured with fMRI. We decoded probability distributions from population-level activity and found that serial dependence effects in behavior are consistent with a statistically advantageous sensory integration strategy, in which uncertain sensory information is given less weight. More fundamentally, our results suggest that probability distributions decoded from human visual cortex reflect the sensory uncertainty that observers rely on in their decisions, providing critical evidence for Bayesian theories of perception.
]]></description>
<dc:creator>van Bergen, R. S.</dc:creator>
<dc:creator>Jehee, J. F. M.</dc:creator>
<dc:date>2019-06-14</dc:date>
<dc:identifier>doi:10.1101/671958</dc:identifier>
<dc:title><![CDATA[Probabilistic representation in human visual cortex reflects uncertainty in serial decisions]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-06-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/671933v1?rss=1">
<title>
<![CDATA[
Dissociating activation and integration of discourse referents: evidence from ERPs and oscillations 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/671933v1?rss=1"
</link>
<description><![CDATA[
A key challenge in understanding stories and conversations is the comprehension of  anaphora, words that refer back to previously mentioned words or concepts ( antecedents). In psycholinguistic theories, anaphor comprehension involves the initial activation of the antecedent and its subsequent integration into the unfolding representation of the narrated event. A recent proposal suggests that these processes draw upon the brains recognition memory and language networks, respectively, and may be dissociable in patterns of neural oscillatory synchronization (Nieuwland & Martin, 2017). We addressed this proposal in an electroencephalogram (EEG) study with pre-registered data acquisition and analyses, using event-related potentials (ERPs) and neural oscillations. Dutch participants read two-sentence mini stories containing proper names, which were repeated or new (ease of activation) and coherent or incoherent with the preceding discourse (ease of integration). Repeated names elicited lower N400 and Late Positive Component amplitude than new names, and also an increase in theta-band (4-7 Hz) synchronization, which was largest around 240-450 ms after name onset. Discourse-coherent proper names elicited an increase in gamma-band (60-80 Hz) synchronization compared to discourse-incoherent names. This effect was largest around 690-1000 ms after name onset and was localized to the left frontal cortex. We argue that the initial activation and subsequent discourse-level integration of referents can be dissociated with event-related EEG activity, and are associated with respectively theta- and gamma-band activity. These findings further establish the link between memory and language through neural oscillations.
]]></description>
<dc:creator>Coopmans, C. W.</dc:creator>
<dc:creator>Nieuwland, M. S.</dc:creator>
<dc:date>2019-06-14</dc:date>
<dc:identifier>doi:10.1101/671933</dc:identifier>
<dc:title><![CDATA[Dissociating activation and integration of discourse referents: evidence from ERPs and oscillations]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-06-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/670489v1?rss=1">
<title>
<![CDATA[
Familiarity increases processing speed in the visual system 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/670489v1?rss=1"
</link>
<description><![CDATA[
Familiarity with a stimulus leads to an attenuated neural response to the stimulus. Alongside this attenuation, recent studies have also observed a truncation of stimulus-evoked activity for familiar visual input. One proposed function of this truncation is to rapidly put neurons in a state of readiness to respond to new input. Here, we examined this hypothesis by presenting human participants with target stimuli that were embedded in rapid streams of familiar or novel distractor stimuli at different speeds of presentation, while recording brain activity using magnetoencephalography (MEG) and measuring behavioral performance. We investigated the temporal and spatial dynamics of signal truncation and whether this phenomenon bears relationship to participants ability to categorize target items within a visual stream. Behaviorally, target categorization performance was markedly better when the target was embedded within familiar distractors, and this benefit became more pronounced with increasing speed of presentation. Familiar distractors showed a truncation of neural activity in the visual system, and this truncation was strongest for the fastest presentation speeds. Moreover, neural processing of the target was stronger when it was preceded by familiar distractors. Taken together, these findings suggest that truncation of neural responses for familiar items may result in stronger processing of relevant target information, resulting in superior perceptual performance.nnSignificance statementThe visual response to familiar input is attenuated more rapidly than for novel input. Here we find that this truncation of the neural response for familiar input is strongest for very fast image presentations. We also find a tentative function for this truncation: the neural response to a target image that is embedded within distractors is much greater when the distractors are familiar than when they are novel. Similarly, target categorization performance is much better when the target is embedded within familiar distractors, and this advantage is most obvious for very fast image presentations. This suggests that neural truncation helps to rapidly put neurons in a state of readiness to respond to new input.
]]></description>
<dc:creator>Manahova, M. E.</dc:creator>
<dc:creator>Spaak, E.</dc:creator>
<dc:creator>de Lange, F.</dc:creator>
<dc:date>2019-06-13</dc:date>
<dc:identifier>doi:10.1101/670489</dc:identifier>
<dc:title><![CDATA[Familiarity increases processing speed in the visual system]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-06-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/661678v1?rss=1">
<title>
<![CDATA[
Sensor localization using magnetic dipole-like coils: A method for highly accurate co-registration in on-scalp MEG 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/661678v1?rss=1"
</link>
<description><![CDATA[
Source modelling in magnetoencephalography (MEG) requires precise co-registration of the sensor array and the anatomical structure of the measured individuals head. In conventional MEG, positions and orientations of the sensors relative to each other are fixed and known beforehand, requiring only localization of the head relative to the sensor array. Since the sensors in on-scalp MEG are positioned on the scalp, locations of the individual sensors depend on the subjects head shape and size. The positions and orientations of on-scalp sensors must therefore be measured at every recording. This can be achieved by inverting conventional head localization, localizing the sensors relative to the head - rather than the other way around.nnIn this study we present a practical method for localizing sensors using magnetic dipole-like coils attached to the subjects head. We implement and evaluate the method in a set of on-scalp MEG recordings using a 7-channel on-scalp MEG system based on high critical temperature superconducting quantum interference devices (high-Tc SQUIDs). The method provides accurate estimates of individual sensor positions and orientations with short averaging time ([&le;] 2 mm and < 3 degrees, respectively, with 1-second averaging), enabling continuous sensor localization. Calibrating and jointly localizing the sensor array can further improve the localization accuracy (< 1 mm and < 2.5 degrees, respectively, with 1-second coil recordings).nnWe demonstrate source localization of on-scalp recorded somatosensory evoked activity based on co-registration with our method. Equivalent current dipole fits of the evoked responses corresponded well (within 5.3 mm) with those based on a commercial, whole-head MEG system.
]]></description>
<dc:creator>Pfeiffer, C.</dc:creator>
<dc:creator>Ruffieux, S.</dc:creator>
<dc:creator>Andersen, L. M.</dc:creator>
<dc:creator>Kalaboukhov, A.</dc:creator>
<dc:creator>Winkler, D.</dc:creator>
<dc:creator>Oostenveld, R.</dc:creator>
<dc:creator>Lundqvist, D.</dc:creator>
<dc:creator>Schneiderman, J. F.</dc:creator>
<dc:date>2019-06-06</dc:date>
<dc:identifier>doi:10.1101/661678</dc:identifier>
<dc:title><![CDATA[Sensor localization using magnetic dipole-like coils: A method for highly accurate co-registration in on-scalp MEG]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-06-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/661587v1?rss=1">
<title>
<![CDATA[
Molecular characterization of the stress network in the human brain 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/661587v1?rss=1"
</link>
<description><![CDATA[
The biological mechanisms underlying inter-individual differences in human stress reactivity remain poorly understood. We aimed to identify the molecular underpinning of neural stress sensitivity. Linking mRNA expression data from the Allen Human Brain Atlas to task-based fMRI revealed 201 differentially expressed genes in cortex-specific brain regions differentially activated by stress in individuals with low or high stress sensitivity. These genes are associated with stress-related psychiatric disorders (e.g. schizophrenia and anxiety) and include markers for specific neuronal populations (e.g. ADCYAP1, GABRB1, SSTR1, and TNFRSF12A), neurotransmitter receptors (e.g. GRIN3A, SSTR1, GABRB1, and HTR1E), and signaling factors that interact with the corticosteroid receptor and hypothalamic-pituitary-adrenal axis (e.g. ADCYAP1, IGSF11, and PKIA). Overall, the identified genes potentially underlie altered stress reactivity in individuals at risk for psychiatric disorders and play a role in mounting an adaptive stress response, making them potentially druggable targets for stress-related diseases.
]]></description>
<dc:creator>Meijer, M.</dc:creator>
<dc:creator>Keo, A.</dc:creator>
<dc:creator>van Leeuwen, J. M. C.</dc:creator>
<dc:creator>Dzyubachyk, O.</dc:creator>
<dc:creator>Meijer, O. C.</dc:creator>
<dc:creator>Vinkers, C. H.</dc:creator>
<dc:creator>Mahfouz, A.</dc:creator>
<dc:date>2019-06-06</dc:date>
<dc:identifier>doi:10.1101/661587</dc:identifier>
<dc:title><![CDATA[Molecular characterization of the stress network in the human brain]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-06-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/656348v1?rss=1">
<title>
<![CDATA[
The influence of transcranial magnetic stimulation of the medial prefrontal cortex on emotional memory schemas 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/656348v1?rss=1"
</link>
<description><![CDATA[
Memory bias for negative information is a critical characteristic of major depression, but the underlying neural mechanisms are largely unknown. The recently revived concept of memory schemas may shed new light on memory bias in depression: negative schemas might enhance the encoding and consolidation of negative experiences, thereby contributing to the genesis and perpetuation of depressive pathology. To investigate this relationship, we aimed to transiently perturb processing in the medial prefrontal cortex (mPFC), a core region involved in schema memory, using neuronavigated transcranial magnetic stimulation (TMS) targeting the mPFC. Forty healthy volunteers first underwent a negative mood induction to activate negative schema processing after which they received either active inhibitory (N = 20) or control (N = 20) stimulation to the mPFC. Then, all participants performed the encoding of an emotional false memory task. Recall and recognition performance was tested the following morning. Polysomnographic data was recorded continuously during the night before and after encoding. Secondary measures included sleep and mood questionnaires. We observed a significantly lower number of false recognition of negative critical lures following mPFC perturbation compared to the control group, whereas no differences in veridical memory performance were observed. These findings were supported by reaction time data. No relation between REM sleep and (false) emotional memory performance was observed. These findings support previous causal evidence for a role of the mPFC in schema memory processing and further suggest a role of the mPFC in memory bias.
]]></description>
<dc:creator>Bovy, L.</dc:creator>
<dc:creator>Berkers, R. M. W. J.</dc:creator>
<dc:creator>Pottkaemper, J.</dc:creator>
<dc:creator>Varatheeswaran, R.</dc:creator>
<dc:creator>Fernandez, G.</dc:creator>
<dc:creator>Tendolkar, I.</dc:creator>
<dc:creator>Dresler, M.</dc:creator>
<dc:date>2019-06-03</dc:date>
<dc:identifier>doi:10.1101/656348</dc:identifier>
<dc:title><![CDATA[The influence of transcranial magnetic stimulation of the medial prefrontal cortex on emotional memory schemas]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-06-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/653782v1?rss=1">
<title>
<![CDATA[
Statistical learning attenuates visual activity only for attended stimuli 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/653782v1?rss=1"
</link>
<description><![CDATA[
Perception and behavior can be guided by predictions, which are often based on learned statistical regularities. Neural responses to expected stimuli are frequently found to be attenuated after statistical learning. However, whether this sensory attenuation following statistical learning occurs automatically or depends on attention remains unknown. In the present fMRI study, we exposed human volunteers to sequentially presented object stimuli, in which the first object predicted the identity of the second object. We observed a strong attenuation of neural activity for expected compared to unexpected stimuli in the ventral visual stream. Crucially, this sensory attenuation was only apparent when stimuli were attended, and vanished when attention was directed away from the predictable objects. These results put important constraints on neurocomputational theories that cast perception as a process of probabilistic integration of prior knowledge and sensory information.
]]></description>
<dc:creator>Richter, D.</dc:creator>
<dc:creator>de Lange, F. P.</dc:creator>
<dc:date>2019-05-31</dc:date>
<dc:identifier>doi:10.1101/653782</dc:identifier>
<dc:title><![CDATA[Statistical learning attenuates visual activity only for attended stimuli]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-05-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/608034v1?rss=1">
<title>
<![CDATA[
Genetic overlap between obsessive-compulsive disorder, related symptoms in the population and insulin signaling: etiological implications 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/608034v1?rss=1"
</link>
<description><![CDATA[
ObjectiveObsessive-compulsive symptoms (OCS) in the population have been linked to obsessive-compulsive disorder (OCD) in genetic and epidemiological studies. Insulin signaling has been implicated in OCD. We extend previous work by assessing genetic overlap between OCD, population-based OCS, and central nervous system (CNS) and peripheral insulin signaling.nnMethodsWe conducted genome-wide association studies (GWASs) in the population-based Philadelphia Neurodevelopmental Cohort (PNC, 650 children and adolescents) of the total OCS score and six OCS factors from an exploratory factor analysis of 22 questions. Subsequently, we performed polygenic risk score (PRS) analysis to assess shared genetic etiologies between clinical OCD (using GWAS data from the Psychiatric Genomics Consortium), the total OCS score and OCS factors. We then performed gene-set analyses with a set of OCD-linked genes centered around CNS insulin-regulated synaptic function and PRS analyses for five peripheral insulin signaling-related traits. For validation purposes, we explored data from the independent Spit for Science population cohort (5047 children and adolescents).nnResultsIn the PNC, we found a shared genetic etiology between OCD and  impairment,  contamination/cleaning and  guilty taboo thoughts. In the Spit for Science cohort, we were able to validate the finding for  contamination/cleaning, and additionally observed genetic sharing between OCD and  symmetry/counting/ordering. The CNS insulin-linked gene-set associated with  symmetry/counting/ordering. We also identified genetic sharing between peripheral insulin signaling-related traits (type 2 diabetes and the blood levels of HbA1C, fasting insulin and 2 hour glucose) and OCD as well as certain OCS.nnConclusionsOCD, OCS in the population and insulin-related traits share genetic risk factors, indicating a common etiological mechanism underlying somatic and psychiatric disorders.
]]></description>
<dc:creator>Bralten, J.</dc:creator>
<dc:creator>Widomska, J.</dc:creator>
<dc:creator>De Witte, W.</dc:creator>
<dc:creator>Yu, D.</dc:creator>
<dc:creator>Mathews, C. A.</dc:creator>
<dc:creator>Scharf, J. M.</dc:creator>
<dc:creator>Buitelaar, J.</dc:creator>
<dc:creator>Crosbie, J.</dc:creator>
<dc:creator>Schachar, R.</dc:creator>
<dc:creator>Arnold, P.</dc:creator>
<dc:creator>Lemire, M.</dc:creator>
<dc:creator>Burton, C. L.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Poelmans, G.</dc:creator>
<dc:date>2019-04-13</dc:date>
<dc:identifier>doi:10.1101/608034</dc:identifier>
<dc:title><![CDATA[Genetic overlap between obsessive-compulsive disorder, related symptoms in the population and insulin signaling: etiological implications]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-04-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/562827v1?rss=1">
<title>
<![CDATA[
Transient perturbation of the left temporal cortex evokes plasticity-related reconfiguration of the lexical network 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/562827v1?rss=1"
</link>
<description><![CDATA[
Language impairment is common after left-hemisphere damage. However, the involvement of perilesional and homologous contralateral regions in compensating for left-sided lesions remains poorly understood. The aim of this study was to examine acute organizational changes in brain activity related to conceptual and lexical retrieval in unimpaired language production following transient disruption of the left middle temporal gyrus (MTG). In a randomized singleblind within-subject experiment, we recorded the electroencephalogram from sixteen healthy participants during a context-driven picture-naming task. Prior to the task, the left MTG was perturbed with real neuronavigated continuous theta-burst stimulation (cTBS) or sham stimulation. During the task, participants read lead-in sentences that created a constraining (e.g. "The farmer milks the") or non-constraining context (e.g. "The farmer buys the"). The last word was shown as a picture that participants had to name (e.g. "cow"). Replicating behavioral studies, participants were overall faster in naming pictures following a constraining relative to a non-constraining context, but this effect did not differ between real and sham cTBS. Real cTBS, however, increased overall error rates compared to sham cTBS. In line with previous studies, we observed a decrease in alpha-beta (8-24 Hz) oscillatory power for constraining relative to non-constraining contexts over left temporal-parietal cortex after participants received sham cTBS. However, following real cTBS, this decrease extended towards left prefrontal regions associated with both domain-general and domain-specific control mechanisms. Our findings provide evidence that immediately after the disruption of the left MTG, the lexical-semantic network is able to quickly reconfigure, also recruiting domain-general regions.
]]></description>
<dc:creator>Klaus, J.</dc:creator>
<dc:creator>Schutter, D. J. L. G.</dc:creator>
<dc:creator>Piai, V.</dc:creator>
<dc:date>2019-02-28</dc:date>
<dc:identifier>doi:10.1101/562827</dc:identifier>
<dc:title><![CDATA[Transient perturbation of the left temporal cortex evokes plasticity-related reconfiguration of the lexical network]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-02-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/651505v1?rss=1">
<title>
<![CDATA[
Action of cocaine involves depletion of dopaminergic and serotonergic storage vesicles 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/651505v1?rss=1"
</link>
<description><![CDATA[
Cocaine is known to increase the extracellular levels of dopamine (DA) and serotonin (5-HT) by inhibiting the neuronal reuptake of these monoamines. However, individuals with reduced monoamine reuptake transporter expression do not display a reduction in cocaine intake, suggesting that a mechanism other than inhibition of monoamine reuptake contributes to the rewarding and addictive effects of the psychostimulant. Here we report that cocaine depletes the dopaminergic and serotonergic storage vesicles of the rat nucleus accumbens. This cocaine-induced vesicle depletion gave rise to acute increases in the extracellular levels of DA and 5-HT, which in turn correlated with monoamine-type-specific changes in behavior. Both the neurochemical and behavioral responses to cocaine varied among individual animals, which was not due to individual differences in the reuptake of DA and 5-HT, but rather to individual differences in their vesicular release. Furthermore, we found that reserpine-induced depletion of storage vesicles reduced both short and long access cocaine self-administration, and the degree of reduction was linked to the vesicular storage capacity of the animals. In conclusion, we demonstrate a novel mechanism by which cocaine increases the extracellular concentrations of accumbal DA and 5-HT, namely via release from storage vesicles. Furthermore, individual differences in cocaine-induced vesicular monoamine release shape individual differences in not only the acute behavioral and neurochemical effects of the stimulant, but also in its intake. Thus, intracellular storage vesicles represent an attractive novel drug target to combat psychostimulant addiction.
]]></description>
<dc:creator>Homberg, J. R.</dc:creator>
<dc:creator>Karel, P.</dc:creator>
<dc:creator>Meyer, F.</dc:creator>
<dc:creator>Rink, K.</dc:creator>
<dc:creator>van Hulten, J. A.</dc:creator>
<dc:creator>van Bakel, N. H. M.</dc:creator>
<dc:creator>de Mulder, E. L. W.</dc:creator>
<dc:creator>Caffino, L.</dc:creator>
<dc:creator>Fumagalli, F.</dc:creator>
<dc:creator>Jansen, J.</dc:creator>
<dc:creator>Masereeuw, R.</dc:creator>
<dc:creator>Martens, G. J. M.</dc:creator>
<dc:creator>Cools, A. R.</dc:creator>
<dc:creator>Verheij, M. M. M.</dc:creator>
<dc:date>2019-05-27</dc:date>
<dc:identifier>doi:10.1101/651505</dc:identifier>
<dc:title><![CDATA[Action of cocaine involves depletion of dopaminergic and serotonergic storage vesicles]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-05-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/646703v1?rss=1">
<title>
<![CDATA[
Behaviour, biology, and evolution of vocal learning in bats 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/646703v1?rss=1"
</link>
<description><![CDATA[
The comparative approach can provide insight into the evolution of human speech, language, and social communication by studying relevant traits in animal systems. Bats are emerging as a model system with great potential to shed light on these processes given their learned vocalisations, close social interactions, and mammalian brains and physiology. A recent framework outlined the multiple levels of investigation needed to understand vocal learning across a broad range of non-human species including cetaceans, pinnipeds, elephants, birds and bats. Herein we apply this framework to the current state of the art in bat research. This encompasses our understanding of the abilities bats have displayed for vocal learning, what is known about the timing and social structure needed for such learning, and current knowledge about the prevalence of the trait across the order. It also addresses the biology (vocal tract morphology, neurobiology, and genetics) and phylogenetics of this trait. We conclude by highlighting some key questions that should be answered to advance our understanding of the biological encoding and evolution of speech and spoken communication.
]]></description>
<dc:creator>Vernes, S.</dc:creator>
<dc:creator>Wilkinson, G.</dc:creator>
<dc:date>2019-05-25</dc:date>
<dc:identifier>doi:10.1101/646703</dc:identifier>
<dc:title><![CDATA[Behaviour, biology, and evolution of vocal learning in bats]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-05-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/320515v1?rss=1">
<title>
<![CDATA[
Functional rerouting via the structural connectome is associated with better recovery after mild TBI 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/320515v1?rss=1"
</link>
<description><![CDATA[
Traumatic brain injury damages white matter pathways that connect brain regions, disrupting transmission of electrochemical signals and causing cognitive and emotional dysfunction. Connectome-level mechanisms for how the brain compensates for injury have not been fully characterized. Here, we collected serial MRI-based structural and functional connectome metrics and neuropsychological scores in 26 mild traumatic brain injury subjects (29.4{+/-}8.0 years, 20 male) at 1 and 6 months post-injury. We quantified the relationship between functional and structural connectomes using network diffusion model propagation time, a measure that can be interpreted as how much of the structural connectome is being utilized for the spread of functional activation, as captured via the functional connectome. Overall cognition showed significant improvement from 1 to 6 months (t25=-2.15, p=0.04). None of the structural or functional global connectome metrics were significantly different between 1 and 6 months, or when compared to 34 age- and gender-matched controls (28.6{+/-}8.8 years, 25 male). We predicted longitudinal changes in overall cognition from changes in global connectome measures using a partial least squares regression model (cross-validated R2 = 0.27). We observe that increased network diffusion model propagation time, increased structural connectome segregation and increased functional connectome integration were related to better cognitive recovery. We interpret these findings as suggesting two connectome-based post-injury recovery mechanisms: one of neuroplasticity that increases functional connectome integration and one of remote white matter degeneration that increases structural connectome segregation. We hypothesize that our inherently multi-modal measure of network diffusion model propagation time captures the interplay between these two mechanisms.nnAbbreviationsmild traumatic brain injury (mTBI), structural connectome (SC), functional connectome (FC), network diffusion (ND), functional MRI (fMRI), diffusion MRI (dMRI), principal component analysis (PCA), partial least squares regression (PLSR), confidence interval (CI), Attention Network Test (ANT), California Verbal Learning Test II (CVLT-II), Coma Recovery Scale - Revised (CRS-R)
]]></description>
<dc:creator>Kuceyeski, A.</dc:creator>
<dc:creator>Jamison, K. W.</dc:creator>
<dc:creator>Owen, J.</dc:creator>
<dc:creator>Raj, A.</dc:creator>
<dc:creator>Mukherjee, P.</dc:creator>
<dc:date>2018-05-18</dc:date>
<dc:identifier>doi:10.1101/320515</dc:identifier>
<dc:title><![CDATA[Functional rerouting via the structural connectome is associated with better recovery after mild TBI]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-05-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/473108v1?rss=1">
<title>
<![CDATA[
Real-time contextual feedback for close-loop control of navigation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/473108v1?rss=1"
</link>
<description><![CDATA[
ObjectiveClose-loop control of brain and behavior will benefit from real-time detection of behavioral events to enable low-latency communication with peripheral devices. In animal experiments, this is typically achieved by using sparsely distributed (embedded) sensors that detect animal presence in select regions of interest. High-speed cameras provide high-density sampling across large arenas, capturing the richness of animal behavior, however, the image processing bottleneck prohibits real-time feedback in the context of rapidly evolving behaviors.nnApproachHere we developed an open-source software, named PolyTouch, to track animal behavior in large arenas and provide rapid close-loop feedback in ~5.7 ms, ie. average latency from the detection of an event to analog stimulus delivery, e.g. auditory tone, TTL pulse, when tracking a single body. This stand-alone software is written in JAVA. The included wrapper for MATLAB provides experimental flexibility for data acquisition, analysis and visualization.nnMain resultsAs a proof-of-principle application we deployed the PolyTouch for place awareness training. A user-defined portion of the arena was used as a virtual target; visit (or approach) to the target triggered auditory feedback. We show that mice develop awareness to virtual spaces, tend to stay shorter and move faster when they reside in the virtual target zone if their visits are coupled to relatively high stimulus intensity ([&ge;]49dB). Thus, close-loop presentation of perceived aversive feedback is sufficient to condition mice to avoid virtual targets within the span of a single session (~20min).nnSignificanceNeuromodulation techniques now allow control of neural activity in a cell-type specific manner in spiking resolution. Using animal behavior to drive closed-loop control of neural activity would help to address the neural basis of behavioral state and environmental context-dependent information processing in the brain.
]]></description>
<dc:creator>Lim, J.</dc:creator>
<dc:creator>Celikel, T.</dc:creator>
<dc:date>2018-11-19</dc:date>
<dc:identifier>doi:10.1101/473108</dc:identifier>
<dc:title><![CDATA[Real-time contextual feedback for close-loop control of navigation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-11-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/399733v1?rss=1">
<title>
<![CDATA[
Frequency-specific brain dynamics related to prediction during language comprehension 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/399733v1?rss=1"
</link>
<description><![CDATA[
The brains remarkable capacity to process spoken language virtually in real time requires fast and efficient information processing machinery. In this study, we investigated how frequency-specific brain dynamics relate to models of probabilistic language prediction during auditory narrative comprehension. We recorded MEG activity while participants were listening to auditory stories in Dutch. Using trigram statistical language models, we estimated for every word in a story its conditional probability of occurrence. On the basis of word probabilities, we computed how unexpected the current word is given its context (word perplexity) and how (un)predictable the current linguistic context is (word entropy). We then evaluated whether source-reconstructed MEG oscillations at different frequency bands are modulated as a function of these language processing metrics. We show that theta-band source dynamics are increased in high relative to low entropy states, likely reflecting lexical computations. Beta-band dynamics are increased in situations of low word entropy and perplexity possibly reflecting maintenance of ongoing cognitive context. These findings lend support to the idea that the brain engages in the active generation and evaluation of predicted language based on the statistical properties of the input signal.
]]></description>
<dc:creator>Armeni, K.</dc:creator>
<dc:creator>Willems, R. M.</dc:creator>
<dc:creator>van den Bosch, A.</dc:creator>
<dc:creator>Schoffelen, J.-M.</dc:creator>
<dc:date>2018-08-25</dc:date>
<dc:identifier>doi:10.1101/399733</dc:identifier>
<dc:title><![CDATA[Frequency-specific brain dynamics related to prediction during language comprehension]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/532572v1?rss=1">
<title>
<![CDATA[
Experience-related alterations in white matter structure and gene expression in adult rats 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/532572v1?rss=1"
</link>
<description><![CDATA[
White matter (WM) plasticity during adulthood is a recently described phenomenon by which experience can shape brain structure. It has been observed in humans using diffusion tensor imaging (DTI). However, it remains unclear which mechanisms drive or underlie WM plasticity in adulthood. Here, we combined DTI and mRNA expression analysis and examined the effects of somatosensory experience in adult rats. Somatosensory experience resulted in differences in WM and grey matter structure. C-FOS mRNA expression, a marker of cortical activity, in the barrel cortex correlated with the structural WM measures, suggesting that WM plasticity is activity-dependent. Analysis of myelin-related genes revealed higher myelin basic protein expression in WM, while genome-wide RNA sequencing analysis identified 134 differentially-expressed genes regulating proteins involved in functions related to cell proliferation and differentiation, neuronal activity modulation and regulation of myelination. In conclusion, the macroscale measures of WM differences identified in response to somatosensory experience are supported by molecular evidence, which strongly suggest myelination as, at least, one of the underlying mechanisms.
]]></description>
<dc:creator>Sampaio-Baptista, C.</dc:creator>
<dc:creator>Valles, A.</dc:creator>
<dc:creator>Khrapitchev, A. A.</dc:creator>
<dc:creator>Akkermans, G.</dc:creator>
<dc:creator>Winkler, A.</dc:creator>
<dc:creator>Foxley, S.</dc:creator>
<dc:creator>Sibson, N. R.</dc:creator>
<dc:creator>Roberts, M.</dc:creator>
<dc:creator>Miller, K.</dc:creator>
<dc:creator>Diamond, M. E.</dc:creator>
<dc:creator>Martens, G. J. M.</dc:creator>
<dc:creator>De Weerd, P.</dc:creator>
<dc:creator>Johansen-Berg, H.</dc:creator>
<dc:date>2019-02-04</dc:date>
<dc:identifier>doi:10.1101/532572</dc:identifier>
<dc:title><![CDATA[Experience-related alterations in white matter structure and gene expression in adult rats]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-02-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/631929v1?rss=1">
<title>
<![CDATA[
Single-cell selectivity and functional architecture of human lateral occipital complex. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/631929v1?rss=1"
</link>
<description><![CDATA[
The human lateral occipital complex (LOC) is more strongly activated by images of objects compared to scrambled controls, but detailed information at the neuronal level is currently lacking. We recorded with microelectrode arrays in the LOC of two patients, and obtained highly selective single-unit, multi-unit and high-gamma responses to images of objects. Contrary to predictions derived from functional imaging studies, all neuronal properties indicated that the subsector of LOC we recorded from occupies an unexpectedly high position in the hierarchy of visual areas. Notably, the response latencies of LOC neurons were long, the shape selectivity was spatially clustered, LOC receptive fields were large and bilateral, and a number of LOC neurons exhibited 3D-structure selectivity (a preference for convex or concave stimuli), which are all properties typical of end-stage ventral stream areas. Thus, our results challenge prevailing ideas about the position of the LOC in the hierarchy of visual areas.
]]></description>
<dc:creator>Decramer, T.</dc:creator>
<dc:creator>Premereur, E.</dc:creator>
<dc:creator>Uytterhoeven, M.</dc:creator>
<dc:creator>Van Paesschen, W.</dc:creator>
<dc:creator>van Loon, J.</dc:creator>
<dc:creator>Janssen, P.</dc:creator>
<dc:creator>Theys, T.</dc:creator>
<dc:date>2019-05-08</dc:date>
<dc:identifier>doi:10.1101/631929</dc:identifier>
<dc:title><![CDATA[Single-cell selectivity and functional architecture of human lateral occipital complex.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-05-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/622381v1?rss=1">
<title>
<![CDATA[
Genetic effects on planum temporale asymmetry and their limited relevance to neurodevelopmental disorders, intelligence or educational attainment 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/622381v1?rss=1"
</link>
<description><![CDATA[
Previous studies have suggested that altered asymmetry of the planum temporale (PT) is associated with neurodevelopmental disorders, including dyslexia, schizophrenia, and autism. Shared genetic factors have been suggested to link PT asymmetry to these disorders. In a dataset of unrelated subjects from the general population (UK Biobank, N= 18,057), we found that PT volume asymmetry had a significant heritability of roughly 14%. In genome-wide association analysis, two loci were significantly associated with PT asymmetry, including a coding polymorphism within the gene ITIH5 that is predicted to affect the proteins function and to be deleterious (rs41298373, P=2.01x10-15), and a locus that affects the expression of the genes BOK and DTYMK (rs7420166, P=7.54x10-10). DTYMK showed left-right asymmetry of mRNA expression in post mortem PT tissue. Cortex-wide mapping of these SNP effects revealed influences on asymmetry that went somewhat beyond the PT. Using publicly available genome-wide association statistics from large-scale studies, we saw no significant genetic correlations of PT asymmetry with autism spectrum disorder, attention deficit hyperactivity disorder, schizophrenia, educational attainment or intelligence. Of the top two individual loci associated with PT asymmetry, rs41298373 showed a tentative association with intelligence (unadjusted P=0.025), while the locus at BOK/DTYMK showed tentative association with educational attainment (unadjusted Ps<0.05). These findings provide novel insights into the genetic contributions to human brain asymmetry, but do not support a substantial polygenic association of PT asymmetry with cognitive variation and mental disorders, as far as can be discerned with current sample sizes.
]]></description>
<dc:creator>Carrion-Castillo, A.</dc:creator>
<dc:creator>Pepe, A.</dc:creator>
<dc:creator>Xiangzhen, K.</dc:creator>
<dc:creator>Fisher, S. E.</dc:creator>
<dc:creator>Mazoyer, B.</dc:creator>
<dc:creator>Tzourio-Mazoyer, N.</dc:creator>
<dc:creator>Crivello, F.</dc:creator>
<dc:creator>Francks, C.</dc:creator>
<dc:date>2019-05-08</dc:date>
<dc:identifier>doi:10.1101/622381</dc:identifier>
<dc:title><![CDATA[Genetic effects on planum temporale asymmetry and their limited relevance to neurodevelopmental disorders, intelligence or educational attainment]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-05-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/440586v1?rss=1">
<title>
<![CDATA[
Dysregulated Oscillatory Connectivity in the Visual System in Autism Spectrum Disorder 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/440586v1?rss=1"
</link>
<description><![CDATA[
Autism Spectrum Disorder is increasingly associated with atypical perceptual and sensory symptoms. Here we explore the hypothesis that aberrant sensory processing in Autism Spectrum Disorder could be linked to atypical intra- (local) and inter-regional (global) brain connectivity. To elucidate oscillatory dynamics and connectivity in the visual domain we used magnetoencephalography and a simple visual grating paradigm with a group of 18 adolescent autistic participants and 18 typically developing controls. Both groups showed similar increases in gamma (40-80Hz) and decreases in alpha (8-13Hz) frequency power in occipital cortex. However, systematic group differences emerged when analysing intra- and inter-regional connectivity in detail. Firstly, directed connectivity was estimated using non-parametric Granger causality between visual areas V1 and V4. Feedforward V1-to-V4 connectivity, mediated by gamma oscillations, was equivalent between Autism Spectrum Disorder and control groups, but importantly, feedback V4-to-V1 connectivity, mediated by alpha (8-13Hz) oscillations, was significantly reduced in the Autism Spectrum Disorder group. This reduction was positively correlated with autistic quotient scores, consistent with an atypical visual hierarchy in autism, characterised by reduced top-down modulation of visual input via alpha-band oscillations. Secondly, at the local level in V1, coupling of alpha-phase to gamma amplitude (alpha-gamma phase amplitude coupling, PAC) was reduced in the Autism Spectrum Disorder group. This implies dysregulated local visual processing, with gamma oscillations decoupled from patterns of wider alpha-band phase synchrony (i.e. reduced PAC), possibly due to an excitation-inhibition imbalance. More generally, these results are in agreement with predictive coding accounts of neurotypical perception and indicate that visual processes in autism are less modulated by contextual feedback information.
]]></description>
<dc:creator>Seymour, R. A.</dc:creator>
<dc:creator>Rippon, G.</dc:creator>
<dc:creator>Gooding-Williams, G.</dc:creator>
<dc:creator>Schoffelen, J.-M.</dc:creator>
<dc:creator>Kessler, K.</dc:creator>
<dc:date>2018-10-10</dc:date>
<dc:identifier>doi:10.1101/440586</dc:identifier>
<dc:title><![CDATA[Dysregulated Oscillatory Connectivity in the Visual System in Autism Spectrum Disorder]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-10-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/619726v1?rss=1">
<title>
<![CDATA[
Selective Influence and Sequential Operations: A Research Strategy for Visual Search 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/619726v1?rss=1"
</link>
<description><![CDATA[
We introduce conceptually and empirically a powerful but underutilized experimental approach to dissect the cognitive processes supporting performance of a visual search task with factorial manipulations of singleton-distractor identifiability and stimulus-response cue discriminability. We show that systems factorial technology can distinguish processing architectures from the performance of macaque monkeys. This demonstration offers new opportunities to distinguish neural mechanisms through selective manipulation of visual encoding, search selection, rule encoding, and stimulus-response mapping.
]]></description>
<dc:creator>Lowe, K. A.</dc:creator>
<dc:creator>Reppert, T. R.</dc:creator>
<dc:creator>Schall, J.</dc:creator>
<dc:date>2019-04-26</dc:date>
<dc:identifier>doi:10.1101/619726</dc:identifier>
<dc:title><![CDATA[Selective Influence and Sequential Operations: A Research Strategy for Visual Search]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-04-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/404558v1?rss=1">
<title>
<![CDATA[
Planar cell polarity pathway and development of the human visual cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/404558v1?rss=1"
</link>
<description><![CDATA[
The radial unit hypothesis provides a framework for global (proliferation) and regional (distribution) expansion of the primate cerebral cortex. Using principal component analysis (PCA), we have identified cortical regions with shared variance in their surface area and cortical thickness, respectively, segmented from magnetic resonance images obtained in 23,800 participants. We then carried out meta-analyses of genome-wide association studies of the first two principal components for each phenotype. For surface area (but not cortical thickness), we have detected strong associations between each of the components and single nucleotide polymorphisms in a number of gene loci. The first (global) component was associated mainly with loci on chromosome 17 (9.5e-32 [&le;] p [&le;] 2.8e-10), including those detected previously as linked with intracranial volume and/or general cognitive function. The second (regional) component captured shared variation in the surface area of the primary and adjacent secondary visual cortices and showed a robust association with polymorphisms in a locus on chromosome 14 containing Disheveled Associated Activator of Morphogenesis 1 (DAAM1; p=2.4e-34). DAAM1 is a key component in the planar-cell-polarity signaling pathway. In follow-up studies, we have focused on the latter finding and established that: (1) DAAM1 is highly expressed between 12th and 22nd post-conception weeks in the human cerebral cortex; (2) genes co-expressed with DAAM1 in the primary visual cortex are enriched in mitochondria-related pathways; and (3) volume of the lateral geniculate nucleus, which projects to regions of the visual cortex staining for cytochrome oxidase (a mitochondrial enzyme), correlates with the surface area of the visual cortex in major-allele homozygotes but not in carriers of the minor allele. Altogether, we speculate that, in concert with thalamocortical input to cortical subplate, DAAM1 enables migration of neurons to cytochrome-oxidase rich regions of the visual cortex, and, in turn, facilitates regional expansion of this set of cortical regions during development.
]]></description>
<dc:creator>Shin, J.</dc:creator>
<dc:creator>Ma, S.</dc:creator>
<dc:creator>Hofer, E.</dc:creator>
<dc:creator>Patel, Y.</dc:creator>
<dc:creator>Roshchupkin, G.</dc:creator>
<dc:creator>Sousa, A. M.</dc:creator>
<dc:creator>Jian, X.</dc:creator>
<dc:creator>Gottesmann, R.</dc:creator>
<dc:creator>Mosley, T. H.</dc:creator>
<dc:creator>Fornage, M.</dc:creator>
<dc:creator>Saba, Y.</dc:creator>
<dc:creator>Pirpamer, L.</dc:creator>
<dc:creator>Schmidt, R.</dc:creator>
<dc:creator>Schmidt, H.</dc:creator>
<dc:creator>Mazoyer, B.</dc:creator>
<dc:creator>Carrion-Castillo, A.</dc:creator>
<dc:creator>Bis, J.</dc:creator>
<dc:creator>Li, S.</dc:creator>
<dc:creator>Yang, Q.</dc:creator>
<dc:creator>Luciano, M.</dc:creator>
<dc:creator>Karama, S.</dc:creator>
<dc:creator>Lewis, L.</dc:creator>
<dc:creator>Bastin, M.</dc:creator>
<dc:creator>Harris, M. A.</dc:creator>
<dc:creator>Deary, I.</dc:creator>
<dc:creator>Wardlaw, J. M.</dc:creator>
<dc:creator>Scholz, M.</dc:creator>
<dc:creator>Loeffler, M.</dc:creator>
<dc:creator>Witte, V.</dc:creator>
<dc:creator>Beyer, F.</dc:creator>
<dc:creator>Villringer, A.</dc:creator>
<dc:creator>Adams, H. H.</dc:creator>
<dc:creator>Ikrum, M. A.</dc:creator>
<dc:creator>Kremen, W. S.</dc:creator>
<dc:creator>Gillespie, N. A.</dc:creator>
<dc:creator>Sestan, N.</dc:creator>
<dc:creator>Pausova, Z.</dc:creator>
<dc:creator>Seshadri, S.</dc:creator>
<dc:creator>Paus, T.</dc:creator>
<dc:date>2018-08-31</dc:date>
<dc:identifier>doi:10.1101/404558</dc:identifier>
<dc:title><![CDATA[Planar cell polarity pathway and development of the human visual cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/379214v1?rss=1">
<title>
<![CDATA[
Explore or reset? Pupil diameter transiently increases in self-chosen switches between cognitive labor and leisure in either direction 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/379214v1?rss=1"
</link>
<description><![CDATA[
When people invest effort in cognitive work, they often keep an eye open for rewarding alternative activities. Previous research suggests that the norepinephrine (NE) system regulates such trade-offs between exploitation of the current task and exploration of alternative possibilities. Here we examine the possibility that the NE-system is involved in a related trade-off, i.e., the trade-off between cognitive labor and leisure. We conducted two pre-registered studies (total N = 62) in which participants freely chose to perform either a paid 2-back task (labor) vs. a non-paid task (leisure), while we tracked their pupil diameter--which is an indicator of the state of the NE system. In both studies, consistent with prior work, we found (a) increases in pupil baseline and (b) decreases in pupil dilation when participants switched from labor to leisure. Unexpectedly, we found the same pattern when participants switched from leisure back to labor. Both increases in pupil baseline and decreases in pupil dilation were short-lived. Collectively, these results are more consistent with a role of norepinephrine in reorienting attention and task switching, as suggested by network reset theory, than with a role in motivation, as suggested by adaptive gain theory.
]]></description>
<dc:creator>Algermissen, J.</dc:creator>
<dc:creator>Bijleveld, E.</dc:creator>
<dc:creator>Jostmann, N. B.</dc:creator>
<dc:creator>Holland, R. W.</dc:creator>
<dc:date>2018-07-30</dc:date>
<dc:identifier>doi:10.1101/379214</dc:identifier>
<dc:title><![CDATA[Explore or reset? Pupil diameter transiently increases in self-chosen switches between cognitive labor and leisure in either direction]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/517128v1?rss=1">
<title>
<![CDATA[
The effects of a TMS double lesion to a cortical network 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/517128v1?rss=1"
</link>
<description><![CDATA[
Transcranial magnetic stimulation (TMS) has contributed to our understanding of the functions of individual brain regions, but its use to examine distributed functions throughout a network has been more limited. We assess the functional consequences of a TMS pulse to the oculomotor network which was first perturbed by continuous theta-burst stimulation (cTBS), to examine the potential for additive effects from lesions to two network nodes. Twenty-three humans performed pro-(look towards) and anti-(look away) saccades after receiving cTBS to right frontal eye fields (FEF), dorsolateral prefrontal cortex (DLPFC) or somatosensory cortex (S1) (control). On a subset of trials, a TMS pulse was applied to right posterior parietal cortex (PPC). We assessed changes in saccade amplitudes, performance (percentage correct) and reaction times, as these parameters relate to computations in networks involving these nodes. We observed impairments in ipsilateral anti-saccade amplitudes following DLPFC cTBS that were enhanced by a PPC pulse, but that were not enhanced relative to the effect of the PPC pulse alone. There was no evidence for effects from the double lesion to performance or reaction times. This suggests that computations are distributed across the network, such that even a single lesion is consequential.
]]></description>
<dc:creator>Cameron, I.</dc:creator>
<dc:creator>Cretu, A.</dc:creator>
<dc:creator>Struik, F.</dc:creator>
<dc:creator>Toni, I.</dc:creator>
<dc:date>2019-01-10</dc:date>
<dc:identifier>doi:10.1101/517128</dc:identifier>
<dc:title><![CDATA[The effects of a TMS double lesion to a cortical network]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-01-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/443549v1?rss=1">
<title>
<![CDATA[
Genetic control of variability in subcortical and intracranial volumes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/443549v1?rss=1"
</link>
<description><![CDATA[
Sensitivity to external demands is essential for adaptation to dynamic environments, but comes at the cost of increased risk of adverse outcomes when facing poor environmental conditions. Here, we apply a novel methodology to perform genome-wide association analysis of mean and variance in nine key brain features (accumbens, amygdala, caudate, hippocampus, pallidum, putamen, thalamus, intracranial volume and cortical thickness), integrating genetic and neuroanatomical data from a large lifespan sample (n=25,575 individuals; 8 to 89 years, mean age 51.9 years). We identify genetic loci associated with phenotypic variability in cortical thickness, thalamus, pallidum, and intracranial volumes. The variance-controlling loci included genes with a documented role in brain and mental health and were not associated with the mean anatomical volumes. This proof-of-principle of the hypothesis of a genetic regulation of brain volume variability contributes to establishing the genetic basis of phenotypic variance (i.e., heritability), allows identifying different degrees of brain robustness across individuals, and opens new research avenues in the search for mechanisms controlling brain and mental health.
]]></description>
<dc:creator>Cordova-Palomera, A.</dc:creator>
<dc:creator>Meer, D. v. d.</dc:creator>
<dc:creator>Kaufmann, T.</dc:creator>
<dc:creator>Bettella, F.</dc:creator>
<dc:creator>Wang, Y.</dc:creator>
<dc:creator>Alnaes, D.</dc:creator>
<dc:creator>Doan, N. T.</dc:creator>
<dc:creator>Agartz, I.</dc:creator>
<dc:creator>Bertolino, A.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Coynel, D.</dc:creator>
<dc:creator>Djurovic, S.</dc:creator>
<dc:creator>Dorum, E. S.</dc:creator>
<dc:creator>Espeseth, T.</dc:creator>
<dc:creator>Fazio, L.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Frei, O.</dc:creator>
<dc:creator>Haberg, A.</dc:creator>
<dc:creator>Le Hellard, S.</dc:creator>
<dc:creator>Jonsson, E. G.</dc:creator>
<dc:creator>Kolskar, K. K.</dc:creator>
<dc:creator>Lund, M. J.</dc:creator>
<dc:creator>Moberget, T.</dc:creator>
<dc:creator>Nordvik, J. E.</dc:creator>
<dc:creator>Nyberg, L.</dc:creator>
<dc:creator>Papassotiropoulos, A.</dc:creator>
<dc:creator>Pergola, G.</dc:creator>
<dc:creator>de Quervain, D.</dc:creator>
<dc:creator>Rampino, A.</dc:creator>
<dc:creator>Richard, G.</dc:creator>
<dc:creator>Rokicki, J.</dc:creator>
<dc:creator>Sanders, A.-M.</dc:creator>
<dc:creator>Schwarz, E.</dc:creator>
<dc:creator>Smeland, O. B.</dc:creator>
<dc:creator>Steen, V. M.</dc:creator>
<dc:creator>Starrfelt, J.</dc:creator>
<dc:creator>Sonderby, I. E.</dc:creator>
<dc:creator>Ulrichsen, K. M.</dc:creator>
<dc:creator>Andreassen, O. A.</dc:creator>
<dc:creator>Westlye, L. T.</dc:creator>
<dc:date>2018-10-15</dc:date>
<dc:identifier>doi:10.1101/443549</dc:identifier>
<dc:title><![CDATA[Genetic control of variability in subcortical and intracranial volumes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-10-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/611129v1?rss=1">
<title>
<![CDATA[
Implicit learning and exploitation of regularities involve hippocampal and prefrontal theta activity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/611129v1?rss=1"
</link>
<description><![CDATA[
Observers rapidly and seemingly automatically learn to predict where to expect relevant items when those items are repeatedly presented in the same spatial context. This form of statistical learning in visual search has been studied extensively using a paradigm known as contextual cueing. The neural mechanisms underlying the learning and exploiting of such regularities remain unclear. We sought to elucidate these by examining behaviour and recording neural activity using magneto-encephalography (MEG) while observers were implicitly acquiring and exploiting statistical regularities. Computational modelling of behavioural data suggested that after repeated exposures to a spatial context, participants behaviour was marked by an abrupt switch to an exploitation strategy of the learnt regularities. MEG recordings showed that the initial learning phase was associated with larger hippocampal theta band activity for repeated scenes, while the subsequent exploitation phase showed larger prefrontal theta band activity for these repeated scenes. Strikingly, the behavioural benefit of repeated exposures to certain scenes was inversely related to explicit awareness of such repeats, demonstrating the implicit nature of the expectations acquired. This elucidates how theta activity in the hippocampus and prefrontal cortex underpins the implicit learning and exploitation of spatial statistical regularities to optimize visual search behaviour.
]]></description>
<dc:creator>Spaak, E.</dc:creator>
<dc:creator>de Lange, F. P.</dc:creator>
<dc:date>2019-04-17</dc:date>
<dc:identifier>doi:10.1101/611129</dc:identifier>
<dc:title><![CDATA[Implicit learning and exploitation of regularities involve hippocampal and prefrontal theta activity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-04-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/609586v1?rss=1">
<title>
<![CDATA[
Predicting cognitive and mental health traits and their polygenic architecture using large-scale brain connectomics 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/609586v1?rss=1"
</link>
<description><![CDATA[
Cognitive abilities and mental disorders are complex traits sharing a largely unknown neuronal basis and aetiology. Their genetic architectures are highly polygenic and overlapping, which is supported by heterogeneous phenotypic expression and substantial clinical overlap. Brain network analysis provides a non-invasive means of dissecting biological heterogeneity yet its sensitivity, specificity and validity in clinical applications remains a major challenge. We used machine learning on static and dynamic temporal synchronization between all brain network nodes in 10,343 healthy individuals from the UK Biobank to predict (i) cognitive and mental health traits and (ii) their genetic underpinnings. We predicted age and sex to serve as our reference point. The traits of interest included individual level educational attainment and fluid intelligence (cognitive) and dimensional measures of depression, anxiety, and neuroticism (mental health). We predicted polygenic scores for educational attainment, fluid intelligence, depression, anxiety, and different neuroticism traits, in addition to schizophrenia. Beyond high accuracy for age and sex, permutation tests revealed above chance-level prediction accuracy for educational attainment and fluid intelligence. Educational attainment and fluid intelligence were mainly negatively associated with static brain connectivity in frontal and default mode networks, whereas age showed positive correlations with a more widespread pattern. In comparison, prediction accuracy for polygenic scores was at chance level across traits, which may serve as a benchmark for future studies aiming to link genetic factors and fMRI-based brain connectomics.nnSignificanceAlthough cognitive abilities and susceptibility to mental disorders reflect individual differences in brain function, neuroimaging is yet to provide a coherent account of the neuronal underpinnings. Here, we aimed to map the brain functional connectome of (i) cognitive and mental health traits and (ii) their polygenic architecture in a large population-based sample. We discovered high prediction accuracy for age and sex, and above-chance accuracy for educational attainment and intelligence (cognitive). In contrast, accuracies for dimensional measures of depression, anxiety and neuroticism (mental health), and polygenic scores across traits, were at chance level. These findings support the link between cognitive abilities and brain connectomics and provide a reference for studies mapping the brain connectomics of mental disorders and their genetic architectures.
]]></description>
<dc:creator>Maglanoc, L. A.</dc:creator>
<dc:creator>Kaufmann, T.</dc:creator>
<dc:creator>van der Meer, D.</dc:creator>
<dc:creator>Marquand, A. F.</dc:creator>
<dc:creator>Wolfers, T.</dc:creator>
<dc:creator>Jonassen, R.</dc:creator>
<dc:creator>Hilland, E.</dc:creator>
<dc:creator>Andreassen, O. A.</dc:creator>
<dc:creator>Landro, N. I.</dc:creator>
<dc:creator>Westlye, L. T.</dc:creator>
<dc:date>2019-04-16</dc:date>
<dc:identifier>doi:10.1101/609586</dc:identifier>
<dc:title><![CDATA[Predicting cognitive and mental health traits and their polygenic architecture using large-scale brain connectomics]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-04-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/607770v1?rss=1">
<title>
<![CDATA[
Individual differences in the influence of mental imagery on conscious perception 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/607770v1?rss=1"
</link>
<description><![CDATA[
Mental imagery and visual perception rely on similar neural mechanisms, but the function of this overlap remains unclear. One idea is that imagery can influence perception. Previous research has shown that imagining a stimulus prior to binocular presentation of rivalling stimuli increases the chance of perceiving the imagined stimulus. In this study we investigated how this effect interacts with bottom-up sensory input by comparing psychometric response curves for congruent and incongruent imagery in humans. A Bayesian hierarchical model was used, allowing us to simultaneously study group-level effects as well as effects for individual participants. We found strong effects of both imagery as well as its interaction with sensory evidence within individual participants. However, the direction of these effects were highly variable between individuals, leading to weak effects at the group level. This highlights the heterogeneity of conscious perception and emphasizes the need for individualized investigation of such complex cognitive processes.
]]></description>
<dc:creator>Dijkstra, N.</dc:creator>
<dc:creator>Hinne, M.</dc:creator>
<dc:creator>Bosch, S. E.</dc:creator>
<dc:creator>van Gerven, M. A. J.</dc:creator>
<dc:date>2019-04-13</dc:date>
<dc:identifier>doi:10.1101/607770</dc:identifier>
<dc:title><![CDATA[Individual differences in the influence of mental imagery on conscious perception]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-04-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/285981v1?rss=1">
<title>
<![CDATA[
Integrative cross-species analyses identify deficits in habituation learning as a widely affected mechanism in Autism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/285981v1?rss=1"
</link>
<description><![CDATA[
BackgroundAlthough habituation is one of the most ancient and fundamental forms of learning, its regulators and relevance for human disease are poorly understood.nnMethodsWe manipulated the orthologs of 286 genes implicated in intellectual disability (ID) with or without comorbid autism spectrum disorder (ASD) specifically in Drosophila neurons, and tested these models in light-off jump habituation. We dissected neuronal substrates underlying the identified habituation deficits and integrated genotype-phenotype annotations, gene ontologies and interaction networks to determine the clinical features and molecular processes that are associated with habituation deficits.nnResultsWe identified more than 100 genes required for habituation learning. For the vast majority of these, 93 genes, a role in habituation learning was previously unknown. These genes characterize ID disorders with overgrowth/macrocephaly and comorbid ASD. Moreover, ASD individuals from the Simons Simplex Collection carrying disruptive de novo mutations in these genes exhibit increased rates of specific aberrant behaviors including stereotypic speech, hyperactivity and irritability. At the molecular level, ID genes required for normal habituation are enriched in synaptic function and converge on Ras-MAPK signaling. Both increased Ras-MAPK signaling in GABAergic and decreased Ras-MAPK signaling in cholinergic neurons specifically inhibit the adaptive habituation response.nnConclusionsOur work demonstrates the relevance of habituation learning to autism, identifies an unprecedented number of novel habituation players, supports an emerging role for inhibitory neurons in habituation and reveals an opposing, circuit-level-based mechanism for Ras-MAPK signaling. This establishes habituation as a possible, widely applicable target for pharmacologic intervention in ID/ASD.
]]></description>
<dc:creator>Fenckova, M.</dc:creator>
<dc:creator>Asztalos, L.</dc:creator>
<dc:creator>Cizek, P.</dc:creator>
<dc:creator>Singgih, E. L.</dc:creator>
<dc:creator>Blok, L. E. R.</dc:creator>
<dc:creator>Glennon, J. C.</dc:creator>
<dc:creator>IntHout, J.</dc:creator>
<dc:creator>Zweier, C.</dc:creator>
<dc:creator>Eichler, E. E.</dc:creator>
<dc:creator>Bernier, R.</dc:creator>
<dc:creator>Asztalos, Z.</dc:creator>
<dc:creator>Schenck, A.</dc:creator>
<dc:date>2018-03-20</dc:date>
<dc:identifier>doi:10.1101/285981</dc:identifier>
<dc:title><![CDATA[Integrative cross-species analyses identify deficits in habituation learning as a widely affected mechanism in Autism]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-03-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/587196v1?rss=1">
<title>
<![CDATA[
RICOPILI: Rapid Imputation for COnsortias PIpeLIne 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/587196v1?rss=1"
</link>
<description><![CDATA[
MotivationGenome-wide association study (GWAS) analyses, at sufficient sample sizes and power, have successfully revealed biological insights for several complex traits. RICOPILI, an open sourced Perl-based pipeline was developed to address the challenges of rapidly processing large scale multi-cohort GWAS studies including quality control, imputation and downstream analyses. The pipeline is computationally efficient with portability to a wide range of high-performance computing (HPC) environments.nnSummaryRICOPILI was created as the Psychiatric Genomics Consortium (PGC) pipeline for GWAS and has been adopted by other users. The pipeline features i) technical and genomic quality control in case-control and trio cohorts ii) genome-wide phasing and imputation iv) association analysis v) meta-analysis vi) polygenic risk scoring and vii) replication analysis. Notably, a major differentiator from other GWAS pipelines, RICOPILI leverages on automated parallelization and cluster job management approaches for rapid production of imputed genome-wide data. A comprehensive meta-analysis of simulated GWAS data has been incorporated demonstrating each step of the pipeline. This includes all of the associated visualization plots, to allow ease of data interpretation and manuscript preparation. Simulated GWAS datasets are also packaged with the pipeline for user training tutorials and developer work.nnAvailability and ImplementationRICOPILI has a flexible architecture to allow for ongoing development and incorporation of newer available algorithms and is adaptable to various HPC environments (QSUB, BSUB, SLURM and others). Specific links for genomic resources are either directly provided in this paper or via tutorials and external links. The central location hosting scripts and tutorials is found at this URL: https://sites.google.com/a/broadinstitute.org/RICOPILI/homennContactsripke@broadinstitute.orgnnSupplementary informationSupplementary data are available.
]]></description>
<dc:creator>Lam, M.</dc:creator>
<dc:creator>Awasthi, S.</dc:creator>
<dc:creator>Watson, H.</dc:creator>
<dc:creator>Goldstein, J.</dc:creator>
<dc:creator>Panagiotaropoulou, G.</dc:creator>
<dc:creator>Trubetskoy, V.</dc:creator>
<dc:creator>Karlsson, R.</dc:creator>
<dc:creator>Frei, O.</dc:creator>
<dc:creator>Fan, C.-C.</dc:creator>
<dc:creator>De Witte, W.</dc:creator>
<dc:creator>Mota, N. R.</dc:creator>
<dc:creator>Mullins, N.</dc:creator>
<dc:creator>Skarabis, N.</dc:creator>
<dc:creator>Huang, H.</dc:creator>
<dc:creator>Neale, B.</dc:creator>
<dc:creator>Daly, M.</dc:creator>
<dc:creator>Mattheissen, M.</dc:creator>
<dc:creator>Walters, R.</dc:creator>
<dc:creator>Ripke, S.</dc:creator>
<dc:date>2019-04-11</dc:date>
<dc:identifier>doi:10.1101/587196</dc:identifier>
<dc:title><![CDATA[RICOPILI: Rapid Imputation for COnsortias PIpeLIne]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-04-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/603530v1?rss=1">
<title>
<![CDATA[
Behavioral flexibility is associated with changes in structure and function distributed across a frontal cortical network in macaques 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/603530v1?rss=1"
</link>
<description><![CDATA[
One of the most influential accounts of central orbitofrontal cortex- that it mediates behavioral flexibility - has been challenged by the finding that discrimination reversal in macaques -the classic test of behavioral flexibility -is unaffected when lesions are made by excitotoxin injection rather than aspiration. This suggests the critical brain circuit mediating behavioral flexibility in reversal tasks lies beyond the central orbitofrontal cortex. To determine its identity a group of nine macaques were taught discrimination reversal learning tasks and its impact on grey matter was measured. Magnetic resonance imaging scans were taken before and after learning and compared with scans from two control groups each comprising ten animals. One control group learned similar discrimination tasks but which lacked any reversal component and the other control group engaged in no learning. Grey matter changes were prominent in posterior orbitofrontal cortex/anterior insula but also were found in three other frontal cortical regions: lateral orbitofrontal cortex (12o), cingulate cortex, and lateral prefrontal cortex. In a second analysis, neural activity in posterior orbitofrontal cortex/anterior insula was measured at rest and its pattern of coupling with the other frontal cortical regions was assessed. Activity coupling increased significantly in the reversal learning group in comparison to controls. In a final set of experiments we used similar structural imaging procedures and analyses to demonstrate that aspiration lesion of central orbitofrontal cortex, of the type known to affect discrimination learning, affected structure and activity in the same frontal cortical circuit. The results identify a distributed frontal cortical circuit associated with behavioral flexibility.
]]></description>
<dc:creator>Sallet, J.</dc:creator>
<dc:creator>Noonan, M.</dc:creator>
<dc:creator>Thomas, A.</dc:creator>
<dc:creator>O'Reilly, J. X.</dc:creator>
<dc:creator>Anderson, J.</dc:creator>
<dc:creator>Papageorgiou, G. K.</dc:creator>
<dc:creator>Neubert, F. X.</dc:creator>
<dc:creator>Ahmed, B.</dc:creator>
<dc:creator>Smith, J.</dc:creator>
<dc:creator>Bell, A.</dc:creator>
<dc:creator>Buckley, M.</dc:creator>
<dc:creator>Roumazeilles, L.</dc:creator>
<dc:creator>Cuell, S.</dc:creator>
<dc:creator>Walton, M.</dc:creator>
<dc:creator>Krug, K.</dc:creator>
<dc:creator>Mars, R.</dc:creator>
<dc:creator>Rushworth, M.</dc:creator>
<dc:date>2019-04-10</dc:date>
<dc:identifier>doi:10.1101/603530</dc:identifier>
<dc:title><![CDATA[Behavioral flexibility is associated with changes in structure and function distributed across a frontal cortical network in macaques]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-04-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/595777v1?rss=1">
<title>
<![CDATA[
Active head motion reduction in Magnetic Resonance Imaging using tactile feedback 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/595777v1?rss=1"
</link>
<description><![CDATA[
Head motion is a common problem in clinical as well as empirical (functional) Magnetic Resonance Imaging applications, as it can lead to severe artefacts that reduce image quality. The scanned individuals themselves, however, are often not aware of their head motion. The current study explored whether providing subjects with this information using tactile feedback would reduce their head motion and consequently improve image quality. In a single session that included six runs, 24 participants performed three different cognitive tasks: (1) passive viewing, (2) mental imagery, and (3) speeded responses. These tasks occurred in two different conditions: (a) with a strip of medical tape applied from one side of the MR head-coil, via the participants forehead, to the other side, and (b) without the medical tape being applied. Results revealed that application of medical tape to the forehead of subjects to provide tactile feedback significantly reduced both translational as well as rotational head motion. While this effect did not differ between the three cognitive tasks, there was a negative quadratic relationship between head motion with and without feedback. That is, the more head motion a subject produced without feedback, the stronger the motion reduction given the feedback. In conclusion, the here tested method provides a simple and cost-efficient way to reduce subjects head motion, and might be especially beneficial when extensive head motion is expected a priori.
]]></description>
<dc:creator>Krause, F.</dc:creator>
<dc:creator>Benjamins, C.</dc:creator>
<dc:creator>Eck, J.</dc:creator>
<dc:creator>Luehrs, M.</dc:creator>
<dc:creator>van Hoof, R.</dc:creator>
<dc:creator>Goebel, R.</dc:creator>
<dc:date>2019-04-09</dc:date>
<dc:identifier>doi:10.1101/595777</dc:identifier>
<dc:title><![CDATA[Active head motion reduction in Magnetic Resonance Imaging using tactile feedback]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-04-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/602276v1?rss=1">
<title>
<![CDATA[
D-Cycloserine as Adjunct to Brief Computerised CBT for Spider Fear: Effects on Fear, Behaviour, and Cognitive Biases 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/602276v1?rss=1"
</link>
<description><![CDATA[
In anxiety disorders, cognitive behavioural therapy (CBT) improves information-processing biases such as implicit fear evaluations and avoidance tendencies, which predicts treatment response, so they might constitute important treatment targets. This study investigated (i) whether information-processing biases changed following single-session computerised CBT for spider fear, and (ii) whether this effect could be augmented by administration of D-cycloserine (DCS). Spider-fearful individuals were randomized to receiving 250mg of DCS (n=21) or placebo (n=17) and spider fear was assessed using self-report, behavioural, and information-processing (Extrinsic Affective Simon Task & Approach Avoidance Task) measures. Linear mixed-effects analyses indicated improvements on self-report and behavioural spider fear following CBT, but not on cognitive bias measures. There was no evidence of an augmentation effect of DCS on any outcome. Cognitive biases at 1-day were not predictive of 1-month follow-up spider fear. These findings provide no evidence for information-processing biases relating to CBT response or augmentation with DCS.
]]></description>
<dc:creator>Kappelmann, N.</dc:creator>
<dc:creator>Suesse, M.</dc:creator>
<dc:creator>Schmiedgen, S.</dc:creator>
<dc:creator>Kaldewaij, R.</dc:creator>
<dc:creator>Browning, M.</dc:creator>
<dc:creator>Michael, T.</dc:creator>
<dc:creator>Rinck, M.</dc:creator>
<dc:creator>Reinecke, A.</dc:creator>
<dc:date>2019-04-08</dc:date>
<dc:identifier>doi:10.1101/602276</dc:identifier>
<dc:title><![CDATA[D-Cycloserine as Adjunct to Brief Computerised CBT for Spider Fear: Effects on Fear, Behaviour, and Cognitive Biases]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-04-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/462382v1?rss=1">
<title>
<![CDATA[
Aggression Subtypes Relate to Distinct Resting State Functional Connectivity in Disruptive Children and Adolescents 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/462382v1?rss=1"
</link>
<description><![CDATA[
ObjectiveThere is increasing evidence to suggest altered resting state functional connectivity (rsFC) in adolescents with conduct problems. However, no rsFC studies have addressed the effects of reactive and proactive aggression. Herein, we examined the associations between these aggression subtypes along with subdimensions of callous-unemotional (CU) traits and rsFC using predefined seeds in aggression-related salience network (SN) and default mode network (DMN).nnMethodAggression subtype-specific whole-brain rsFC of SN and DMN seeds was investigated in a resting state sequence (mean acquisition time = 8 min 25 sec) acquired from 207 children and adolescents of both sexes aged 8 - 18 years (mean age (SD) = 13.30 (2.60) years; range = 8.02 - 18.35) in a multi-center study. One hundred eighteen individuals exhibited disruptive behavior (conduct disorder/oppositional defiant disorder) with different levels of comorbid ADHD symptoms, 89 were healthy.nnResultsCompared to healthy controls, cases demonstrated reduced DMN and - after controlling for ADHD scores - SN seed-based rsFC with left hemispheric frontal clusters. We found increased and distinct aggression-subtype specific rsFC patterns in brain regions linked to processes like emotion, empathy, moral, cognitive control, and decision-making. Specifically, reactive and proactive aggression correlated with distinct SN and DMN seed-based rsFC patterns. CU dimensions led to different DMN and SN rsFC with clusters including frontal, parietal, and cingulate areas, with uncaring-related clusters extended to cerebellar regions.nnConclusionsThis first study investigating reactive and proactive aggression along with CU dimensions reveals new subtype-specific whole-brain rsFC patterns, extending the knowledge of neural networks to further distinct forms of disruptive behavior.
]]></description>
<dc:creator>Werhahn, J. E.</dc:creator>
<dc:creator>Mohl, S.</dc:creator>
<dc:creator>Willinger, D.</dc:creator>
<dc:creator>Smigielski, L.</dc:creator>
<dc:creator>Roth, A.</dc:creator>
<dc:creator>Naaijen, J.</dc:creator>
<dc:creator>Mulder, L. M.</dc:creator>
<dc:creator>Glennon, J. C.</dc:creator>
<dc:creator>Hoekstra, P. J.</dc:creator>
<dc:creator>Dietrich, A.</dc:creator>
<dc:creator>Kleine Deters, R.</dc:creator>
<dc:creator>Aggensteiner, P. M.</dc:creator>
<dc:creator>Holz, N. E.</dc:creator>
<dc:creator>Baumeister, S.</dc:creator>
<dc:creator>Banaschewski, T.</dc:creator>
<dc:creator>Saam, M. C.</dc:creator>
<dc:creator>Schulze, U. M. E.</dc:creator>
<dc:creator>Lythgoe, D. J.</dc:creator>
<dc:creator>Sethi, A.</dc:creator>
<dc:creator>Craig, M.</dc:creator>
<dc:creator>Mastroianni, M.</dc:creator>
<dc:creator>Sagar-Ouriaghli, I.</dc:creator>
<dc:creator>Santosh, P. J.</dc:creator>
<dc:creator>Rosa, M.</dc:creator>
<dc:creator>Bargallo, N.</dc:creator>
<dc:creator>Castro-Fornieles, J.</dc:creator>
<dc:creator>Aragno, C.</dc:creator>
<dc:creator>Penzol, M. J.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Zwiers, M. P.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Walitza, S.</dc:creator>
<dc:creator>Brandeis, D.</dc:creator>
<dc:date>2018-11-07</dc:date>
<dc:identifier>doi:10.1101/462382</dc:identifier>
<dc:title><![CDATA[Aggression Subtypes Relate to Distinct Resting State Functional Connectivity in Disruptive Children and Adolescents]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-11-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/598516v1?rss=1">
<title>
<![CDATA[
Auditory and semantic cues facilitate decoding of visual object category in MEG 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/598516v1?rss=1"
</link>
<description><![CDATA[
Sounds (e.g., barking) help us to visually identify objects (e.g., a dog) that are distant or ambiguous. While neuroimaging studies have revealed neuroanatomical sites of audiovisual interactions, little is known about the time-course by which sounds facilitate visual object processing. Here we used magnetoencephalography (MEG) to reveal the time-course of the facilitatory influence of natural sounds (e.g., barking) on visual object processing, and compared this to the facilitatory influence of spoken words (e.g., "dog"). Participants viewed images of blurred objects preceded by a task-irrelevant natural sound, a spoken word, or uninformative noise. A classifier was trained to discriminate multivariate sensor patterns evoked by animate and inanimate intact objects with no sounds, presented in a separate experiment, and tested on sensor patterns evoked by the blurred objects in the three auditory conditions. Results revealed that both sounds and words, relative to uninformative noise, significantly facilitated visual object category decoding between 300-500 ms after visual onset. We found no evidence for earlier facilitation by sounds than by words. These findings provide evidence for a semantic route of facilitation by both natural sounds and spoken words, whereby the auditory input first activates semantic object representations, which then modulate the visual processing of objects.
]]></description>
<dc:creator>Brandman, T.</dc:creator>
<dc:creator>Avancini, C.</dc:creator>
<dc:creator>Leticevscaia, O.</dc:creator>
<dc:creator>Peelen, M. V.</dc:creator>
<dc:date>2019-04-05</dc:date>
<dc:identifier>doi:10.1101/598516</dc:identifier>
<dc:title><![CDATA[Auditory and semantic cues facilitate decoding of visual object category in MEG]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-04-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/599548v1?rss=1">
<title>
<![CDATA[
Different Whole-Brain Functional Connectivity Correlates of Reactive-Proactive Aggression and Callous-Unemotional Traits in Disruptive Children and Adolescents 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/599548v1?rss=1"
</link>
<description><![CDATA[
BackgroundDisruptive behavior in children and adolescents can manifest itself in reactive (RA) and proactive (PA) aggression and is modulated by callous-unemotional (CU) traits and comorbidity. Research on aggression subtype-specific neural correlates is limited and the role of comorbid symptoms largely neglected.nnMethodsThe current multi-center study extended previous efforts by investigating unrestricted resting state functional connectivity (rsFC) alterations. The large sample (n = 207) of children and adolescents aged 8 - 18 years (mean age = 13.30 {+/-} 2.60 years) included 118 cases with disruptive behavior (80 diagnosed with Oppositional Defiant Disorder and/or Conduct Disorder) and 89 controls. Attention-deficit/hyperactivity disorder (ADHD) and anxiety symptoms were added as covariates. We measured changes in global and local voxel-to-voxel rsFC using functional magnetic resonance imaging at 3T (mean acquisition time = 8 min 25 sec).nnResultsCompared to controls, cases demonstrated altered rsFC including frontal areas when anxiety but not ADHD symptoms were considered. Within cases, RA and PA scores related to changes in global and local rsFC in central gyrus and precuneus previously linked to aggression-related impairments. CU trait severity correlated with global rsFC alterations including inferior and middle temporal gyrus implicated in empathy, emotion, and reward-related activity. Importantly, most observed aggression subtype-specific patterns could only be identified when ADHD and anxiety problems were also accounted for.nnConclusionsThe current study clarifies that distinct though overlapping brain connectivity measures can disentangle differing manifestations of aggressive behavior. Moreover, our results highlight the importance of considering comorbid symptoms for detecting aggression-related rsFC alterations.
]]></description>
<dc:creator>Werhahn, J. E.</dc:creator>
<dc:creator>Mohl, S.</dc:creator>
<dc:creator>Willinger, D.</dc:creator>
<dc:creator>Smigielski, L.</dc:creator>
<dc:creator>Roth, A.</dc:creator>
<dc:creator>Naaijen, J.</dc:creator>
<dc:creator>Mulder, L. M.</dc:creator>
<dc:creator>Glennon, J. C.</dc:creator>
<dc:creator>Hoekstra, P. J.</dc:creator>
<dc:creator>Dietrich, A.</dc:creator>
<dc:creator>Kleine Deters, R.</dc:creator>
<dc:creator>Aggensteiner, P. M.</dc:creator>
<dc:creator>Holze, N. E.</dc:creator>
<dc:creator>Baumeister, S.</dc:creator>
<dc:creator>Banaschewski, T.</dc:creator>
<dc:creator>Saam, M. C.</dc:creator>
<dc:creator>Schulze, U. M. E.</dc:creator>
<dc:creator>Lythgoe, D. J.</dc:creator>
<dc:creator>Sethi, A.</dc:creator>
<dc:creator>Craig, M.</dc:creator>
<dc:creator>Mastroianni, M.</dc:creator>
<dc:creator>Sagar-Ouriaghli, I.</dc:creator>
<dc:creator>Santosh, P. J.</dc:creator>
<dc:creator>Rosa, M.</dc:creator>
<dc:creator>Bargallo, N.</dc:creator>
<dc:creator>Castro-Fornieles, J.</dc:creator>
<dc:creator>Arango, C.</dc:creator>
<dc:creator>Penzol, M.</dc:creator>
<dc:creator>Zwiers, M. P.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Walitza, S.</dc:creator>
<dc:creator>Brandeis, D.</dc:creator>
<dc:date>2019-04-04</dc:date>
<dc:identifier>doi:10.1101/599548</dc:identifier>
<dc:title><![CDATA[Different Whole-Brain Functional Connectivity Correlates of Reactive-Proactive Aggression and Callous-Unemotional Traits in Disruptive Children and Adolescents]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-04-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/589614v1?rss=1">
<title>
<![CDATA[
Shared genetic background between children and adults with attention deficit/hyperactivity disorder 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/589614v1?rss=1"
</link>
<description><![CDATA[
Attention deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder characterized by age-inappropriate symptoms of inattention, impulsivity and hyperactivity that persist into adulthood in the majority of the diagnosed children. Despite several risk factors during childhood predicting the persistence of ADHD symptoms into adulthood, the genetic architecture underlying the trajectory of ADHD over time is still unclear. We set out to study the contribution of common genetic variants to the risk for ADHD across the lifespan by conducting meta-analyses of genome-wide association studies on persistent ADHD in adults and ADHD in childhood separately and comparing the genetic background between them in a total sample of 17,149 cases and 32,411 controls. Our results show nine new independent loci and support a shared contribution of common genetic variants to ADHD in children and adults. No subgroup heterogeneity was observed among children, while this group consists of future remitting and persistent individuals. We report similar patterns of genetic correlation of ADHD with other ADHD-related datasets and different traits and disorders among adults, children and when combining both groups. These findings confirm that persistent ADHD in adults is a neurodevelopmental disorder and extend the existing hypothesis of a shared genetic architecture underlying ADHD and different traits to a lifespan perspective.
]]></description>
<dc:creator>Rovira, P.</dc:creator>
<dc:creator>Demontis, D.</dc:creator>
<dc:creator>Sanchez-Mora, C.</dc:creator>
<dc:creator>Zayats, T.</dc:creator>
<dc:creator>Klein, M.</dc:creator>
<dc:creator>Roth Mota, N.</dc:creator>
<dc:creator>Weber, H.</dc:creator>
<dc:creator>Garcia-Martinez, I.</dc:creator>
<dc:creator>Pagerols, M.</dc:creator>
<dc:creator>Vilar, L.</dc:creator>
<dc:creator>Arribas, L.</dc:creator>
<dc:creator>Richarte, V.</dc:creator>
<dc:creator>Corrales, M.</dc:creator>
<dc:creator>Fadeuilhe, C.</dc:creator>
<dc:creator>Bosch, R.</dc:creator>
<dc:creator>Espanol Martin, G.</dc:creator>
<dc:creator>Almos, P.</dc:creator>
<dc:creator>Doyle, A. E.</dc:creator>
<dc:creator>Grevet, E. H.</dc:creator>
<dc:creator>Grimm, O.</dc:creator>
<dc:creator>Halmoy, A.</dc:creator>
<dc:creator>Hoogman, M.</dc:creator>
<dc:creator>Hutz, M.</dc:creator>
<dc:creator>Jacob, C. P.</dc:creator>
<dc:creator>Kittel-Schneider, S.</dc:creator>
<dc:creator>Knappskog, P. M.</dc:creator>
<dc:creator>Lundervold, A.</dc:creator>
<dc:creator>Rivero, O.</dc:creator>
<dc:creator>Rovaris, D. L.</dc:creator>
<dc:creator>Salatino-Oliveira, A.</dc:creator>
<dc:creator>Santos da Silva, B.</dc:creator>
<dc:creator>Svirin, E.</dc:creator>
<dc:creator>Sprooten, E.</dc:creator>
<dc:creator>Strekalova, T.</dc:creator>
<dc:creator>ADHD Working Group of the Psychiatric Genomics Con,</dc:creator>
<dc:creator>23andMe Research team,</dc:creator>
<dc:creator>Arias-Vasquez, A.</dc:creator>
<dc:creator>Sonu</dc:creator>
<dc:date>2019-03-28</dc:date>
<dc:identifier>doi:10.1101/589614</dc:identifier>
<dc:title><![CDATA[Shared genetic background between children and adults with attention deficit/hyperactivity disorder]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-03-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/596445v1?rss=1">
<title>
<![CDATA[
Dynamics of inhibitory control during bilingual speech production: An electrophysiological study 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/596445v1?rss=1"
</link>
<description><![CDATA[
Bilingual speakers have to control their languages to avoid interference, which may be achieved by enhancing the target language and/or inhibiting the nontarget language. Previous research has provided evidence that bilinguals may use inhibition (e.g., Jackson, Swainson, Cunnington, & Jackson, 2001), which is reflected in the N2 component of the event-related potential (ERP). In the current study, we investigated the dynamics of inhibitory control by measuring the N2 during language switching and repetition in picture naming. We recorded the EEG of 30 unbalanced Dutch-English bilinguals in a cued language-switching task. Participants had to name pictures in Dutch or English depending on the cue. A run of same-language trials could be short (two or three trials) or long (five or six trials). We assessed whether RTs and N2 changed over the course of same-language runs, and at a switch between languages. Results showed that speakers named pictures more quickly late as compared to early in a run of same-language trials. Moreover, they made a language switch more quickly after a long run than after a short run. In ERPs, we observed a widely distributed switch effect in the N2, which was larger after a short run than after a long run. The N2 was not modulated during a same-language run, challenging Kleinman and Gollan (2018), who maintained that inhibition accumulates over time. Our results suggests that speakers adjust the level of inhibitory control at a language switch, but not when repeatedly naming in the same language.
]]></description>
<dc:creator>Zheng, X.</dc:creator>
<dc:creator>Roelofs, A.</dc:creator>
<dc:creator>Erkan, H.</dc:creator>
<dc:creator>Lemhofer, K.</dc:creator>
<dc:date>2019-04-02</dc:date>
<dc:identifier>doi:10.1101/596445</dc:identifier>
<dc:title><![CDATA[Dynamics of inhibitory control during bilingual speech production: An electrophysiological study]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-04-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/593459v1?rss=1">
<title>
<![CDATA[
Modeling longitudinal imaging biomarkers with parametric Bayesian multi-task learning 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/593459v1?rss=1"
</link>
<description><![CDATA[
Longitudinal imaging biomarkers are invaluable for understanding the course of neurodegeneration, promising the ability to track disease progression and to detect disease earlier than cross-sectional biomarkers. To properly realize their potential, biomarker trajectory models must be robust to both under-sampling and measurement errors and should be able to integrate multi-modal information to improve trajectory inference and prediction. Here we present a parametric Bayesian multi-task learning based approach to modeling univariate trajectories across subjects that addresses these criteria.nnOur approach learns multiple subjects trajectories within a single model that allows for different types of information sharing, i.e. coupling, across subjects. It optimizes a combination of uncoupled, fully coupled and kernel coupled models. Kernel-based coupling allows linking subjects trajectories based on one or more biomarker measures. We demonstrate this using Alzheimers Disease Neuroimaging Initiative (ADNI) data, where we model longitudinal trajectories of MRI-derived cortical volumes in neurodegeneration, with coupling based on APOE genotype, cerebrospinal fluid (CSF) and amyloid PET-based biomarkers. In addition to detecting established disease effects, we detect disease related changes within the insula that have not received much attention within the literature.nnDue to its sensitivity in detecting disease effects, its competitive predictive performance and its ability to learn the optimal parameter covariance from data rather than choosing a specific set of random and fixed effects a priori, we propose that our model can be used in place of or in addition to linear mixed effects models when modeling biomarker trajectories. A software implementation of the method is publicly available.
]]></description>
<dc:creator>Aksman, L. M.</dc:creator>
<dc:creator>Scelsi, M. A.</dc:creator>
<dc:creator>Marquand, A. F.</dc:creator>
<dc:creator>Alexander, D. C.</dc:creator>
<dc:creator>Ourselin, S.</dc:creator>
<dc:creator>Altmann, A.</dc:creator>
<dc:date>2019-03-31</dc:date>
<dc:identifier>doi:10.1101/593459</dc:identifier>
<dc:title><![CDATA[Modeling longitudinal imaging biomarkers with parametric Bayesian multi-task learning]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-03-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/585836v1?rss=1">
<title>
<![CDATA[
Genome-wide association study of Parkinson's disease progression biomarkers in 12 longitudinal patients' cohorts 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/585836v1?rss=1"
</link>
<description><![CDATA[
BackgroundSeveral reports have identified different patterns of Parkinsons disease progression in individuals carrying missense variants in the GBA or LRRK2 genes. The overall contribution of genetic factors to the severity and progression of Parkinsons disease, however, has not been well studied.

ObjectivesTo test the association between genetic variants and the clinical features and progression of Parkinsons disease on a genome-wide scale.

MethodsWe accumulated individual data from 12 longitudinal cohorts in a total of 4,093 patients with 25,254 observations over a median of 3.81 years. Genome-wide associations were evaluated for 25 cross-sectional and longitudinal phenotypes. Specific variants of interest, including 90 recently-identified disease risk variants, were also investigated for the associations with these phenotypes.

ResultsTwo variants were genome-wide significant. Rs382940(T>A), within the intron of SLC44A1, was associated with reaching Hoehn and Yahr stage 3 or higher faster (HR 2.04 [1.58, 2.62], P-value = 3.46E-8). Rs61863020(G>A), an intergenic variant and eQTL for ADRA2A, was associated with a lower prevalence of insomnia at baseline (OR 0.63 [0,52, 0.75], P-value = 4.74E-8). In the targeted analysis, we found nine associations between known Parkinsons risk variants and more severe motor/cognitive symptoms. Also, we replicated previous reports of GBA coding variants (rs2230288: p.E365K, rs75548401: p.T408M) being associated with greater motor and cognitive decline over time, and APOE E4 tagging variant (rs429358) being associated with greater cognitive deficits in patients.

ConclusionsWe identified novel genetic factors associated with heterogeneity of progression in Parkinsons disease. The results provide new insights into the pathogenesis of Parkinsons disease as well as patient stratification for clinical trials.
]]></description>
<dc:creator>Iwaki, H.</dc:creator>
<dc:creator>Blauwendraat, C.</dc:creator>
<dc:creator>Leonard, H. L.</dc:creator>
<dc:creator>Kim, J. J.</dc:creator>
<dc:creator>Liu, G.</dc:creator>
<dc:creator>Maple-Grodem, J.</dc:creator>
<dc:creator>Corvol, J.-C.</dc:creator>
<dc:creator>Pihlstrom, L.</dc:creator>
<dc:creator>van Nimwegen, M.</dc:creator>
<dc:creator>Hutten, S. J.</dc:creator>
<dc:creator>Nguyen, K.-D. H.</dc:creator>
<dc:creator>Rick, J.</dc:creator>
<dc:creator>Eberly, S.</dc:creator>
<dc:creator>Faghri, F.</dc:creator>
<dc:creator>Auinger, P.</dc:creator>
<dc:creator>Scott, K. M.</dc:creator>
<dc:creator>Wijeyekoon, R.</dc:creator>
<dc:creator>Van Deerlin, V. M.</dc:creator>
<dc:creator>Hernandez, D.</dc:creator>
<dc:creator>Gibbs, J. R.</dc:creator>
<dc:creator>Chitrala, K. N.</dc:creator>
<dc:creator>Day-Williams, A. G.</dc:creator>
<dc:creator>Brice, A.</dc:creator>
<dc:creator>Alves, G.</dc:creator>
<dc:creator>Noyce, A. J.</dc:creator>
<dc:creator>Tysnes, O.-B.</dc:creator>
<dc:creator>Evans, J.</dc:creator>
<dc:creator>Breen, D. P.</dc:creator>
<dc:creator>Estrada, K.</dc:creator>
<dc:creator>Wegel, C. E.</dc:creator>
<dc:creator>Danjou, F.</dc:creator>
<dc:creator>Simon, D. K.</dc:creator>
<dc:creator>Andreassen, O. A.</dc:creator>
<dc:creator>Ravina, B.</dc:creator>
<dc:creator>Toft, M.</dc:creator>
<dc:creator>Heutink, P.</dc:creator>
<dc:creator>Bloem, B. R.</dc:creator>
<dc:creator>Weintraub, D.</dc:creator>
<dc:creator>Barker, R. A.</dc:creator>
<dc:creator>Williams-Gray, C. H.</dc:creator>
<dc:creator>van de Warrenburg, B.</dc:creator>
<dc:date>2019-03-25</dc:date>
<dc:identifier>doi:10.1101/585836</dc:identifier>
<dc:title><![CDATA[Genome-wide association study of Parkinson's disease progression biomarkers in 12 longitudinal patients' cohorts]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-03-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/584789v1?rss=1">
<title>
<![CDATA[
The role of feature-based attention in visual serial dependence 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/584789v1?rss=1"
</link>
<description><![CDATA[
Perceptual decisions about current sensory input are biased towards input of the recent past - a phenomenon termed serial dependence. Serial dependence may serve to stabilize neural representations in the face of external and internal noise. However, it is unclear under which circumstances previous input attracts subsequent perceptual decisions, and thus, whether serial dependence reflects a broad smoothing or selective stabilization operation. Here, we investigated whether focusing attention on particular features of the previous stimulus modulates serial dependence. We found an attractive bias in orientation estimations when previous and current stimuli had similar orientations, and a repulsive bias when they had dissimilar orientations. The attractive bias was markedly reduced when observers attended to the size, rather than the orientation, of the previous stimulus. Conversely, the repulsive bias for stimuli with large orientation differences was not modulated by feature-based attention. This suggests separate sources of these positive and negative perceptual biases.
]]></description>
<dc:creator>Fritsche, M.</dc:creator>
<dc:creator>de Lange, F. P.</dc:creator>
<dc:date>2019-03-21</dc:date>
<dc:identifier>doi:10.1101/584789</dc:identifier>
<dc:title><![CDATA[The role of feature-based attention in visual serial dependence]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-03-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/585596v1?rss=1">
<title>
<![CDATA[
Neuronal network dysfunction in a human model for Kleefstra syndrome mediated by enhanced NMDAR signaling 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/585596v1?rss=1"
</link>
<description><![CDATA[
Epigenetic regulation of gene transcription plays a critical role in neural network development and in the etiology of Intellectual Disability (ID) and Autism Spectrum Disorder (ASD). However, little is known about the mechanisms by which epigenetic dysregulation leads to neural network defects. Kleefstra syndrome (KS), caused by mutation in the histone methyltransferase EHMT1, is a neurodevelopmental disorder with the clinical features of both ID and ASD. To study the impact of decreased EHMT1 function in human cells, we generated excitatory cortical neurons from induced pluripotent stem (iPS) cells derived from KS patients. In addition, we created an isogenic set by genetically editing healthy iPS cells. Characterization of the neurons at the single-cell and neuronal network level revealed consistent discriminative properties that distinguished EHMT1-mutant from wildtype neurons. Mutant neuronal networks exhibited network bursting with a reduced rate, longer duration, and increased temporal irregularity compared to control networks. We show that these changes were mediated by the upregulation of the NMDA receptor (NMDAR) subunit 1 and correlate with reduced deposition of the repressive H3K9me2 mark, the catalytic product of EHMT1, at the GRIN1 promoter. Furthermore, we show that EHMT1 deficiency in mice leads to similar neuronal network impairments and increased NMDAR function. Finally, we could rescue the KS patient-derived neuronal network phenotypes by pharmacological inhibition of NMDARs. Together, our results demonstrate a direct link between EHMT1 deficiency in human neurons and NMDAR hyperfunction, providing the basis for a more targeted therapeutic approach to treating KS.
]]></description>
<dc:creator>Frega, M.</dc:creator>
<dc:creator>Linda, K.</dc:creator>
<dc:creator>Keller, J. M.</dc:creator>
<dc:creator>Gumus-Akay, G.</dc:creator>
<dc:creator>Mossink, B.</dc:creator>
<dc:creator>van Rhijn, J.-R.</dc:creator>
<dc:creator>Negwer, M.</dc:creator>
<dc:creator>Klein Gunnewiek, T.</dc:creator>
<dc:creator>Foreman, K.</dc:creator>
<dc:creator>Kompier, N.</dc:creator>
<dc:creator>Schoenmaker, C.</dc:creator>
<dc:creator>van den Akker, W.</dc:creator>
<dc:creator>Oudakker, A.</dc:creator>
<dc:creator>Zhou, H.</dc:creator>
<dc:creator>Kleefstra, T.</dc:creator>
<dc:creator>Schubert, D.</dc:creator>
<dc:creator>van Bokhoven, H.</dc:creator>
<dc:creator>Nadif Kasri, N.</dc:creator>
<dc:date>2019-03-21</dc:date>
<dc:identifier>doi:10.1101/585596</dc:identifier>
<dc:title><![CDATA[Neuronal network dysfunction in a human model for Kleefstra syndrome mediated by enhanced NMDAR signaling]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-03-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/461558v1?rss=1">
<title>
<![CDATA[
Multiple mechanisms link prestimulus neural oscillations to sensory responses 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/461558v1?rss=1"
</link>
<description><![CDATA[
Spontaneous fluctuations of neural activity may explain why sensory responses vary across repeated presentation of the same physical stimulus. To test this hypothesis, we recorded electroencephalography in humans during stimulation with identical visual stimuli and analyzed how prestimulus neural oscillations modulate different stages of sensory processing reflected by distinct components of the event-related potential (ERP). We found that strong prestimulus alpha- and beta-band power resulted in a suppression of early ERP components (C1 and N150) and in an amplification of late components (after 0.4 s). Whereas functional inhibition of sensory processing underlies the reduction of early ERP responses, we found that the modulation of non-zero-mean oscillations (baseline shift) accounted for the amplification of late responses. Distinguishing between these two mechanisms is crucial for the understanding of how internal brain states modulate the processing of incoming sensory information.
]]></description>
<dc:creator>Iemi, L.</dc:creator>
<dc:creator>Busch, N. A.</dc:creator>
<dc:creator>Laudini, A.</dc:creator>
<dc:creator>Samaha, J.</dc:creator>
<dc:creator>Villringer, A.</dc:creator>
<dc:creator>Nikulin, V. V.</dc:creator>
<dc:date>2018-11-04</dc:date>
<dc:identifier>doi:10.1101/461558</dc:identifier>
<dc:title><![CDATA[Multiple mechanisms link prestimulus neural oscillations to sensory responses]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-11-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/585182v1?rss=1">
<title>
<![CDATA[
The principle of inverse effectiveness in audiovisual speech perception 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/585182v1?rss=1"
</link>
<description><![CDATA[
We assessed how synchronous speech listening and lip reading affects speech recognition in acoustic noise. In simple audiovisual perceptual tasks, inverse effectiveness is often observed, which holds that the weaker the unimodal stimuli, or the poorer their signal-to-noise ratio, the stronger the audiovisual benefit. So far, however, inverse effectiveness has not been demonstrated for complex audiovisual speech stimuli. Here we assess whether this multisensory integration effect can also be observed for the recognizability of spoken words.nnTo that end, we presented audiovisual sentences to 18 native-Dutch normal-hearing participants, who had to identify the spoken words from a finite list. Speech-recognition performance was determined for auditory-only, visual-only (lipreading) and auditory-visual conditions. To modulate acoustic task difficulty, we systematically varied the auditory signal-to-noise ratio. In line with a commonly-observed multisensory enhancement on speech recognition, audiovisual words were more easily recognized than auditory-only words (recognition thresholds of -15 dB and -12 dB, respectively).nnWe here show that the difficulty of recognizing a particular word, either acoustically or visually, determines the occurrence of inverse effectiveness in audiovisual word integration. Thus, words that are better heard or recognized through lipreading, benefit less from bimodal presentation.nnAudiovisual performance at the lowest acoustic signal-to-noise ratios (45%) fell below the visual recognition rates (60%), reflecting an actual deterioration of lipreading in the presence of excessive acoustic noise. This suggests that the brain may adopt a strategy in which attention has to be divided between listening and lip reading.
]]></description>
<dc:creator>van Wanrooij, M. M.</dc:creator>
<dc:creator>van de Rijt, L. P. H.</dc:creator>
<dc:creator>Roye, A.</dc:creator>
<dc:creator>Mylanus, E. A. M.</dc:creator>
<dc:creator>van Opstal, A. J.</dc:creator>
<dc:date>2019-03-21</dc:date>
<dc:identifier>doi:10.1101/585182</dc:identifier>
<dc:title><![CDATA[The principle of inverse effectiveness in audiovisual speech perception]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-03-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/561811v1?rss=1">
<title>
<![CDATA[
Two fiber pathways connecting amygdala and prefrontal cortex in humans and monkeys 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/561811v1?rss=1"
</link>
<description><![CDATA[
The interactions between amygdala and prefrontal cortex are pivotal to many neural processes involved in learning, decision-making, emotion, and social regulation. The broad functional role of amygdala-prefrontal interplay may reflect the diversity of its anatomical connections. Little, however, is known of the structural wiring linking amygdala and prefrontal cortex in humans. Using diffusion imaging techniques, we reconstructed connections between amygdala, anterior temporal and prefrontal cortex in human and macaque brains. First, by studying macaques we were able to assess which aspects of connectivity known from tracer studies could be identified with diffusion imaging. Second, by comparing diffusion imaging results in humans and macaques we were able to estimate amygdala-prefrontal connection patterns in humans and compare them with those in the monkey. We observed a prominent and well-preserved bifurcation of connections between amygdala and frontal lobe into two fiber networks - an amygdalofugal path and an uncinate fascicle path - in both species.
]]></description>
<dc:creator>Folloni, D.</dc:creator>
<dc:creator>Sallet, J.</dc:creator>
<dc:creator>Khrapichev, A. A.</dc:creator>
<dc:creator>Sibson, N. R.</dc:creator>
<dc:creator>Verhagen, L.</dc:creator>
<dc:creator>Mars, R. B.</dc:creator>
<dc:date>2019-03-20</dc:date>
<dc:identifier>doi:10.1101/561811</dc:identifier>
<dc:title><![CDATA[Two fiber pathways connecting amygdala and prefrontal cortex in humans and monkeys]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-03-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/576769v1?rss=1">
<title>
<![CDATA[
Supramodal sentence processing in the human brain: fMRI evidence for the influence of syntactic complexity in more than 200 participants 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/576769v1?rss=1"
</link>
<description><![CDATA[
This study investigated two questions. One is to which degree sentence processing beyond single words is independent of the input modality (speech vs. reading). The second question is which parts of the network recruited by both modalities is sensitive to syntactic complexity. These questions were investigated by having more than 200 participants read or listen to well-formed sentences or series of unconnected words. A largely left-hemisphere fronto-temporoparietal network was found to be supramodal in nature, i.e. independent of input modality. In addition, the left inferior frontal gyrus (LIFG) and the left posterior middle temporal gyrus (LpMTG) were most clearly associated with left-branching complexity. The left anterior middle temporal gyrus (LaMTG) showed the greatest sensitivity to sentences that differed in right-branching complexity. Moreover, activity in LIFG and LpMTG increased from sentence onset to end, in parallel with an increase of the left-branching complexity. While LIFG, bilateral anterior and posterior MTG and left inferior parietal lobe (LIPL) all contribute to the supramodal unification processes, the results suggest that these regions differ in their respective contributions to syntactic complexity related processing. The consequences of these findings for neurobiological models of language processing are discussed.
]]></description>
<dc:creator>Udden, J.</dc:creator>
<dc:creator>Hulten, A.</dc:creator>
<dc:creator>Schoffelen, J. M.</dc:creator>
<dc:creator>Lam, N.</dc:creator>
<dc:creator>Harbusch, K.</dc:creator>
<dc:creator>van den Bosch, A.</dc:creator>
<dc:creator>Kempen, G.</dc:creator>
<dc:creator>Petersson, K. M.</dc:creator>
<dc:creator>Hagoort, P.</dc:creator>
<dc:date>2019-03-14</dc:date>
<dc:identifier>doi:10.1101/576769</dc:identifier>
<dc:title><![CDATA[Supramodal sentence processing in the human brain: fMRI evidence for the influence of syntactic complexity in more than 200 participants]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-03-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/570655v1?rss=1">
<title>
<![CDATA[
Altered structural brain asymmetry in autism spectrum disorder: large-scale analysis via the ENIGMA Consortium 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/570655v1?rss=1"
</link>
<description><![CDATA[
BackgroundLeft-right asymmetry is an important organizing feature of the healthy brain. Various studies have reported altered structural brain asymmetry in autism spectrum disorder (ASD). However, findings have been inconsistent, likely due to limited sample sizes and low statistical power.nnMethodsWe investigated 1,774 subjects with ASD and 1,809 controls, from 54 datasets, for differences in the asymmetry of thickness and surface area of 34 cerebral cortical regions. We also examined global hemispheric measures of cortical thickness and area asymmetry, and volumetric asymmetries of subcortical structures. Data were obtained via the ASD Working Group of the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium. T1-weighted MRI data were processed with a single protocol using FreeSurfer and the Desikan-Killiany atlas.nnResultsASD was significantly associated with reduced leftward asymmetry of total hemispheric average cortical thickness, compared to controls. Eight regional thickness asymmetries, distributed over the cortex, also showed significant associations with diagnosis after correction for multiple comparisons, for which asymmetry was again generally lower in ASD versus controls. In addition, the medial orbitofrontal surface area was less rightward asymmetric in ASD than controls, and the putamen volume was more leftward asymmetric in ASD than controls. The largest effect size had Cohens d = 0.15. Most effects did not depend on age, sex, IQ, or disorder severity.nnConclusionAltered lateralized neurodevelopment is suggested in ASD, affecting widespread cortical regions with diverse functions. Large-scale analysis was necessary to reliably detect, and accurately describe, subtle alterations of structural brain asymmetry in this disorder.
]]></description>
<dc:creator>Postema, M. C.</dc:creator>
<dc:creator>van Rooij, D.</dc:creator>
<dc:creator>Anagnostou, E.</dc:creator>
<dc:creator>Arango, C.</dc:creator>
<dc:creator>Auzias, G.</dc:creator>
<dc:creator>Behrmann, M.</dc:creator>
<dc:creator>Filho, G. B.</dc:creator>
<dc:creator>Calderoni, S.</dc:creator>
<dc:creator>Calvo, R.</dc:creator>
<dc:creator>Daly, E.</dc:creator>
<dc:creator>Deruelle, C.</dc:creator>
<dc:creator>Di Martino, A.</dc:creator>
<dc:creator>Dinstein, I.</dc:creator>
<dc:creator>Duran, F. L. S.</dc:creator>
<dc:creator>Durston, S.</dc:creator>
<dc:creator>Ecker, C.</dc:creator>
<dc:creator>Ehrlich, S.</dc:creator>
<dc:creator>Fair, D.</dc:creator>
<dc:creator>Fedor, J.</dc:creator>
<dc:creator>Feng, X.</dc:creator>
<dc:creator>Fitzgerald, J.</dc:creator>
<dc:creator>Floris, D. L.</dc:creator>
<dc:creator>Freitag, C. M.</dc:creator>
<dc:creator>Gallagher, L.</dc:creator>
<dc:creator>Glahn, D. C.</dc:creator>
<dc:creator>Gori, I.</dc:creator>
<dc:creator>Haar, S.</dc:creator>
<dc:creator>Hoekstra, L.</dc:creator>
<dc:creator>Jahansad, N.</dc:creator>
<dc:creator>Jalbrzikowski, M.</dc:creator>
<dc:creator>Janssen, J.</dc:creator>
<dc:creator>King, J. A.</dc:creator>
<dc:creator>Zaro, L. L.</dc:creator>
<dc:creator>Lerch, J. P.</dc:creator>
<dc:creator>Luna, B.</dc:creator>
<dc:creator>Martinho, M. M.</dc:creator>
<dc:creator>McGrath, J.</dc:creator>
<dc:creator>Medland, S. E.</dc:creator>
<dc:creator>Muratori, F.</dc:creator>
<dc:creator>Murphy, C. M.</dc:creator>
<dc:creator>Murphy, D. G. M.</dc:creator>
<dc:creator>O'Hearn, K.</dc:creator>
<dc:creator>Oranje, B.</dc:creator>
<dc:creator>Parellada,</dc:creator>
<dc:date>2019-03-09</dc:date>
<dc:identifier>doi:10.1101/570655</dc:identifier>
<dc:title><![CDATA[Altered structural brain asymmetry in autism spectrum disorder: large-scale analysis via the ENIGMA Consortium]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-03-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/563783v1?rss=1">
<title>
<![CDATA[
Definitely saw it coming? An ERP study on the role of article gender and definiteness in predictive processing 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/563783v1?rss=1"
</link>
<description><![CDATA[
People sometimes anticipate specific words during language comprehension. Consistent with word anticipation, pre-nominal articles elicit differential neural activity when they mismatch the gender of a predictable noun compared with when they match. However, the functional significance of this pre-nominal effect is unclear: Do people only predict the noun or do they predict the entire article-noun combination? We addressed this question in an event-related potential study (N=48) with pre-registered data acquisition and analyses, capitalizing on gender-marking on Dutch definite articles and the lack thereof on indefinite articles. Participants read mini-story contexts that strongly suggested either a definite or indefinite noun phrase (e.g.,  het/een boek, the/a book) as its best continuation, followed by a definite noun phrase with the expected noun or an unexpected, different gender noun ( het boek/de roman, the book/the novel). We observed an enhanced negativity (N400) for articles that were unexpectedly definite or mismatched the expected gender, with the former effect being strongest. Pre-registered analyses and exploratory Bayesian analyses did not yield convincing evidence that the effect of gender-mismatch depended on expected definiteness. While prediction of article form cannot be excluded, it may not be required to elicit pre-nominal effects.
]]></description>
<dc:creator>Fleur, D.</dc:creator>
<dc:creator>Flecken, M.</dc:creator>
<dc:creator>Rommers, J.</dc:creator>
<dc:creator>Nieuwland, M.</dc:creator>
<dc:date>2019-02-28</dc:date>
<dc:identifier>doi:10.1101/563783</dc:identifier>
<dc:title><![CDATA[Definitely saw it coming? An ERP study on the role of article gender and definiteness in predictive processing]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-02-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/563809v1?rss=1">
<title>
<![CDATA[
Joint modelling of diffusion MRI and microscopy 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/563809v1?rss=1"
</link>
<description><![CDATA[
The combination of diffusion MRI with microscopy provides unique opportunities to study microstructural features of tissue, particularly when acquired in the same sample. Microscopy is frequently used to validate diffusion MRI microstructure models, addressing the indirect nature of dMRI signals. Typically, these modalities are analysed separately, and microscopy is taken as a gold standard against which dMRI-derived parameters are validated. Here we propose an alternative approach in which we combine diffusion MRI and microscopy data obtained from the same tissue sample to drive a single, joint model. This simultaneous analysis allows us to take advantage of the breadth of information provided by complementary data acquired from different modalities. By applying this framework to a spherical-deconvolution analysis, we are able to overcome a known degeneracy between fibre dispersion and radial diffusion. Spherical-deconvolution based approaches typically estimate a global fibre response function to determine the fibre orientation distribution in each voxel. However, the assumption of a  brain-wide fibre response function may be challenged if the diffusion characteristics of white matter vary across the brain. Using a generative joint dMRI-histology model, we demonstrate that the fibre response function is dependent on local anatomy, and that current spherical-deconvolution based models may be overestimating dispersion and underestimating the number of distinct fibre populations per voxel.
]]></description>
<dc:creator>Howard, A. F.</dc:creator>
<dc:creator>Mollink, J.</dc:creator>
<dc:creator>Kleinnijenhuis, M.</dc:creator>
<dc:creator>Pallebage-Gamarallage, M.</dc:creator>
<dc:creator>Bastiani, M.</dc:creator>
<dc:creator>Cottaar, M.</dc:creator>
<dc:creator>Miller, K. L.</dc:creator>
<dc:creator>Jbabdi, S.</dc:creator>
<dc:date>2019-02-28</dc:date>
<dc:identifier>doi:10.1101/563809</dc:identifier>
<dc:title><![CDATA[Joint modelling of diffusion MRI and microscopy]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-02-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/560623v1?rss=1">
<title>
<![CDATA[
Brain Aging in Major Depressive Disorder: Results from the ENIGMA Major Depressive Disorder working group 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/560623v1?rss=1"
</link>
<description><![CDATA[
BackgroundMajor depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in MDD patients, and whether this process is associated with clinical characteristics in a large multi-center international dataset.

MethodsWe performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 29 samples worldwide. Normative brain aging was estimated by predicting chronological age (10-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 1,147 male and 1,386 female controls from the ENIGMA MDD working group. The learned model parameters were applied to 1,089 male controls and 1,167 depressed males, and 1,326 female controls and 2,044 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain predicted age difference (brain-PAD).

FindingsOn average, MDD patients showed a higher brain-PAD of +0.90 (SE 0.21) years (Cohens d=0.12, 95% CI 0.06-0.17) compared to controls. Relative to controls, first-episode and currently depressed patients showed higher brain-PAD (+1.2 [0.3] years), and the largest effect was observed in those with late-onset depression (+1.7 [0.7] years). In addition, higher brain-PAD was associated with higher self-reported depressive symptomatology (b=0.05, p=0.004).

InterpretationThis highly powered collaborative effort showed subtle patterns of abnormal structural brain aging in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the predictive value of these brain-PAD estimates.

FundingThis work was supported, in part, by NIH grants U54 EB020403 and R01 MH116147.
]]></description>
<dc:creator>Han, L. K.</dc:creator>
<dc:creator>Dinga, R.</dc:creator>
<dc:creator>Hahn, T.</dc:creator>
<dc:creator>Ching, C.</dc:creator>
<dc:creator>Eyler, L.</dc:creator>
<dc:creator>Aftanas, L.</dc:creator>
<dc:creator>Aghajani, M.</dc:creator>
<dc:creator>Aleman, A.</dc:creator>
<dc:creator>Baune, B.</dc:creator>
<dc:creator>Berger, K.</dc:creator>
<dc:creator>Brak, I.</dc:creator>
<dc:creator>Busatto Filho, G.</dc:creator>
<dc:creator>Carballedo, A.</dc:creator>
<dc:creator>Connolly, C.</dc:creator>
<dc:creator>Couvy-Duchesne, B.</dc:creator>
<dc:creator>Cullen, K.</dc:creator>
<dc:creator>Dannlowski, U.</dc:creator>
<dc:creator>Davey, C.</dc:creator>
<dc:creator>Dima, D.</dc:creator>
<dc:creator>Duran, F.</dc:creator>
<dc:creator>Enneking, V.</dc:creator>
<dc:creator>Filimonova, E.</dc:creator>
<dc:creator>Frenzel, S.</dc:creator>
<dc:creator>Frodl, T.</dc:creator>
<dc:creator>Fu, C.</dc:creator>
<dc:creator>Godlewska, B.</dc:creator>
<dc:creator>Gotlib, I.</dc:creator>
<dc:creator>Grabe, H.</dc:creator>
<dc:creator>Groenewold, N.</dc:creator>
<dc:creator>Grotegerd, D.</dc:creator>
<dc:creator>Gruber, O.</dc:creator>
<dc:creator>Hall, G.</dc:creator>
<dc:creator>Harrison, B.</dc:creator>
<dc:creator>Hatton, S.</dc:creator>
<dc:creator>Hermesdorf, M.</dc:creator>
<dc:creator>Hickie, I.</dc:creator>
<dc:creator>Ho, T.</dc:creator>
<dc:creator>Hosten, N.</dc:creator>
<dc:creator>Jansen, A.</dc:creator>
<dc:creator>Kahler, C.</dc:creator>
<dc:creator>Kircher, T.</dc:creator>
<dc:creator>Klimes-Dougan, B.</dc:creator>
<dc:creator>Kramer, B.</dc:creator>
<dc:creator>Krug, A.</dc:creator>
<dc:creator>Lagopoulos, J.</dc:creator>
<dc:creator>Leenings, R.</dc:creator>
<dc:creator>MacMaster</dc:creator>
<dc:date>2019-02-26</dc:date>
<dc:identifier>doi:10.1101/560623</dc:identifier>
<dc:title><![CDATA[Brain Aging in Major Depressive Disorder: Results from the ENIGMA Major Depressive Disorder working group]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-02-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/554840v1?rss=1">
<title>
<![CDATA[
Human defensive freezing is associated with acute threat coping, long term hair cortisol levels and trait anxiety. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/554840v1?rss=1"
</link>
<description><![CDATA[
The detection and anticipation of threat facilitates innate defensive behaviours including freezing reactions. Freezing in humans is characterized by reductions in body sway and heart rate and limited evidence suggests that individual differences in freezing reactions are associated with hypothalamic-pituitary-adrenal (HPA) axis activity and anxiety. However, previous measurements of human freezing reactions were largely based on passive threat contexts where natural variations in adaptive threat coping could not be assessed. In a well powered sample (N=419), we studied individual differences in anticipatory freezing reactions, by measuring body sway and heart rate, during an active shooting task where shooting decisions had to be taken under threat of shock. We linked freezing measures to subsequent actions and predictors of anxiety-related psychopathology, including accumulated long-term (3 months) hair cortisol concentrations (HCC) and trait anxiety. The anticipation of threat of shock elicited significant body sway- and heart rate reductions consistent with freezing. Whereas both freezing-related reductions in body sway and heart rate were associated with faster correct shooting decisions, body sway reductions were additionally related to more impulsive shooting (false alarms). Individual differences in threat-related reductions in body sway but not heart rate were further associated to lower HCC and higher trait anxiety. The observed links between freezing and subsequent defensive actions as well as predictors of stress-related psychopathology suggest the potential value of defensive freezing reactions as somatic marker for stress-vulnerability and resilience.
]]></description>
<dc:creator>Hashemi, M. M.</dc:creator>
<dc:creator>Zhang, W.</dc:creator>
<dc:creator>Kaldewaij, R.</dc:creator>
<dc:creator>Koch, S.</dc:creator>
<dc:creator>Jonker, R.</dc:creator>
<dc:creator>Figner, B.</dc:creator>
<dc:creator>Klumpers, F.</dc:creator>
<dc:creator>Roelofs, K.</dc:creator>
<dc:date>2019-02-20</dc:date>
<dc:identifier>doi:10.1101/554840</dc:identifier>
<dc:title><![CDATA[Human defensive freezing is associated with acute threat coping, long term hair cortisol levels and trait anxiety.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-02-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/552877v1?rss=1">
<title>
<![CDATA[
Hippocampal and neocortical oscillations are tuned to behavioral state in freely-behaving macaques 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/552877v1?rss=1"
</link>
<description><![CDATA[
Wireless recordings in macaque neocortex and hippocampus showed stronger theta oscillations during early-stage sleep than during alert volitional movement including walking. In contrast, hippocampal beta and gamma oscillations were prominent during walking and other active behaviors. These relations between hippocampal rhythms and behavioral states in the primate differ markedly from those observed in rodents. Primate neocortex showed similar changes in spectral content across behavioral state as the hippocampus.
]]></description>
<dc:creator>Talakoub, O.</dc:creator>
<dc:creator>Sayegh, P. F.</dc:creator>
<dc:creator>Womelsdorf, T.</dc:creator>
<dc:creator>Zinke, W.</dc:creator>
<dc:creator>Fries, P.</dc:creator>
<dc:creator>Lewis, C. M.</dc:creator>
<dc:creator>Hoffman, K. L.</dc:creator>
<dc:date>2019-02-18</dc:date>
<dc:identifier>doi:10.1101/552877</dc:identifier>
<dc:title><![CDATA[Hippocampal and neocortical oscillations are tuned to behavioral state in freely-behaving macaques]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-02-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/547588v1?rss=1">
<title>
<![CDATA[
White matter changes in the perforant path in patients with amyotrophic lateral sclerosis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/547588v1?rss=1"
</link>
<description><![CDATA[
Amyotrophic lateral sclerosis (ALS) is a progressive and incurable motor neuron disease. Some ALS patients are affected by a level of cognitive or behavioural decline that meets the criteria for frontotemporal dementia (FTD). ALS and FTD share genetic and pathological features; for example, the deposition of phosphorylated 43 kDa TAR DNA-binding protein (pTDP-43) in the brain. Spreading of pTDP-43 pathology in ALS towards brain areas that connect via the Papez circuit is a possible indicator of progression towards FTD. For example, pTDP-43 aggregates in the granule cells of the hippocampus correlate well with clinically manifest FTD. Here, we test the hypothesis that white matter degeneration of the perforant path - as part of the Papez circuit - in the hippocampus is a feature of ALS, even in the absence of fully developed FTD or deposition of pTDP-43 inclusions in hippocampal granule cells. We used diffusion MRI (dMRI), polarized light imaging (PLI) and immunohistochemical analysis of hippocampus sections from controls (n=5) and ALS patients (n=14) to perform an in-depth study of white matter in the perforant path.

The dMRI results show a significant decrease in fractional anisotropy (p=0.01) and an increase in mean diffusivity (p=0.01), axial diffusivity (p=0.03) and radial diffusivity (p=0.03) in the perforant path in ALS patients compared to controls, possibly indicating a loss of white matter fibres. Myelin density (measured with PLI retardance) was lower in ALS patients compared to controls (p=0.05) and correlated with dMRI fractional anisotropy (r=0.52, p=0.03). The dMRI and PLI results were confirmed by the immunohistochemistry; both myelin (proteolipid protein, p=0.03) and neurofilaments (SMI-312, p=0.02) were lower in ALS patients. The activated microglial (CD68) density was similar in ALS and controls. Only two out of the fourteen ALS cases showed pTDP-43 pathology in the dentate gyrus; however, while these two ALS-FTD cases showed reduced myelination in the perforant path, the values were comparable to other ALS cases.

We conclude that degeneration of the perforant path occurs in ALS patients and that this may occur before, or independent of, pTDP-43 aggregation in the dentate gyrus of the hippocampus. Future research should focus on correlating the degree of clinically observed cognitive decline to the amount of white matter atrophy in the perforant path.
]]></description>
<dc:creator>Mollink, J.</dc:creator>
<dc:creator>Hiemstra, M.</dc:creator>
<dc:creator>Miller, K. L.</dc:creator>
<dc:creator>Huszar, I. N.</dc:creator>
<dc:creator>Jenkinson, M.</dc:creator>
<dc:creator>Raaphorst, J.</dc:creator>
<dc:creator>Wiesmann, M.</dc:creator>
<dc:creator>Ansorge, O.</dc:creator>
<dc:creator>Pallebage-Gamarallage, M.</dc:creator>
<dc:creator>van Cappellen van Walsum, A.-M.</dc:creator>
<dc:date>2019-02-12</dc:date>
<dc:identifier>doi:10.1101/547588</dc:identifier>
<dc:title><![CDATA[White matter changes in the perforant path in patients with amyotrophic lateral sclerosis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-02-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/422964v1?rss=1">
<title>
<![CDATA[
The genetics of situs inversus totalis without primary ciliary dyskinesia 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/422964v1?rss=1"
</link>
<description><![CDATA[
Situs inversus totalis (SIT), a complete left-right mirror reversal of the visceral organs, is usually described as a recessive disorder. SIT can occur with Primary Ciliary Dyskinesia (PCD). However, most people with SIT do not have PCD, and the etiology of their condition remains poorly studied. Those without PCD may have an elevated rate of left-handedness, implying developmental mechanisms linking brain and body laterality. We sequenced the genomes of 15 people with SIT, of which six had PCD, and 15 controls. The SIT subjects with PCD all had likely recessive mutations in genes already known to cause PCD. Two non-PCD SIT cases also had recessive mutations in known PCD genes, suggesting reduced penetrance for PCD in some SIT cases. One non-PCD SIT case had a recessive mutation in PKD1L1, which has previously been linked to SIT without PCD. However, six of the nine non-PCD SIT cases, including most of the left-handers in this dataset, had no obvious candidate genes or significant pathways affected by the mutations that they carried. While we cannot exclude a monogenic basis, more complex genetic models must also be considered, as well as environmental influences or random effects in early development.
]]></description>
<dc:creator>Postema, M. C.</dc:creator>
<dc:creator>Carrion-Castillo, A.</dc:creator>
<dc:creator>Fisher, S. E.</dc:creator>
<dc:creator>Vingerhoets, G.</dc:creator>
<dc:creator>Francks, C.</dc:creator>
<dc:date>2018-09-21</dc:date>
<dc:identifier>doi:10.1101/422964</dc:identifier>
<dc:title><![CDATA[The genetics of situs inversus totalis without primary ciliary dyskinesia]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/536243v1?rss=1">
<title>
<![CDATA[
A new comprehensive Eye-Tracking Test Battery concurrently evaluating the Pupil Labs Glasses and the EyeLink 1000 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/536243v1?rss=1"
</link>
<description><![CDATA[
Eye-tracking experiments rely heavily on good data quality of eye-trackers. Unfortunately, it is often that only the spatial accuracy and precision values are available from the manufacturers. These two values alone are not sufficient enough to serve as a benchmark for an eye-tracker: Eye-tracking quality deteriorates during an experimental session due to head movements, changing illumination or calibration decay. Additionally, different experimental paradigms require the analysis of different types of eye movements, for instance smooth pursuit movements, blinks or microsaccades, which themselves cannot readily be evaluated by using spatial accuracy or precision alone. To obtain a more comprehensive description of properties, we developed an extensive eye-tracking test battery. In 10 different tasks, we evaluated eye-tracking related measures such as: the decay of accuracy, fixation durations, pupil dilation, smooth pursuit movement, microsaccade detection, blink detection, or the influence of head motion. For some measures, true theoretical values exist. For others, a relative comparison to a gold standard eye-tracker is needed. Therefore, we collected our gaze data simultaneously from a gold standard remote EyeLink 1000 eye-tracker and compared it with the mobile Pupil Labs glasses.

As expected, the average spatial accuracy of 0.57{degrees} for the EyeLink 1000 eye-tracker was better than the 0.82{degrees} for the Pupil Labs glasses (N=15). Furthermore, we detected less fixations and shorter saccade durations for the Pupil Labs glasses. Similarly, we found fewer microsaccades using the Pupil Labs glasses. The accuracy over time decayed only slightly for the EyeLink 1000, but strongly for the Pupil Labs glasses. Finally we observed that the measured pupil diameters differed between eye-trackers on the individual subject level but not the group level.

To conclude, our eye-tracking test battery offers 10 tasks that allow us to benchmark the many parameters of interest in stereotypical eye-tracking situations, or addresses a common source of confounds in measurement errors (e.g. yaw and roll head movements).

All recorded eye-tracking data (including Pupil Labs eye video files), the stimulus code for the test battery and the modular analysis pipeline are available (https://github.com/behinger/etcomp).

BVE, KG, II and PK conceived the experiment. II and BVE created the experiment and recorded the gaze data. BVE and KG performed the analysis. BVE, KG and PK reviewed the manuscript critically.
]]></description>
<dc:creator>Ehinger, B. V.</dc:creator>
<dc:creator>Gross, K.</dc:creator>
<dc:creator>Ibs, I.</dc:creator>
<dc:creator>Koenig, P.</dc:creator>
<dc:date>2019-02-03</dc:date>
<dc:identifier>doi:10.1101/536243</dc:identifier>
<dc:title><![CDATA[A new comprehensive Eye-Tracking Test Battery concurrently evaluating the Pupil Labs Glasses and the EyeLink 1000]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-02-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/532879v1?rss=1">
<title>
<![CDATA[
Applying stochastic spike train theory for high-accuracy MEG/EEG 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/532879v1?rss=1"
</link>
<description><![CDATA[
The accuracy of electroencephalography (EEG) and magnetoencephalography (MEG) is challenged by overlapping sources from within the brain. This lack of accuracy is a severe limitation to the possibilities and reliability of modern stimulation protocols in basic research and clinical diagnostics. As a solution, we here introduce a theory of stochastic neuronal spike timing probability densities for describing the large-scale spiking activity in neural networks, and a novel spike density component analysis (SCA) method for isolating specific neural sources. Three studies are conducted based on 564 cases of evoked responses to auditory stimuli from 94 human subjects each measured with 60 EEG electrodes and 306 MEG sensors. In the first study we show that the large-scale spike timing (but not non-encephalographic artifacts) in MEG/EEG waveforms can be modeled with Gaussian probability density functions with high accuracy (median 99.7%-99.9% variance explained), while gamma and sine functions fail describing the MEG and EEG waveforms. In the second study we confirm that SCA can isolate a specific evoked response of interest. Our findings indicate that the mismatch negativity (MMN) response is accurately isolated with SCA, while principal component analysis (PCA) fails supressing interference from overlapping brain activity, e.g. from P3a and alpha waves, and independent component analysis (ICA) distorts the evoked response. Finally, we confirm that SCA accurately reveals inter-individual variation in evoked brain responses, by replicating findings relating individual traits with MMN variations. The findings of this paper suggest that the commonly overlapping neural sources in single-subject or patient data can be more accurately separated by applying the introduced theory of large-scale spike timing and method of SCA in comparison to PCA and ICA.

Significance statementElectroencephalography (EEG) and magnetoencelopraphy (MEG) are among the most applied non-invasive brain recording methods in humans. They are the only methods to measure brain function directly and in time resolutions smaller than seconds. However, in modern research and clinical diagnostics the brain responses of interest cannot be isolated, because of interfering signals of other ongoing brain activity. For the first time, we introduce a theory and method for mathematically describing and isolating overlapping brain signals, which are based on prior intracranial in vivo research on brain cells in monkey and human neural networks. Three studies mutually support our theory and suggest that a new level of accuracy in MEG/EEG can achieved by applying the procedures presented in this paper.
]]></description>
<dc:creator>Haumann, N. T.</dc:creator>
<dc:creator>Huotilainen, M.</dc:creator>
<dc:creator>Vuust, P.</dc:creator>
<dc:creator>Brattico, E.</dc:creator>
<dc:date>2019-01-28</dc:date>
<dc:identifier>doi:10.1101/532879</dc:identifier>
<dc:title><![CDATA[Applying stochastic spike train theory for high-accuracy MEG/EEG]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-01-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/528117v1?rss=1">
<title>
<![CDATA[
Genome wide meta-analysis identifies genomic relationships, novel loci, and pleiotropic mechanisms across eight psychiatric disorders. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/528117v1?rss=1"
</link>
<description><![CDATA[
Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed a meta-analysis of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders identifying three groups of inter-related disorders. We detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning in the second trimester prenatally, and play prominent roles in a suite of neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.
]]></description>
<dc:creator>Cross-Disorder Group of the Psychiatric Genomics Consortium,</dc:creator>
<dc:creator>Lee, P. H.</dc:creator>
<dc:creator>Anttila, V.</dc:creator>
<dc:creator>Won, H.</dc:creator>
<dc:creator>Feng, Y.-C. A.</dc:creator>
<dc:creator>Rosenthal, J.</dc:creator>
<dc:creator>Zhu, Z.</dc:creator>
<dc:creator>Tucker-Drob, E. M.</dc:creator>
<dc:creator>Nivard, M. G.</dc:creator>
<dc:creator>Grotzinger, A. D.</dc:creator>
<dc:creator>Posthuma, D.</dc:creator>
<dc:creator>Wang, M. M.- J.</dc:creator>
<dc:creator>Yu, D.</dc:creator>
<dc:creator>Stahl, E.</dc:creator>
<dc:creator>Walters, R. K.</dc:creator>
<dc:creator>Anney, R. J. L.</dc:creator>
<dc:creator>Duncan, L. E.</dc:creator>
<dc:creator>Belangero, S.</dc:creator>
<dc:creator>Luykx, J.</dc:creator>
<dc:creator>Kranzler, H.</dc:creator>
<dc:creator>Keski-Rahkonen, A.</dc:creator>
<dc:creator>Cook, E. H.</dc:creator>
<dc:creator>Kirov, G.</dc:creator>
<dc:creator>Coppola, G.</dc:creator>
<dc:creator>Kaprio, J.</dc:creator>
<dc:creator>Zai, C. C.</dc:creator>
<dc:creator>Hoekstra, P. J.</dc:creator>
<dc:creator>Banaschewski, T.</dc:creator>
<dc:creator>Rohde, L. A.</dc:creator>
<dc:creator>PGC Attention Deficit Hyperactivity Disorder Group,</dc:creator>
<dc:creator>PGC Autism Spectrum Disorder Group,</dc:creator>
<dc:creator>PGC Bipolar Disorder Group,</dc:creator>
<dc:creator>PGC Eating Diso</dc:creator>
<dc:date>2019-01-26</dc:date>
<dc:identifier>doi:10.1101/528117</dc:identifier>
<dc:title><![CDATA[Genome wide meta-analysis identifies genomic relationships, novel loci, and pleiotropic mechanisms across eight psychiatric disorders.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-01-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/531368v1?rss=1">
<title>
<![CDATA[
Dissociation of broadband high-frequency activity and neuronal firing in the neocortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/531368v1?rss=1"
</link>
<description><![CDATA[
Broadband High-frequency Activity (BHA; 70-150 Hz), also known as "high gamma," a key analytic signal in human intracranial recordings is often assumed to reflect local neural firing (multiunit activity; MUA). Accordingly, BHA has been used to study neuronal population responses in auditory (1,2), visual (3,4), language (5), mnemonic processes (6-9) and cognitive control (10,11). BHA is arguably the electrophysiological measure best correlated with the Blood Oxygenation Level Dependent (BOLD) signal in fMRI (12-13). However, beyond the fact that BHA correlates with neuronal spiking (12, 14-16), the neuronal populations and physiological processes generating BHA are not precisely defined. Although critical for interpreting intracranial signals in human and non-human primates, the precise physiology of BHA remains unknown. Here, we show that BHA dissociates from MUA in primary visual and auditory cortex. Using laminar multielectrode data in monkeys, we found a bimodal distribution of stimulus-evoked BHA across depth of a cortical column: an early-deep, followed by a later-superficial layer response. Only, the early-deep layer BHA had a clear local MUA correlate, while the more prominent superficial layer BHA had a weak or undetectable MUA correlate. In many cases, particularly in V1 (70%), supragranular sites showed strong BHA in lieu of any detectable increase in MUA. Due to volume conduction, BHA from both the early-deep and the later-supragranular generators contribute to the field potential at the pial surface, though the contribution may be weighted towards the late-supragranular BHA. Our results demonstrate that the strongest generators of BHA are in the superficial cortical layers and show that the origins of BHA include a mixture of the neuronal action potential firing and dendritic processes separable from this firing. It is likely that the typically-recorded BHA signal emphasizes the latter processes to a greater extent than previously recognized.
]]></description>
<dc:creator>Leszczynski, M.</dc:creator>
<dc:creator>Barczak, A.</dc:creator>
<dc:creator>Kajikawa, Y.</dc:creator>
<dc:creator>Ulbert, I.</dc:creator>
<dc:creator>Falchier, A.</dc:creator>
<dc:creator>Tal, I.</dc:creator>
<dc:creator>Haegens, S.</dc:creator>
<dc:creator>Melloni, L.</dc:creator>
<dc:creator>Knight, R.</dc:creator>
<dc:creator>Schroeder, C.</dc:creator>
<dc:date>2019-01-25</dc:date>
<dc:identifier>doi:10.1101/531368</dc:identifier>
<dc:title><![CDATA[Dissociation of broadband high-frequency activity and neuronal firing in the neocortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-01-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/520502v1?rss=1">
<title>
<![CDATA[
The relationship between spatial configuration and functional connectivity of brain regions revisited 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/520502v1?rss=1"
</link>
<description><![CDATA[
In our previous paper (Bijsterbosch et al., 2018), we showed that network-based modelling of brain connectivity interacts strongly with the shape and exact location of brain regions, such that cross-subject variations in the spatial configuration of functional brain regions are being interpreted as changes in functional connectivity. Here we show that these spatial effects on connectivity estimates actually occur as a result of spatial overlap between brain networks. This is shown to systematically bias connectivity estimates obtained from group spatial ICA followed by dual regression. We introduce an extended method that addresses the bias and achieves more accurate connectivity estimates.nnImpact statementWe show that functional connectivity network matrices as estimated from resting state functional MRI are biased by spatially overlapping network structure.
]]></description>
<dc:creator>Bijsterbosch, J. D.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>Woolrich, M. W.</dc:creator>
<dc:creator>Smith, S. M.</dc:creator>
<dc:creator>Harrison, S. J.</dc:creator>
<dc:date>2019-01-15</dc:date>
<dc:identifier>doi:10.1101/520502</dc:identifier>
<dc:title><![CDATA[The relationship between spatial configuration and functional connectivity of brain regions revisited]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-01-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/520395v1?rss=1">
<title>
<![CDATA[
Plasticity versus stability across the human cortical visual connectome 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/520395v1?rss=1"
</link>
<description><![CDATA[
Whether and how the balance between plasticity and stability varies across the brain is an important open question. Within a processing hierarchy, it is thought that plasticity is increased at higher levels of cortical processing, but direct quantitative comparisons between low- and high-level plasticity have not been made so far. Here, we addressed this issue for the human cortical visual system. By quantifying plasticity as the complement of the heritability of functional connectivity, we demonstrate a non-monotonic relationship between plasticity and hierarchical level, such that plasticity decreases from early to mid-level cortex, and then increases further of the visual hierarchy. This non-monotonic relationship argues against recent theory that the balance between plasticity and stability is governed by the costs of the "coding-catastrophe", and can be explained by a concurrent decline of short-term adaptation and rise of long-term plasticity up the visual processing hierarchy.
]]></description>
<dc:creator>Haak, K. V.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:date>2019-01-15</dc:date>
<dc:identifier>doi:10.1101/520395</dc:identifier>
<dc:title><![CDATA[Plasticity versus stability across the human cortical visual connectome]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-01-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/514505v1?rss=1">
<title>
<![CDATA[
The role of hippocampal spatial representations in contextualization and generalization of fear 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/514505v1?rss=1"
</link>
<description><![CDATA[
Using contextual information to predict aversive events is a critical ability that protects from generalizing fear responses to safe contexts. Animal models have demonstrated the importance of spatial context representations within the hippocampal formation in contextualization of fear learning. The ventromedial prefrontal cortex (vmPFC) is known to play an important role in safety learning, possibly also through the incorporation of context information. However, if contextual representations are related to context-dependent expression of fear memory in humans remains unclear. Twenty-one healthy participants underwent functional MRI combined with a cue-context conditioning paradigm within a self-navigated virtual reality environment. The environment included two buildings (Threat and Safe context), which had distinct features outside but were identical inside. Within each context, participants saw two cues (CS+, CS-). The CS+ was consistently (100% reinforcement rate) paired with an electric shock in the Threat context, but never in the Safe context. The CS- was never paired with a shock. We found robust differential skin conductance responses (SCRs; CS+ > CS-) in the Threat context, but also within the Safe context, indicating fear generalization. Within the Safe context, vmPFC responses to the CS+ were larger than those in the Threat context. We furthermore found environment-specific representantions for the two contexts in the training paradigm (i.e., before conditioning took place) in the hippocampus to be related to fear expression and generalization. Namely, participants with a weak context representation (z-score < 1.65) showed stronger fear generalization compared to participants with a strong context representation (z-score > 1.65). Thus, a low neural representation of spatial context may explain overgeneralization of memory to safe contexts. In addition, our findings demonstrate that context-dependent regulation of fear expression engages ventromedial prefrontal pathways suggesting this involves a similar mechanism that is known to be involved in retrieval of extinction memory.
]]></description>
<dc:creator>de Voogd, L. D.</dc:creator>
<dc:creator>Murray, Y. P. J.</dc:creator>
<dc:creator>Barte, R. M.</dc:creator>
<dc:creator>van der Heide, A.</dc:creator>
<dc:creator>Fernandez, G.</dc:creator>
<dc:creator>Doeller, C. F.</dc:creator>
<dc:creator>Hermans, E. J.</dc:creator>
<dc:date>2019-01-09</dc:date>
<dc:identifier>doi:10.1101/514505</dc:identifier>
<dc:title><![CDATA[The role of hippocampal spatial representations in contextualization and generalization of fear]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-01-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/514687v1?rss=1">
<title>
<![CDATA[
Dual-site high-density 4Hz transcranial alternating current stimulation applied over auditory and motor cortical speech areas does not influence auditory-motor mapping 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/514687v1?rss=1"
</link>
<description><![CDATA[
BackgroundVerbal repetition of auditory speech requires the mapping of a sensory acoustic input onto articulatory motor plans (auditory-motor mapping). Recent evidence indicates that auditory-motor mapping could rely on low frequency neural synchronization (i.e., theta oscillatory phase coupling) between sensory and motor speech areas.nnObjectiveIn the present study, we apply dual-site high-density (HD) Transcranial Alternating Current Stimulation (TACS) above the auditory and motor cortex to induce, or disrupt, theta phase coupling between the two areas. We predicted that functionally coupling the two areas would strengthen auditory-motor mapping, compared with functionally decoupling them. We assessed the strength of auditory-motor mapping using a verbal repetition task.nnResultsWe found no significant effect of TACS-induced theta phase coupling on auditory-motor mapping as indexed by verbal repetition performance.nnConclusionAuditory-motor mapping may rely on a different mechanism than we hypothesized, for example, oscillatory phase-coupling outside the theta range. Alternatively, modulation of interregional theta-phase coupling may require more effective stimulation protocols, for example, TACS at higher intensities.
]]></description>
<dc:creator>Preisig, B. C.</dc:creator>
<dc:creator>Sjerps, M. J.</dc:creator>
<dc:creator>Kosem, A.</dc:creator>
<dc:creator>Riecke, L.</dc:creator>
<dc:date>2019-01-09</dc:date>
<dc:identifier>doi:10.1101/514687</dc:identifier>
<dc:title><![CDATA[Dual-site high-density 4Hz transcranial alternating current stimulation applied over auditory and motor cortical speech areas does not influence auditory-motor mapping]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-01-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/514703v1?rss=1">
<title>
<![CDATA[
An incremental training method with automated, extendible T-maze for training spatial behavioral tasks in rodents 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/514703v1?rss=1"
</link>
<description><![CDATA[
We present a training procedure and a T-maze equipped with sensors and automated feeders for training spatial behavioral tasks in rodents. The maze can be transformed from an enclosed box to a maze of variable dimensions. The modularity of the protocol and setup makes it highly flexible and suitable for training a wide variety of spatial tasks, and facilitates incremental training stages of increasing maze size for more efficient learning. The apparatus, in its software and hardware, is able to adapt to animal performance, adjusting task challenges and difficulty.nnTwo different methods of automatic behavioral scoring are evaluated against manual methods. Sensors embedded in the maze provide information regarding the order of reward locations visited and the time between the activation of the cue via the nose-poke and the activation of the reward location sensors. The distributions of these reaction times differ between correct and incorrect trials, providing an index of behavior and motivation. The automated maze system allows the trainer to operate and monitor the task away from the experimental set-up, minimizing human interference and improving the reproducibility of the experiment. We show that our method succeeds in training a binary forced-choice task in rats.
]]></description>
<dc:creator>Holleman, E.</dc:creator>
<dc:creator>Maka, J.</dc:creator>
<dc:creator>Schroeder, T.</dc:creator>
<dc:creator>Battaglia, F.</dc:creator>
<dc:date>2019-01-09</dc:date>
<dc:identifier>doi:10.1101/514703</dc:identifier>
<dc:title><![CDATA[An incremental training method with automated, extendible T-maze for training spatial behavioral tasks in rodents]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-01-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/267815v1?rss=1">
<title>
<![CDATA[
Dissociable effects of prediction and integration during language comprehension: Evidence from a large-scale study using brain potentials 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/267815v1?rss=1"
</link>
<description><![CDATA[
Composing sentence meaning is easier for predictable words than for unpredictable words. Are predictable words genuinely predicted, or simply more plausible and therefore easier to integrate with sentence context? We addressed this persistent and fundamental question using data from a recent, large-scale (N = 334) replication study, by investigating the effects of word predictability and sentence plausibility on the N400, the brains electrophysiological index of semantic processing. A spatiotemporally fine-grained mixed effects multiple regression analysis revealed overlapping effects of predictability and plausibility on the N400, albeit with distinct spatiotemporal profiles. Our results challenge the view that the predictability-dependent N400 reflects the effects of either prediction or integration, and suggest that semantic facilitation of predictable words arises from a cascade of processes that activate and integrate word meaning with context into a sentence-level meaning.
]]></description>
<dc:creator>Nieuwland, M. S.</dc:creator>
<dc:creator>Barr, D. J.</dc:creator>
<dc:creator>Bartolozzi, F.</dc:creator>
<dc:creator>Busch-Moreno, S.</dc:creator>
<dc:creator>Darley, E.</dc:creator>
<dc:creator>Donaldson, D. I.</dc:creator>
<dc:creator>Ferguson, H. J.</dc:creator>
<dc:creator>Fu, X.</dc:creator>
<dc:creator>Heyselaar, E.</dc:creator>
<dc:creator>Huettig, F.</dc:creator>
<dc:creator>Husband, E. M.</dc:creator>
<dc:creator>Ito, A.</dc:creator>
<dc:creator>Kazanina, N.</dc:creator>
<dc:creator>Kogan, V.</dc:creator>
<dc:creator>Kohut, Z.</dc:creator>
<dc:creator>Kulakova, E.</dc:creator>
<dc:creator>Meziere, D.</dc:creator>
<dc:creator>Politzer-Ahles, S.</dc:creator>
<dc:creator>Rousselet, G.</dc:creator>
<dc:creator>Rueschemeyer, S.-A.</dc:creator>
<dc:creator>Segaert, K.</dc:creator>
<dc:creator>Tuomainen, J.</dc:creator>
<dc:creator>Von Grebmer Zu Wolfsthurn, S.</dc:creator>
<dc:date>2018-02-19</dc:date>
<dc:identifier>doi:10.1101/267815</dc:identifier>
<dc:title><![CDATA[Dissociable effects of prediction and integration during language comprehension: Evidence from a large-scale study using brain potentials]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-02-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/345652v1?rss=1">
<title>
<![CDATA[
Exploratory analyses suggest less cognitive decline on nilvadipine treatment in very mild Alzheimer’s disease subjects 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/345652v1?rss=1"
</link>
<description><![CDATA[
BackgroundWe explored whether the effects of nilvadipine on cognition were influenced by baseline Alzheimers disease (AD) severity.nnMethodsExploratory analyses were performed on the modified intention-to-treat (mITT) dataset (n = 497) of a phase III randomized placebo-controlled trial to examine the response to nilvadipine in very mild, mild and moderate AD subjects. The outcome measures included total and subscale scores of the Alzheimers Disease Assessment Scale Cognitive 12 (ADAS-Cog 12), the Clinical Dementia Rating Scale sum of boxes (CDR-sb) and the AD composite score (ADCOMS), an outcome measure recently developed to detect treatment responses in subjects with prodromal AD. Cerebrospinal fluid (CSF) biomarkers A{beta}38, A{beta}40, A{beta}42, total tau and P181 tau were measured in a subset of samples (n = 55). Regression analyses were adjusted for potential confounders and effect modifiers in order to examine the interactive effects of nilvadipine and AD severity on cognitive outcomes over 78-weeks.nnResultsCompared to their respective placebo-controls, nilvadipine-treated, very mild AD subjects showed less decline, whereas moderate AD subjects showed greater decline on the ADAS-Cog 12. Also in very mild AD, a beneficial effect (as measured by ADCOMS), was detected in the nilvadipine treated group. Therapeutic effects of nilvadipine were also observed for a composite memory trait in very mild AD subjects and a composite language trait in mild AD subjects. CSF A{beta}42/A{beta}40 ratios were increased in mild AD and decreased in moderate AD patients treated with nilvadipine, compared to their respective controls.nnConclusionThese data suggest that very mild AD subjects benefited from nilvadipine and that future clinical trials of nilvadipine in this population are required to confirm these findings.nnTrial RegistrationNCT02017340 Registered 20 December 2013, https://clinicaltrials.gov/ct2/show/NCT02017340nnEUDRACT Reference Number 2012-002764-27 Registered 04 February 2013, https://www.clinicaltrialsregister.eu/ctr-search/search?query=2012-002764-27
]]></description>
<dc:creator>Abdullah, L.</dc:creator>
<dc:creator>Crawford, F.</dc:creator>
<dc:creator>Langlois, H.</dc:creator>
<dc:creator>Hendrix, S.</dc:creator>
<dc:creator>Kennelly, S.</dc:creator>
<dc:creator>Lawlor, B.</dc:creator>
<dc:creator>Mullan, M.</dc:creator>
<dc:date>2018-06-15</dc:date>
<dc:identifier>doi:10.1101/345652</dc:identifier>
<dc:title><![CDATA[Exploratory analyses suggest less cognitive decline on nilvadipine treatment in very mild Alzheimer’s disease subjects]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/509935v1?rss=1">
<title>
<![CDATA[
MetaDome: Pathogenicity analysis of genetic variants through aggregation of homologous human protein domains 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/509935v1?rss=1"
</link>
<description><![CDATA[
The growing availability of human genetic variation has given rise to novel methods of measuring genetic tolerance that better interpret variants of unknown significance. We recently developed a novel concept based on protein domain homology in the human genome to improve variant interpretation. For this purpose we mapped population variation from the Exome Aggregation Consortium (ExAC) and pathogenic mutations from the Human Gene Mutation Database (HGMD) onto Pfam protein domains. The aggregation of these variation data across homologous domains into meta-domains allowed us to generate base-pair resolution of genetic intolerance profiles for human protein domains.nnHere we developed MetaDome, a fast and easy-to-use web service that visualizes meta-domain information and gene-wide profiles of genetic tolerance. We updated the underlying data of MetaDome to contain information from 56,319 human transcripts, 71,419 protein domains, 12,164,292 genetic variants from gnomAD, and 34,076 pathogenic mutations from ClinVar. MetaDome allows researchers to easily investigate their variants of interest for the presence or absence of variation at corresponding positions within homologous domains. We illustrate the added value of MetaDome by an example that highlights how it may help in the interpretation of variants of unknown significance. The MetaDome web server is freely accessible at https://stuart.radboudumc.nl/metadome.
]]></description>
<dc:creator>Wiel, L.</dc:creator>
<dc:creator>Baakman, C.</dc:creator>
<dc:creator>Gilissen, D.</dc:creator>
<dc:creator>Veltman, J. A.</dc:creator>
<dc:creator>Vriend, G.</dc:creator>
<dc:creator>Gilissen, C.</dc:creator>
<dc:date>2019-01-02</dc:date>
<dc:identifier>doi:10.1101/509935</dc:identifier>
<dc:title><![CDATA[MetaDome: Pathogenicity analysis of genetic variants through aggregation of homologous human protein domains]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2019-01-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/495168v1?rss=1">
<title>
<![CDATA[
Neural dynamics of accumulating and updating linguistic knowledge structures 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/495168v1?rss=1"
</link>
<description><![CDATA[
Knowledge is acquired by generalization and integration across learning experiences, which can then be applied to future instances. This study provides novel insights into how linguistic associative knowledge is acquired by systematically tracking schematic knowledge formation while participants were learning an abstract artificial language organized by higher-order associative regularity. During learning, we found activity in the left inferior frontal gyrus in response to knowledge updating during feedback presentation, as well as in response to available accumulated knowledge during retrieval. A complementary signal was found in the caudate nucleus, where activity correlated with the availability of recently acquired knowledge during retrieval, suggesting it initially supports the retrieval of knowledge. Furthermore, we find that activity in a set of regions, including the medial prefrontal cortex and hippocampus, scaled with accumulated knowledge during feedback presentation, which might be indicative of increased generalization of features of the hierarchical knowledge structure. Together, these results provide a mechanistic insight into how linguistic associative knowledge is acquired by generalization across repeated learning experiences.
]]></description>
<dc:creator>Berkers, R. M. W. J.</dc:creator>
<dc:creator>van der Linden, M.</dc:creator>
<dc:creator>Neville, D. A.</dc:creator>
<dc:creator>van Kesteren, M. T. R.</dc:creator>
<dc:creator>Morris, R. G. M.</dc:creator>
<dc:creator>Murre, J. M. J.</dc:creator>
<dc:creator>Fernandez, G.</dc:creator>
<dc:date>2018-12-13</dc:date>
<dc:identifier>doi:10.1101/495168</dc:identifier>
<dc:title><![CDATA[Neural dynamics of accumulating and updating linguistic knowledge structures]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-12-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/366393v1?rss=1">
<title>
<![CDATA[
Reference Repulsion Is Not a Perceptual Illusion 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/366393v1?rss=1"
</link>
<description><![CDATA[
Perceptual decisions are often influenced by contextual factors. For instance, when engaged in a visual discrimination task against a reference boundary, subjective reports about the judged stimulus feature are biased away from the boundary - a phenomenon termed reference repulsion. Until recently, this phenomenon has been thought to reflect a perceptual illusion regarding the appearance of the stimulus, but new evidence suggests that it may rather reflect a post-perceptual decision bias. To shed light on this issue, we examined whether and how orientation judgments affect perceptual appearance. In a first experiment, we confirmed that after judging a grating stimulus against a discrimination boundary, the subsequent reproduction response was indeed repelled from the boundary. To investigate the perceptual nature of this bias, in a second experiment we measured the perceived orientation of the grating stimulus more directly, in comparison to a reference stimulus visible at the same time. Although we did observe a small repulsive bias away from the boundary, this bias was explained by random trial-by-trial fluctuations in sensory representations together with classical stimulus adaptation effects and did not reflect a systematic bias due to the discrimination judgment. Overall, the current study indicates that discrimination judgments do not elicit a perceptual illusion and points towards a post-perceptual locus of reference repulsion.
]]></description>
<dc:creator>Fritsche, M.</dc:creator>
<dc:creator>de Lange, F. P.</dc:creator>
<dc:date>2018-07-10</dc:date>
<dc:identifier>doi:10.1101/366393</dc:identifier>
<dc:title><![CDATA[Reference Repulsion Is Not a Perceptual Illusion]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/498873v1?rss=1">
<title>
<![CDATA[
Dissociable laminar profiles of concurrent bottom-up and top-down modulation in the human visual cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/498873v1?rss=1"
</link>
<description><![CDATA[
Recent developments in human neuroimaging make it possible to non-invasively measure neural activity from different cortical layers. This can potentially reveal not only which brain areas are engaged by a task, but also how. Specifically, bottom-up and top-down responses are associated with distinct laminar profiles. Here, we measured lamina-resolved fMRI responses during a visual task designed to induce concurrent bottom-up and top-down modulations via orthogonal manipulations of stimulus contrast and feature-based attention. BOLD responses were modulated by both stimulus contrast (bottom-up) and by engaging feature-based attention (top-down). Crucially, these effects operated at different cortical depths: Bottom-up modulations were strongest in the middle cortical layer, while top-down modulations were strong at all depths, being significantly stronger in deep and superficial layers compared to bottom-up effects. As such, we demonstrate that laminar activity profiles can discriminate between concurrent top-down and bottom-up processing, and are diagnostic of how a brain region is activated.
]]></description>
<dc:creator>Lawrence, S. J.</dc:creator>
<dc:creator>Norris, D. G.</dc:creator>
<dc:creator>de Lange, F.</dc:creator>
<dc:date>2018-12-18</dc:date>
<dc:identifier>doi:10.1101/498873</dc:identifier>
<dc:title><![CDATA[Dissociable laminar profiles of concurrent bottom-up and top-down modulation in the human visual cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-12-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/496844v1?rss=1">
<title>
<![CDATA[
Semantic Probing: Feasibility of using sequential probes to decode what is on a user’s mind 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/496844v1?rss=1"
</link>
<description><![CDATA[
In this paper, we investigate the feasibility of using multiple sequential probe words to decode their relatedness to an active semantic concept on a users mind from the respective electrophysiological brain responses. If feasible, this relatedness information could be used by a Brain Computer Interface to infer that semantic concept, by integrating the knowledge of the relationship between the multiple probe words and the  unknown target. Such a BCI can take advantage of the N400: an event related potential that is sensitive to semantic content of a stimulus in relation to an established semantic context. However, it is unknown whether the N400 is suited for the multiple probing paradigm we propose, as other intervening words might distract from the established context (i.e., the target word). We perform an experiment in which we present up to ten words after an initial target word, and find no attenuation of the strength of the N400 in grand average ERPs and no decrease in classification accuracy for probes occurring later in the sequences. These results lay the groundwork for the development of a BCI that infers the concept on a users mind through repeated probing.
]]></description>
<dc:creator>Dijkstra, K.</dc:creator>
<dc:creator>Farquhar, J.</dc:creator>
<dc:creator>Desain, P.</dc:creator>
<dc:date>2018-12-16</dc:date>
<dc:identifier>doi:10.1101/496844</dc:identifier>
<dc:title><![CDATA[Semantic Probing: Feasibility of using sequential probes to decode what is on a user’s mind]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-12-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/447177v1?rss=1">
<title>
<![CDATA[
The molecular genetics of hand preference revisited 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/447177v1?rss=1"
</link>
<description><![CDATA[
Hand preference is a prominent behavioural trait linked to human brain asymmetry. A handful of genetic variants have been reported to associate with hand preference or quantitative measures related to it. Most of these reports were on the basis of limited sample sizes, by current standards for genetic analysis of complex traits. Here we performed a genome-wide association analysis of hand preference in the large, population-based UK Biobank cohort (N=331,037). We used gene-set enrichment analysis to investigate whether genes involved in visceral asymmetry are particularly relevant to hand preference, following one previous report. We found no evidence implicating any specific candidate variants previously reported. We also found no evidence that genes involved in visceral laterality play a role in hand preference. It remains possible that some of the previously reported genes or pathways are relevant to hand preference as assessed in other ways, or else are relevant within specific disorder populations. However, some or all of the earlier findings are likely to be false positives, and none of them appear relevant to hand preference as defined categorically in the general population. Within the UK Biobank itself, a significant association implicates the gene MAP2 in handedness.
]]></description>
<dc:creator>de Kovel, C. G. F.</dc:creator>
<dc:creator>Francks, C.</dc:creator>
<dc:date>2018-10-18</dc:date>
<dc:identifier>doi:10.1101/447177</dc:identifier>
<dc:title><![CDATA[The molecular genetics of hand preference revisited]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-10-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/490086v1?rss=1">
<title>
<![CDATA[
Reactive/proactive aggression specific cortical and subcortical alterations in children and adolescents with disruptive behavior 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/490086v1?rss=1"
</link>
<description><![CDATA[
ObjectiveMaladaptive aggression, as present in conduct disorder (CD) and, to a lesser extent, oppositional defiant disorder (ODD), has been associated with structural alterations in various brain regions, such as ventromedial prefrontal cortex (vmPFC), anterior cingulate cortex (ACC), amygdala, insula and ventral striatum. Although aggression can be subdivided into reactive and proactive subtypes, no neuroimaging studies have yet investigated if any structural brain alterations are associated with either of the subtypes specifically. Here we investigated this association in predefined regions of interest.nnMethodT1-weighted magnetic resonance images were acquired from 158 children and adolescents with aggressive behavior (ODD/CD) and 96 controls in a multi-centre study. Aggression subtypes were assessed by questionnaires. Cortical volume and subcortical volumes and shape were determined using Freesurfer and the FMRIB integrated registration and segmentation tool. Associations between volumes and continuous measures of aggression were established using multilevel linear mixed effects models.nnResultsIn cases only proactive aggression was negatively associated with amygdala volume (b=-11.82, p=0.05), while reactive aggression was negatively associated with insula volume (b=-46.41, p=0.01). Classical group comparison showed that children and adolescents with aggressive behavior had smaller volumes than controls in (bilateral) ventral striatum (p=0.003), ACC (p=0.01), and vmPFC (p=0.003) with modest effect sizes.nnConclusionsAggression was associated with reduced volume in brain regions involved in decision making. Negative associations were found between reactive aggression and volumes in regions involved in threat responsivity and between proactive aggression and regions linked to empathy. This provides evidence for aggression subtype-specific alterations in brain structure.
]]></description>
<dc:creator>Naaijen, J.</dc:creator>
<dc:creator>Mulder, L. M.</dc:creator>
<dc:creator>Ilbegi, S.</dc:creator>
<dc:creator>de Bruijn, S.</dc:creator>
<dc:creator>Kleine-Deters, R.</dc:creator>
<dc:creator>Dietrich, A.</dc:creator>
<dc:creator>Hoekstra, P. J.</dc:creator>
<dc:creator>Marsman, J.-B.</dc:creator>
<dc:creator>Aggensteiner, P. M.</dc:creator>
<dc:creator>Holz, N. E.</dc:creator>
<dc:creator>Boettinger, B.</dc:creator>
<dc:creator>Baumeister, S.</dc:creator>
<dc:creator>Banaschewski, T.</dc:creator>
<dc:creator>Saam, M. C.</dc:creator>
<dc:creator>Schulze, U. M.</dc:creator>
<dc:creator>Santosh, P. J.</dc:creator>
<dc:creator>Sagar-Ouriaghli, I.</dc:creator>
<dc:creator>Mastroianni, M.</dc:creator>
<dc:creator>Castro Fornieles, J.</dc:creator>
<dc:creator>Bargallo, N.</dc:creator>
<dc:creator>Rosa, M.</dc:creator>
<dc:creator>Arango, C.</dc:creator>
<dc:creator>Penzol, M. J.</dc:creator>
<dc:creator>Werhahn, J. E.</dc:creator>
<dc:creator>Walitza, S.</dc:creator>
<dc:creator>Brandeis, D.</dc:creator>
<dc:creator>Glennon, J. C.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Zwiers, M. P.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:date>2018-12-08</dc:date>
<dc:identifier>doi:10.1101/490086</dc:identifier>
<dc:title><![CDATA[Reactive/proactive aggression specific cortical and subcortical alterations in children and adolescents with disruptive behavior]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-12-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/477596v1?rss=1">
<title>
<![CDATA[
Dissecting the heterogeneous cortical anatomy of autism spectrum disorder using normative models 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/477596v1?rss=1"
</link>
<description><![CDATA[
BackgroundThe neuroanatomical basis of autism spectrum disorder (ASD) has remained elusive, mostly due to high biological and clinical heterogeneity among diagnosed individuals. Despite considerable effort towards understanding ASD using neuroimaging biomarkers, heterogeneity remains a barrier, partly because studies mostly employ case-control approaches, which assume that the clinical group is homogeneous.nnMethodsHere, we used an innovative normative modelling approach to parse biological heterogeneity in ASD. We aimed to dissect the neuroanatomy of ASD by mapping the deviations from a typical pattern of neuroanatomical development at the level of the individual and to show the necessity to look beyond the case-control paradigm to understand the neurobiology of ASD. We first estimated a vertex-wise normative model of cortical thickness development using Gaussian process regression, then mapped the deviation of each participant from the typical pattern. For this we employed a heterogeneous cross-sectional sample of 206 typically developing (TD) individuals (127 male), and 321 individuals (232 male) with ASD (aged 6-31).nnResultsWe found few case-control differences but the ASD cohort showed highly individualized patterns of deviations in cortical thickness that were widespread across the brain. These deviations correlated with severity of repetitive behaviors and social communicative symptoms, although only repetitive behaviors survived corrections for multiple testing.nnConclusionsOur results: (i) reinforce the notion that individuals with ASD show distinct, highly individualized trajectories of brain development and (ii) show that by focusing on common effects (i.e. the  average ASD participant), the case-control approach disguises considerable inter-individual variation crucial for precision medicine.
]]></description>
<dc:creator>Zabihi, M.</dc:creator>
<dc:creator>Oldehinkel, M.</dc:creator>
<dc:creator>Wolfers, T.</dc:creator>
<dc:creator>Frouin, V.</dc:creator>
<dc:creator>Goyard, D.</dc:creator>
<dc:creator>Loth, E.</dc:creator>
<dc:creator>Charman, T.</dc:creator>
<dc:creator>Tilmann, J.</dc:creator>
<dc:creator>Banaschewski, T.</dc:creator>
<dc:creator>Dumas, G.</dc:creator>
<dc:creator>Holt, R.</dc:creator>
<dc:creator>Baron-Cohen, S.</dc:creator>
<dc:creator>Durston, S.</dc:creator>
<dc:creator>Bolte, S.</dc:creator>
<dc:creator>Murphy, D.</dc:creator>
<dc:creator>Ecker, C.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>Marquand, A. F.</dc:creator>
<dc:date>2018-11-27</dc:date>
<dc:identifier>doi:10.1101/477596</dc:identifier>
<dc:title><![CDATA[Dissecting the heterogeneous cortical anatomy of autism spectrum disorder using normative models]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-11-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/472043v1?rss=1">
<title>
<![CDATA[
A databank for intracellular electrophysiological mapping of the adult somatosensory cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/472043v1?rss=1"
</link>
<description><![CDATA[
BackgroundNeurons in the supragranular layers of the somatosensory cortex integrate sensory (bottom-up) and cognitive/perceptual (top-down) information as they orchestrate communication across cortical columns. It has been inferred, based on intracellular recordings from juvenile animals, that supragranular neurons are electrically mature by the fourth postnatal week. However, the dynamics of the neuronal integration in the adulthood is largely unknown. Electrophysiological characterization of the active properties of these neurons throughout adulthood will help to address the biophysical and computational principles of the neuronal integration.nnFindingsHere we provide a database of whole-cell intracellular recordings from 315 neurons located in the supragranular layers (L2/3) of the primary somatosensory cortex in adult mice (9-45 weeks old) from both sexes (females, N=195; males, N=120). Data include 361 somatic current-clamp (CC) and 476 voltage-clamp (VC) experiments, recorded using a step-and-hold protocol (CC, N=257; VC, N=46), frozen noise injections (CC, N=104) and triangular voltage sweeps (VC, 10 (N=132), 50 (N=146) and 100 ms (N=152)), from regular spiking (N=169) and fast-spiking neurons (N=66).nnConclusionsThe data can be used to systematically study the properties of somatic integration, and the principles of action potential generation across sexes and across electrically characterized neuronal classes in adulthood. Understanding the principles of the somatic transformation of postsynaptic potentials into action potentials will shed light onto the computational principles of intracellular information transfer in single neurons and information processing in neuronal networks, helping to recreate neuronal functions in artificial systems.
]]></description>
<dc:creator>Lantyer, A. d. S.</dc:creator>
<dc:creator>Calcini, N.</dc:creator>
<dc:creator>Biljsma, A.</dc:creator>
<dc:creator>Kole, K.</dc:creator>
<dc:creator>Emmelkamp, M.</dc:creator>
<dc:creator>Peeters, M.</dc:creator>
<dc:creator>Scheenen, W. J. J.</dc:creator>
<dc:creator>Zeldenrust, F.</dc:creator>
<dc:creator>Celikel, T.</dc:creator>
<dc:date>2018-11-17</dc:date>
<dc:identifier>doi:10.1101/472043</dc:identifier>
<dc:title><![CDATA[A databank for intracellular electrophysiological mapping of the adult somatosensory cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-11-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/348276v1?rss=1">
<title>
<![CDATA[
Time-delay model of perceptual decision making in cortical networks 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/348276v1?rss=1"
</link>
<description><![CDATA[
It is known that cortical networks operate on the edge of instability, in which oscillations can appear. However, the influence of this dynamic regime on performance in decision making, is not well understood. In this work, we propose a population model of decision making based on a winner-take-all mechanism. Using this model, we demonstrate that local slow inhibition within the competing neuronal populations can lead to Hopf bifurcation. At the edge of instability, the system exhibits ambiguity in the decision making, which can account for the perceptual switches observed in human experiments. We further validate this model with fMRI datasets from an experiment on semantic priming in perception of ambivalent (male versus female) faces. We demonstrate that the model can correctly predict the drop in the variance of the BOLD within the Superior Parietal Area and Inferior Parietal Area while watching ambiguous visual stimuli.nnAuthor summaryHuman cortex is a complex structure composed of thousands of tangled neural circuits. These circuits exhibit multiple modes of activity, depending on the local balance between excitatory and inhibitory activity. In particular, these circuits can exhibit oscillatory behavior, which is believed to be a manifestation of a so-called criticality: balancing on the edge between stable and unstable dynamics. Circuits in the cortex are responsible for higher cognitive functions such as, in example, perceptual decision making, i.e., evaluating properties of objects appearing in the visual field. However, it is not well known how aforementioned balancing on the edge of instability influences perceptual decision making.nnIn this work, we build a model to simulate dynamics of a very simple decision-making network consisting of two subpopulations. We then demonstrate that criticality in the network can account for ambiguity in decision making, and cause perceptual switches observed in human experiments. We further validate our model with datasets coming from a functional Magnetic Resonance Imaging experiment on semantic priming in perception of ambivalent (male versus female) faces. We demonstrate that the model can correctly predict the drop in the variance of the BOLD within the parietal areas of the cortex while watching ambiguous visual stimuli.
]]></description>
<dc:creator>Bielczyk, N.</dc:creator>
<dc:creator>Piska?a, K.</dc:creator>
<dc:creator>P?omecka, M.</dc:creator>
<dc:creator>Radzi?ski, P.</dc:creator>
<dc:creator>Todorova, L.</dc:creator>
<dc:creator>Fory?, U.</dc:creator>
<dc:date>2018-06-15</dc:date>
<dc:identifier>doi:10.1101/348276</dc:identifier>
<dc:title><![CDATA[Time-delay model of perceptual decision making in cortical networks]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/408252v1?rss=1">
<title>
<![CDATA[
Distinct pathogenic genes causing intellectual disability and autism exhibit overlapping effects on neuronal network development 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/408252v1?rss=1"
</link>
<description><![CDATA[
An intriguing question in medical biology is how mutations in functionally distinct genes can lead to similar clinical phenotypes. For example, patients with mutations in distinct epigenetic regulators EHMT1, MBD5, MLL3 or SMARCB1 share the core clinical features of intellectual disability (ID), autism spectrum disorder (ASD) and facial dysmorphisms. To elucidate how these phenotypic similarities are reflected by convergence at the molecular, cellular and neuronal network level, we directly compared the effects of their loss of function in neurons. Interestingly, knockdown of each gene resulted in hyperactive neuronal networks with altered patterns of synchronized activity. At the single-cell level, we found genotype-specific changes in intrinsic excitability and excitatory-inhibitory balance, but in all cases leading to increased excitability. Congruent with our physiological findings, we identified dysregulated genes that converge on biological and cellular pathways related to neuronal excitability and synaptic function, including genes previously implicated in ID/ASD. Yet, our data suggests that the common cellular phenotypes depend on the ensemble of dysregulated genes engaged in neuronal excitability rather than the direction of transcriptional changes of individual genes. The demonstration of increasing convergence from molecular pathways to neuronal networks may be a paradigm for other types of ID/ASD.
]]></description>
<dc:creator>Frega, M.</dc:creator>
<dc:creator>Selten, M.</dc:creator>
<dc:creator>Mossink, B.</dc:creator>
<dc:creator>Keller, J. M.</dc:creator>
<dc:creator>Linda, K.</dc:creator>
<dc:creator>Moerschen, R.</dc:creator>
<dc:creator>Qu, J.</dc:creator>
<dc:creator>Koerner, P.</dc:creator>
<dc:creator>Jansen, S.</dc:creator>
<dc:creator>Bijvank, E.</dc:creator>
<dc:creator>Oudakker, A.</dc:creator>
<dc:creator>Kleefstra, T.</dc:creator>
<dc:creator>van Bokhoven, H.</dc:creator>
<dc:creator>Zhou, H.</dc:creator>
<dc:creator>Schubert, D.</dc:creator>
<dc:creator>Nadif Kasri, N.</dc:creator>
<dc:date>2018-09-05</dc:date>
<dc:identifier>doi:10.1101/408252</dc:identifier>
<dc:title><![CDATA[Distinct pathogenic genes causing intellectual disability and autism exhibit overlapping effects on neuronal network development]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/449546v1?rss=1">
<title>
<![CDATA[
A genetically encoded fluorescent sensor for rapid and specific in vivo detection ofnorepinephrine 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/449546v1?rss=1"
</link>
<description><![CDATA[
Norepinephrine (NE) and epinephrine (Epi), two key biogenic monoamine neurotransmitters, are involved in a wide range of physiological processes. However, their precise dynamics and regulation remain poorly characterized, in part due to limitations of available techniques for measuring these molecules in vivo. Here, we developed a family of GPCR Activation-Based NE/Epi (GRABNE) sensors with a 230% peak {Delta}F/F0 response to NE, good photostability, nanomolar-to-micromolar sensitivities, sub-second rapid kinetics, high specificity to NE vs. dopamine. Viral- or transgenic- mediated expression of GRABNE sensors were able to detect electrical-stimulation evoked NE release in the locus coeruleus (LC) of mouse brain slices, looming-evoked NE release in the midbrain of live zebrafish, as well as optogenetically and behaviorally triggered NE release in the LC and hypothalamus of freely moving mice. Thus, GRABNE sensors are a robust tool for rapid and specific monitoring of in vivo NE/Epi transmission in both physiological and pathological processes.
]]></description>
<dc:creator>Feng, J.</dc:creator>
<dc:creator>Zhang, C.</dc:creator>
<dc:creator>Lischinsky, J.</dc:creator>
<dc:creator>Jing, M.</dc:creator>
<dc:creator>Zhou, J.</dc:creator>
<dc:creator>Wang, H.</dc:creator>
<dc:creator>Zhang, Y.</dc:creator>
<dc:creator>Dong, A.</dc:creator>
<dc:creator>Wu, Z.</dc:creator>
<dc:creator>Wu, H.</dc:creator>
<dc:creator>Chen, W.</dc:creator>
<dc:creator>Zhang, P.</dc:creator>
<dc:creator>Zou, J.</dc:creator>
<dc:creator>Hires, A.</dc:creator>
<dc:creator>Zhu, J.</dc:creator>
<dc:creator>Cui, G.</dc:creator>
<dc:creator>Lin, D.</dc:creator>
<dc:creator>Du, J.</dc:creator>
<dc:creator>Li, Y.</dc:creator>
<dc:date>2018-10-23</dc:date>
<dc:identifier>doi:10.1101/449546</dc:identifier>
<dc:title><![CDATA[A genetically encoded fluorescent sensor for rapid and specific in vivo detection ofnorepinephrine]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-10-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/443846v1?rss=1">
<title>
<![CDATA[
Perceptual phenotypes: Perceptual gains and losses in synesthesia and schizophrenia 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/443846v1?rss=1"
</link>
<description><![CDATA[
Individual differences in perception are widespread. Considering inter-individual variability, synesthetes experience stable additional sensations; schizophrenia patients suffer perceptual deficits in e.g. perceptual organization (alongside hallucinations and delusions). Is there a unifying principle explaining inter-individual variability in perception? There is good reason to believe perceptual experience results from inferential processes whereby sensory evidence is weighted by prior knowledge about the world. Different perceptual phenotypes may result from different precision weighting of sensory evidence and prior knowledge. We tested this hypothesis by comparing visibility thresholds in a perceptual hysteresis task across medicated schizophrenia patients, synesthetes, and controls. Participants rated the subjective visibility of stimuli embedded in noise while we parametrically manipulated the availability of sensory evidence. Additionally, precise long-term priors in synesthetes were leveraged by presenting either synesthesia-inducing or neutral stimuli. Schizophrenia patients showed increased visibility thresholds, consistent with overreliance on sensory evidence. In contrast, synesthetes exhibited lowered thresholds exclusively for synesthesia-inducing stimuli suggesting high-precision long-term priors. Additionally, in both synesthetes and schizophrenia patients explicit, short-term priors - introduced during the hysteresis experiment - lowered thresholds but did not normalize perception. Our results imply that distinct perceptual phenotypes might result from differences in the precision afforded to prior beliefs and sensory evidence, respectively.
]]></description>
<dc:creator>van Leeuwen, T. M.</dc:creator>
<dc:creator>Sauer, A.</dc:creator>
<dc:creator>Jurjut, A.-M.</dc:creator>
<dc:creator>Wibral, M.</dc:creator>
<dc:creator>Uhlhaas, P.</dc:creator>
<dc:creator>Singer, W.</dc:creator>
<dc:creator>Melloni, L.</dc:creator>
<dc:date>2018-10-16</dc:date>
<dc:identifier>doi:10.1101/443846</dc:identifier>
<dc:title><![CDATA[Perceptual phenotypes: Perceptual gains and losses in synesthesia and schizophrenia]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-10-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/441089v1?rss=1">
<title>
<![CDATA[
Brain responses to anticipating and receiving beer: Comparing light, at-risk, and dependent alcohol users 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/441089v1?rss=1"
</link>
<description><![CDATA[
BackgroundImpaired brain processing of alcohol-related rewards has been suggested to play a central role in alcohol use disorder. Yet, evidence remains inconsistent, and mainly originates from studies in which participants passively observe alcohol cues or taste alcohol. Here we designed a protocol in which beer consumption was predicted by incentive cues and contingent on instrumental action, closer to real life situations. We predicted that anticipating and receiving beer (compared with water) would elicit activity in the brain reward network, and that this activity would correlate with drinking level across participants.nnMethodsThe sample consisted of 150 beer-drinking males, aged 18-25 years. Three groups were defined based on AUDIT scores: light drinkers (n=40), at-risk drinkers (n=63), and dependent drinkers (n=47). fMRI measures were obtained while participants engaged in the Beer Incentive Delay task involving beer- and water-predicting cues, followed by real sips of beer or water.nnResultsDuring anticipation, outcome notification and delivery of beer compared with water, higher activity was found in a reward-related brain network including the medial prefrontal cortex, orbitofrontal cortex and amygdala. Yet, no activity was observed in the striatum, and no differences were found between the groups.nnConclusionsOur results reveal that anticipating, obtaining and tasting beer activates parts of the brain reward network, but that these brain responses do not differentiate between different drinking levels. We speculate that other factors, such as cognitive control or sensitivity to social context, may be more discriminant predictors of drinking behaviour in young adults.
]]></description>
<dc:creator>Groefsema, M.</dc:creator>
<dc:creator>Engels, R.</dc:creator>
<dc:creator>Voon, V.</dc:creator>
<dc:creator>Schellekens, A.</dc:creator>
<dc:creator>Luijten, M.</dc:creator>
<dc:creator>Sescousse, G.</dc:creator>
<dc:date>2018-10-13</dc:date>
<dc:identifier>doi:10.1101/441089</dc:identifier>
<dc:title><![CDATA[Brain responses to anticipating and receiving beer: Comparing light, at-risk, and dependent alcohol users]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-10-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/437582v1?rss=1">
<title>
<![CDATA[
Integrative Network and Brain Expression Analysis reveals Mechanistic Modules in Ataxia 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/437582v1?rss=1"
</link>
<description><![CDATA[
Background: Genetic forms of ataxia are a heterogenous group of degenerative diseases of the cerebellum. Many causative genes have been identified, but a systematic investigation of these genes to understand ataxia pathophysiology has not been performed. Methods: A manually curated catalogue of 71 genes involved in disorders with progressive ataxias as a major clinical feature was subjected to an integrated gene ontology (GO), protein network, and brain gene expression profiling analysis. Results: We found that ataxia genes operate in networks with significantly enriched protein connectivity, demonstrating coherence on a global level, independent of inheritance mode. Moreover, elevated expression specifically in the cerebellum predisposes to ataxia. Genes expressed in this pattern are significantly overrepresented among ataxia genes and are enriched for ion homeostasis/synaptic functions. The majority of ataxia genes, however, does not show elevated cerebellar expression that could account for region-specific degeneration. For these, we identified defective cellular stress responses as a major common biological theme, suggesting that the defense pathways against stress are more critical to maintain cerebellar integrity than integrity of other brain regions. Approximately half of the ataxia genes, mostly part of the stress module, show higher expression at embryonic stages, which argues for a developmental predisposition. Conclusion: Genetic defects in ataxia predominantly affect neuronal homeostasis, to which the cerebellum appears to be excessively susceptible. Based on the identified modules, it is conceivable to propose common therapeutic interventions that target deregulated calcium and ROS levels, or mechanisms that can decrease the harmful downstream effects of these deleterious insults.
]]></description>
<dc:creator>Eidhof, I.</dc:creator>
<dc:creator>van de Warrenburg, B.</dc:creator>
<dc:creator>Schenck, A.</dc:creator>
<dc:date>2018-10-08</dc:date>
<dc:identifier>doi:10.1101/437582</dc:identifier>
<dc:title><![CDATA[Integrative Network and Brain Expression Analysis reveals Mechanistic Modules in Ataxia]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-10-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/428292v1?rss=1">
<title>
<![CDATA[
The functional organisation of the hippocampus along its long axis is gradual and predicts recollection 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/428292v1?rss=1"
</link>
<description><![CDATA[
Understanding the functional organisation of the hippocampus is crucial for understanding its role in cognition and disorders in which it is implicated. Different views have been proposed of how function is distributed along its long axis: one view suggests segregation, whereas the alternative view postulates a more gradual organisation. Here, we applied a novel  connectopic mapping data-analysis approach to the resting-state fMRI data of participants of the Human Connectome Project, and demonstrate that the functional organisation of the hippocampal longitudinal axis is gradual rather than segregated into parcels. In addition, we show that inter-individual variations in this gradual organisation predicts variations in recollection memory better than a characterisation based on parcellation. These results present an important step forward in understanding the functional organisation of the human hippocampus and have important implications for translating between rodent and human research.
]]></description>
<dc:creator>Przezdzik, I.</dc:creator>
<dc:creator>Faber, M.</dc:creator>
<dc:creator>Fernandez, G.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>Haak, K. V.</dc:creator>
<dc:date>2018-09-27</dc:date>
<dc:identifier>doi:10.1101/428292</dc:identifier>
<dc:title><![CDATA[The functional organisation of the hippocampus along its long axis is gradual and predicts recollection]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/427302v1?rss=1">
<title>
<![CDATA[
Macaque anterior cingulate cortex deactivation impairs performance and alters lateral prefrontal oscillatory activities in a rule-switching task 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/427302v1?rss=1"
</link>
<description><![CDATA[
In primates, both the dorsal anterior cingulate cortex (dACC) and the dorsolateral prefrontal cortex (dlPFC) are key regions of the frontoparietal cognitive control network. To study the role of the dACC and its communication with the dlPFC in cognitive control, we recorded the local field potentials from the dlPFC before and during the reversible deactivation of the dACC, in macaque monkeys engaging in uncued switches between two stimulus-response rules. Cryogenic dACC deactivation impaired response accuracy during rule-maintenance, but not rule-switching, which coincided with a reduction in the correct-error difference in dlPFC beta activities specifically during maintenance of the more challenging rule. During both rule switching and maintenance, dACC deactivation prolonged the animals reaction time and reduced task-related theta/alpha activities in the dlPFC; it also weakened dlPFC theta-gamma phase-amplitude modulation. Thus, the dACC and its interaction with the dlPFC plays a critical role in the maintenance of a new, challenging rule.
]]></description>
<dc:creator>Ma, L.</dc:creator>
<dc:creator>Chan, J.</dc:creator>
<dc:creator>Johnston, K.</dc:creator>
<dc:creator>Lomber, S.</dc:creator>
<dc:creator>Everling, S.</dc:creator>
<dc:date>2018-09-25</dc:date>
<dc:identifier>doi:10.1101/427302</dc:identifier>
<dc:title><![CDATA[Macaque anterior cingulate cortex deactivation impairs performance and alters lateral prefrontal oscillatory activities in a rule-switching task]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/424127v1?rss=1">
<title>
<![CDATA[
Microstimulation in a spiking neural network model of the midbrain superior colliculus 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/424127v1?rss=1"
</link>
<description><![CDATA[
The midbrain superior colliculus (SC) generates a rapid saccadic eye movement to a sensory stimulus by recruiting a population of cells in its topographically organized motor map. Supra-threshold electrical microstimulation in the SC reveals that the site of stimulation produces a normometric saccade vector with little effect of the stimulation parameters. Moreover, electrically evoked saccades (E-saccades) have kinematic properties that strongly resemble natural, visual-evoked saccades (V-saccades). These findings support models in which the saccade vector is determined by a center-of-gravity computation of activated neurons, while its trajectory and kinematics arise from downstream feedback circuits in the brainstem. Recent single-unit recordings, however, have indicated that the SC population also specifies instantaneous kinematics. These results support an alternative model, in which the desired saccade trajectory, including its kinematics, follows from instantaneous summation of movement effects of all SC spike trains. But how to reconcile this model with microstimulation results? Although it is thought that microstimulation activates a large population of SC neurons, the mechanism through which it arises is unknown. We developed a spiking neural network model of the SC, in which microstimulation directly activates a relatively small set of neurons around the electrode tip, which subsequently sets up a large population response through lateral synaptic interactions. We show that through this mechanism the population drives an E-saccade with near-normal kinematics that are largely independent of the stimulation parameters. Only at very low stimulus intensities the network recruits a population with low firing rates, resulting in abnormally slow saccades.nnAuthor SummaryThe midbrain Superior Colliculus (SC) contains a topographically organized map for rapid goal-directed gaze shifts, in which the location of the active population determines size and direction of the eye-movement vector, and the neural firing rates specify the eye-movement kinematics. Electrical microstimulation in this map produces eye movements that correspond to the site of stimulation with normal kinematics. We here explain how intrinsic lateral interactions within the SC network of spiking neurons sets up the population activity profile in response to local microstimulation to explain these results.
]]></description>
<dc:creator>Van Opstal, A. J.</dc:creator>
<dc:creator>Kasap, B.</dc:creator>
<dc:date>2018-09-21</dc:date>
<dc:identifier>doi:10.1101/424127</dc:identifier>
<dc:title><![CDATA[Microstimulation in a spiking neural network model of the midbrain superior colliculus]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/421743v1?rss=1">
<title>
<![CDATA[
How the level of reward awareness changes the computational and electrophysiological signatures of reinforcement learning 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/421743v1?rss=1"
</link>
<description><![CDATA[
The extent to which subjective awareness influences reward processing, and thereby affects future decisions is currently largely unknown. In the present report, we investigated this question in a reinforcement-learning framework, combining perceptual masking, computational modeling and electroencephalographic recordings (human male and female participants). Our results indicate that degrading the visibility of the reward decreased -without completely obliterating- the ability of participants to learn from outcomes, but concurrently increased their tendency to repeat previous choices. We dissociated electrophysiological signatures evoked by the reward-based learning processes from those elicited by the reward-independent repetition of previous choices and showed that these neural activities were significantly modulated by reward visibility. Overall, this report sheds new light on the neural computations underlying reward-based learning and decision-making and highlights that awareness is beneficial for the trial-by-trial adjustment of decision-making strategies.nnSignificance statementThe notion of reward is strongly associated with subjective evaluation, related to conscious processes such as "pleasure", "liking" and "wanting". Here we show that degrading reward visibility in a reinforcement learning task decreases -without completely obliterating- the ability of participants to learn from outcomes, but concurrently increases subjects tendency to repeat previous choices. Electrophysiological recordings, in combination with computational modelling, show that neural activities were significantly modulated by reward visibility. Overall, we dissociate different neural computations underlying reward-based learning and decision-making, which highlights a beneficial role of reward awareness in adjusting decision-making strategies.
]]></description>
<dc:creator>Correa, C.</dc:creator>
<dc:creator>Noorman, S.</dc:creator>
<dc:creator>Jiang, J.</dc:creator>
<dc:creator>Palminteri, S.</dc:creator>
<dc:creator>Cohen, M. X.</dc:creator>
<dc:creator>Lebreton, M.</dc:creator>
<dc:creator>van Gaal, S.</dc:creator>
<dc:date>2018-09-19</dc:date>
<dc:identifier>doi:10.1101/421743</dc:identifier>
<dc:title><![CDATA[How the level of reward awareness changes the computational and electrophysiological signatures of reinforcement learning]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/416404v1?rss=1">
<title>
<![CDATA[
Sentence processing is modulated by the current linguistic environment and a priori information: An fMRI study 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/416404v1?rss=1"
</link>
<description><![CDATA[
Words are not processed in isolation but in rich contexts that are used to modulate and facilitate language comprehension. Here, we investigate distinct neural networks underlying two types of contexts. Firstly, the current linguistic environment, presented as the relative frequencies of two syntactic structures (prepositional object (PO) and double-object (DO)), which would either follow everyday linguistic experience or not. Secondly, preference towards one or the other structure depending on the verb; learned in everyday language use and stored in memory. German participants were reading PO and DO sentences in German while brain activity was measured with functional magnetic resonance imaging. Firstly, the anterior cingulate cortex (ACC) showed a pattern of activation that integrated the current linguistic environment with everyday linguistic experience. When the input did not match everyday experience, the unexpectedly frequent structure showed higher activation in the ACC than the other conditions and more connectivity from the ACC to posterior parts of the language network. Secondly, verb-based surprisal of seeing a structure given a verb (PO verb preference but DO structure presentation) resulted, within the language network (left inferior frontal and left middle/superior temporal gyrus) and the precuneus, in increased activation compared to a predictable situation. In conclusion, 1) beyond the canonical language network, brain areas engaged in cognitive control, such as the ACC, might use the statistics of syntactic structures to facilitate language comprehension, 2) the language network is directly engaged in processing verb preferences. These two networks show distinct influences on sentence processing.
]]></description>
<dc:creator>Weber, K.</dc:creator>
<dc:creator>Micheli, C.</dc:creator>
<dc:creator>Ruigendijk, E.</dc:creator>
<dc:creator>Rieger, J.</dc:creator>
<dc:date>2018-09-14</dc:date>
<dc:identifier>doi:10.1101/416404</dc:identifier>
<dc:title><![CDATA[Sentence processing is modulated by the current linguistic environment and a priori information: An fMRI study]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/416321v1?rss=1">
<title>
<![CDATA[
Evaluating the evidence for biotypes of depression: attempted replication of Drysdale et.al. 2017 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/416321v1?rss=1"
</link>
<description><![CDATA[
BackgroundPsychiatric disorders are highly heterogeneous, defined based on symptoms with little connection to potential underlying biological mechanisms. A possible approach to dissect biological heterogeneity is to look for biologically meaningful subtypes. A recent study Drysdale et al. (2017) showed promising results along this line by simultaneously using resting state fMRI and clinical data and identified four distinct subtypes of depression with different clinical profiles and abnormal resting state fMRI connectivity. These subtypes were predictive of treatment response to transcranial magnetic stimulation therapy.nnObjectiveHere, we attempted to replicate the procedure followed in the Drysdale et al. study and their findings in an independent dataset of a clinically more heterogeneous sample of 187 participants with depression and anxiety. We aimed to answer the following questions: 1) Using the same procedure, can we find a statistically significant and reliable relationship between brain connectivity and clinical symptoms? 2) Is the observed relationship similar to the one found in the original study? 3) Can we identify distinct and reliable subtypes? 4) Do they have similar clinical profiles as the subtypes identified in the original study?nnMethodsWe followed the original procedure as closely as possible, including a canonical correlation analysis to find a low dimensional representation of clinically relevant resting state fMRI features, followed by hierarchical clustering to identify subtypes. We extended the original procedure using additional statistical tests, to test the statistical significance of the relationship between resting state fMRI and clinical data, and the existence of distinct subtypes. Furthermore, we examined the stability of the whole procedure using resampling.nnResults and ConclusionWe were not able to replicate the findings of the original study. Relationships between brain connectivity and clinical symptoms were not statistically significant and we also did not find clearly distinct subtypes of depression. We argue, that based on our rigorous approach and in-depth review of the original results, that the evidence for the existence of the distinct resting state connectivity based subtypes of depression is weak and should be interpreted with caution.
]]></description>
<dc:creator>Dinga, R.</dc:creator>
<dc:creator>Schmaal, L.</dc:creator>
<dc:creator>Penninx, B.</dc:creator>
<dc:creator>van Tol, M. J.</dc:creator>
<dc:creator>Veltman, D.</dc:creator>
<dc:creator>van Velzen, L.</dc:creator>
<dc:creator>van der Wee, N.</dc:creator>
<dc:creator>Marquand, A.</dc:creator>
<dc:date>2018-09-14</dc:date>
<dc:identifier>doi:10.1101/416321</dc:identifier>
<dc:title><![CDATA[Evaluating the evidence for biotypes of depression: attempted replication of Drysdale et.al. 2017]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/413286v1?rss=1">
<title>
<![CDATA[
Cortico-basal-ganglia communication: Temporally structured activity for selective motor control 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/413286v1?rss=1"
</link>
<description><![CDATA[
Despite the hard-wired structural connectivity of neural pathways, neural circuits allow context-dependent reactions to sensory cues by triggering the desired movement. Cortico-basal-ganglia circuits seem particularly important for flexible motor control as this is impaired in Parkinsons disease (PD). We analysed subthalamic nucleus (STN) spike and cortical ECoG activity from PD patients performing a visually-cued hand grip task. Fast reaction times were preceded by enhanced STN spike-to-cortical gamma phase coupling irrespective of firing rate changes, suggesting a role of gamma coupling in motor preparation. STN spike timing was offset by half a cycle when comparing ipsilateral with contralateral movements. Additionally, cortical high-frequency activity increased more steeply within each gamma cycle at the sites that showed the strongest coupling with STN spikes. Cortico-basal-ganglia gamma coupling may thus help shape neural activity to facilitate selective motor control. The observation that this effect occurs independent of changes in mean firing rate has far-reaching implications.nnHighlightsO_LIFast RTs were preceded by enhanced STN spike-to-cortical gamma phase couplingnC_LIO_LISTN spike probability was significantly modulated relative to the gamma cyclenC_LIO_LIDuring ipsilateral movement, spikes were more likely at the opposite part of the cyclenC_LIO_LISTN output may thus help shape cortical gamma for selective motor controlnC_LI
]]></description>
<dc:creator>Fischer, P.</dc:creator>
<dc:creator>Lipski, W.</dc:creator>
<dc:creator>Neumann, W.-J.</dc:creator>
<dc:creator>Turner, R. S.</dc:creator>
<dc:creator>Fries, P.</dc:creator>
<dc:creator>Brown, P.</dc:creator>
<dc:creator>Richardson, R. M.</dc:creator>
<dc:date>2018-09-11</dc:date>
<dc:identifier>doi:10.1101/413286</dc:identifier>
<dc:title><![CDATA[Cortico-basal-ganglia communication: Temporally structured activity for selective motor control]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/413104v1?rss=1">
<title>
<![CDATA[
Inter-individual differences in human brain structure and morphometry link to population variation in demographics and behavior 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/413104v1?rss=1"
</link>
<description><![CDATA[
We perform a comprehensive integrative analysis of multiple structural MR-based brain features and find strong evidence relating inter-individual structural variations to demographic and behavioral variates across a large cohort of healthy human volunteers. In particular, our findings shed some light on functional & structural integration, as we find a mode of structural variation that relates to and extends the  positive-negative behavioral spectrum which was recently reported as being associated with variations in functional connectivity.nnSignificance statementThis work provides for the first-time strong evidence relating human brain structure variations to a wide range of demographic and behavioral measures. We show that several measures previously associated to variation in functional MRI connectivity are in fact already associated at the structural level, pointing towards structure-function integration.
]]></description>
<dc:creator>Llera Arenas, A.</dc:creator>
<dc:creator>Wolfers, T.</dc:creator>
<dc:creator>Mulders, P.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:date>2018-09-11</dc:date>
<dc:identifier>doi:10.1101/413104</dc:identifier>
<dc:title><![CDATA[Inter-individual differences in human brain structure and morphometry link to population variation in demographics and behavior]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-09-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/405696v1?rss=1">
<title>
<![CDATA[
Anodal Transcranial Direct Current Stimulation (tDCS) of hMT+ Does Not Affect Motion Perception Learning 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/405696v1?rss=1"
</link>
<description><![CDATA[
BackgroundHuman visual cortical area hMT+, like its homologue MT in the macaque monkey, has been shown to be particularly selective to visual motion. After damage to the primary visual cortex (V1), patients often exhibit preserved ability to detect moving stimuli, which is associated with neural activity in area hMT+. As an anatomical substrate underlying residual function in the absence of V1, promoting functional plasticity in hMT+ could potentially boost visual performance despite cortical damage.nnObjectiveTo establish in healthy participants whether it is possible to use transcranial direct current stimulation (tDCS) over hMT+ to potentiate learning of visual motion direction discrimination.nnMethodsParticipants were trained daily for five days on a visual motion direction discrimination task. Task difficulty was increased as performance improved, by decreasing the proportion of coherently moving dots, such that participants were always performing at psychophysical threshold. tDCS, either anodal or sham, was applied daily during the 20-minute training session. Task performance was assessed at baseline and at the end of the training period.nnResultsAll participants showed improved task performance both during and after training. Contrary to our hypothesis, anodal tDCS did not further improve performance compared to sham stimulation. Bayesian statistics indicated significant evidence in favour of the null hypothesis.nnConclusionAnodal tDCS to hMT+ does not enhance visual motion direction discrimination learning in the young healthy visual system.
]]></description>
<dc:creator>Larcombe, S.</dc:creator>
<dc:creator>Kennard, C.</dc:creator>
<dc:creator>O'Shea, J.</dc:creator>
<dc:creator>Bridge, H.</dc:creator>
<dc:date>2018-08-31</dc:date>
<dc:identifier>doi:10.1101/405696</dc:identifier>
<dc:title><![CDATA[Anodal Transcranial Direct Current Stimulation (tDCS) of hMT+ Does Not Affect Motion Perception Learning]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/322008v1?rss=1">
<title>
<![CDATA[
Lead-DBS v2: Toward a comprehensive pipeline for deep brain stimulation imaging 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/322008v1?rss=1"
</link>
<description><![CDATA[
Deep brain stimulation (DBS) is a highly efficacious treatment option for movement disorders and a growing number of other indications are investigated in clinical trials. To ensure optimal treatment outcome, exact electrode placement is required. Moreover, to analyze the relationship between electrode location and clinical results, a precise reconstruction of electrode placement is required, posing specific challenges to the field of neuroimaging. Since 2014 the open source toolbox Lead-DBS is available, which aims at facilitating this process. The tool has since become a popular platform for DBS imaging. With support of a broad community of researchers worldwide, methods have been continuously updated and complemented by new tools for tasks such as multispectral nonlinear registration, structural / functional connectivity analyses, brain shift correction, reconstruction of microelectrode recordings and orientation detection of segmented DBS leads. The rapid development and emergence of these methods in DBS data analysis require us to revisit and revise the pipelines introduced in the original methods publication. Here we demonstrate the updated DBS and connectome pipelines of Lead-DBS using a single patient example with state-of-the-art high-field imaging as well as a retrospective cohort of patients scanned in a typical clinical setting at 1.5T. Imaging data of the 3T example patient is co-registered using five algorithms and nonlinearly warped into template space using ten approaches for comparative purposes. After reconstruction of DBS electrodes (which is possible using three methods and a specific refinement tool), the volume of tissue activated is calculated for two DBS settings using four distinct models and various parameters. Finally, four whole-brain tractography algorithms are applied to the patients preoperative diffusion MRI data and structural as well as functional connectivity between the stimulation volume and other brain areas are estimated using a total of eight approaches and datasets. In addition, we demonstrate impact of selected preprocessing strategies on the retrospective sample of 51 PD patients. We compare the amount of variance in clinical improvement that can be explained by the computer model depending on the method of choice.nnThis work represents a multi-institutional collaborative effort to develop a comprehensive, open source pipeline for DBS imaging and connectomics, which has already empowered several studies, and may facilitate a variety of future studies in the field.
]]></description>
<dc:creator>Horn, A.</dc:creator>
<dc:creator>Li, N.</dc:creator>
<dc:creator>Dembek, T. A.</dc:creator>
<dc:creator>Kappel, A.</dc:creator>
<dc:creator>Boulay, C.</dc:creator>
<dc:creator>Ewert, S.</dc:creator>
<dc:creator>Tietze, A.</dc:creator>
<dc:creator>Husch, A.</dc:creator>
<dc:creator>Perera, T.</dc:creator>
<dc:creator>Neumann, W.-J.</dc:creator>
<dc:creator>Reisert, M.</dc:creator>
<dc:creator>Si, H.</dc:creator>
<dc:creator>Oostenveld, R.</dc:creator>
<dc:creator>Rorden, C.</dc:creator>
<dc:creator>Yeh, F.-C.</dc:creator>
<dc:creator>Fang, Q.</dc:creator>
<dc:creator>Herrington, T. M.</dc:creator>
<dc:creator>Vorwerk, J.</dc:creator>
<dc:creator>Kuehn, A. A.</dc:creator>
<dc:date>2018-05-15</dc:date>
<dc:identifier>doi:10.1101/322008</dc:identifier>
<dc:title><![CDATA[Lead-DBS v2: Toward a comprehensive pipeline for deep brain stimulation imaging]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-05-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/401174v1?rss=1">
<title>
<![CDATA[
The context-dependent nature of the neural implementation of intentions 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/401174v1?rss=1"
</link>
<description><![CDATA[
Many studies have identified networks in parietal and prefrontal cortex that are involved in intentional action. Yet, knowledge about what these networks exactly encoded is still scarce. In this study we look into the content of those processes. We ask whether the neural representations of intentions are context- and reason-invariant, or whether these processes depend on the context we are in, and the reasons we have for choosing an action. We use a combination of functional magnetic resonance imaging and multivariate decoding to directly assess the context- and reason-dependency of the processes underlying intentional action. We were able to decode action decisions in the same context and for the same reasons from the fMRI data, in line with previous decoding studies. Furthermore, we could decode action decisions across different reasons for choosing an action. Importantly, though, decoding decisions across different contexts was at chance level. These results suggest that for voluntary action, there is considerable context-dependency in intention representations. This suggests that established invariance in neural processes may not reflect an essential feature of a certain process, but that this stable character could be dependent on invariance in the experimental setup, in line with predictions from situated cognition theory.
]]></description>
<dc:creator>Uithol, S.</dc:creator>
<dc:creator>Goergen, K.</dc:creator>
<dc:creator>Pischedda, D.</dc:creator>
<dc:creator>Toni, I.</dc:creator>
<dc:creator>Haynes, J.-D.</dc:creator>
<dc:date>2018-08-27</dc:date>
<dc:identifier>doi:10.1101/401174</dc:identifier>
<dc:title><![CDATA[The context-dependent nature of the neural implementation of intentions]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/399840v1?rss=1">
<title>
<![CDATA[
Perceptual inference employs intrinsic alpha frequency to resolve perceptual ambiguity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/399840v1?rss=1"
</link>
<description><![CDATA[
The brain uses its intrinsic dynamics to actively predict observed sensory inputs, especially under perceptual ambiguity. However, it remains unclear how this inference process is neurally implemented in biasing perception of ambiguous inputs towards the predicted percepts. Using electroencephalography and intracranial recordings, we first show that the alpha-band frequency defines a unified time window for perceptual grouping across both space and time: information segments, either spatially or temporally segregated, will be integrated if they fall within the same alpha cycle. Moreover, predictions employ this prior knowledge on intrinsic alpha frequency to shift perceptual inference towards the most possibly observed percepts. Multivariate decoding analysis showed that perceptual inference, based on variance in prestimulus alpha frequency (PAF), biases post-stimulus neural representations by inducing preactivation of the predicted percepts. fMRI results additionally showed that prestimulus activity and intrinsic organization status in the frontoparietal attentional network predict perceptual outcomes, probably by modulating occipitoparietal PAFs.
]]></description>
<dc:creator>Shen, L.</dc:creator>
<dc:creator>Han, B.</dc:creator>
<dc:creator>Chen, L.</dc:creator>
<dc:creator>Chen, Q.</dc:creator>
<dc:date>2018-08-24</dc:date>
<dc:identifier>doi:10.1101/399840</dc:identifier>
<dc:title><![CDATA[Perceptual inference employs intrinsic alpha frequency to resolve perceptual ambiguity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/397026v1?rss=1">
<title>
<![CDATA[
Speaker-normalized vowel representations in the human auditory cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/397026v1?rss=1"
</link>
<description><![CDATA[
Humans identify speech sounds, the fundamental building blocks of spoken language, using the same cues, or acoustic dimensions, as those that differentiate the voices of different speakers. The correct interpretation of speech cues is hence uncertain, and requires normalizing to the specific speaker. Here we assess how the human brain uses speaker-related contextual information to constrain the processing of speech cues. Using high-density electrocorticography, we recorded local neural activity from the cortical surface of participants who were engaged in a speech sound identification task. The speech sounds were preceded by speech from different speakers whose voices differed along the same acoustic dimension that differentiated the target speech sounds (the first formant; the lowest resonance frequency of the vocal tract). We found that the same acoustic speech sound tokens were perceived differently, and evoked different neural responses in auditory cortex, when they were heard in the context of different speakers. Such normalization involved the rescaling of acoustic-phonetic representations of speech, demonstrating a form of recoding before the signal is mapped onto phonemes or higher level linguistic units. This process is the result of auditory cortex sensitivity to the contrast between the dominant frequencies in speech sounds and those in their just preceding context. These findings provide important insights into the mechanistic implementation of normalization in human listeners. Moreover, they provide the first direct evidence of speaker-normalized speech sound representations in human parabelt auditory cortex, highlighting its critical role in resolving variability in sensory signals.
]]></description>
<dc:creator>Sjerps, M. J.</dc:creator>
<dc:creator>Fox, N. P.</dc:creator>
<dc:creator>Johnson, K.</dc:creator>
<dc:creator>Chang, E. F.</dc:creator>
<dc:date>2018-08-22</dc:date>
<dc:identifier>doi:10.1101/397026</dc:identifier>
<dc:title><![CDATA[Speaker-normalized vowel representations in the human auditory cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/397182v1?rss=1">
<title>
<![CDATA[
A better way to define and describe Morlet wavelets for time-frequency analysis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/397182v1?rss=1"
</link>
<description><![CDATA[
Morlet wavelets are frequently used for time-frequency analysis of non-stationary time series data, such as neuroelectrical signals recorded from the brain. The crucial parameter of Morlet wavelets is the width of the Gaussian that tapers the sine wave. This width parameter controls the trade-off between temporal precision and frequency precision. It is typically defined as the "number of cycles," but this parameter is opaque, and often leads to uncertainty and suboptimal analysis choices, as well as being difficult to interpret and evaluate. The purpose of this paper is to present alternative formulations of Morlet wavelets in time and in frequency that allow parameterizing the wavelets directly in terms of the desired temporal and spectral smoothing (as full-width at half-maximum). This formulation provides clarity on an important data analysis parameter, and should facilitate proper analyses, reporting, and interpretation of results. MATLAB code is provided.
]]></description>
<dc:creator>Cohen, M. X.</dc:creator>
<dc:date>2018-08-21</dc:date>
<dc:identifier>doi:10.1101/397182</dc:identifier>
<dc:title><![CDATA[A better way to define and describe Morlet wavelets for time-frequency analysis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/238584v1?rss=1">
<title>
<![CDATA[
MEG sensor patterns reflect perceptual but not categorical similarity of animate and inanimate objects 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/238584v1?rss=1"
</link>
<description><![CDATA[
Human high-level visual cortex shows a distinction between animate and inanimate objects, as revealed by fMRI. Recent studies have shown that object animacy can similarly be decoded from MEG sensor patterns. Which object properties drive this decoding? Here, we disentangled the influence of perceptual and categorical object properties by presenting perceptually matched objects (e.g., snake and rope) that were nonetheless easily recognizable as being animate or inanimate. In a series of behavioral experiments, three aspects of perceptual dissimilarity of these objects were quantified: overall dissimilarity, outline dissimilarity, and texture dissimilarity. Neural dissimilarity of MEG sensor patterns was modeled using regression analysis, in which perceptual dissimilarity (from the behavioral experiments) and categorical dissimilarity served as predictors of neural dissimilarity. We found that perceptual dissimilarity was strongly reflected in MEG sensor patterns from 80ms after stimulus onset, with separable contributions of outline and texture dissimilarity. Surprisingly, when controlling for perceptual dissimilarity, MEG patterns did not carry information about object category (animate vs inanimate) at any time point. Nearly identical results were found in a second MEG experiment that required basic-level object recognition. These results suggest that MEG sensor patterns do not capture object animacy independently of perceptual differences between animate and inanimate objects. This is in contrast to results observed in fMRI using the same stimuli, task, and analysis approach: fMRI showed a highly reliable categorical distinction in visual cortex even when controlling for perceptual dissimilarity. Results thus point to a discrepancy in the information contained in multivariate fMRI and MEG patterns.
]]></description>
<dc:creator>Proklova, D.</dc:creator>
<dc:creator>Kaiser, D.</dc:creator>
<dc:creator>Peelen, M.</dc:creator>
<dc:date>2017-12-24</dc:date>
<dc:identifier>doi:10.1101/238584</dc:identifier>
<dc:title><![CDATA[MEG sensor patterns reflect perceptual but not categorical similarity of animate and inanimate objects]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-12-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/391805v1?rss=1">
<title>
<![CDATA[
The Subjective Value of Cognitive Effort is Encoded by a Domain-General Valuation Network 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/391805v1?rss=1"
</link>
<description><![CDATA[
Cognitive control is necessary for goal-directed behavior, yet people treat control as costly, discounting goal value by cognitive demands in a similar manner as they would for delayed or risky outcomes. It is unclear, however, whether a putatively domain-general valuation network implicated in other cost domains also encodes the subjective value (SV) of cognitive effort. Here, we demonstrate that a valuation network, centered on the ventromedial prefrontal cortex and ventral striatum, also encodes SV during cognitive effort-based decision-making. We doubly dissociate this network from a primarily frontoparietal network recruited as a function of decision difficulty. We also find evidence that SV signals predict choice and are influenced by state and trait motivation, including sensitivity to reward and anticipated task performance. These findings unify cognitive effort with other cost domains, and inform physiological mechanisms of SV representations underlying the willingness to expend cognitive effort.
]]></description>
<dc:creator>Westbrook, A.</dc:creator>
<dc:creator>Lamichhane, B.</dc:creator>
<dc:creator>Braver, T.</dc:creator>
<dc:date>2018-08-14</dc:date>
<dc:identifier>doi:10.1101/391805</dc:identifier>
<dc:title><![CDATA[The Subjective Value of Cognitive Effort is Encoded by a Domain-General Valuation Network]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/390807v1?rss=1">
<title>
<![CDATA[
Spatial attention follows category-based attention during naturalistic visual search: evidence from MEG decoding 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/390807v1?rss=1"
</link>
<description><![CDATA[
In daily life, attention is often directed to high-level object attributes, such as when we look out for cars before crossing a road. Previous work used MEG decoding to investigate the influence of such category-based attention on the time course of object category representations. Attended object categories were more strongly represented than unattended categories from 180 ms after scene onset. In the present study, we used a similar approach to determine when, relative to this category-level modulation, attention is spatially focused on the target. Participants completed two tasks. In the first, they detected cars and people at varying locations in photographs of real-world scenes. In the second, they detected a cross that appeared at salient locations in an array of lines. Multivariate classifiers were trained on data of the artificial salience experiment and tested on data of the naturalistic visual search experiment. Results showed that the location of both target and distracter objects could be accurately decoded shortly after scene onset (50 ms). However, the emergence of spatial attentional selection - reflected in better decoding of target location than distracter location - emerged only later in time (240 ms). Target presence itself (irrespective of location and category) could be decoded from 180 ms after stimulus onset. Combined with earlier work, these results indicate that naturalistic category search operates through an initial spatially-global modulation of category processing that then guides attention to the location of the target.
]]></description>
<dc:creator>Battistoni, E.</dc:creator>
<dc:creator>Kaiser, D.</dc:creator>
<dc:creator>Hickey, C.</dc:creator>
<dc:creator>Peelen, M. V.</dc:creator>
<dc:date>2018-08-14</dc:date>
<dc:identifier>doi:10.1101/390807</dc:identifier>
<dc:title><![CDATA[Spatial attention follows category-based attention during naturalistic visual search: evidence from MEG decoding]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/388587v1?rss=1">
<title>
<![CDATA[
Stimulus-induced Gamma Power Predicts the Amplitude of the Subsequent Visual Evoked Response 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/388587v1?rss=1"
</link>
<description><![CDATA[
The efficiency of neuronal information transfer in activated brain networks may affect behavioral performance. Gamma-band synchronization has been proposed to be a mechanism that facilitates neuronal processing of behaviorally relevant stimuli. In line with this, it has been shown that strong gamma-band activity in visual cortical areas leads to faster responses to a visual go cue. We investigated whether there are directly observable consequences of trial-by-trial fluctuations in non-invasively observed gamma-band activity on the neuronal response. Specifically, we hypothesizedthat the amplitude of the visual evoked response to a go cue can be predicted by gamma power in the visual system, in the window preceding the evoked response. Thirty-three human subjects (22 female) performed a visual speeded response task while their magnetoencephalogram (MEG) was recorded. The participants had to respond to a pattern reversal of a concentric moving grating. We estimated single trial stimulus-induced visual cortical gamma power, and correlated this with the estimated single trial amplitude of the most prominent event-related field (ERF) peak within the first 100 ms after the pattern reversal. In parieto-occipital cortical areas, the amplitude of the ERF correlated positively with gamma power, and correlated negatively with reaction times. No effects were observed for the alpha and beta frequency bands, despite clear stimulus onset induced modulation at those frequencies. These results support a mechanistic model, in which gamma-band synchronization enhances the neuronal gain to relevant visual input, thus leading to more efficient downstream processing and to faster responses.nnSignificance statementGamma-band activity has been associated with many cognitive functions and improved behavioral performance. For example, high amplitude gamma-band activity in visual cortical areas before a go cue leads to faster reaction times. However, it remains unclear through which neural mechanism(s) gamma-band activity eventually affects behavior. We tested whether the strength of induced gamma-band activity affects evoked activity elicited by a subsequent visual stimulus. We found enhanced amplitudes of early visual evoked activity, and faster responses with higher gamma power. This suggests that gamma-band activity affects the neuronal gain to new sensory input, and thus these results bridge the gap between gamma power and behavior, and support the putative role of gamma-band activity in the efficiency of cortical processing.
]]></description>
<dc:creator>van Es, M. W. J.</dc:creator>
<dc:creator>Schoffelen, J.-M.</dc:creator>
<dc:date>2018-08-09</dc:date>
<dc:identifier>doi:10.1101/388587</dc:identifier>
<dc:title><![CDATA[Stimulus-induced Gamma Power Predicts the Amplitude of the Subsequent Visual Evoked Response]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/387902v1?rss=1">
<title>
<![CDATA[
Mutant p63 affects epidermal cell identity through rewiring the enhancer landscape 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/387902v1?rss=1"
</link>
<description><![CDATA[
Transcription factor p63 is a key regulator of epidermal keratinocyte proliferation and differentiation. In humans mutations in p63 cause several developmental disorders with defects of ectoderm-derived structures including the epidermis. The underlying molecular mechanisms of these mutations however remain unclear. Here we characterized the transcriptome and epigenome from EEC syndrome patients carrying mutations in the p63 DNA-binding domain. The transcriptome of p63 mutant keratinocytes deviated from the normal epidermal cell identity. Epigenomic analyses showed that the deregulated gene expression in p63 mutant keratinocytes resulted from an altered enhancer landscape contributed by loss of p63-bound active enhancers and by unexpected gain of enhancers. The gained enhancers in mutant keratinocytes were frequently bound by deregulated transcription factors such as RUNX1. Reversing RUNX1 overexpression partially rescued deregulated gene expression as well as the enhancer distribution. Our findings support the pivotal role of p63 in controlling the enhancer landscape of epidermal keratinocytes and identify a novel mechanism whereby p63 DNA-binding mutations associated with EEC syndrome rewire the enhancer landscape and affect epidermal cell identity.
]]></description>
<dc:creator>Qu, J.</dc:creator>
<dc:creator>Tanis, S.</dc:creator>
<dc:creator>Smits, J. P.</dc:creator>
<dc:creator>Kouwenhoven, E. N.</dc:creator>
<dc:creator>Oti, M.</dc:creator>
<dc:creator>van den Bogaard, E. H.</dc:creator>
<dc:creator>Logie, C.</dc:creator>
<dc:creator>Stunnenberg, H.</dc:creator>
<dc:creator>van Bokhoven, H.</dc:creator>
<dc:creator>Mulder, K. W.</dc:creator>
<dc:creator>Zhou, H.</dc:creator>
<dc:date>2018-08-09</dc:date>
<dc:identifier>doi:10.1101/387902</dc:identifier>
<dc:title><![CDATA[Mutant p63 affects epidermal cell identity through rewiring the enhancer landscape]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/386813v1?rss=1">
<title>
<![CDATA[
Fndc3a (Fibronectin Domain Containing Protein 3A) influences median fin fold development and caudal fin regeneration in zebrafish by ECM alteration. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/386813v1?rss=1"
</link>
<description><![CDATA[
Summary statementWe investigated potential functions of Fndc3a during caudal fin development and regeneration in zebrafish. Reduced function interferes with correct epidermal cells structure and implies a role during vertebrate extremity development.nnAbstractInherited genetic alterations are often found to be disease-causing factors of patient phenotypes. To unravel the molecular consequences of newly identified factors functional investigations in vivo are eminent. We investigated molecular functions of FNDC3A (Fibronectin Domain Containing Protein 3A; HUGO), a novel candidate gene for split-hand/foot malformations (SHFM) in humans, by utilizing zebrafish (Danio rerio) as a vertebrate model. Patients with congenital SHFM display prominent limb malformations, which are caused by disturbance of limb development due to defects in apical ectodermal ridge (AER) establishment and maintenance. Initial gene expression and protein localization studies clarified the presence of fndc3a in developing and regenerating fins of zebrafish. For functional studies we established a hypomorphic fndc3a mutant line (fndc3awue1/wue1) via CRISPR/Cas9, exhibiting phenotypic malformations and changed gene expression patterns during early stages of median fin fold development. Furthermore, fndc3awue1/wue1 mutants display abnormal collagen localization, actinotrichia breakup and cellular defects in epidermal cells during caudal fin development. The observed effects are only temporary and later result in rather normal fin development in adults. In accordance with early fin development, proper caudal fin regeneration in adult fndc3awue1/wue1 mutants is hampered by interference with actinotrichia formation and epidermal cell abnormalities. Investigation of cellular matrix formation implied that loss of ECM structure is a common cause for both phenotypes. Our results thereby provide a molecular link between Fndc3a function during both developmental processes in zebrafish and foreshadow Fndc3a as a novel temporal regulator of epidermal cell properties during extremity development in vertebrates.
]]></description>
<dc:creator>Liedtke, D.</dc:creator>
<dc:creator>Orth, M.</dc:creator>
<dc:creator>Meissler, M.</dc:creator>
<dc:creator>Geuer, S.</dc:creator>
<dc:creator>Knaup, S.</dc:creator>
<dc:creator>Koblitz, I.</dc:creator>
<dc:creator>Klopocki, E.</dc:creator>
<dc:date>2018-08-07</dc:date>
<dc:identifier>doi:10.1101/386813</dc:identifier>
<dc:title><![CDATA[Fndc3a (Fibronectin Domain Containing Protein 3A) influences median fin fold development and caudal fin regeneration in zebrafish by ECM alteration.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/383893v1?rss=1">
<title>
<![CDATA[
Faded visual afterimages reappear after TMS over early visual cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/383893v1?rss=1"
</link>
<description><![CDATA[
In the complete absence of small transients in visual inputs (e.g. by experimentally stabilizing an image on the retina, or in everyday life during intent staring), information perceived by the eyes will fade from the perceptual experience. While the mechanisms of visual fading remain poorly understood, one possibility is that higher-level brain regions actively suppress the stable visual signals via targeted inhibitory feedback onto Early Visual Cortex (EVC). Here, we used positive afterimages and multisensory conflict to induce gestaltlike fading of participants own hands. In two separate experiments, participants rated the perceived quality of their hands both before and after Transcranial Magnetic Stimulation (TMS) was applied over EVC. In a first experiment, triple pulse TMS was able to make a faded hand appear less faded after the pulses were applied, compared to placebo pulses. A second experiment demonstrated that this was because triple pulse TMS inoculated the removed hand from fading over time. Interestingly, TMS similarly affected the left and right hand, despite being applied only over right EVC. Together, our results suggest that TMS can lift inhibitory processes in EVC and reverse the effects of visual fading. And it might do so by crossing transcollosal connections, or via multimodal integration sites in which both hands are represented.
]]></description>
<dc:creator>Engelen, T.</dc:creator>
<dc:creator>Rademaker, R. L.</dc:creator>
<dc:creator>Sack, A. T.</dc:creator>
<dc:date>2018-08-02</dc:date>
<dc:identifier>doi:10.1101/383893</dc:identifier>
<dc:title><![CDATA[Faded visual afterimages reappear after TMS over early visual cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/342303v1?rss=1">
<title>
<![CDATA[
Manipulation of deep brain activity in primates using transcranial focused ultrasound stimulation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/342303v1?rss=1"
</link>
<description><![CDATA[
The causal role of an area within a neural network can be determined by interfering with its activity and measuring the impact. Many current reversible manipulation techniques have limitations preventing their focal application particularly in deep areas of the primate brain. Here we demonstrate a transcranial focused ultrasound stimulation (TUS) protocol that manipulates activity even in deep brain areas: a subcortical brain structure, the amygdala (experiment 1), and a deep cortical region, anterior cingulate cortex (ACC, experiment 2), in macaques. TUS neuromodulatory effects were measured by examining relationships between activity in each area and the rest of the brain using functional magnetic resonance imaging (fMRI). In control conditions without sonication, activity in a given area is related to activity in interconnected regions but such relationships are reduced after sonication. Dissociable and focal effects on neural activity could not be explained by auditory artefacts.
]]></description>
<dc:creator>Folloni, D.</dc:creator>
<dc:creator>Verhagen, L.</dc:creator>
<dc:creator>Mars, R. B.</dc:creator>
<dc:creator>Fouragnan, E.</dc:creator>
<dc:creator>Aubry, J.-F.</dc:creator>
<dc:creator>Rushworth, M. F. S.</dc:creator>
<dc:creator>Sallet, J.</dc:creator>
<dc:date>2018-06-08</dc:date>
<dc:identifier>doi:10.1101/342303</dc:identifier>
<dc:title><![CDATA[Manipulation of deep brain activity in primates using transcranial focused ultrasound stimulation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/374397v1?rss=1">
<title>
<![CDATA[
Individual slow wave morphology is a marker of ageing 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/374397v1?rss=1"
</link>
<description><![CDATA[
Slow wave activity is a hallmark of deep NREM sleep. Scalp slow wave morphology is stereotypical, it is highly correlated with the synchronized onset and cessation of cortical neuronal firing measured from the surface or depth of the cortex, strongly affected by ageing, and these changes are causally associated with age-related cognitive decline. We investigated how normal ageing affects the individual morphology of the slow wave, and whether these changes are captured by the summary slow wave parameters generally used in the literature. We recorded full-night polysomnography in 159 subjects (age 17-69 years) and automatically detected slow waves using six different detection methods to ensure methodological robustness. We established individual slow morphologies at 501 data points for each subject and also calculated the individual average slow wave amplitude, average ascending and descending slope steepness and the total number of slow waves (gross parameters). Using LASSO penalized regression we found that fine-grained slow wave morphology is associated with age beyond gross parameters, with young subjects having faster slow wave polarity reversals, suggesting a more efficient initiation and termination of slow wave down- and upstates. Our results demonstrate the superiority of the high-resolution slow wave morphology as a biomarker of ageing, and highlights state transitions as promising targets of restorative stimulation-based interventions.
]]></description>
<dc:creator>Ujma, P. P.</dc:creator>
<dc:creator>Simor, P.</dc:creator>
<dc:creator>Steiger, A.</dc:creator>
<dc:creator>Dresler, M.</dc:creator>
<dc:creator>Bodizs, R.</dc:creator>
<dc:date>2018-08-02</dc:date>
<dc:identifier>doi:10.1101/374397</dc:identifier>
<dc:title><![CDATA[Individual slow wave morphology is a marker of ageing]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-08-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/198382v1?rss=1">
<title>
<![CDATA[
The Object Space Task for mice and rats 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/198382v1?rss=1"
</link>
<description><![CDATA[
Declarative memory encompasses representations of specific events as well as knowledge extracted by accumulation over multiple episodes. To investigate how these different sorts of memories are created, we developed a new behavioral task in rodents. The task consists of three distinct conditions (stable, overlapping, random). Rodents are exposed to multiple sample trials, in which they explore objects in specific spatial arrangements. In the stable condition, the locations are constant during all sample trials; in the test trial, one objects location is changed. In the random condition, object locations are presented in the sample phase without a specific spatial pattern. In the overlapping condition, one location is shared (overlapping) between all trials while the other location changes during sample trials. We show that in the overlapping condition, instead of only remembering the last sample trial, rodents form a cumulative memory of the sample trials.nnHere we could show that both mice and rats can accumulate information across multiple trials and express a long-term abstracted memory.
]]></description>
<dc:creator>Genzel, L.</dc:creator>
<dc:creator>Schut, E.</dc:creator>
<dc:creator>Schroeder, T.</dc:creator>
<dc:creator>Eichler, R.</dc:creator>
<dc:creator>Bayraktar, G.</dc:creator>
<dc:creator>Cornelisse, N.</dc:creator>
<dc:creator>Gareth, H.</dc:creator>
<dc:creator>Giuliani, F.</dc:creator>
<dc:creator>Gomez, A.</dc:creator>
<dc:creator>Hulzebos, S.</dc:creator>
<dc:creator>Igoli, J.</dc:creator>
<dc:creator>Loizou, S.</dc:creator>
<dc:creator>Navarro Lobato, I.</dc:creator>
<dc:creator>Nijssen, L.</dc:creator>
<dc:creator>Reinik, L.</dc:creator>
<dc:creator>Stoutjedijk, O.</dc:creator>
<dc:creator>Verheag, M.</dc:creator>
<dc:creator>Battaglia, F.</dc:creator>
<dc:date>2017-10-04</dc:date>
<dc:identifier>doi:10.1101/198382</dc:identifier>
<dc:title><![CDATA[The Object Space Task for mice and rats]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/338228v1?rss=1">
<title>
<![CDATA[
Functionally distinct ERAP1 and ERAP2 are a hallmark of HLA-A29-(Birdshot) Uveitis. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/338228v1?rss=1"
</link>
<description><![CDATA[
Birdshot Uveitis (Birdshot) is a rare eye condition that affects HLA-A29-positive individuals and could be considered a prototypic member of the recently proposed "MHC-I-opathy" family. Genetic studies have pinpointed the ERAP1 and ERAP2 genes as shared associations across MHC-I-opathies, which suggests ERAP dysfunction may be a root cause for MHC-I-opathies. We mapped the ERAP1 and ERAP2 haplotypes in 84 Dutch cases and 890 controls. We identified association at variant rs10044354, which mediated a marked increase in ERAP2 expression. We also identified and cloned an independently associated ERAP1 haplotype (tagged by rs2287987) present in more than half of the cases; this ERAP1 haplotype is also the primary risk and protective haplotype for other MHC-I-opathies. We show that the risk ERAP1 haplotype conferred significantly altered expression of ERAP1 isoforms in transcriptomic data (n=360), resulting in lowered protein expression and distinct enzymatic activity. Both the association for rs10044354 (meta-analysis: OR[95% CI]=2.07[1.58-2.71], p=1.24 x 10(-7)) and rs2287987 (OR[95% CI]: =2.01 [1.51-2.67], p=1.41 x 10(-6)) replicated and showed consistent direction of effect in an independent Spanish cohort of 46 cases and 2,103 controls. In both cohorts, the combined rs2287987-rs10044354 haplotype associated with Birdshot more strongly than either SNP alone (meta-analysis: p=3.9 x 10(-9)). Finally, we observed that ERAP2 protein expression is dependent on the ERAP1 background across three European populations (n=3,353). In conclusion, a functionally distinct combination of ERAP1 and ERAP2 are a hallmark of Birdshot and provide rationale for strategies designed to correct ERAP function for treatment of Birdshot and MHC-I-opathies more broadly.
]]></description>
<dc:creator>Kuiper, J. J.</dc:creator>
<dc:creator>Setten, J. v.</dc:creator>
<dc:creator>Devall, M.</dc:creator>
<dc:creator>Cretu-Stancu, M.</dc:creator>
<dc:creator>Hiddingh, S.</dc:creator>
<dc:creator>Ophoff, R. A.</dc:creator>
<dc:creator>Missotten, T.</dc:creator>
<dc:creator>Velthoven, M. v.</dc:creator>
<dc:creator>Hollander, A. D.</dc:creator>
<dc:creator>Hoyng, C.</dc:creator>
<dc:creator>James, E.</dc:creator>
<dc:creator>Reeves, E.</dc:creator>
<dc:creator>Cordero-Coma, M.</dc:creator>
<dc:creator>Fonollosa, A.</dc:creator>
<dc:creator>Adan, A.</dc:creator>
<dc:creator>Martin, J.</dc:creator>
<dc:creator>Koeleman, B. P.</dc:creator>
<dc:creator>de Boer, J. H.</dc:creator>
<dc:creator>Pulit, S. L.</dc:creator>
<dc:creator>Marquez, A. M.</dc:creator>
<dc:creator>Radstake, T. R.</dc:creator>
<dc:date>2018-06-04</dc:date>
<dc:identifier>doi:10.1101/338228</dc:identifier>
<dc:title><![CDATA[Functionally distinct ERAP1 and ERAP2 are a hallmark of HLA-A29-(Birdshot) Uveitis.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/342337v1?rss=1">
<title>
<![CDATA[
Offline impact of transcranial focused ultrasound on cortical activation in primates 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/342337v1?rss=1"
</link>
<description><![CDATA[
To understand brain circuits it is necessary both to record and manipulate their activity. Despite increased availability of techniques for manipulating neural activity in rodents, manipulating neural activity in primates remains difficult. Here we show that a minimally invasive technique, transcranial focused ultrasound stimulation (TUS), induced offline changes to activity of circumscribed brain regions in the macaque. Applying TUS to the supplementary motor area or frontal polar cortex resulted in spatially specific patterns of activity change measurable with functional magnetic resonance imaging. In each case changes reflected each areas known network of interactions with the rest of the brain. Independent of these specific neural effects, TUS over these regions also induced widespread signal changes that might have a non-neuronal origin possibly mediated by the cerebral spinal fluid compartment. Although sustained for more than one hour beyond the 40s stimulation period, TUS effects were reversible and not associated with histological changes.nnHighlights O_LIMany studies of ultrasound neuromodulation focus on online effects in rodents.nC_LIO_LIWe use fMRI connectivity to investigate its offline impact in the primate brain.nC_LIO_LI40 s of ultrasound leads to a sustained, specific, reversible neural modulation.nC_LIO_LIUltrasound caused a sharpening of the stimulated regions connectivity profile.nC_LInnIn BriefA new application of focused ultrasound safely modulates brain activation in primates for up to 2 hours after 40 seconds of stimulation. Ultrasound caused the stimulated area to interact more selectively with the rest of the brain.
]]></description>
<dc:creator>Verhagen, L.</dc:creator>
<dc:creator>Gallea, C.</dc:creator>
<dc:creator>Folloni, D.</dc:creator>
<dc:creator>Constans, C.</dc:creator>
<dc:creator>Jensen, D.</dc:creator>
<dc:creator>Ahnine, H.</dc:creator>
<dc:creator>Roumazeilles, L.</dc:creator>
<dc:creator>Santin, M.</dc:creator>
<dc:creator>Ahmed, B.</dc:creator>
<dc:creator>Lehericy, S.</dc:creator>
<dc:creator>Klein-Flugge, M.</dc:creator>
<dc:creator>Krug, K.</dc:creator>
<dc:creator>Mars, R. B.</dc:creator>
<dc:creator>Rushworth, M. F.</dc:creator>
<dc:creator>Pouget, P.</dc:creator>
<dc:creator>Aubry, J.-F.</dc:creator>
<dc:creator>Sallet, J.</dc:creator>
<dc:date>2018-06-08</dc:date>
<dc:identifier>doi:10.1101/342337</dc:identifier>
<dc:title><![CDATA[Offline impact of transcranial focused ultrasound on cortical activation in primates]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/303115v1?rss=1">
<title>
<![CDATA[
Reproducible functional connectivity alterations are associated with autism spectrum disorder 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/303115v1?rss=1"
</link>
<description><![CDATA[
Despite the high clinical burden little is known about pathophysiology underlying autism spectrum disorder (ASD). Recent resting state functional magnetic resonance imaging (rs-fMRI) studies have found atypical synchronization of brain activity in ASD. However, no consensus has been reached on the nature and clinical relevance of these alterations. Here we address these questions in the most comprehensive, large-scale effort to date comprising evaluation of four large ASD cohorts. We followed a strict exploration and replication procedure to identify core rs-fMRI functional connectivity (degree centrality) alterations associated with ASD as compared to typically developing (TD) controls (ASD: N=841, TD: N=984). We then tested for associations of these imaging phenotypes with clinical and demographic factors such as age, sex, medication status and clinical symptom severity. We find reproducible patterns of ASD-associated functional hyper- and hypo-connectivity with hypo-connectivity being primarily restricted to sensory-motor regions and hyper-connectivity hubs being predominately located in prefrontal and parietal cortices. We establish shifts in between-network connectivity from outside to within the identified regions as a key driver of these abnormalities. The magnitude of these alterations is linked to core ASD symptoms related to communication and social interaction and is not affected by age, sex or medication status. The identified brain functional alterations provide a reproducible pathophysiological phenotype underlying the diagnosis of ASD reconciling previous divergent findings. The large effect sizes in standardized cohorts and the link to clinical symptoms emphasize the importance of the identified imaging alterations as potential treatment and stratification biomarkers for ASD.
]]></description>
<dc:creator>Holiga, S.</dc:creator>
<dc:creator>Hipp, J. F.</dc:creator>
<dc:creator>Chatham, C. H.</dc:creator>
<dc:creator>Garces, P.</dc:creator>
<dc:creator>Spooren, W.</dc:creator>
<dc:creator>Logier D'Ardhuy, X.</dc:creator>
<dc:creator>Bertolino, A.</dc:creator>
<dc:creator>Bouquet, C.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Bours, C.</dc:creator>
<dc:creator>Rausch, A.</dc:creator>
<dc:creator>Oldehinkel, M.</dc:creator>
<dc:creator>Bouvard, M.</dc:creator>
<dc:creator>Amestoy, A.</dc:creator>
<dc:creator>Caralp, M.</dc:creator>
<dc:creator>Gueguen, S.</dc:creator>
<dc:creator>Ly-Le Moal, M.</dc:creator>
<dc:creator>Houenou, J.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>Loth, E.</dc:creator>
<dc:creator>Murphy, D.</dc:creator>
<dc:creator>Charman, T.</dc:creator>
<dc:creator>Tillmann, J.</dc:creator>
<dc:creator>Laidi, C.</dc:creator>
<dc:creator>Delorme, R.</dc:creator>
<dc:creator>Beggiato, A.</dc:creator>
<dc:creator>Gaman, A.</dc:creator>
<dc:creator>Scheid, I.</dc:creator>
<dc:creator>Leboyer, M.</dc:creator>
<dc:creator>d'Albis, M.-A.</dc:creator>
<dc:creator>Sevigny, J.</dc:creator>
<dc:creator>Czech, C.</dc:creator>
<dc:creator>Bolognani, F.</dc:creator>
<dc:creator>Honey, G. D.</dc:creator>
<dc:creator>Dukart, J.</dc:creator>
<dc:date>2018-04-18</dc:date>
<dc:identifier>doi:10.1101/303115</dc:identifier>
<dc:title><![CDATA[Reproducible functional connectivity alterations are associated with autism spectrum disorder]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-04-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/364042v1?rss=1">
<title>
<![CDATA[
Distracting linguistic information impairs neural entrainment to attended speech 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/364042v1?rss=1"
</link>
<description><![CDATA[
Listening to speech is difficult in noisy environments, and is even harder when the interfering noise consists of intelligible speech as compared to unintelligible sounds. This suggests that the competing linguistic information interferes with the neural processing of target speech. Interference could either arise from a degradation of the neural representation of the target speech, or from increased representation of distracting speech that enters in competition with the target speech. We tested these alternative hypotheses using magnetoencephalography (MEG) while participants listened to a target clear speech in the presence of distracting noise-vocoded speech. Crucially, the distractors were initially unintelligible but became more intelligible after a short training session. Results showed that the comprehension of the target speech was poorer after training than before training. The neural tracking of target speech in the delta range (1-4 Hz) reduced in strength in the presence of a more intelligible distractor. In contrast, the neural tracking of distracting signals was not significantly modulated by intelligibility. These results suggest that the presence of distracting speech signals degrades the linguistic representation of target speech carried by delta oscillations.
]]></description>
<dc:creator>Dai, B.</dc:creator>
<dc:creator>McQueen, J. M.</dc:creator>
<dc:creator>Terporten, R.</dc:creator>
<dc:creator>Hagoort, P.</dc:creator>
<dc:creator>Kosem, A.</dc:creator>
<dc:date>2018-07-06</dc:date>
<dc:identifier>doi:10.1101/364042</dc:identifier>
<dc:title><![CDATA[Distracting linguistic information impairs neural entrainment to attended speech]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/360578v1?rss=1">
<title>
<![CDATA[
Predicting audiovisual speech: Early combined effects of sentential and visual constraints 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/360578v1?rss=1"
</link>
<description><![CDATA[
In language comprehension, a variety of contextual cues act in unison to render upcoming words more or less predictable. As a sentence unfolds, we use prior context (sentential constraints) to predict what the next words might be. Additionally, in a conversation, we can predict upcoming sounds through observing the mouth movements of a speaker (visual constraints). In electrophysiological studies, effects of visual salience have typically been observed early in language processing, while effects of sentential constraints have typically been observed later. We hypothesized that the visual and the sentential constraints might feed into the same predictive process such that effects of sentential constraints might also be detectable early in language processing through modulations of the early effects of visual salience. We presented participants with audiovisual speech while recording their brain activity with magnetoencephalography. Participants saw videos of a person saying sentences where the last word was either sententially constrained or not, and began with a salient or non-salient mouth movement. We found that sentential constraints indeed exerted an early (N1) influence on language processing. Sentential modulations of the N1 visual predictability effect were visible in brain areas associated with semantic processing, and were differently expressed in the two hemispheres. In the left hemisphere, visual and sentential constraints jointly suppressed the auditory evoked field, while the right hemisphere was sensitive to visual constraints only in the absence of strong sentential constraints. These results suggest that sentential and visual constraints can jointly influence even very early stages of audiovisual speech comprehension.
]]></description>
<dc:creator>Solberg Okland, H.</dc:creator>
<dc:creator>Todorovic, A.</dc:creator>
<dc:creator>Luettke, C. S.</dc:creator>
<dc:creator>McQueen, J. M.</dc:creator>
<dc:creator>de Lange, F. P.</dc:creator>
<dc:date>2018-07-03</dc:date>
<dc:identifier>doi:10.1101/360578</dc:identifier>
<dc:title><![CDATA[Predicting audiovisual speech: Early combined effects of sentential and visual constraints]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-07-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/358143v1?rss=1">
<title>
<![CDATA[
Classification of mouse ultrasonic vocalizations using deep learning 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/358143v1?rss=1"
</link>
<description><![CDATA[
Vocalizations are a widespread means of communication in the animal kingdom. Mice use a large repertoire of ultrasonic vocalizations (USVs) in different social contexts, for instance courtship, territorial dispute, dominance and mother-pup interaction. Previous studies have pointed to differences in the USVs in different context, sexes, strains and individuals, however, in many cases the outcomes of the analyses remained inconclusive.nnWe here provide a more general approach to automatically classify USVs using deep neural networks (DNN). We classified the sex of the emitting mouse (C57Bl/6) based on the vocalizations spectrogram, reaching unprecedented performance (~84% correct) in comparison with other techniques (Support Vector Machines: 64%, Ridge regression: 52%). Vocalization characteristics of individual mice only contribute mildly, and sex-only classification reaches ~78%. The performance can only partially be explained by a set of classical shape features, with duration, volume and bandwidth being the most useful predictors. Splitting estimation into two DNNs, from spectrograms to features (57-82%) and features to sex (67%) does not reach the single-step performance.nnIn summary, the emitters sex can be successfully predicted from their spectrograms using DNNs, excelling over other classification techniques. In contrast to previous research, this suggests that male and female vocalizations differ in their spectrotemporal structure, recognizable even in single vocalizations.
]]></description>
<dc:creator>Ivanenko, A.</dc:creator>
<dc:creator>Watkins, P.</dc:creator>
<dc:creator>van Gerven, M. A. J.</dc:creator>
<dc:creator>Hammerschmidt, K.</dc:creator>
<dc:creator>Englitz, B.</dc:creator>
<dc:date>2018-06-28</dc:date>
<dc:identifier>doi:10.1101/358143</dc:identifier>
<dc:title><![CDATA[Classification of mouse ultrasonic vocalizations using deep learning]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/357061v1?rss=1">
<title>
<![CDATA[
Monitoring of language selection errors in switching: Not all about conflict 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/357061v1?rss=1"
</link>
<description><![CDATA[
Although bilingual speakers are very good at selectively using one language rather than another, sometimes language selection errors occur. To investigate how bilinguals monitor their speech errors and control their languages in use, we recorded event-related potentials (ERPs) in unbalanced Dutch-English bilingual speakers in a cued language-switching task. We tested the conflict-based monitoring model by investigating the error-related negativity (ERN) and comparing the effects of the two switching directions (i.e., to the first language, L1 vs. to the second language, L2). Results show that the speakers made more language selection errors when switching from their L2 to the L1 than vice versa. In the EEG, we observed a robust ERN effect following language selection errors compared to correct responses, reflecting monitoring of speech errors. Most interestingly, the ERN effect was enlarged when the speakers were switching to their L2 (less conflict) compared to switching to the L1 (more conflict). Our findings do not support the conflict-based monitoring model. We discuss an alternative account in terms of error prediction and reinforcement learning.
]]></description>
<dc:creator>Zheng, X.</dc:creator>
<dc:creator>Roelofs, A.</dc:creator>
<dc:creator>Farquhar, J.</dc:creator>
<dc:creator>Lemhöfer, K.</dc:creator>
<dc:date>2018-06-27</dc:date>
<dc:identifier>doi:10.1101/357061</dc:identifier>
<dc:title><![CDATA[Monitoring of language selection errors in switching: Not all about conflict]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/354910v1?rss=1">
<title>
<![CDATA[
Laminar profile of task-related plasticity in ferret primary auditory cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/354910v1?rss=1"
</link>
<description><![CDATA[
Rapid task-related plasticity is a neural correlate of selective attention in primary auditory cortex (A1). Top-down feedback from higher-order cortex may drive task-related plasticity in A1, characterized by enhanced neural representation of behaviorally meaningful sounds during auditory task performance. Since intracortical connectivity is greater within A1 layers 2/3 (L2/3) than in layers 4-6 (L4-6), we hypothesized that enhanced representation of behaviorally meaningful sounds might be greater in A1 L2/3 than L4-6. To test this hypothesis and study the laminar profile of task-related plasticity, we trained 2 ferrets to detect pure tones while we recorded laminar activity across a 1.8 mm depth in A1. In each experiment, we analyzed current-source densities (CSDs), high-gamma local field potentials (LFPs), and multi-unit spiking in response to identical acoustic stimuli during both passive listening and active task performance. We found that neural responses to auditory targets were enhanced during task performance, and target enhancement was greater in L2/3 than in L4-6. Spectrotemporal receptive fields (STRFs) computed from CSDs, high-gamma LFPs, and multi-unit spiking showed similar increases in auditory target selectivity, also greatest in L2/3. Our results suggest that activity within intracortical networks plays a key role in shaping the underlying neural mechanisms of selective attention.
]]></description>
<dc:creator>Francis, N.</dc:creator>
<dc:creator>Elgueda, D.</dc:creator>
<dc:creator>Englitz, B.</dc:creator>
<dc:creator>Fritz, J.</dc:creator>
<dc:creator>Shamma, S.</dc:creator>
<dc:date>2018-06-26</dc:date>
<dc:identifier>doi:10.1101/354910</dc:identifier>
<dc:title><![CDATA[Laminar profile of task-related plasticity in ferret primary auditory cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/349845v1?rss=1">
<title>
<![CDATA[
Low-frequency variation in TP53 has large effects on head circumference and intracranial volume 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/349845v1?rss=1"
</link>
<description><![CDATA[
Cranial growth and development affects the closely related traits of head circumference (HC) and intracranial volume (ICV). Here we model the developmental genetic architecture of HC, showing this is genetically stable and correlated with genetic determinants of ICV. Investigating up to 46,000 children and adults of European descent, we identify association with final HC and/or final ICV+HC at 9 novel common and low-frequency loci, illustrating that genetic variation from a wide allele frequency spectrum contributes to cranial growth. The largest effects are reported for low-frequency variants within TP53, with 0.5 cm wider heads in increaser-allele carriers versus non-carriers during mid-childhood.
]]></description>
<dc:creator>Haworth, S.</dc:creator>
<dc:creator>Shapland, C. Y.</dc:creator>
<dc:creator>Hayward, C.</dc:creator>
<dc:creator>Prins, B. P.</dc:creator>
<dc:creator>Felix, J. F.</dc:creator>
<dc:creator>Medina-Gomez, C.</dc:creator>
<dc:creator>Rivadeneira, F.</dc:creator>
<dc:creator>Wang, C.</dc:creator>
<dc:creator>Ahluwalia, T. S.</dc:creator>
<dc:creator>Vrijheid, M.</dc:creator>
<dc:creator>Guxens, M.</dc:creator>
<dc:creator>Sunyer, J.</dc:creator>
<dc:creator>Tachmazidou, I.</dc:creator>
<dc:creator>Walter, K.</dc:creator>
<dc:creator>Iotchkova, V.</dc:creator>
<dc:creator>Jackson, A.</dc:creator>
<dc:creator>Cleal, L.</dc:creator>
<dc:creator>Huffmann, J.</dc:creator>
<dc:creator>Min, J. L.</dc:creator>
<dc:creator>Sass, L.</dc:creator>
<dc:creator>Timmers, P. R. H. J.</dc:creator>
<dc:creator>UK10K consortium,</dc:creator>
<dc:creator>Davey Smith, G.</dc:creator>
<dc:creator>Fisher, S. E.</dc:creator>
<dc:creator>Wilson, J. F.</dc:creator>
<dc:creator>Cole, T. J.</dc:creator>
<dc:creator>Fernandez-Orth, D.</dc:creator>
<dc:creator>Bonnelykke, K.</dc:creator>
<dc:creator>Bisgaard, H.</dc:creator>
<dc:creator>Pennell, C. E.</dc:creator>
<dc:creator>Jaddoe, V. W. V.</dc:creator>
<dc:creator>Dedoussis, G.</dc:creator>
<dc:creator>Timpson, N. J.</dc:creator>
<dc:creator>Zeggini, E.</dc:creator>
<dc:creator>Vitart, V.</dc:creator>
<dc:creator>St Pourcain, B.</dc:creator>
<dc:date>2018-06-18</dc:date>
<dc:identifier>doi:10.1101/349845</dc:identifier>
<dc:title><![CDATA[Low-frequency variation in TP53 has large effects on head circumference and intracranial volume]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/350066v1?rss=1">
<title>
<![CDATA[
Causal inference for spatial constancy across whole-body motion 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/350066v1?rss=1"
</link>
<description><![CDATA[
The brain can estimate the amplitude and direction of self-motion by integrating multiple sources of sensory information, and use this estimate to update object positions in order to provide us with a stable representation of the world. A strategy to improve the precision of the object position estimate would be to integrate this internal estimate and the sensory feedback about the object position based on their reliabilities. Integrating these cues, however, would only be optimal under the assumption that the object has not moved in the world during the intervening body displacement. Therefore, the brain would have to infer whether the internal estimate and the feedback relate to a same external position (stable object), and integrate and/or segregate these cues based on this inference - a process that can be modeled as Bayesian Causal inference. To test this hypothesis, we designed a spatial updating task across passive whole body translation in complete darkness, in which participants (n=11), seated on a vestibular sled, had to remember the world-fixed position of a visual target. Immediately after the translation, a second target (feedback) was briefly flashed around the estimated "updated" target location, and participants had to report the initial target location. We found that the participants responses were systematically biased toward the position of the second target position for relatively small but not for large differences between the "updated" and the second target location. This pattern was better captured by a Bayesian causal inference model than by alternative models that would always either integrate or segregate the internally-updated target position and the visual feedback. Our results suggest that the brain implicitly represents the posterior probability that the internally updated estimate and the sensory feedback come from a common cause, and use this probability to weigh the two sources of information in mediating spatial constancy across whole-body motion.nnAuthor SummaryA change of an objects position on our retina can be caused by a change of the objects location in the world or by a movement of the eye and body. Here, we examine how the brain solves this problem for spatial updating by assessing the probability that the internally-updated location during body motion and observed retinal feedback after the motion stems from the same object location in the world. Guided by Bayesian causal inference model, we demonstrate that participants errrors in spatial updating depend nonlinearly on the spatial discrepancy between internally-updated and reafferent visual feedback about the objects location in the world. We propose that the brain implicitly represents the probability that the internally updated estimate and the sensory feedback come from a common cause, and use this probability to weigh the two sources of information in mediating spatial constancy across whole-body motion.
]]></description>
<dc:creator>Perdreau, F.</dc:creator>
<dc:creator>Cooke, J. R. H.</dc:creator>
<dc:creator>Koppen, M.</dc:creator>
<dc:creator>Medendorp, P. W.</dc:creator>
<dc:date>2018-06-18</dc:date>
<dc:identifier>doi:10.1101/350066</dc:identifier>
<dc:title><![CDATA[Causal inference for spatial constancy across whole-body motion]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/305425v1?rss=1">
<title>
<![CDATA[
Early life factors influencing hand preference in the UK biobank cohort 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/305425v1?rss=1"
</link>
<description><![CDATA[
Hand preference is a conspicuous variation in human behaviour, with a worldwide proportion of around 90% of people preferring to use the right hand for many tasks, and 10% the left hand. We used the large, general population cohort of the UK biobank (~500,000 participants) to study possible relations between early life factors and adult hand preference. The probability of being left-handed was affected by the year and location of birth, likely due to cultural effects. In addition, handedness was affected by birthweight, being part of a multiple birth, season of birth, breastfeeding, and sex, with each effect remaining significant after accounting for all others. Maternal smoking showed no association with handedness. Analysis of genome-wide genotype data showed that left-handedness was very weakly heritable, but shared no genetic basis with birthweight. Although on average left-handers and right-handers differed for a number of early life factors, all together these factors had only a minimal predictive value for individual hand preference. Therefore other, unknown effects must be involved, including possible environmental factors, and/or random developmental variation with respect to the left-right formation of the embryonic brain.nnSignificance statementLeft-right laterality is an important aspect of human brain organization which is set up early in development. Left-handedness is an overt and relatively prevalent form of atypical brain laterality. Various, often related, early life factors have been previously studied in relation to handedness, but often in small samples, or samples with biased selection schemes. Here we have performed the largest ever study of left-handedness in relation to early life factors. Left-handedness was very weakly heritable and there were significant effects of various factors such as birthweight, which remained significant after controlling for all others. However, considered all together, early life factors still had poor predictive power for the handedness of any given individual. Very early developmental perturbations, caused by environmental or chance effects in embryonic development, are therefore likely to cause left-handedness.
]]></description>
<dc:creator>de Kovel, C. G. F.</dc:creator>
<dc:creator>Carrion-Castillo, A.</dc:creator>
<dc:creator>Francks, C.</dc:creator>
<dc:date>2018-04-20</dc:date>
<dc:identifier>doi:10.1101/305425</dc:identifier>
<dc:title><![CDATA[Early life factors influencing hand preference in the UK biobank cohort]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-04-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/339200v1?rss=1">
<title>
<![CDATA[
Simultaneous representation of sensory and mnemonic information in human visual cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/339200v1?rss=1"
</link>
<description><![CDATA[
Traversing sensory environments requires keeping relevant information in mind while simultaneously processing new inputs. Visual information is kept in working memory via feature selective responses in early visual cortex, but recent work had suggested that new sensory inputs wipe out this information. Here we show region-wide multiplexing abilities in classic sensory areas, with population-level response patterns in visual cortex representing the contents of working memory concurrently with new sensory inputs.
]]></description>
<dc:creator>Rademaker, R. L.</dc:creator>
<dc:creator>Chunharas, C.</dc:creator>
<dc:creator>Serences, J. T.</dc:creator>
<dc:date>2018-06-05</dc:date>
<dc:identifier>doi:10.1101/339200</dc:identifier>
<dc:title><![CDATA[Simultaneous representation of sensory and mnemonic information in human visual cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-06-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/325787v1?rss=1">
<title>
<![CDATA[
The spatial correspondence and genetic influence of inter-hemispheric connectivity with white matter microstructure 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/325787v1?rss=1"
</link>
<description><![CDATA[
Microscopic features (i.e., microstructure) of axons affect neural circuit activity through characteristics such as conduction speed. Deeper understanding of structure-function relationships and translating this into human neuroscience has been limited by the paucity of studies relating axonal microstructure in white matter pathways to functional connectivity (synchrony) between macroscopic brain regions. Using magnetic resonance imaging data in 11354 subjects, we constructed multi-variate models that predict the functional connectivity of pairs of brain regions from the microstructural signature of white matter pathways that connect them. Microstructure-derived models provide predictions of functional connectivity that were significant in up to 86% of the brain region pairs considered. These relationships are specific to the relevant white matter pathway and have high reproducibility. The microstructure-function relationships are associated to genetic variants (single-nucleotide polymorphisms), co-located with genes DAAM1 and LPAR1, that have previously been reported to play a role in neural development. Our results demonstrate that variation in white matter microstructure across individuals consistently and specifically predicts functional connectivity, and that this relationship is underpinned by genetic variability.
]]></description>
<dc:creator>Mollink, J.</dc:creator>
<dc:creator>Smith, S. M.</dc:creator>
<dc:creator>Elliott, L. T.</dc:creator>
<dc:creator>Kleinnijenhuis, M.</dc:creator>
<dc:creator>Hiemstra, M.</dc:creator>
<dc:creator>Alfaro-Almagro, F.</dc:creator>
<dc:creator>Marchini, J.</dc:creator>
<dc:creator>van Cappellen van Walsum, A.-M.</dc:creator>
<dc:creator>Jbabdi, S.</dc:creator>
<dc:creator>Miller, K. L.</dc:creator>
<dc:date>2018-05-18</dc:date>
<dc:identifier>doi:10.1101/325787</dc:identifier>
<dc:title><![CDATA[The spatial correspondence and genetic influence of inter-hemispheric connectivity with white matter microstructure]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-05-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/313734v1?rss=1">
<title>
<![CDATA[
Expert Specification of the ACMG/AMP Variant Interpretation Guidelines for Genetic Hearing Loss 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/313734v1?rss=1"
</link>
<description><![CDATA[
Due to the high genetic heterogeneity of hearing loss, current clinical testing includes sequencing large numbers of genes, which often yields a significant number of novel variants. Therefore, the standardization of variant interpretation is crucial to provide consistent and accurate diagnoses. The Hearing Loss Variant Curation Expert Panel was created within the Clinical Genome Resource to provide expert guidance for standardized genomic interpretation in the context of hearing loss. As one of its major tasks, our Expert Panel has adapted the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) standards and guidelines for the interpretation of sequence variants in hearing loss genes. Here, we provide a comprehensive illustration of the newly specified ACMG/AMP hearing loss rules. Three rules remained unchanged, four rules were removed, and the remaining twenty-one rules were specified. Of the specified rules, four had general recommendations, seven were gene/disease considerations, seven had strength-level specifications, and three rules had both gene/disease and strength-level specifications. These rules were further validated and refined using a pilot set of 51 variants assessed by curators. These hearing loss-specific ACMG/AMP rules will help standardize variant interpretation, ultimately leading to better care for individuals with hearing loss.nnGRANT NUMBERSResearch reported in this publication was supported by the National Human Genome Research Institute (NHGRI) under award number U41HG006834.
]]></description>
<dc:creator>Oza, A.</dc:creator>
<dc:creator>DiStefano, M.</dc:creator>
<dc:creator>Hemphill, S.</dc:creator>
<dc:creator>Cushman, B.</dc:creator>
<dc:creator>Grant, A.</dc:creator>
<dc:creator>Siegert, R.</dc:creator>
<dc:creator>Shen, J.</dc:creator>
<dc:creator>Chapin, A.</dc:creator>
<dc:creator>Boczek, N.</dc:creator>
<dc:creator>Schimmenti, L.</dc:creator>
<dc:creator>Murry, J.</dc:creator>
<dc:creator>Hasadsri, L.</dc:creator>
<dc:creator>Nara, K.</dc:creator>
<dc:creator>Kenna, M.</dc:creator>
<dc:creator>Booth, K.</dc:creator>
<dc:creator>Azaiez, H.</dc:creator>
<dc:creator>Griffith, A.</dc:creator>
<dc:creator>Avraham, K.</dc:creator>
<dc:creator>Kremer, H.</dc:creator>
<dc:creator>Rehm, H.</dc:creator>
<dc:creator>Amr, S.</dc:creator>
<dc:creator>Abou Tayoun, A.</dc:creator>
<dc:creator>The ClinGen Hearing Loss Expert Workgroup,</dc:creator>
<dc:date>2018-05-08</dc:date>
<dc:identifier>doi:10.1101/313734</dc:identifier>
<dc:title><![CDATA[Expert Specification of the ACMG/AMP Variant Interpretation Guidelines for Genetic Hearing Loss]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-05-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/316786v1?rss=1">
<title>
<![CDATA[
Immediate stimulus repetition abolishes stimulus expectation and surprise effects in fast periodic visual oddball designs 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/316786v1?rss=1"
</link>
<description><![CDATA[
Oddball designs are widely used to investigate the sensitivity of the visual system to statistical regularities in sensory environments. However, the underlying mechanisms that give rise to visual mismatch responses remain unknown. Much research has focused on identifying separable, additive effects of stimulus repetition and stimulus appearance probability (expectation/surprise) but findings from non-oddball designs indicate that these effects also interact. We adapted the fast periodic visual stimulation (FPVS) unfamiliar face identity oddball design (Liu-Shuang et al., 2014) to test for both additive and interactive effects of stimulus repetition and stimulus expectation. In two experiments, a given face identity was presented at a 6 Hz periodic rate; a different identity face (the oddball) appeared as every 7th image in the sequence (i.e., at 0.857 Hz). Electroencephalographic (EEG) activity was recorded during these stimulation sequences. In Experiment 1, we tested for surprise responses evoked by unexpected face image repetitions by replacing 10% of the commonly-presented oddball faces with exact repetitions of the base rate face identity image. In Experiment 2, immediately repeated or unrepeated face identity oddballs were presented in high and low presentation probability contexts (i.e., expected or surprising), allowing assessment of expectation effects on responses to both repeated and unrepeated stimuli. Across both experiments objective (i.e., frequency-locked) visual mismatch responses driven by stimulus expectation were only found for oddball faces of a different identity to base rate faces (i.e., unrepeated identity oddballs). Our results show that immediate stimulus repetition (i.e., repetition suppression) can reduce or abolish expectation effects as indexed by EEG responses in visual oddball designs.nnHighlights- We studied visual mismatch responses with a fast periodic oddball designn- Our design cleanly separates immediate stimulus repetition and expectation effectsn- Stimulus expectation effects were only present for unrepeated stimulin- Immediate stimulus repetition reduced EEG expectation effects
]]></description>
<dc:creator>Feuerriegel, D.</dc:creator>
<dc:creator>Keage, H. A. D.</dc:creator>
<dc:creator>Rossion, B.</dc:creator>
<dc:creator>Quek, G. L.</dc:creator>
<dc:date>2018-05-08</dc:date>
<dc:identifier>doi:10.1101/316786</dc:identifier>
<dc:title><![CDATA[Immediate stimulus repetition abolishes stimulus expectation and surprise effects in fast periodic visual oddball designs]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-05-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/276527v1?rss=1">
<title>
<![CDATA[
Disentangling genetic overlap between Attention-Deficit/Hyperactivity Disorder, literacy and language 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/276527v1?rss=1"
</link>
<description><![CDATA[
Interpreting polygenic overlap between ADHD and both literacy- and language-related impairments is challenging as genetic confounding can bias associations. Here, we investigate evidence for links between polygenic ADHD risk and multiple literacy- and language-related abilities (LRAs), assessed in UK children (N[&le;]5,919), conditional on genetic effects shared with educational attainment (EA). Genome-wide summary statistics on clinical ADHD and years-of-schooling were obtained from large consortia (N[&le;]326,041). ADHD-polygenic scores (ADHD-PGS) were inversely associated with LRAs in ALSPAC, most consistently with reading-related abilities, and explained [&le;]1.6% phenotypic variation. Polygenic links were then dissected into both genetic effects shared with and independent of EA using multivariable regressions (MVR), analogous to Mendelian Randomization approaches accounting for mediating effects. Conditional on EA, polygenic ADHD risk remained associated with multiple literacy-related skills, phonemic awareness and verbal intelligence, but not language-related skills such as listening comprehension and non-word repetition. Pooled reading performance showed the strongest overlap with ADHD independent of EA. Using conservative ADHD-instruments (P-threshold<5x10-8) this corresponded to a 0.35 decrease in Z-scores per log-odds in ADHD-liability (P=9.2x10-5). Using subthreshold ADHD-instruments (P-threshold<0.0015), these associations had lower magnitude, but higher predictive accuracy, with a 0.03 decrease in Z-scores (P=1.4x10-6). Polygenic ADHD-effects shared with EA were of equal strength and at least equal magnitude compared to those independent of EA, for all LRAs studied, and only detectable using subthreshold instruments. Thus, ADHD-related polygenic links are highly susceptible to genetic confounding, concealing an ADHD-specific association profile that primarily involves reading-related impairments, but few language-related problems.
]]></description>
<dc:creator>Verhoef, E.</dc:creator>
<dc:creator>Demontis, D.</dc:creator>
<dc:creator>Burgess, S.</dc:creator>
<dc:creator>Shapland, C. Y.</dc:creator>
<dc:creator>Dale, P. S.</dc:creator>
<dc:creator>Okbay, A.</dc:creator>
<dc:creator>Neale, B. M.</dc:creator>
<dc:creator>Faraone, S. V.</dc:creator>
<dc:creator>iPSYCH-Broad-PGC ADHD Consortium,</dc:creator>
<dc:creator>Stergiakouli, E.</dc:creator>
<dc:creator>Davey Smith, G.</dc:creator>
<dc:creator>Fisher, S. E.</dc:creator>
<dc:creator>Borglum, A.</dc:creator>
<dc:creator>St Pourcain, B.</dc:creator>
<dc:date>2018-03-05</dc:date>
<dc:identifier>doi:10.1101/276527</dc:identifier>
<dc:title><![CDATA[Disentangling genetic overlap between Attention-Deficit/Hyperactivity Disorder, literacy and language]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-03-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/309336v1?rss=1">
<title>
<![CDATA[
Genome Wide Association Scan identifies new variants associated with a cognitive predictor of dyslexia. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/309336v1?rss=1"
</link>
<description><![CDATA[
Developmental dyslexia (DD) is one of the most prevalent learning disorders among children and is characterized by deficits in different cognitive skills, including reading, spelling, short term memory and others. To help unravel the genetic basis of these skills, we conducted a Genome Wide Association Study (GWAS), including nine cohorts of reading-impaired and typically developing children of European ancestry, recruited across different countries (N=2,562-3,468).nnWe observed a genome-wide significant effect (p<1x10-8) on rapid automatized naming of letters (RANlet) for variants on 18q12.2 within MIR924HG (micro-RNA 924 host gene; p = 4.73x10-9), and a suggestive association on 8q12.3 within NKAIN3 (encoding a cation transporter; p = 2.25 x10-8). RAN represents one of the best universal predictors of reading fluency across orthographies and linkage to RAN has been previously reported within CELF4 (18q12.2), a gene highly expressed in the fetal brain which is co-expressed with NKAIN3 and predicted to be a target of MIR924. These findings suggest new candidate DD susceptibility genes and provide insights into the genetics and neurobiology of dyslexia.
]]></description>
<dc:creator>Gialluisi, A.</dc:creator>
<dc:creator>Andlauer, T. F.</dc:creator>
<dc:creator>Mirza-Schreiber, N.</dc:creator>
<dc:creator>Moll, K.</dc:creator>
<dc:creator>Hoffmann, P.</dc:creator>
<dc:creator>Ludwig, K. U.</dc:creator>
<dc:creator>Czamara, D.</dc:creator>
<dc:creator>Francks, C.</dc:creator>
<dc:creator>St Pourcain, B.</dc:creator>
<dc:creator>Brandler, W.</dc:creator>
<dc:creator>Honbolygo, F.</dc:creator>
<dc:creator>Toth, D.</dc:creator>
<dc:creator>Csepe, V.</dc:creator>
<dc:creator>Huguet, G.</dc:creator>
<dc:creator>Morris, A. P.</dc:creator>
<dc:creator>Hulslander, J.</dc:creator>
<dc:creator>Willcutt, E. G.</dc:creator>
<dc:creator>DeFries, J. C.</dc:creator>
<dc:creator>Olson, R. K.</dc:creator>
<dc:creator>Smith, S. D.</dc:creator>
<dc:creator>Pennington, B. F.</dc:creator>
<dc:creator>Vaessen, A.</dc:creator>
<dc:creator>Maurer, U.</dc:creator>
<dc:creator>Lyytinen, H.</dc:creator>
<dc:creator>Peyrard-Janvid, M.</dc:creator>
<dc:creator>Leppanen, P. H.</dc:creator>
<dc:creator>Brandeis, D.</dc:creator>
<dc:creator>Bonte, M.</dc:creator>
<dc:creator>Stein, J. F.</dc:creator>
<dc:creator>Talcott, J.</dc:creator>
<dc:creator>Fauchereau, F.</dc:creator>
<dc:creator>Bourgeron, T.</dc:creator>
<dc:creator>Monaco, A. P.</dc:creator>
<dc:creator>Ramus, F.</dc:creator>
<dc:creator>Landerl, K.</dc:creator>
<dc:creator>Kere, J.</dc:creator>
<dc:creator>Scerri, T. S.</dc:creator>
<dc:creator>Paracchini, S.</dc:creator>
<dc:creator>Fisher, S. E.</dc:creator>
<dc:creator>Schumacher, J.</dc:creator>
<dc:creator>Nothen, M. M.</dc:creator>
<dc:creator>Muller-</dc:creator>
<dc:date>2018-05-02</dc:date>
<dc:identifier>doi:10.1101/309336</dc:identifier>
<dc:title><![CDATA[Genome Wide Association Scan identifies new variants associated with a cognitive predictor of dyslexia.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-05-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/117804v1?rss=1">
<title>
<![CDATA[
A Theta Rhythm In Awake Macaque V1 And V4 And Its Attentional Modulation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/117804v1?rss=1"
</link>
<description><![CDATA[
Theta rhythms govern rodent sniffing and whisking, and human language processing. Human psychophysics suggests a role for theta also in visual attention. Yet, little is known about theta in visual areas and its attentional modulation. We used electrocorticography (ECoG) to record local field potentials (LFPs) simultaneously from areas V1, V2, V4 and TEO of two macaque monkeys performing a selective visual attention task. We found a {approx}4 Hz theta rhythm within both the V1-V2 and the V4-TEO region, and theta synchronization between them, with a predominantly feedforward directed influence. ECoG coverage of large parts of these regions revealed a surprising spatial correspondence between theta and visually induced gamma. Furthermore, gamma power was modulated with theta phase. Selective attention to the respective visual stimulus strongly reduced these theta-rhythmic processes, leading to an unusually strong attention effect for V1. Microsaccades (MSs) were partly locked to theta. Yet, neuronal theta rhythms tended to be even more pronounced for epochs devoid of MSs. Thus, we find an MS-independent theta rhythm specific to visually driven parts of V1-V2, which rhythmically modulates local gamma and entrains V4-TEO, and which is strongly reduced by attention. We propose that the less theta-rhythmic and thereby more continuous processing of the attended stimulus serves the exploitation of this behaviorally most relevant information. The theta-rhythmic and thereby intermittent processing of the unattended stimulus likely reflects the ecologically important exploration of less relevant sources of information.
]]></description>
<dc:creator>Spyropoulos, G.</dc:creator>
<dc:creator>Bosman, C. A.</dc:creator>
<dc:creator>Fries, P.</dc:creator>
<dc:date>2017-03-17</dc:date>
<dc:identifier>doi:10.1101/117804</dc:identifier>
<dc:title><![CDATA[A Theta Rhythm In Awake Macaque V1 And V4 And Its Attentional Modulation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-03-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/252791v1?rss=1">
<title>
<![CDATA[
A novel distance measure for the unsupervised clustering of temporal patterns in high-dimensional neuronal ensembles 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/252791v1?rss=1"
</link>
<description><![CDATA[
Temporally ordered multi-neuron patterns likely encode information in the brain. We introduce an unsupervised method, SPOTDisClust (Spike Pattern Optimal Transport Dissimilarity Clustering), for their detection from high-dimensional neural ensembles. SPOTDisClust measures similarity between two ensemble spike patterns by determining the minimum transport cost of transforming their corresponding normalized cross-correlation matrices into each other (SPOTDis). Then, it performs density-based clustering based on the resulting inter-pattern dissimilarity matrix. SPOTDisClust does not require binning and can detect complex patterns (beyond sequential activation) even when high levels of out-of-pattern "noise" spiking are present. Our method handles efficiently the additional information from increasingly large neuronal ensembles and can detect a number of patterns that far exceeds the number of recorded neurons. In an application to neural ensemble data from macaque monkey V1 cortex, SPOTDisClust can identify different moving stimulus directions on the sole basis of temporal spiking patterns.nnAuthor summaryThe brain encodes information by ensembles of neurons, and recent technological developments allow researchers to simultaneously record from over thousands of neurons. Neurons exhibit spontaneous activity patterns, which are constrained by experience and development, limiting the portion of state space that is effectively visited. Patterns of spontaneous activity may contribute to shaping the synaptic connectivity matrix and contribute to memory consolidation, and synaptic plasticity formation depends crucially on the temporal spiking order among neurons. Hence, the unsupervised detection of spike sequences is a sine qua non for understanding how spontaneous activity contributes to memory formation. Yet, sequence detection presents major methodological challenges like the sparsity and stochasticity of neuronal output, and its high dimensionality. We propose a dissimilarity measure between neuronal patterns based on optimal transport theory, determining their similarity from the pairwise cross-correlation matrix, which can be taken as a proxy of the "trace" that is left on the synaptic matrix. We then perform unsupervised clustering and visualization of patterns using density clustering on the dissimilarity matrix and low-dimensional embedding techniques. This method does not require binning of spike times, is robust to noise, jitter and rate fluctuations, and can detect more patterns than the number of neurons.
]]></description>
<dc:creator>Grossberger, L.</dc:creator>
<dc:creator>Battaglia, F. P.</dc:creator>
<dc:creator>Vinck, M.</dc:creator>
<dc:date>2018-01-24</dc:date>
<dc:identifier>doi:10.1101/252791</dc:identifier>
<dc:title><![CDATA[A novel distance measure for the unsupervised clustering of temporal patterns in high-dimensional neuronal ensembles]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-01-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/303982v1?rss=1">
<title>
<![CDATA[
Catecholamine Challenge Uncovers Distinct Mechanisms For Direct Versus Indirect, But Not Social Versus Non-Social, Learning 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/303982v1?rss=1"
</link>
<description><![CDATA[
Evidence that social and individual learning are at least partially dissociable sustains the belief that humans possess adaptive specialisations for social learning. However, in most extant paradigms, social information comprises an indirect source that can be used to supplement ones own, direct, experience. Thus, social and individual learning differ both in terms of social nature (social versus non-social) and directness (indirect versus direct). To test whether the dissociation between social and individual learning is best explained in terms of social nature or directness, we used a catecholaminergic challenge known to modulate learning. Two groups completed a decision-making task which required direct learning, from own experience, and indirect learning from an additional source. The groups differed in terms of whether the indirect source was social or non-social. The catecholamine transporter blocker, methylphenidate, affected direct learning by improving adaptation to changes in the volatility of the environment but there was no effect of methylphenidate on learning from the social or non-social indirect source. Thus, we report positive evidence for a dissociable effect of methylphenidate on direct and indirect learning, but no evidence for a distinction between social and non-social. These data fail to support the adaptive specialisation view, instead providing evidence for distinct mechanisms for direct versus indirect learning.
]]></description>
<dc:creator>Cook, J. L.</dc:creator>
<dc:creator>Swart, J. C.</dc:creator>
<dc:creator>Frobose, M. I.</dc:creator>
<dc:creator>Diaconescu, A.</dc:creator>
<dc:creator>Geurts, D. E. M.</dc:creator>
<dc:creator>den Ouden, H. E. M.</dc:creator>
<dc:creator>Cools, R.</dc:creator>
<dc:date>2018-04-24</dc:date>
<dc:identifier>doi:10.1101/303982</dc:identifier>
<dc:title><![CDATA[Catecholamine Challenge Uncovers Distinct Mechanisms For Direct Versus Indirect, But Not Social Versus Non-Social, Learning]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-04-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/308387v1?rss=1">
<title>
<![CDATA[
Ablation of proliferating neural stem cells during early life is sufficient to reduce adult hippocampal neurogenesis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/308387v1?rss=1"
</link>
<description><![CDATA[
Environmental exposures during early life, but not during adolescence or adulthood, lead to persistent reductions in neurogenesis in the adult hippocampal dentate gyrus (DG). The mechanisms by which early life exposures lead to long-term deficits in neurogenesis remain unclear. Here, we investigated whether targeted ablation of dividing neural stem cells during early life is sufficient to produce long-term decreases in DG neurogenesis. Having previously found that the stem cell lineage is resistant to long-term effects of transient ablation of dividing stem cells during adolescence or adulthood (Kirshenbaum et al., 2014), we used a similar pharmacogenetic approach to target dividing neural stem cells for elimination during early life periods sensitive to environmental insults. We then assessed the Nestin stem cell lineage in adulthood. We found that the adult neural stem cell reservoir was depleted following ablation during the first postnatal week, when stem cells were highly proliferative, but not during the third postnatal week, when stem cells were more quiescent. Remarkably, ablating proliferating stem cells during either the first or third postnatal week led to reduced adult neurogenesis out of proportion to the changes in the stem cell pool, indicating a disruption of the stem cell function or niche following stem cell ablation in early life. These results highlight the first three postnatal weeks as a series of sensitive periods during which elimination of dividing stem cells leads to lasting alterations in adult DG neurogenesis and stem cell function. These findings contribute to our understanding of the relationship between DG development and adult neurogenesis, as well as suggest a possible mechanism by which early life experiences may lead to lasting deficits in adult hippocampal neurogenesis.
]]></description>
<dc:creator>Youssef, M.</dc:creator>
<dc:creator>Krish, V. S.</dc:creator>
<dc:creator>Kirshenbaum, G. S.</dc:creator>
<dc:creator>Atsak, P.</dc:creator>
<dc:creator>Lass, T. J.</dc:creator>
<dc:creator>Lieberman, S. R.</dc:creator>
<dc:creator>Leonardo, E. D.</dc:creator>
<dc:creator>Dranovsky, A.</dc:creator>
<dc:date>2018-04-25</dc:date>
<dc:identifier>doi:10.1101/308387</dc:identifier>
<dc:title><![CDATA[Ablation of proliferating neural stem cells during early life is sufficient to reduce adult hippocampal neurogenesis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-04-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/303990v1?rss=1">
<title>
<![CDATA[
Disruption of The Psychiatric Risk Gene Ankyrin 3 Enhances Microtubule Dynamics Through GSK3/CRMP2 Signaling 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/303990v1?rss=1"
</link>
<description><![CDATA[
The ankyrin 3 gene (ANK3) is a well-established risk gene for psychiatric illness, but the mechanisms underlying its pathophysiology remain elusive. We examined the molecular effects of disrupting brain-specific Ank3 isoforms in mouse and neuronal model systems. RNA sequencing of hippocampus from Ank3+/- and Ank3+/+ mice identified altered expression of 282 genes that were enriched for microtubule-related functions. Results were supported by increased expression of microtubule end-binding protein 3 (EB3), an indicator of microtubule dynamics, in Ank3+/- mouse hippocampus. Live-cell imaging of EB3 movement in primary neurons from Ank3+/- mice revealed impaired elongation of microtubules. Using a CRISPR-dCas9-KRAB transcriptional repressor in mouse neuro-2a cells, we determined that repression of brain-specific Ank3 increased EB3 expression, decreased tubulin acetylation, and increased the soluble:polymerized tubulin ratio, indicating enhanced microtubule dynamics. These changes were rescued by inhibition of glycogen synthase kinase 3 (GSK3) with lithium or CHIR99021, a highly selective GSK3 inhibitor. Brain-specific Ank3 repression in neuro-2a cells increased GSK3 activity (reduced inhibitory phosphorylation) and elevated collapsin response mediator protein 2 (CRMP2) phosphorylation, a known GSK3 substrate and microtubule-binding protein. Pharmacological inhibition of CRMP2 activity attenuated the rescue of EB3 expression and tubulin polymerization in Ank3 repressed cells by lithium or CHIR99021, suggesting microtubule instability induced by Ank3 repression is dependent on CRMP2 activity. Taken together, our data indicate that aNK3 functions in neuronal microtubule dynamics through GSK3 and its downstream substrate CRMP2. These findings reveal cellular and molecular mechanisms underlying brain-specific ANK3 disruption that may be related to its role in psychiatric illness.
]]></description>
<dc:creator>Garza, J. C.</dc:creator>
<dc:creator>Qi, X.</dc:creator>
<dc:creator>Gjeluci, K.</dc:creator>
<dc:creator>Leussis, M. P.</dc:creator>
<dc:creator>Basu, H.</dc:creator>
<dc:creator>Reis, S. A.</dc:creator>
<dc:creator>Zhao, W. N.</dc:creator>
<dc:creator>Piguel, N. H.</dc:creator>
<dc:creator>Penzes, P.</dc:creator>
<dc:creator>Haggarty, S. J.</dc:creator>
<dc:creator>Martens, G. J.</dc:creator>
<dc:creator>Poelmans, G.</dc:creator>
<dc:creator>Petryshen, T. L.</dc:creator>
<dc:date>2018-04-21</dc:date>
<dc:identifier>doi:10.1101/303990</dc:identifier>
<dc:title><![CDATA[Disruption of The Psychiatric Risk Gene Ankyrin 3 Enhances Microtubule Dynamics Through GSK3/CRMP2 Signaling]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-04-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/303164v1?rss=1">
<title>
<![CDATA[
Genetics of brain age suggest an overlap with common brain disorders 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/303164v1?rss=1"
</link>
<description><![CDATA[
Numerous genetic and environmental factors contribute to psychiatric disorders and other brain disorders. Common risk factors likely converge on biological pathways regulating the optimization of brain structure and function across the lifespan. Here, using structural magnetic resonance imaging and machine learning, we estimated the gap between brain age and chronological age in 36,891 individuals aged 3 to 96 years, including individuals with different brain disorders. We show that several disorders are associated with accentuated brain aging, with strongest effects in schizophrenia, multiple sclerosis and dementia, and document differential regional patterns of brain age gaps between disorders. In 16,269 healthy adult individuals, we show that brain age gap is heritable with a polygenic architecture overlapping those observed in common brain disorders. Our results identify brain age gap as a genetically modulated trait that offers a window into shared and distinct mechanisms in different brain disorders.
]]></description>
<dc:creator>Kaufmann, T.</dc:creator>
<dc:creator>van der Meer, D.</dc:creator>
<dc:creator>Doan, N. T.</dc:creator>
<dc:creator>Schwarz, E.</dc:creator>
<dc:creator>Lund, M. J.</dc:creator>
<dc:creator>Agartz, I.</dc:creator>
<dc:creator>Alnaes, D.</dc:creator>
<dc:creator>Barch, D. M.</dc:creator>
<dc:creator>Baur-Streubel, R.</dc:creator>
<dc:creator>Bertolino, A.</dc:creator>
<dc:creator>Bettella, F.</dc:creator>
<dc:creator>Beyer, M. K.</dc:creator>
<dc:creator>Boen, E.</dc:creator>
<dc:creator>Borgwardt, S.</dc:creator>
<dc:creator>Brandt, C. L.</dc:creator>
<dc:creator>Buitelaar, J.</dc:creator>
<dc:creator>Celius, E. G.</dc:creator>
<dc:creator>Cervenka, S.</dc:creator>
<dc:creator>Conzelmann, A.</dc:creator>
<dc:creator>Cordova-Palomera, A.</dc:creator>
<dc:creator>Dale, A. M.</dc:creator>
<dc:creator>de Quervain, D. J.- F.</dc:creator>
<dc:creator>Di Carlo, P.</dc:creator>
<dc:creator>Djurovic, S.</dc:creator>
<dc:creator>Dorum, E. S.</dc:creator>
<dc:creator>Eisenacher, S.</dc:creator>
<dc:creator>Elvsashagen, T.</dc:creator>
<dc:creator>Espeseth, T.</dc:creator>
<dc:creator>Fatouros-Bergman, H.</dc:creator>
<dc:creator>Flyckt, L.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Frei, O.</dc:creator>
<dc:creator>Haatveit, B.</dc:creator>
<dc:creator>Haberg, A. K.</dc:creator>
<dc:creator>Harbo, H. F.</dc:creator>
<dc:creator>Hartman, C. A.</dc:creator>
<dc:creator>Heslenfeld, D.</dc:creator>
<dc:creator>Hoekstra, P. J.</dc:creator>
<dc:creator>Hogestol, E. A.</dc:creator>
<dc:creator>Jernigan, T.</dc:creator>
<dc:creator>Jo</dc:creator>
<dc:date>2018-04-17</dc:date>
<dc:identifier>doi:10.1101/303164</dc:identifier>
<dc:title><![CDATA[Genetics of brain age suggest an overlap with common brain disorders]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-04-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/299578v1?rss=1">
<title>
<![CDATA[
Brain scans from 21297 individuals reveal the genetic architecture of hippocampal subfield volumes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/299578v1?rss=1"
</link>
<description><![CDATA[
The hippocampus is a heterogeneous structure, comprising histologically distinguishable subfields. These subfields are differentially involved in memory consolidation, spatial navigation and pattern separation, complex functions often impaired in individuals with brain disorders characterized by reduced hippocampal volume, including Alzheimers disease (AD) and schizophrenia. Given the structural and functional heterogeneity of the hippocampal formation, we sought to characterize the subfields genetic architecture. T1-weighted brain scans (n=21297, 16 cohorts) were processed with the hippocampal subfields algorithm in FreeSurfer v6.0. We ran a genome-wide association analysis on each subfield, covarying for total hippocampal volume. We further calculated the single nucleotide polymorphism (SNP)-based heritability of twelve subfields, as well as their genetic correlation with each other, with other structural brain features, and with AD and schizophrenia. All outcome measures were corrected for age, sex, and intracranial volume. We found 15 unique genome-wide significant loci across six subfields, of which eight had not been previously linked to the hippocampus. Top SNPs were mapped to genes associated with neuronal differentiation, locomotor behaviour, schizophrenia and AD. The volumes of all the subfields were estimated to be heritable (h2 from .14 to .27, all p< 1x10-16) and clustered together based on their genetic correlations compared to other structural brain features. There was also evidence of genetic overlap of subicular subfield volumes with schizophrenia. We conclude that hippocampal subfields have partly distinct genetic determinants associated with specific biological processes and traits. Taking into account this specificity may increase our understanding of hippocampal neurobiology and associated pathologies.
]]></description>
<dc:creator>van der Meer, D.</dc:creator>
<dc:creator>Rokicki, J.</dc:creator>
<dc:creator>Kaufmann, T.</dc:creator>
<dc:creator>Cordova Palomera, A.</dc:creator>
<dc:creator>Moberget, T.</dc:creator>
<dc:creator>Alnaes, D.</dc:creator>
<dc:creator>Bettella, F.</dc:creator>
<dc:creator>Frei, O.</dc:creator>
<dc:creator>Doan, N. T.</dc:creator>
<dc:creator>Agartz, I.</dc:creator>
<dc:creator>Bertolino, A.</dc:creator>
<dc:creator>Bralten, J.</dc:creator>
<dc:creator>Brandt, C.</dc:creator>
<dc:creator>Buitelaar, J.</dc:creator>
<dc:creator>Djurovic, S.</dc:creator>
<dc:creator>van Donkelaar, M.</dc:creator>
<dc:creator>Dorum, E.</dc:creator>
<dc:creator>Espeseth, T.</dc:creator>
<dc:creator>Faraone, S.</dc:creator>
<dc:creator>Fernandez, G.</dc:creator>
<dc:creator>Fisher, S.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Haatveit, B.</dc:creator>
<dc:creator>Hartman, C.</dc:creator>
<dc:creator>Hoekstra, P.</dc:creator>
<dc:creator>Haberg, A.</dc:creator>
<dc:creator>Jonsson, E.</dc:creator>
<dc:creator>Kolskaar, K.</dc:creator>
<dc:creator>Le Hellard, S.</dc:creator>
<dc:creator>Lund, M.</dc:creator>
<dc:creator>Lundervold, A.</dc:creator>
<dc:creator>Lundervold, A.</dc:creator>
<dc:creator>Melle, I.</dc:creator>
<dc:creator>Monereo Sanchez, J.</dc:creator>
<dc:creator>Norbom, L.</dc:creator>
<dc:creator>Nordvik, J.</dc:creator>
<dc:creator>Nyberg, L.</dc:creator>
<dc:creator>Oosterlaan, J.</dc:creator>
<dc:creator>Papalino, M.</dc:creator>
<dc:creator>Papassotiropoulos, A.</dc:creator>
<dc:creator>Pergola, G.</dc:creator>
<dc:creator>de Quervain, D.</dc:creator>
<dc:creator>Ric</dc:creator>
<dc:date>2018-04-11</dc:date>
<dc:identifier>doi:10.1101/299578</dc:identifier>
<dc:title><![CDATA[Brain scans from 21297 individuals reveal the genetic architecture of hippocampal subfield volumes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-04-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/129130v1?rss=1">
<title>
<![CDATA[
The Neural Circuitry Of Emotion-Induced Distortions Of Trust 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/129130v1?rss=1"
</link>
<description><![CDATA[
Aversive emotions are likely to be a key source of irrational human decision-making but still little is known about the underlying neural circuitry. Here, we show that aversive emotions distort trust decisions and cause significant changes in the associated neural circuitry. They reduce trust and suppress trust-specific activity in left temporoparietal junction (TPJ). In addition, aversive emotions reduce the functional connectivity between TPJ and emotion-related regions such as the amygdala. We also find that the posterior superior temporal sulcus (pSTS) plays a key role in mediating the impact of aversive emotions on brain-behavior relationships. Functional connectivity of right pSTS with left TPJ not only predicts mean trust taking in the absence of negative emotions, but aversive emotions also largely remove this association between TPJ-pSTS connectivity and behavioral trust. These findings may be useful for a better understanding of the neural circuitry of affective distortions and may thus help identify the neural bases of psychiatric diseases that are associated with emotion-related psychological and behavioral dysfunctions.
]]></description>
<dc:creator>Engelmann, J. B.</dc:creator>
<dc:creator>Meyer, F.</dc:creator>
<dc:creator>Ruff, C. C.</dc:creator>
<dc:creator>Fehr, E.</dc:creator>
<dc:date>2017-04-24</dc:date>
<dc:identifier>doi:10.1101/129130</dc:identifier>
<dc:title><![CDATA[The Neural Circuitry Of Emotion-Induced Distortions Of Trust]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-04-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/297481v1?rss=1">
<title>
<![CDATA[
Predictive remapping of visual features beyond saccadic targets 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/297481v1?rss=1"
</link>
<description><![CDATA[
Visual stability is thought to be mediated by predictive remapping of the relevant object information from its current, pre-saccadic locations to its future, post-saccadic location on the retina. However, it is heavily debated whether and what feature information is predictively remapped during the pre-saccadic interval. Using an orientation adaptation paradigm, we investigated whether predictive remapping occurs for stimulus features and whether adaptation itself is remapped. We found strong evidence for predictive remapping of a stimulus presented shortly before saccade onset, but no remapping of adaptation. Furthermore, we establish that predictive remapping also occurs for stimuli that are not saccade targets, pointing toward a  forward remapping process operating across the whole visual field. Together, our findings suggest that predictive feature remapping of object information plays an important role in mediating visual stability.
]]></description>
<dc:creator>He, T.</dc:creator>
<dc:creator>Fritsche, M.</dc:creator>
<dc:creator>de Lange, F. P.</dc:creator>
<dc:date>2018-04-08</dc:date>
<dc:identifier>doi:10.1101/297481</dc:identifier>
<dc:title><![CDATA[Predictive remapping of visual features beyond saccadic targets]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-04-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/290817v1?rss=1">
<title>
<![CDATA[
Gamma synchronization between V1 and V4 improves behavioral performance 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/290817v1?rss=1"
</link>
<description><![CDATA[
Motor behavior is often driven by visual stimuli, relying on efficient feedforward communication from lower to higher visual areas. The Communication-through-Coherence hypothesis proposes that interareal communication depends on coherence at an optimal phase relation. While previous studies have linked effective communication to enhanced interareal coherence, it remains unclear, whether this interareal coherence occurs at an optimal phase relation that actually improves the stimulus transmission to behavioral report. We recorded local field potentials simultaneously from areas V1 and V4 of macaque monkeys performing a selective visual attention task, during which they reported changes of the attended stimulus. Gamma synchronization between V1 and V4, immediately preceding the stimulus change, predicted subsequent reaction times (RTs). Crucially, RTs were systematically slowed as trial-by-trial interareal gamma phase relations deviated from the phase relation at which V1 and V4 synchronized on average. These effects were specific to the attended stimulus and not due to local power or phase inside V1 or V4. We conclude that interareal gamma synchronization occurs at the optimal phase relation and thereby improves interareal communication and the effective transformation of sensory inputs into motor responses.
]]></description>
<dc:creator>Rohenkohl, G.</dc:creator>
<dc:creator>Bosman, C. A.</dc:creator>
<dc:creator>Fries, P.</dc:creator>
<dc:date>2018-04-02</dc:date>
<dc:identifier>doi:10.1101/290817</dc:identifier>
<dc:title><![CDATA[Gamma synchronization between V1 and V4 improves behavioral performance]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-04-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/292508v1?rss=1">
<title>
<![CDATA[
Stimulus predictability does not modulate bottom-up attentional capture 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/292508v1?rss=1"
</link>
<description><![CDATA[
Attention can be involuntarily captured by physically salient stimuli, a phenomenon known as bottom-up attention. Typically, these salient stimuli occur unpredictably in time and space. Therefore, in a series of three behavioral experiments, we investigated the extent to which such bottom-up attentional capture is a function of ones prior expectations. In the context of an exogenous cueing task, we systematically manipulated participants spatial (Experiment 1) or temporal (Experiment 2 and 3) expectations about an uninformative cue, and examined the extent of attentional capture by the cue. We anticipated larger attentional capture for unexpected compared to expected cues. However, while we observed robust attentional capture in all experiments, we did not find any evidence for a modulation of attentional capture by prior expectation. This underscores the automatic and reflexive nature of bottom-up attention.
]]></description>
<dc:creator>Meijs, E.</dc:creator>
<dc:creator>Klaassen, F. H.</dc:creator>
<dc:creator>Bokeria, L.</dc:creator>
<dc:creator>van Gaal, S.</dc:creator>
<dc:creator>de Lange, F.</dc:creator>
<dc:date>2018-03-30</dc:date>
<dc:identifier>doi:10.1101/292508</dc:identifier>
<dc:title><![CDATA[Stimulus predictability does not modulate bottom-up attentional capture]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-03-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/220590v1?rss=1">
<title>
<![CDATA[
Bayesian adaptive stimulus selection for dissociating models of psychophysical data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/220590v1?rss=1"
</link>
<description><![CDATA[
Comparing models facilitates testing different hypotheses regarding the computational basis of perception and action. Effective model comparison requires stimuli for which models make different predictions. Typically, experiments use a predetermined set of stimuli or sample stimuli randomly. Both methods have limitations; a predetermined set may not contain stimuli that dissociate the models whereas random sampling may be inefficient. To overcome these limitations, we expanded the psi-algorithm (Kontsevich & Tyler, 1999) from estimating the parameters of a psychometric curve to distinguishing models. To test our algorithm, we applied it to two distinct problems. First, we investigated dissociating sensory noise models. We simulated ideal observers with different noise models performing a 2-afc task. Stimuli were selected randomly or using our algorithm. We found using our algorithm improved the accuracy of model comparison. We also validated the algorithm in subjects by inferring which noise model underlies speed perception. Our algorithm converged quickly to the model previously proposed (Stocker & Simoncelli, 2006), whereas if stimuli were selected randomly model probabilities separated slower and sometimes supported alternative models. Second, we applied our algorithm to a different problem; comparing models of target selection under body acceleration. Previous work found target choice preference is modulated by whole body acceleration (Rincon-Gonzalez et al., 2016). However, the effect is subtle making model comparison difficult. We show that selecting stimuli adaptively could have led to stronger conclusions in model comparison. We conclude that our technique is more efficient and more reliable than current methods of stimulus selection for dissociating models.nnData AvailabilityAll data and code will be posted on our institutional repository system following acceptance. In the meantime feel free to contact the authors if you would like any of the code.
]]></description>
<dc:creator>Cooke, J. R. H.</dc:creator>
<dc:creator>Selen, L. P. J.</dc:creator>
<dc:creator>van Beers, R. J.</dc:creator>
<dc:creator>Medendorp, W. P.</dc:creator>
<dc:date>2017-11-17</dc:date>
<dc:identifier>doi:10.1101/220590</dc:identifier>
<dc:title><![CDATA[Bayesian adaptive stimulus selection for dissociating models of psychophysical data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/157644v1?rss=1">
<title>
<![CDATA[
From curiosity relief to epistemic surprise: complementary roles of the prefrontal cortex and the ventral striatum in the neural valuation of knowledge 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/157644v1?rss=1"
</link>
<description><![CDATA[
Epistemic curiosity (EC) is a cornerstone of human cognition that contributes to the actualization of our cognitive potential by stimulating a myriad of information-seeking behaviours. Yet, its fundamental relationship with uncertainty remains poorly understood, which limits our ability to predict within- and between-individual variability in the willingness to acquire knowledge. Here, a two-step stochastic trivia quiz designed to induce curiosity and manipulate answer uncertainty provided behavioural and neural evidence for an integrative model of EC inspired from predictive coding. More precisely, our behavioural data indicated an inverse relationship between average surprise and EC levels, which depended upon hemodynamic activity in the rostrolateral prefrontal cortex from one trial to another and from one individual to another. Complementary, the elicitation of epistemic surprise and the relief of acute curiosity states were respectively related to ventromedial prefrontal cortex and ventral striatum activity. Taken together, our results account for the temporal evolution of EC over time, as well as for the interplay of EC, prior knowledge and surprise in controlling memory gain.
]]></description>
<dc:creator>Ligneul, R.</dc:creator>
<dc:creator>Mermillod, M.</dc:creator>
<dc:creator>Morisseau, T.</dc:creator>
<dc:date>2017-06-30</dc:date>
<dc:identifier>doi:10.1101/157644</dc:identifier>
<dc:title><![CDATA[From curiosity relief to epistemic surprise: complementary roles of the prefrontal cortex and the ventral striatum in the neural valuation of knowledge]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-06-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/285809v1?rss=1">
<title>
<![CDATA[
Ipsilateral finger representations are engaged in active movement, but not sensory processing 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/285809v1?rss=1"
</link>
<description><![CDATA[
Hand and finger movements are mostly controlled through crossed corticospinal projections from the contralateral hemisphere. During unimanual movements, activity in the contralateral hemisphere is increased while the ipsilateral hemisphere is suppressed below resting baseline. Despite this suppression, unimanual movements can be decoded from ipsilateral activity alone. This indicates that ipsilateral activity patterns represent parameters of ongoing movement, but the origin and functional relevance of these representations is unclear. Here, we asked whether human ipsilateral representations are caused by active movement, or whether they are driven by sensory input. Participants alternated between performing single finger presses and having fingers passively stimulated, while we recorded brain activity using high-field (7T) functional imaging. We contrasted active and passive finger representations in sensorimotor areas of ipsilateral and contralateral hemispheres. Finger representations in the contralateral hemisphere were equally strong under passive and active conditions, highlighting the importance of sensory information in feedback control. In contrast, ipsilateral finger representations were stronger during active presses. Furthermore, the spatial distribution of finger representations differed between hemispheres: the contralateral hemisphere showed the strongest finger representations in Brodmann area 3a and 3b, while the ipsilateral hemisphere exhibited stronger representations in premotor and parietal areas. This suggests that finger representations in the two hemispheres have different origins - contralateral representations are driven by both active movement and sensory stimulation, whereas ipsilateral representations are mainly engaged during active movement. This suggests that a possible contribution of the ipsilateral hemisphere lies in movement planning, rather than in the dexterous feedback control of the movement.nnSignificance statementMovements of the human body are mostly controlled by contralateral cortical regions. However, activity in ipsilateral sensorimotor regions is also modulated during active movements. The origin and functional relevance of these ipsilateral representations is unclear. Here we used high-field neuroimaging to investigate how human contralateral and ipsilateral hemispheres represent active finger presses and passive finger stimulation. We report that while the contralateral hemisphere was equally strongly recruited during active and passive conditions, the ipsilateral hemisphere was mostly recruited during active movement. We propose that the ipsilateral hemisphere may play a role in bilateral movement planning.
]]></description>
<dc:creator>Berlot, E.</dc:creator>
<dc:creator>Prichard, G.</dc:creator>
<dc:creator>O'Reilly, J.</dc:creator>
<dc:creator>Ejaz, N.</dc:creator>
<dc:creator>Diedrichsen, J.</dc:creator>
<dc:date>2018-03-20</dc:date>
<dc:identifier>doi:10.1101/285809</dc:identifier>
<dc:title><![CDATA[Ipsilateral finger representations are engaged in active movement, but not sensory processing]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-03-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/285544v1?rss=1">
<title>
<![CDATA[
Laminar signal extraction over extended cortical areas by means of a spatial GLM 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/285544v1?rss=1"
</link>
<description><![CDATA[
There is converging evidence that distinct neuronal processes leave distinguishable footprints in the laminar BOLD response. However, even though the achievable spatial resolution in functional MRI has much improved over the years, it is still challenging to separate signals arising from different cortical layers. In this work, we propose a new method to extract laminar signals. We use a spatial General Linear Model in combination with the equivolume principle of cortical layers to unmix laminar signals instead of interpolating through and integrating over a cortical area: thus reducing partial volume effects. Not only do we provide a mathematical framework for extracting laminar signals with a spatial GLM, we also illustrate that the best case scenarios of existing methods can be seen as special cases within the same framework. By means of simulation, we show that this approach has a sharper point spread function, providing better signal localisation. We further assess the partial volume contamination in cortical profiles from high resolution human ex vivo and in vivo structural data, and provide a full account of the benefits and potential caveats. We eschew here any attempt to validate the spatial GLM on the basis of fMRI data as a generally accepted ground-truth pattern of laminar activation does not currently exist. This approach is flexible in terms of the number of layers and their respective thickness, and naturally integrates spatial regularisation along the cortex, while preserving laminar specificity. Care must be taken, however, as this procedure of unmixing is susceptible to sources of noise in the data or inaccuracies in the laminar segmentation.
]]></description>
<dc:creator>van Mourik, T.</dc:creator>
<dc:creator>van der Eerden, J. P.</dc:creator>
<dc:creator>Bazin, P.-L.</dc:creator>
<dc:creator>Norris, D. G.</dc:creator>
<dc:date>2018-03-20</dc:date>
<dc:identifier>doi:10.1101/285544</dc:identifier>
<dc:title><![CDATA[Laminar signal extraction over extended cortical areas by means of a spatial GLM]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-03-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/282467v1?rss=1">
<title>
<![CDATA[
Eye-movement intervention enhances extinction via amygdala deactivation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/282467v1?rss=1"
</link>
<description><![CDATA[
Improving extinction learning is essential to optimize psychotherapy for persistent fear-related disorders. In two independent studies (both n=24), we found that goal-directed eye movements activate a dorsal fronto-parietal network and transiently deactivate the amygdala. Connectivity analyses revealed this down-regulation engages a ventromedial prefrontal pathway known to be involved in cognitive regulation of emotion. Critically, when eye movements followed memory reactivation during extinction learning, this reduced spontaneous fear recovery 24 hours later. Stronger amygdala deactivation furthermore predicted a stronger reduction in subsequent fear recovery after reinstatement. In conclusion, we show that extinction learning can be improved with a non-invasive eye-movement intervention that triggers a transient suppression of the amygdala. Our finding that another task which taxes working memory leads to a similar amygdala suppression furthermore indicates that this effect is likely not specific to eye movements, which is in line with a large body of behavioral studies. This study contributes to the understanding of a widely used treatment for traumatic symptoms by providing a parsimonious account for how working memory tasks and goal-directed eye movements can enhance extinction-based psychotherapy, namely through neural circuits similar to those that support cognitive control of emotion.nnSignificant statementFear-related disorders represent a significant burden on individual sufferers and society. There is a high need to optimize treatment, in particular via non-invasive means. One potentially effective intervention is execution of eye movements following trauma recall. However, a neurobiological understanding of how eye movements can reduce traumatic symptoms is lacking. We demonstrate that goal-directed eye-movements, like working memory tasks, deactivate the amygdala, the core neural substrate of fear learning. Effective connectivity analyses revealed amygdala deactivation engaged dorsolateral and ventromedial prefrontal pathways. When applied during safety learning, this deactivation predicts a reduction in later fear recovery. These findings provide a parsimonious and mechanistic account of how behavioral manipulations taxing working memory and suppress amygdala activity can alter retention of emotional memories.
]]></description>
<dc:creator>de Voogd, L. D.</dc:creator>
<dc:creator>Kanen, J. W.</dc:creator>
<dc:creator>Neville, D. A.</dc:creator>
<dc:creator>Roelofs, K.</dc:creator>
<dc:creator>Fernandez, G.</dc:creator>
<dc:creator>Hermans, E. J.</dc:creator>
<dc:date>2018-03-18</dc:date>
<dc:identifier>doi:10.1101/282467</dc:identifier>
<dc:title><![CDATA[Eye-movement intervention enhances extinction via amygdala deactivation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-03-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/273706v1?rss=1">
<title>
<![CDATA[
Testing competing models of dorsal anterior cingulate 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/273706v1?rss=1"
</link>
<description><![CDATA[
Recent theories have attempted to provide unifying accounts of dorsal anterior cingulate cortex (dACC), a region routinely observed in studies of cognitive control and decision-making. Despite the proliferation of frameworks, rigorous empirical testing has lagged behind theory. Here we test competing predictions of three accounts of dACC using a simple value-based decision-making task. We find that the Predicted Response-Outcome model provides an integrative and parsimonious account of our results. Our results highlight the need for increased emphasis on empirical tests of theoretical frameworks.
]]></description>
<dc:creator>Vassena, E.</dc:creator>
<dc:creator>Deraeve, J.</dc:creator>
<dc:creator>Alexander, W. H.</dc:creator>
<dc:date>2018-02-28</dc:date>
<dc:identifier>doi:10.1101/273706</dc:identifier>
<dc:title><![CDATA[Testing competing models of dorsal anterior cingulate]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-02-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/259671v1?rss=1">
<title>
<![CDATA[
Variable training but not sleep improves consolidation of motor adaptation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/259671v1?rss=1"
</link>
<description><![CDATA[
How motor memory consolidates still remains elusive. Motor tasks consolidation were shown to depend on periods of sleep, whereas pure non-hippocampal dependent tasks, like motor adaptation, might not. Some research suggests that the mode of training might affect the sleep dependency of motor adaptation tasks. Here we investigated whether sleep differentially impacts memory consolidation dependent on the variability during training. Healthy men were trained with their dominant, right hand on a force field adaptation task and re-tested after an 11-h consolidation period either involving overnight sleep (Sleep) or daytime wakefulness (Wake). Retesting also included a transfer to the non-dominant hand. Half of the subjects in each group adapted to different force field magnitudes with low inter-trial variability (Sleep-Blocked; Wake-Blocked), the other half with high variability (Sleep-Random; Wake-Random). EEG was recorded during task execution and overnight polysomnography. Motor adaptation was comparable between Wake and Sleep groups, although performance changes over sleep correlated with sleep spindles nesting in slow wave upstates. Higher training variability improved retest, including transfer learning, and these improvements correlated with higher alpha power in contralateral parietal areas. Enhanced consolidation after training might foster the ability to correct ongoing movements by responsive feedback rather than their pre-execution prediction.
]]></description>
<dc:creator>Thuerer, B.</dc:creator>
<dc:creator>Weber, F.</dc:creator>
<dc:creator>Born, J.</dc:creator>
<dc:creator>Stein, T.</dc:creator>
<dc:date>2018-02-04</dc:date>
<dc:identifier>doi:10.1101/259671</dc:identifier>
<dc:title><![CDATA[Variable training but not sleep improves consolidation of motor adaptation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-02-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/266205v1?rss=1">
<title>
<![CDATA[
Feature Specific Prediction Errors and Surprise across Macaque Fronto-Striatal Circuits during Attention and Learning 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/266205v1?rss=1"
</link>
<description><![CDATA[
Prediction errors signal unexpected outcomes indicating that expectations need to be adjusted. For adjusting expectations efficiently prediction errors need to be associated with the precise features that gave rise to the unexpected outcome. For many visual tasks this credit assignment proceeds in a multidimensional feature space that makes it ambiguous which object defining features are relevant. Here, we report of a potential solution by showing that neurons in all areas of the medial and lateral fronto-striatal networks encode prediction errors that are specific to separate features of attended multidimensional stimuli, with the most ubiquitous prediction error occurring for the reward relevant features. These feature specific prediction error signals (1) are different from a non-specific prediction error signal, (2) arise earliest in the anterior cingulate cortex and later in lateral prefrontal cortex, caudate and ventral striatum, and (3) contribute to feature-based stimulus selection after learning. These findings provide strong evidence for a widely-distributed feature-based eligibility trace that can be used to update synaptic weights for improved feature-based attention.nnHighlightsO_LINeural reward prediction errors carry information for updating feature-based attention in all areas of the fronto-striatal network.nC_LIO_LIFeature specific neural prediction errors emerge earliest in anterior cingulate cortex and later in lateral prefrontal cortex.nC_LIO_LIVentral striatum neurons encode feature specific surprise strongest for the goal-relevant feature.nC_LIO_LINeurons encoding feature-specific prediction errors contribute to attentional selection after learning.nC_LI
]]></description>
<dc:creator>Oemisch, M.</dc:creator>
<dc:creator>Westendorff, S.</dc:creator>
<dc:creator>Azimi, M.</dc:creator>
<dc:creator>Hassani, S. A.</dc:creator>
<dc:creator>Ardid, S.</dc:creator>
<dc:creator>Tiesinga, P.</dc:creator>
<dc:creator>Womelsdorf, T.</dc:creator>
<dc:date>2018-02-15</dc:date>
<dc:identifier>doi:10.1101/266205</dc:identifier>
<dc:title><![CDATA[Feature Specific Prediction Errors and Surprise across Macaque Fronto-Striatal Circuits during Attention and Learning]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-02-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/263673v1?rss=1">
<title>
<![CDATA[
Stress matters: a double-blind, randomized controlled trial on the effects of a multispecies probiotic on neurocognition 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/263673v1?rss=1"
</link>
<description><![CDATA[
Probiotics are microorganisms that can provide health benefits when consumed. Recent animal studies have demonstrated that probiotics can reverse gut microbiome-related alterations in anxiety and depression-like symptoms, in hormonal responses to stress, and in cognition. However, in humans, the effects of probiotics on neurocognition remain poorly understood and a causal understanding of the gut-brain link in emotion and cognition is lacking. We aimed to fill this gap by studying the effects of a probiotics intervention versus placebo on neurocognition in healthy human volunteers.nnWe set out to investigate the effects of a multispecies probiotic (Ecologic(R)Barrier) on specific neurocognitive measures of emotion reactivity, emotion regulation, and cognitive control using fMRI. Critically, we also tested whether the use of probiotics can buffer against the detrimental effects of acute stress on working memory. In a double blind, randomized, placebo-controlled, between-subjects intervention study, 58 healthy participants were tested twice, once before and once after 28 days of intervention with probiotics or placebo.nnProbiotics versus placebo did not affect emotion reactivity, emotion regulation, and cognitive control processes at brain or behavioral level, neither related self-report measures. However, relative to the placebo group, the probiotics group did show a significant stress-related increase in working memory performance after versus before supplementation (digit span backward, p=0.039, {eta}p2=.07). Interestingly, this change was associated with intervention-related neural changes in frontal cortex during cognitive control in the probiotics group, but not in the placebo group. Overall, our results show that neurocognitive effects of supplementation with a multispecies probiotic in healthy women become visible under challenging (stress) situations. Probiotics buffered against the detrimental effects of stress in terms of cognition, especially in those individuals with probiotics-induced changes in frontal brain regions during cognitive control.nnHighlightsO_LIWe ran a randomized placebo-controlled fMRI study with a multispecies probioticnC_LIO_LIProbiotics did not affect neurocognitive measures of emotion and cognitive controlnC_LIO_LIProbiotics did affect stress-related working memory and neural correlatesnC_LIO_LIProbiotics in healthy individuals can support cognition under stressnC_LI
]]></description>
<dc:creator>Papalini, S.</dc:creator>
<dc:creator>Michels, F.</dc:creator>
<dc:creator>Kohn, N.</dc:creator>
<dc:creator>Wegman, J.</dc:creator>
<dc:creator>van Hemert, S.</dc:creator>
<dc:creator>Roelofs, K.</dc:creator>
<dc:creator>Arias Vasquez, A.</dc:creator>
<dc:creator>Aarts, E.</dc:creator>
<dc:date>2018-02-13</dc:date>
<dc:identifier>doi:10.1101/263673</dc:identifier>
<dc:title><![CDATA[Stress matters: a double-blind, randomized controlled trial on the effects of a multispecies probiotic on neurocognition]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-02-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/263111v1?rss=1">
<title>
<![CDATA[
Subtle left-right asymmetry of gene expression profiles in embryonic and foetal human brains 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/263111v1?rss=1"
</link>
<description><![CDATA[
Left-right laterality is an important aspect of human brain organization for which the genetic basis is poorly understood. Using RNA sequencing data we contrasted gene expression in left- and right-sided samples from several structures of the anterior central nervous systems of post mortem human embryos and fetuses. While few individual genes stood out as significantly lateralized, most structures showed evidence of laterality of their overall transcriptomic profiles. These left-right differences showed overlap with age-dependent changes in expression, indicating lateralized maturation rates, but not consistently in left-right orientation over all structures. Brain asymmetry may therefore originate in multiple locations, or if there is a single origin, it is earlier than 5 weeks post conception, with structure-specific lateralized processes already underway by this age. This pattern is broadly consistent with the weak correlations reported between various aspects of adult brain laterality, such as language dominance and handedness.
]]></description>
<dc:creator>de Kovel, C. G. F.</dc:creator>
<dc:creator>Lisgo, S. N.</dc:creator>
<dc:creator>Fisher, S. E.</dc:creator>
<dc:creator>Francks, C.</dc:creator>
<dc:date>2018-02-09</dc:date>
<dc:identifier>doi:10.1101/263111</dc:identifier>
<dc:title><![CDATA[Subtle left-right asymmetry of gene expression profiles in embryonic and foetal human brains]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-02-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/255166v1?rss=1">
<title>
<![CDATA[
Reactivation of neural patterns during memory reinstatement supports encoding specificity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/255166v1?rss=1"
</link>
<description><![CDATA[
Encoding specificity or transfer appropriate processing state that memory benefits when items are encoded and retrieved in the same modality compared to when encoding and retrieval is conducted in different modalities. In neural terms, these effects can be expressed by a resonance process between a memory cue and a stored engram; the more the two overlap the better memory performance. We here used temporal pattern analysis in MEG to tap into this resonance process. We predicted that reactivation of sensory patterns established during encoding has opposing effects depending on whether there is a match or mismatch between the memory cue and the encoding modality. To test this prediction items were presented either visually or aurally during encoding and in a recognition test to create match (e.g. "dog" presented aurally during encoding and recognition) and mismatch conditions (e.g. "dog" presented aurally during encoding and shown visually during recognition). Memory performance was better for items in the match compared to the mismatch condition. MEG results showed that memory benefitted from neural pattern reinstatement only in the match condition, but suffered from reinstatement in the mismatch condition. These behavioural and neural effects were asymmetric in that they were only obtained for aurally encoded words but not for visually encoded words. A simple computational model was generated in order to simulate these opposing effects of neural pattern reactivation on memory performance. We argue that these results suggest that reactivation of neural patterns established during encoding underlies encoding specificity or transfer appropriate processing.
]]></description>
<dc:creator>Staudigl, T.</dc:creator>
<dc:creator>Hanslmayr, S.</dc:creator>
<dc:date>2018-01-30</dc:date>
<dc:identifier>doi:10.1101/255166</dc:identifier>
<dc:title><![CDATA[Reactivation of neural patterns during memory reinstatement supports encoding specificity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-01-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/255091v1?rss=1">
<title>
<![CDATA[
Causal explanation of individual differences in human sensorimotor memory formation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/255091v1?rss=1"
</link>
<description><![CDATA[
Sensorimotor cortex mediates the formation of adaptation memory. Individuals differ in the rate at which they acquire, retain, and generalize adaptation. We present a mechanistic explanation of the neurochemical and computational causes of this variation in humans. Neuroimaging identified structural, functional and neurochemical covariates of a computational parameter that determines memory persistence. To establish causality, we increased sensorimotor cortex excitability during adaptation, using transcranial direct current stimulation. As predicted, this increased retention. Inter-individual variance in the stimulation-induced E:I increase predicted the computational change, which predicted the memory gain. These relations did not hold, and memory was unchanged, with stimulation applied before adaptation. This cognitive state dependent effect was modulated by the BDNF val66met genetic polymorphism. Memory was enhanced by stimulation in Val/Val carriers only, implicating a mechanistic role for activity-dependent BDNF secretion. Sensorimotor cortex E:I causally determines the time constant of memory persistence, explaining phenotypic variation in adaptation decay.
]]></description>
<dc:creator>Petitet, P.</dc:creator>
<dc:creator>O'Reilly, J. X.</dc:creator>
<dc:creator>Goncalves, A. M.</dc:creator>
<dc:creator>Salvan, P.</dc:creator>
<dc:creator>Kitazawa, S.</dc:creator>
<dc:creator>Johansen-Berg, H.</dc:creator>
<dc:creator>O'Shea, J.</dc:creator>
<dc:date>2018-01-29</dc:date>
<dc:identifier>doi:10.1101/255091</dc:identifier>
<dc:title><![CDATA[Causal explanation of individual differences in human sensorimotor memory formation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-01-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/177279v1?rss=1">
<title>
<![CDATA[
Structural and functional MRI from a cross-sectional Southwest University Adult lifespan Dataset (SALD) 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/177279v1?rss=1"
</link>
<description><![CDATA[
Recently, the field of developmental neuroscience has aimed to uncover the developmental trajectory of the human brain and understand the changes that occur as a function of aging. Here we present an adult lifespan dataset of functional magnetic resonance imaging (fMRI) data including structural MRI and resting-state functional MRI. 494 healthy adults (age range: 19-80 years; Males=187) were recruited and completed two multi-modal MRI scan sessions in the Brain Imaging Central of Southwest University, Chongqing, China. The goals of the dataset are to give researchers the opportunity to map the developmental trajectory of structural and functional changes of human brain and to replicate previous findings.
]]></description>
<dc:creator>Wei, D.</dc:creator>
<dc:creator>Zhuang, K.</dc:creator>
<dc:creator>Chen, Q.</dc:creator>
<dc:creator>Yang, W.</dc:creator>
<dc:creator>Liu, W.</dc:creator>
<dc:creator>Wang, K.</dc:creator>
<dc:creator>Sun, J.</dc:creator>
<dc:creator>Qiu, J.</dc:creator>
<dc:date>2017-08-17</dc:date>
<dc:identifier>doi:10.1101/177279</dc:identifier>
<dc:title><![CDATA[Structural and functional MRI from a cross-sectional Southwest University Adult lifespan Dataset (SALD)]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-08-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/250787v1?rss=1">
<title>
<![CDATA[
Identification of rare de novo epigenetic variations in congenital disorders 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/250787v1?rss=1"
</link>
<description><![CDATA[
Certain human traits such as neurodevelopmental disorders (NDs) and congenital anomalies (CAs) are believed to be primarily genetic in origin. With recent dramatic advances in genomic technologies, genome-wide surveys of cohorts of patients with ND/CAs for point mutations and structural variations have greatly advanced our understanding of their genetic etiologies1,2. However, even after whole genome sequencing (WGS), a substantial fraction of such disorders remain unexplained3. In contrast, the possibility that constitutive epigenetic variations (epivariations) might underlie such traits has not been well explored. We hypothesized that some cases of ND/CA are caused by aberrations of DNA methylation that lead to a dysregulation of normal genome function. By comparing DNA methylation profiles from 489 individuals with ND/CAs against 1,534 population controls, we identified epivariations as a frequent occurrence in the human genome. De novo epivariations were significantly enriched in cases when compared to controls. RNAseq data from population studies showed that epivariations often have an impact on gene expression comparable to loss-of-function mutations. Additionally, we detected and replicated an enrichment of rare sequence mutations overlapping CTCF binding sites close to epivariations. Thus, some epivariations occur secondary to cis-linked mutations in regulatory regions, providing a rationale for interpreting non-coding genetic variation. We propose that epivariations likely represent the causative genomic defect in 5-10% of patients with unexplained ND/CAs. This constitutes a yield comparable to CNV microarrays, and as such has significant diagnostic relevance.
]]></description>
<dc:creator>Barbosa, M.</dc:creator>
<dc:creator>Joshi, R. S.</dc:creator>
<dc:creator>Garg, P.</dc:creator>
<dc:creator>Martin-Trujillo, A.</dc:creator>
<dc:creator>Patel, N.</dc:creator>
<dc:creator>Jadhav, B.</dc:creator>
<dc:creator>Watson, C. T.</dc:creator>
<dc:creator>Gibson, W.</dc:creator>
<dc:creator>Chetnik, K.</dc:creator>
<dc:creator>Tessereau, C.</dc:creator>
<dc:creator>Mei, H.</dc:creator>
<dc:creator>de Rubeis, S.</dc:creator>
<dc:creator>Reichert, J.</dc:creator>
<dc:creator>Lopes, F.</dc:creator>
<dc:creator>Vissers, L.</dc:creator>
<dc:creator>Kleefstra, T.</dc:creator>
<dc:creator>Grice, D. E.</dc:creator>
<dc:creator>Edelmann, L.</dc:creator>
<dc:creator>Soares, G.</dc:creator>
<dc:creator>Maciel, P.</dc:creator>
<dc:creator>Brunner, H. G.</dc:creator>
<dc:creator>Buxbaum, J. D.</dc:creator>
<dc:creator>Gelb, B. D.</dc:creator>
<dc:creator>Sharp, A.</dc:creator>
<dc:date>2018-01-19</dc:date>
<dc:identifier>doi:10.1101/250787</dc:identifier>
<dc:title><![CDATA[Identification of rare de novo epigenetic variations in congenital disorders]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-01-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/171587v1?rss=1">
<title>
<![CDATA[
Dopaminergic drug effects on probability weighting during risky decision-making 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/171587v1?rss=1"
</link>
<description><![CDATA[
Dopamine has been associated with risky decision-making, as well as with pathological gambling, a behavioural addiction characterized by excessive risk-taking behaviour. However, the specific mechanisms through which dopamine might act to foster risk-taking and pathological gambling remain elusive. Here we test the hypothesis that this might be achieved, in part, via modulation of subjective probability weighing during decision-making. Healthy controls (n = 21) and pathological gamblers (n = 16) played a decision-making task involving choices between sure monetary options and risky gambles both in the gain and loss domains. Each participant played the task twice, either under placebo or the dopamine D2/D3 receptor antagonist sulpiride, in a double-blind, counter-balanced, design. A prospect theory modelling approach was used to estimate subjective probability weighting and sensitivity to monetary outcomes. Consistent with prospect theory, we found that participants presented a distortion in the subjective weighting of probabilities, i.e. they overweighted low probabilities and underweighted moderate to high probabilities, both in the gain and loss domains. Compared with placebo, sulpiride attenuated this distortion in the gain domain. Across drugs, the groups did not differ in their probability weighting, although in the placebo condition, gamblers consistently underweighted losing probabilities. Overall, our results reveal that dopamine D2/D3 receptor antagonism modulates the subjective weighting of probabilities in the gain domain, in the direction of more objective, economically rational decision-making.nnSignificance statementDopamine has been implicated in risky decision-making and gambling addiction, but the exact mechanisms underlying this influence remain partly elusive. Here we tested the hypothesis that dopamine modulates subjective probability weighting, by examining the effect of a dopaminergic drug on risk-taking behaviour, both in healthy individuals and pathological gamblers. We found that selectively blocking dopamine D2/D3 receptors diminished the typically observed distortion of winning probabilities, characterized by an overweighting of low probabilities and underweighting of high probabilities. This made participants more linear in their subjective estimation of probabilities, and thus more rational in their decision-making behaviour. Healthy participants and pathological gamblers did not differ in their risk-taking behaviour, except in the placebo condition in which gamblers consistently underweighted losing probabilities.
]]></description>
<dc:creator>Ojala, K. E.</dc:creator>
<dc:creator>Janssen, L. K.</dc:creator>
<dc:creator>Hashemi, M. M.</dc:creator>
<dc:creator>Timmer, M. H. M.</dc:creator>
<dc:creator>Geurts, D. E. M.</dc:creator>
<dc:creator>ter Huurne, N. P.</dc:creator>
<dc:creator>Cools, R.</dc:creator>
<dc:creator>Sescousse, G.</dc:creator>
<dc:date>2017-08-02</dc:date>
<dc:identifier>doi:10.1101/171587</dc:identifier>
<dc:title><![CDATA[Dopaminergic drug effects on probability weighting during risky decision-making]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-08-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/248120v1?rss=1">
<title>
<![CDATA[
Improved cortical boundary registration for locally distorted fMRI scans 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/248120v1?rss=1"
</link>
<description><![CDATA[
With continuing advances in MRI techniques and the emergence of higher static field strengths, submillimetre spatial resolution is now possible in human functional imaging experiments. This has opened up the way for more specific types of analysis, for example investigation of the cortical layers of the brain. With this increased specificity, it is important to correct for the geometrical distortions that are inherent to echo planar imaging (EPI). Inconveniently, higher field strength also increases these distortions. The resulting displacements can easily amount to several millimetres and as such pose a serious problem for laminar analysis. We here present a method, Recursive Boundary Registration (RBR), that corrects distortions between an anatomical and an EPI volume. By recursively applying Boundary Based Registration (BBR) on progressively smaller subregions of the brain we generate an accurate whole-brain registration, based on the grey-white matter contrast. Explicit care is taken that the deformation does not break the topology of the cortical surface, which is an important requirement for several of the most common subsequent steps in laminar analysis. We show that RBR obtains submillimetre accuracy with respect to a manually distorted gold standard, and apply it to a set of human in vivo scans to show a clear increase in spacial specificity. RBR further automates the process of non-linear distortion correction. This is an important step towards routine human laminar fMRI. We provide the code for the RBR algorithm, as well as a variety of functions to better investigate registration performance in a public GitHub repository, https://github.com/TimVanMourik/OpenFmriAnalysis, under the GPL 3.0 license.
]]></description>
<dc:creator>van Mourik, T.</dc:creator>
<dc:creator>Koopmans, P. J.</dc:creator>
<dc:creator>Norris, D. G.</dc:creator>
<dc:date>2018-01-15</dc:date>
<dc:identifier>doi:10.1101/248120</dc:identifier>
<dc:title><![CDATA[Improved cortical boundary registration for locally distorted fMRI scans]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-01-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/244756v1?rss=1">
<title>
<![CDATA[
Identifying long indels in exome sequencing data of patients with intellectual disability 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/244756v1?rss=1"
</link>
<description><![CDATA[
Exome sequencing is a powerful tool for detecting both single and multiple nucleotide variation genome wide. However long indels, in the size range 20 - 200bp, remain difficult to accurately detect. By assessing a set of common exonic long indels, we estimate the sensitivity of long indel detection in exome sequencing data to be 92%. To clarify the role of pathogenic long indels in patients with intellectual disability (ID), we analysed exome sequencing data from 820 patients using two variant callers, Pindel and Platypus. We identified three indels explaining the patients clinical phenotype by disrupting the UBE3A, PGAP3 and MECP2 genes. Comparison of different tools demonstrated the importance of both correct genotyping and annotation variants. In conclusion, specialized long indel detection can improve diagnostic yield in ID patients.
]]></description>
<dc:creator>Pajusalu, S.</dc:creator>
<dc:creator>Pfundt, R.</dc:creator>
<dc:creator>Vissers, L. E. L. M.</dc:creator>
<dc:creator>Kwint, M. P.</dc:creator>
<dc:creator>Reimand, T.</dc:creator>
<dc:creator>Ounap, K.</dc:creator>
<dc:creator>Veltman, J. A.</dc:creator>
<dc:creator>Hehir-Kwa, J.</dc:creator>
<dc:date>2018-01-15</dc:date>
<dc:identifier>doi:10.1101/244756</dc:identifier>
<dc:title><![CDATA[Identifying long indels in exome sequencing data of patients with intellectual disability]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-01-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/245209v1?rss=1">
<title>
<![CDATA[
Whole brain comparative anatomy using connectivity blueprints 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/245209v1?rss=1"
</link>
<description><![CDATA[
Comparing the brains of related species faces the challenges of establishing homologies whilst accommodating evolutionary specializations. Here we propose a general framework for understanding similarities and differences between the brains of primates. The approach uses white matter blueprints of the whole cortex based on a set of white matter tracts that can be anatomically matched across species. The blueprints provide a common reference space that allows us to navigate between brains of different species, identify homologue cortical areas, or to transform whole cortical maps from one species to the other. Specializations are cast within this framework as deviations between the species blueprints. We illustrate how this approach can be used to compare human and macaque brains.
]]></description>
<dc:creator>Mars, R. B.</dc:creator>
<dc:creator>Sotiropoulos, S. N.</dc:creator>
<dc:creator>Passingham, R. E.</dc:creator>
<dc:creator>Sallet, J.</dc:creator>
<dc:creator>Verhagen, L.</dc:creator>
<dc:creator>Krapitchev, A. A.</dc:creator>
<dc:creator>Sibson, N.</dc:creator>
<dc:creator>Jbabdi, S.</dc:creator>
<dc:date>2018-01-10</dc:date>
<dc:identifier>doi:10.1101/245209</dc:identifier>
<dc:title><![CDATA[Whole brain comparative anatomy using connectivity blueprints]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-01-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/243527v1?rss=1">
<title>
<![CDATA[
Theta and gamma oscillations in the rat hippocampus during attentive lever pressing 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/243527v1?rss=1"
</link>
<description><![CDATA[
The hippocampus is known to be pivotal for spatial memory but emerging evidence suggests its contribution to temporal memories as well. However, it is not clear how the hippocampus represents time and how it synchronizes spatial and temporal presentations into a coherent memory. We assessed the specific role of hippocampal theta and gamma oscillations and their interaction in short-term timing of motor reactions. Rats were trained to maintain lever pressing for 2.5 s and then to quickly release the lever and retrieve water reward from a nearby water port guided by a cue light. In essence, this task allows observation of hippocampal rhythms during timed anticipation when no overt movements take place. Then we implanted wire electrodes to five hippocampal layers for recording local field potentials during the task. Consistent with earlier reports, theta showed a declining trend during the lever press. We also found that fast-gamma declined in tandem with theta while slow-gamma showed an opposite trend. Theta-phase to gamma-amplitude cross-frequency coupling measured with modulation index (MI) varied significantly between the three task phases. Interestingly, also changes in MI were opposite for fast- and slow-gamma. The MI was also related to the task performance, so that during omission trials the MI for fast-gamma in CA1 was smaller than during trials with premature lever release. In addition, the MI in dentate hilus was higher during all error trials than during correctly performed trials. Collectively, these data suggest an important role of synchronization of hippocampal theta and gamma rhythms to timing of cued motor reactions.
]]></description>
<dc:creator>Lipponen, A.</dc:creator>
<dc:creator>Tanila, H.</dc:creator>
<dc:creator>Gurevicius, K.</dc:creator>
<dc:date>2018-01-05</dc:date>
<dc:identifier>doi:10.1101/243527</dc:identifier>
<dc:title><![CDATA[Theta and gamma oscillations in the rat hippocampus during attentive lever pressing]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-01-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/230557v1?rss=1">
<title>
<![CDATA[
The Role of Left Dorsolateral Prefrontal Cortex in Language Processing 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/230557v1?rss=1"
</link>
<description><![CDATA[
In addition to the role of left frontotemporal areas in language processing, there is increasing evidence that language comprehension and production require control and working memory resources involving the left dorsolateral prefrontal cortex (DLPFC). The aim of this study was to investigate the role of the left DLPFC in both language comprehension and production. In a double-blind, sham-controlled crossover experiment, thirty-two participants received cathodal or sham transcranial direct current stimulation (tDCS) to the left DLPFC while performing a language comprehension and a language production task. Results showed that cathodal tDCS increases reaction times in the language comprehension task, but decreases naming latencies in the language production task. However, additional analyses revealed that the polarity of tDCS effects was highly correlated across tasks, implying differential individual susceptibility to the effect of tDCS within participants. Overall, our findings demonstrate that left DLPFC is part of the complex cortical network associated with language processing.
]]></description>
<dc:creator>Klaus, J.</dc:creator>
<dc:creator>Schutter, D. J. L. G.</dc:creator>
<dc:date>2017-12-07</dc:date>
<dc:identifier>doi:10.1101/230557</dc:identifier>
<dc:title><![CDATA[The Role of Left Dorsolateral Prefrontal Cortex in Language Processing]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-12-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/191544v1?rss=1">
<title>
<![CDATA[
Enhanced food-related responses in the ventral medial prefrontal cortex in orexin-deficient narcolepsy patients 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/191544v1?rss=1"
</link>
<description><![CDATA[
BackgroundNarcolepsy Type 1 is a chronic sleep disorder caused by a deficiency of orexin (hypocretin). In addition to sleep regulation, orexin is important for motivated control processes. Weight gain and obesity are common in narcolepsy. However, the neurocognitive processes associated with food-related control and overeating in orexin-deficient patients are unknown. We explored the neural correlates of general and food-related attentional control in narcolepsy patients (n=23) and healthy BMI-matched controls (n=20). In secondary analyses, we included patients with idiopathic hypersomnia (n=15) to assess sleepiness-related influences.nnMethodsWe measured attentional bias to food words with a Food Stroop task and general executive control with a Classic Stroop task during fMRI. Moreover, with correlational analyses, we assessed the relative contribution of the neural findings on the Food Stroop and Classic Stroop tasks to spontaneous snack intake.nnResultsRelative to healthy controls, narcolepsy patients showed enhanced ventral medial prefrontal cortex responses and connectivity with motor cortex during the Food Stroop task, but attenuated dorsal medial prefrontal cortex responses during the Classic Stroop task. The ventral medial prefrontal cortex responses on the Food Stroop task, not the dorsal medial prefrontal cortex responses on the Classic Stroop task, were a significant predictor of snack intake. Comparing the narcolepsy patients with idiopathic hypersomnia patients revealed similar results.nnConclusionsThese findings demonstrate that orexin deficiency is associated with decreased dorsal medial prefrontal cortex responses during general executive control and enhanced ventral medial prefrontal cortex responses during food-driven attention, with the latter predicting increases in food intake.nnStatement of SignificancePatients with orexin (hypocretin) deficient narcolepsy type-1 often suffer from obesity as well as increased food craving, in addition to the sleep symptoms. However, whether and how orexin deficiency relates to neural differences in food-directed attention is unclear. We employed a Food Stroop task during fMRI and provide experimental evidence that the ventral medial prefrontal cortex responds more strongly to food words in narcolepsy patients than in controls. The hypothesis that this mechanism contributes to weight problems in narcolepsy is strengthened by the observation that ventral medial prefrontal cortex responses during the Food Stroop task were predictive of snack intake. These mechanistic data might thus advance the development of treatment targets for obesity in narcolepsy.
]]></description>
<dc:creator>van Holst, R. J.</dc:creator>
<dc:creator>Janssen, L. K.</dc:creator>
<dc:creator>van Mierlo, P.</dc:creator>
<dc:creator>Lammers, G. J.</dc:creator>
<dc:creator>Cools, R.</dc:creator>
<dc:creator>Overeem, S.</dc:creator>
<dc:creator>Aarts, E.</dc:creator>
<dc:date>2017-09-20</dc:date>
<dc:identifier>doi:10.1101/191544</dc:identifier>
<dc:title><![CDATA[Enhanced food-related responses in the ventral medial prefrontal cortex in orexin-deficient narcolepsy patients]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/230912v1?rss=1">
<title>
<![CDATA[
Integrated analysis of anatomical and electrophysiological human intracranial data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/230912v1?rss=1"
</link>
<description><![CDATA[
The exquisite spatiotemporal precision of human intracranial EEG recordings (iEEG) permits characterizing neural processing with a level of detail that is inaccessible to scalp-EEG, MEG, or fMRI. However, the same qualities that make iEEG an exceptionally powerful tool also present unique challenges. Until now, the fusion of anatomical data (MRI and CT images) with the electrophysiological data and its subsequent analysis has relied on technologically and conceptually challenging combinations of software. Here, we describe a comprehensive protocol that addresses the complexities associated with human iEEG, providing complete transparency and flexibility in the evolution of raw data into illustrative representations. The protocol is directly integrated with an open source toolbox for electrophysiological data analysis (FieldTrip). This allows iEEG researchers to build on a continuously growing body of scriptable and reproducible analysis methods that, over the past decade, have been developed and employed by a large research community. We demonstrate the protocol for an example complex iEEG data set to provide an intuitive and rapid approach to dealing with both neuroanatomical information and large electrophysiological data sets. We explain how the protocol can be largely automated, taking under an hour to complete, and readily adjusted to iEEG data sets with other characteristics.
]]></description>
<dc:creator>Stolk, A.</dc:creator>
<dc:creator>Griffin, S.</dc:creator>
<dc:creator>van der Meij, R.</dc:creator>
<dc:creator>Dewar, C.</dc:creator>
<dc:creator>Saez, I.</dc:creator>
<dc:creator>Lin, J. J.</dc:creator>
<dc:creator>Piantoni, G.</dc:creator>
<dc:creator>Schoffelen, J.-M.</dc:creator>
<dc:creator>Knight, R. T.</dc:creator>
<dc:creator>Oostenveld, R.</dc:creator>
<dc:date>2017-12-08</dc:date>
<dc:identifier>doi:10.1101/230912</dc:identifier>
<dc:title><![CDATA[Integrated analysis of anatomical and electrophysiological human intracranial data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-12-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/230656v1?rss=1">
<title>
<![CDATA[
Low-frequency alternating current stimulation rhythmically suppresses stimulus-induced gamma-band oscillations in visual cortex and impairs perceptual performance 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/230656v1?rss=1"
</link>
<description><![CDATA[
Alpha oscillations (8-12 Hz) are hypothesized to rhythmically gate sensory processing, reflected by activity in the 40-100 Hz gamma band, via the mechanism of pulsed inhibition. We applied transcranial alternating current stimulation (TACS) at individual alpha frequency (IAF) and flanking frequencies (IAF-4 Hz, IAF+4 Hz) to the occipital cortex of healthy human volunteers during concurrent magnetoencephalography (MEG), while participants performed a visual detection task inducing strong gamma-band responses. Occipital (but not frontal) TACS phasically suppressed stimulus-induced gamma oscillations in the visual cortex and impaired target detection, with stronger phase-to-amplitude coupling predicting behavioral impairments. Frontal control TACS ruled out retino-thalamo-cortical entrainment resulting from (subthreshold) retinal stimulation. All TACS frequencies tested were effective, suggesting that visual gamma-band responses can be modulated by a range of low frequency oscillations. We propose that TACS-induced cortical excitability fluctuations mimic the mechanism of pulsed inhibition, which mediates the function of alpha oscillations in gating sensory processing.
]]></description>
<dc:creator>Herring, J. D.</dc:creator>
<dc:creator>Esterer, S.</dc:creator>
<dc:creator>Marshall, T. R.</dc:creator>
<dc:creator>Jensen, O.</dc:creator>
<dc:creator>Bergmann, T. O.</dc:creator>
<dc:date>2017-12-07</dc:date>
<dc:identifier>doi:10.1101/230656</dc:identifier>
<dc:title><![CDATA[Low-frequency alternating current stimulation rhythmically suppresses stimulus-induced gamma-band oscillations in visual cortex and impairs perceptual performance]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-12-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/228890v1?rss=1">
<title>
<![CDATA[
Suppressed sensory response to predictable object stimuli throughout the ventral visual stream 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/228890v1?rss=1"
</link>
<description><![CDATA[
Prediction plays a crucial role in perception, as prominently suggested by predictive coding theories. However, the exact form and mechanism of predictive modulations of sensory processing remain unclear, with some studies reporting a downregulation of the sensory response for predictable input, while others observed an enhanced response. In a similar vein, downregulation of the sensory response for predictable input has been linked to either sharpening or dampening of the sensory representation, which are opposite in nature. In the present study we set out to investigate the neural consequences of perceptual expectation of object stimuli throughout the visual hierarchy, using fMRI in human volunteers. Participants (n=24) were exposed to pairs of sequentially presented object images in a statistical learning paradigm, in which the first object predicted the identity of the second object. Image transitions were not task relevant; thus all learning of statistical regularities was incidental. We found strong suppression of neural responses to expected compared to unexpected stimuli throughout the ventral visual stream, including primary visual cortex (V1), lateral occipital complex (LOC), and anterior ventral visual areas. Expectation suppression in LOC, but not V1, scaled positively with image preference, lending support to the dampening account of expectation suppression in object perception.nnSignificance StatementStatistical regularities permeate our world and help us to perceive and understand our surroundings. It has been suggested that the brain fundamentally relies on predictions and constructs models of the world in order to make sense of sensory information. Previous research on the neural basis of prediction has documented expectation suppression, i.e. suppressed responses to expected compared to unexpected stimuli. In the present study we queried the presence and characteristics of expectation suppression throughout the ventral visual stream. We demonstrate robust expectation suppression in the entire ventral visual pathway, and underlying this suppression a dampening of the sensory representation in object-selective visual cortex, but not in primary visual cortex. Taken together, our results provide novel evidence in support of theories conceptualizing perception as an active inference process, which selectively dampens cortical representations of predictable objects. This dampening may support our ability to automatically filter out irrelevant, predictable objects.
]]></description>
<dc:creator>Richter, D.</dc:creator>
<dc:creator>Ekman, M.</dc:creator>
<dc:creator>de Lange, F. P.</dc:creator>
<dc:date>2017-12-04</dc:date>
<dc:identifier>doi:10.1101/228890</dc:identifier>
<dc:title><![CDATA[Suppressed sensory response to predictable object stimuli throughout the ventral visual stream]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-12-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/227462v1?rss=1">
<title>
<![CDATA[
An open resource for nonhuman primate imaging 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/227462v1?rss=1"
</link>
<description><![CDATA[
Non-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience.nnUnfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMate Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 13 independent data collections aggregated across 11 sites (total = 98 macaque monkeys). We also outline the unique pitfalls and challenges that should be considered in the analysis of the non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets.
]]></description>
<dc:creator>Milham, M.</dc:creator>
<dc:creator>Ai, L.</dc:creator>
<dc:creator>Koo, B.</dc:creator>
<dc:creator>Xu, T.</dc:creator>
<dc:creator>Balezeau, F.</dc:creator>
<dc:creator>Baxter, M. G.</dc:creator>
<dc:creator>Croxson, P. L.</dc:creator>
<dc:creator>Damatac, C. G.</dc:creator>
<dc:creator>Harel, N.</dc:creator>
<dc:creator>Freiwald, W.</dc:creator>
<dc:creator>Griffiths, T. D.</dc:creator>
<dc:creator>Everling, S.</dc:creator>
<dc:creator>Jung, B.</dc:creator>
<dc:creator>Kastner, S.</dc:creator>
<dc:creator>Leopold, D. A.</dc:creator>
<dc:creator>Mars, R. B.</dc:creator>
<dc:creator>Menon, R. S.</dc:creator>
<dc:creator>Messinger, A.</dc:creator>
<dc:creator>Morrison, J. H.</dc:creator>
<dc:creator>Nacef, J.</dc:creator>
<dc:creator>Nagy, J.</dc:creator>
<dc:creator>Rios, M. O.</dc:creator>
<dc:creator>Petkov, C. I.</dc:creator>
<dc:creator>Pinsk, M.</dc:creator>
<dc:creator>Poirier, C.</dc:creator>
<dc:creator>Rajimehr, R.</dc:creator>
<dc:creator>Rushworth, M. F.</dc:creator>
<dc:creator>Russ, B. E.</dc:creator>
<dc:creator>Schmid, M.</dc:creator>
<dc:creator>Schwiedrzik, C. M.</dc:creator>
<dc:creator>Sallet, J.</dc:creator>
<dc:creator>Seidlitz, J.</dc:creator>
<dc:creator>Ungerleider, L.</dc:creator>
<dc:creator>Thiele, A.</dc:creator>
<dc:creator>Tsao, D.</dc:creator>
<dc:creator>Yacoub, E.</dc:creator>
<dc:creator>Ye, F.</dc:creator>
<dc:creator>Zarco, W.</dc:creator>
<dc:creator>Margulies, D. S.</dc:creator>
<dc:creator>Schroeder, C. E.</dc:creator>
<dc:date>2017-11-30</dc:date>
<dc:identifier>doi:10.1101/227462</dc:identifier>
<dc:title><![CDATA[An open resource for nonhuman primate imaging]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/226217v1?rss=1">
<title>
<![CDATA[
Differential temporal dynamics during visual imagery and perception 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/226217v1?rss=1"
</link>
<description><![CDATA[
Visual perception and imagery rely on similar representations in the visual cortex. During perception, visual activity is characterized by distinct processing stages, but the temporal dynamics underlying imagery remain unclear. Here, we investigated the dynamics of visual imagery in human participants using magnetoencephalography. We show that, contrary to perception, the onset of imagery is characterized by broad temporal generalization. Furthermore, there is consistent overlap between imagery and perceptual processing around 150 ms and from 300 ms after stimulus onset, presumably reflecting completion of the feedforward sweep and perceptual stabilization respectively. These results indicate that during imagery either the complete representation is activated at once and does not include low-level visual areas, or the order in which visual features are activated is less fixed and more flexible than during perception. These findings have important implications for our understanding of the neural mechanisms of visual imagery.
]]></description>
<dc:creator>Dijkstra, N.</dc:creator>
<dc:creator>Mostert, P.</dc:creator>
<dc:creator>de Lange, F.</dc:creator>
<dc:creator>Bosch, S. E.</dc:creator>
<dc:creator>van Gerven, M.</dc:creator>
<dc:date>2017-11-30</dc:date>
<dc:identifier>doi:10.1101/226217</dc:identifier>
<dc:title><![CDATA[Differential temporal dynamics during visual imagery and perception]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/111187v1?rss=1">
<title>
<![CDATA[
Reverse inference via connectivity fingerprinting: task sensitivity, task specificity, and task potency 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/111187v1?rss=1"
</link>
<description><![CDATA[
When an individual engages in a task, the associated evoked activities build upon already ongoing activity, itself shaped by an underlying functional connectivity baseline (Fox et al., 2009; Smith et al., 2009; Tavor et al., 2016). To facilitate understanding the building blocks of cognition we incorporate the idea that task-induced functional connectivity modulation with respect to its underlying resting state functional connectivity is task-specific. Here, we introduce a framework incorporating task potency, providing direct access to task-specificity through enabling direct comparison between task paradigms. In particular, to study functional connectivity modulations related to cognitive involvement in a task we define task potency as the amplitude of connectivity modulations away from the brains baseline functional connectivity architecture as observed during a resting state acquisition. We demonstrate the use of our framework by comparing three tasks (visuo-spatial working memory, reward processing, and stop signal task) available within a large cohort. Using task potency, we demonstrate that cognitive operations are supported by a common baseline of within-network interactions, supplemented by connections between large-scale networks in order to solve a specific task.nnHighlights- Task potency framework defines modulation of functional connectivity away from baseline resting staten- More within-than between-network modulations are induced by task performancen- Between-network modulations are task-specificn- Edges modulated by multiple tasks are mostly within-networkn- The task potency can be used to define the most potent task
]]></description>
<dc:creator>Chauvin, R.</dc:creator>
<dc:creator>Mennes, M.</dc:creator>
<dc:creator>Buitelaar, J.</dc:creator>
<dc:creator>Beckmann, C.</dc:creator>
<dc:date>2017-02-27</dc:date>
<dc:identifier>doi:10.1101/111187</dc:identifier>
<dc:title><![CDATA[Reverse inference via connectivity fingerprinting: task sensitivity, task specificity, and task potency]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-02-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/224774v1?rss=1">
<title>
<![CDATA[
Common risk variants identified in autism spectrum disorder 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/224774v1?rss=1"
</link>
<description><![CDATA[
Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 ASD cases and 27,969 controls that identifies five genome-wide significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), seven additional loci shared with other traits are identified at equally strict significance levels. Dissecting the polygenic architecture we find both quantitative and qualitative polygenic heterogeneity across ASD subtypes, in contrast to what is typically seen in other complex disorders. These results highlight biological insights, particularly relating to neuronal function and corticogenesis and establish that GWAS performed at scale will be much more productive in the near term in ASD, just as it has been in a broad range of important psychiatric and diverse medical phenotypes.
]]></description>
<dc:creator>Grove, J.</dc:creator>
<dc:creator>Ripke, S.</dc:creator>
<dc:creator>Als, T. D.</dc:creator>
<dc:creator>Mattheisen, M.</dc:creator>
<dc:creator>Walters, R.</dc:creator>
<dc:creator>Won, H.</dc:creator>
<dc:creator>Pallesen, J.</dc:creator>
<dc:creator>Agerbo, E.</dc:creator>
<dc:creator>Andreassen, O. A.</dc:creator>
<dc:creator>Anney, R.</dc:creator>
<dc:creator>Belliveau, R.</dc:creator>
<dc:creator>Bettella, F.</dc:creator>
<dc:creator>Buxbaum, J. D.</dc:creator>
<dc:creator>Bybjerg-Grauholm, J.</dc:creator>
<dc:creator>Baekved-Hansen, M.</dc:creator>
<dc:creator>Cerrato, F.</dc:creator>
<dc:creator>Chambert, K.</dc:creator>
<dc:creator>Christensen, J. H.</dc:creator>
<dc:creator>Churchhouse, C.</dc:creator>
<dc:creator>Dellenvall, K.</dc:creator>
<dc:creator>Demontis, D.</dc:creator>
<dc:creator>De Rubeis, S.</dc:creator>
<dc:creator>Devlin, B.</dc:creator>
<dc:creator>Djurovic, S.</dc:creator>
<dc:creator>Dumont, A.</dc:creator>
<dc:creator>Goldstein, J.</dc:creator>
<dc:creator>Hansen, C. S.</dc:creator>
<dc:creator>Hauberg, M. E.</dc:creator>
<dc:creator>Hollegaard, M. V.</dc:creator>
<dc:creator>Hope, S.</dc:creator>
<dc:creator>Howrigan, D. P.</dc:creator>
<dc:creator>Huang, H.</dc:creator>
<dc:creator>Hultman, C.</dc:creator>
<dc:creator>Klei, L.</dc:creator>
<dc:creator>Maller, J.</dc:creator>
<dc:creator>Martin, J.</dc:creator>
<dc:creator>Martin, A. R.</dc:creator>
<dc:creator>Moran, J.</dc:creator>
<dc:creator>Nyegaard, M.</dc:creator>
<dc:creator>Naerland, T.</dc:creator>
<dc:creator>Palmer, D. S.</dc:creator>
<dc:creator>Palotie, A.</dc:creator>
<dc:creator>Peders</dc:creator>
<dc:date>2017-11-25</dc:date>
<dc:identifier>doi:10.1101/224774</dc:identifier>
<dc:title><![CDATA[Common risk variants identified in autism spectrum disorder]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/201293v1?rss=1">
<title>
<![CDATA[
Molecules of map plasticity in the somatosensory cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/201293v1?rss=1"
</link>
<description><![CDATA[
Sensory maps are representations of the sensory epithelia in the brain. Despite the intuitive explanatory power behind sensory maps as being neuronal precursors to sensory perception, and sensory cortical plasticity as a neural correlate of perceptual learning, molecular mechanisms that regulate map plasticity are not well understood. Here we perform a meta-analysis of transcriptional and translational changes during altered whisker use to nominate the major molecular correlates of experience-dependent map plasticity in the barrel cortex. We argue that brain plasticity is a systems level response, involving all cell classes, from neuron and glia to non-neuronal cells including endothelia. Using molecular pathway analysis, we further propose a gene regulatory network that could couple activity dependent changes in neurons to adaptive changes in neurovasculature, and finally we show that transcriptional regulations observed in major brain disorders target genes that are modulated by altered sensory experience. Thus understanding the molecular mechanisms of experience-dependent plasticity of sensory maps might help to unravel the cellular events that shape brain plasticity in health and disease.nnHighlightsO_LIExperience alters gene transcription in all major cell types of the brainnC_LIO_LIGene expression profile during brain plasticity is cell-type specificnC_LIO_LITemporal profile of gene expression is dynamic, regulated by recent experiencenC_LIO_LINeural activity-dependent gene regulation might cause neurovascular reorganizationnC_LIO_LIGenes that are regulated by experience are commonly dysregulated in brain disordersnC_LI
]]></description>
<dc:creator>Kole, K.</dc:creator>
<dc:creator>Scheenen, W.</dc:creator>
<dc:creator>Tiesinga, P.</dc:creator>
<dc:creator>Celikel, T.</dc:creator>
<dc:date>2017-10-11</dc:date>
<dc:identifier>doi:10.1101/201293</dc:identifier>
<dc:title><![CDATA[Molecules of map plasticity in the somatosensory cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/215509v1?rss=1">
<title>
<![CDATA[
Eye movement-related confounds in neural decoding of visual working memory representations 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/215509v1?rss=1"
</link>
<description><![CDATA[
The study of visual working memory (VWM) has recently seen revitalization with the emergence of new insights and theories regarding its neural underpinnings. One crucial ingredient responsible for this progress is the rise of neural decoding techniques. These techniques promise to uncover the representational contents of neural signals, as well as the underlying code and the dynamic profile thereof. Here, we aimed to contribute to the field by subjecting human volunteers to a combined VWM/imagery task, while recording and decoding their neural signals as measured by MEG. At first sight, the results seem to provide evidence for a persistent, stable representation of the memorandum throughout the delay period. However, control analyses revealed that these findings can be explained by subtle, VWM-specific eye movements. As a potential remedy, we demonstrate the use of a functional localizer, which was specifically designed to target bottom-up sensory signals and as such avoids eye movements, to train the neural decoders. This analysis revealed a sustained representation for approximately 1 second, but no longer throughout the entire delay period. We conclude by arguing for more awareness of the potentially pervasive and ubiquitous effects of eye movement-related confounds.nnSignificance statementVisual working memory is an important aspect of higher cognition and has been subject of much investigation within the field of cognitive neuroscience. Over recent years, these studies have increasingly relied on the use of neural decoding techniques. Here, we show that neural decoding may be susceptible to confounds induced by stimulus-specific eye movements. Such eye movements during working memory have been reported before, and may in fact be a common phenomenon. Given the widespread use of neural decoding and the potentially contaminating effects of eye movements, we therefore believe that our results are of significant relevance for the field.
]]></description>
<dc:creator>Mostert, P.</dc:creator>
<dc:creator>Albers, A. M.</dc:creator>
<dc:creator>Brinkman, L.</dc:creator>
<dc:creator>Todorova, L.</dc:creator>
<dc:creator>Kok, P.</dc:creator>
<dc:creator>de Lange, F. P.</dc:creator>
<dc:date>2017-11-20</dc:date>
<dc:identifier>doi:10.1101/215509</dc:identifier>
<dc:title><![CDATA[Eye movement-related confounds in neural decoding of visual working memory representations]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/215178v1?rss=1">
<title>
<![CDATA[
Spontaneous eye blink rate and dopamine synthesis capacity: Preliminary evidence for an absence of positive correlation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/215178v1?rss=1"
</link>
<description><![CDATA[
Dopamine is central to a number of cognitive functions and brain disorders. Given the cost of neurochemical imaging in humans, behavioral proxy measures of dopamine have gained in popularity in the past decade, such as spontaneous eye blink rate (sEBR). Increased sEBR is commonly associated with increased dopamine function based on pharmacological evidence and patient studies. Yet, this hypothesis has not been validated using in vivo measures of dopamine function in humans. In order to fill this gap, we measured sEBR and striatal dopamine synthesis capacity using [18F]DOPA PET in 20 participants (9 healthy individuals and 11 pathological gamblers). Our results, based on frequentist and Bayesian statistics, as well as region-of-interest and voxel-wise analyses, argue against a positive relationship between sEBR and striatal dopamine synthesis capacity. They show that, if anything, the evidence is in favor of a negative relationship. These results, which complement findings from a recent study that failed to observe a relationship between sEBR and dopamine D2 receptor availability, suggest that caution and nuance are warranted when interpreting sEBR in terms of a proxy measure of striatal dopamine.
]]></description>
<dc:creator>Sescousse, G.</dc:creator>
<dc:creator>Ligneul, R.</dc:creator>
<dc:creator>van Holst, R. J.</dc:creator>
<dc:creator>Janssen, L. K.</dc:creator>
<dc:creator>de Boer, F.</dc:creator>
<dc:creator>Janssen, M.</dc:creator>
<dc:creator>Berry, A. S.</dc:creator>
<dc:creator>Jagust, W. J.</dc:creator>
<dc:creator>Cools, R.</dc:creator>
<dc:date>2017-11-17</dc:date>
<dc:identifier>doi:10.1101/215178</dc:identifier>
<dc:title><![CDATA[Spontaneous eye blink rate and dopamine synthesis capacity: Preliminary evidence for an absence of positive correlation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/221051v1?rss=1">
<title>
<![CDATA[
Reconstruction of resting-state networks from macaqueelectrocorticographic data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/221051v1?rss=1"
</link>
<description><![CDATA[
The discovery of haemodynamic (BOLD-fMRI) resting-state networks (RSNs) has brought about a fundamental shift in our thinking about the role of intrinsic brain activity. The electrophysiological underpinnings of RSNs remain largely elusive and it has been shown only recently that electrophysiological cortical rhythms are organized into RSNs. Most electrophysiological studies into RSNs use magnetoencephalography (MEG) or electroencephalography (EEG), which limits the spatial scale on which RSNs can be investigated. Due to their close proximity to the cortical surface, electroencephalographic (ECoG) recordings can potentially provide a more detailed picture of the functional organization of resting-state cortical rhythms. In this study we propose using source-space independent component analysis for identifying generators of resting-state cortical rhythms as recorded with ECoG and reconstructing their network structure. Their network structure is characterized by two kinds of connectivity: instantaneous correlations between band-limited amplitude envelopes and oscillatory phase-locking. Using simulated data, we find that the reconstruction of oscillatory phase-locking is more challenging than that of amplitude correlations, particularly for low signal-to-noise levels. Specifically, phase-lags can both be over- and underestimated as a consequence of first-order and higher-order volume-conduction effects, which troubles the interpretation of interaction measures based on imaginary phase-locking or coherence. The methodology is applied to resting-state beta (15-30 Hz) rhythms within the motor system of a macaque monkey and leads to the identification of a functional network of seven cortical generators that are distributed across the sensorimotor system. The spatial extent of the identified generators, together with consistent phase-lags, suggests that these rhythms can be viewed as being spatially continuous with complex dynamics including traveling waves. Our findings illustrate the level of spatial detail attainable with source-projected ECoG and motivates wider use of the methodology for studying resting-state as well as event-related cortical dynamics in macaque and human.
]]></description>
<dc:creator>Hindriks, R.</dc:creator>
<dc:creator>Micheli, C.</dc:creator>
<dc:creator>Bosman, C.</dc:creator>
<dc:creator>Oostenveld, R.</dc:creator>
<dc:creator>Lewis, C. M.</dc:creator>
<dc:creator>Mantini, D.</dc:creator>
<dc:creator>Fries, P.</dc:creator>
<dc:creator>Deco, G.</dc:creator>
<dc:date>2017-11-17</dc:date>
<dc:identifier>doi:10.1101/221051</dc:identifier>
<dc:title><![CDATA[Reconstruction of resting-state networks from macaqueelectrocorticographic data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/202929v1?rss=1">
<title>
<![CDATA[
Multivariate genome-wide association study of rapid automatized naming and rapid alternating stimulus in Hispanic and African American youth. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/202929v1?rss=1"
</link>
<description><![CDATA[
Reading disability is a complex neurodevelopmental disorder that is characterized by difficulties in reading despite educational opportunity and normal intelligence. Performance on rapid automatized naming (RAN) and rapid alternating stimulus (RAS) tests gives a reliable predictor of reading outcome. These tasks involve the integration of different neural and cognitive processes required in a mature reading brain. Most studies examining the genetic factors that contribute to RAN and RAS performance have focused on pedigree-based analyses in samples of European descent, with limited representation of groups with Hispanic or African ancestry. In the present study, we conducted a multivariate genome-wide association analysis to identify shared genetic factors that contribute to performance across RAN Objects, RAN Letters, and RAS Letters/Numbers in a sample of Hispanic and African American youth (n=1,331). We then tested whether these factors also contribute to variance in reading fluency and word reading. Genome-wide significant, pleiotropic, effects across RAN Objects, RAN Letters, and RAS Letters/Numbers were observed for SNPs located on chromosome 10q23.31 (rs1555839, multivariate association, p=2.23 x 10-8), which also showed significant association with reading fluency and word reading performance (p <0.001). Bioinformatic analysis of this region using epigenetic data from the NIH Roadmap Epigenomics Mapping Consortium indicates active transcription of the gene RNLS in the brain. Neuroimaging genetic analysis of fourteen cortical regions in an independent sample of typically developing children across multiple ethnicities (n=690) showed that rs1555839 was associated with variation in volume of the right inferior parietal cortex--a region of the brain that processes numerical information and has been implicated in reading disability. This study provides support for a novel locus on chromosome 10q23.31 associated with RAN, RAS, and reading-related performance.nnAUTHOR SUMMARYReading disability has a strong genetic component that is explained by multiple genes and genetic factors. The complex genetic architecture along with diverse cognitive impairments associated with reading disability, poses challenges in identifying novel genes and variants that confer risk. One method to begin parsing genetic and neurobiological mechanisms that contribute to reading disability is to take advantage of the high correlation among reading-related cognitive traits like rapid automatized naming (RAN) and rapid alternating stimulus (RAS) to identify shared genetic factors that contribute to common biological mechanisms. In the present study, we used a multivariate genome-wide analysis approach that identified a region of chromosome 10q23.31 associated with variation in RAN Objects, RAN Letters, and RAS Letters/Numbers performance in a sample of 1,331 Hispanic and African American youth in the Genes, Reading, and Dyslexia (GRaD) Study. Genetic variants in this region were also associated with reading fluency in GRaD, and differences in brain structures implicated in reading disability in a separate sample of 690 children. The gene, RNLS, is located within the implicated region of chromosome 10q23.31 and plays a role in breaking down a class of chemical messengers known to affect attention, learning, and memory in the brain. These findings provide a basis to inform our understanding of the biological basis of reading disability.
]]></description>
<dc:creator>Truong, D.</dc:creator>
<dc:creator>Adams, A. K.</dc:creator>
<dc:creator>Boada, R.</dc:creator>
<dc:creator>Frijters, J. C.</dc:creator>
<dc:creator>Hill, D. E.</dc:creator>
<dc:creator>Lovett, M. W.</dc:creator>
<dc:creator>Mahone, M. E.</dc:creator>
<dc:creator>Willcutt, E. G.</dc:creator>
<dc:creator>Wolf, M.</dc:creator>
<dc:creator>Pediatric, Imaging, Neurocognition, and Genetics C,</dc:creator>
<dc:creator>Defries, J. C.</dc:creator>
<dc:creator>Fisher, S. E.</dc:creator>
<dc:creator>Francks, C.</dc:creator>
<dc:creator>Gialluisi, A.</dc:creator>
<dc:creator>Olson, R. K.</dc:creator>
<dc:creator>Pennington, B.</dc:creator>
<dc:creator>Smith, S. D.</dc:creator>
<dc:creator>Bosson-Heenan, J.</dc:creator>
<dc:creator>Gruen, J. R.</dc:creator>
<dc:date>2017-10-16</dc:date>
<dc:identifier>doi:10.1101/202929</dc:identifier>
<dc:title><![CDATA[Multivariate genome-wide association study of rapid automatized naming and rapid alternating stimulus in Hispanic and African American youth.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/220459v1?rss=1">
<title>
<![CDATA[
Ghost interactions in MEG/EEG source space: A note of caution on inter-areal coupling measures 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/220459v1?rss=1"
</link>
<description><![CDATA[
When combined with source modeling, magneto- (MEG) and electroencephalography (EEG) can be used to study long-range interactions among cortical processes non-invasively. Estimation of such inter-areal connectivity is nevertheless hindered by instantaneous field spread and volume conduction, which artificially introduce linear correlations and impair source separability in cortical current estimates. To overcome the inflating effects of linear source mixing inherent to standard interaction measures, alternative phase- and amplitude-correlation based connectivity measures, such as imaginary coherence and orthogonalized amplitude correlation have been proposed. Being by definition insensitive to zero-lag correlations, these techniques have become increasingly popular in the identification of correlations that cannot be attributed to field spread or volume conduction. We show here, however, that while these measures are immune to the direct effects of linear mixing, they may still reveal large numbers of spurious false positive connections through field spread in the vicinity of true interactions. This fundamental problem affects both region-of-interest-based analyses and all-to-all connectome mappings. Most importantly, beyond defining and illustrating the problem of spurious, or "ghost" interactions, we provide a rigorous quantification of this effect through extensive simulations. Additionally, we further show that signal mixing also significantly limits the separability of neuronal phase and amplitude correlations. We conclude that spurious correlations must be carefully considered in connectivity analyses in MEG/EEG source space even when using measures that are immune to zero-lag correlations.nnHighlights{checkmark} Reliable estimation of neuronal coupling with MEG and EEG is challenged by signal mixingn{checkmark}A number of coupling techniques attempt to overcome this limitation by excluding zero-lag interactionsn{checkmark}Contrary to what is commonly admitted, our simulations illustrate that such interaction metrics will still yield false positivesn{checkmark}Spurious, or "ghost", interactions are generally detected between sources in the vicinity of true phase-lagged interacting sourcesn{checkmark}Signal mixing also severely affects the mutual separability of phase and amplitude correlations
]]></description>
<dc:creator>Palva, J. M.</dc:creator>
<dc:creator>Wang, S. H.</dc:creator>
<dc:creator>Palva, S.</dc:creator>
<dc:creator>Zhigalov, A.</dc:creator>
<dc:creator>Monto, S.</dc:creator>
<dc:creator>Brookes, M. J.</dc:creator>
<dc:creator>Schoffelen, J.-M.</dc:creator>
<dc:creator>Jerbi, K.</dc:creator>
<dc:date>2017-11-16</dc:date>
<dc:identifier>doi:10.1101/220459</dc:identifier>
<dc:title><![CDATA[Ghost interactions in MEG/EEG source space: A note of caution on inter-areal coupling measures]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/216036v1?rss=1">
<title>
<![CDATA[
Preparation for mental effort recruits Dorsolateral Prefrontal Cortex: an fNIRS investigation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/216036v1?rss=1"
</link>
<description><![CDATA[
Preparing for a mentally demanding task calls upon cognitive and motivational resources. The underlying neural implementation of these mechanisms is receiving growing attention, given the implications for professional, social, and medical contexts. While several fMRI studies converge in assigning a crucial role to a cortico-subcortical network including Anterior Cigulate Cortex (ACC) and striatum, the involvement of Dorsolateral Prefrontal Cortex (DLPFC) during mental effort anticipation has yet to be replicated. This study was designed to target DLPFC contribution using functional Near Infrared Spectroscopy (fNIRS), as a more cost-effective tool measuring cortical hemodynamics. We adapted a validated mental effort task, where participants performed easy and difficult mental calculation, while measuring DLPFC activity during the anticipation phase. As hypothesized, DLPFC activity increased during preparation for a hard task as compared to an easy task. Besides replicating a previous fMRI study, these results establish fNIRS as an effective tool to investigate cortical contributions to preparation for effortful behavior. This is especially useful if one requires testing large samples (e.g., to target individual differences), populations with contraindication for functional MRI (e.g., infants or patients with metal implants), or subjects in more naturalistic environments (e.g., work or sport).
]]></description>
<dc:creator>Vassena, E.</dc:creator>
<dc:creator>Gerrits, R.</dc:creator>
<dc:creator>Demanet, J.</dc:creator>
<dc:creator>Verguts, T.</dc:creator>
<dc:creator>Siugzdaite, R.</dc:creator>
<dc:date>2017-11-08</dc:date>
<dc:identifier>doi:10.1101/216036</dc:identifier>
<dc:title><![CDATA[Preparation for mental effort recruits Dorsolateral Prefrontal Cortex: an fNIRS investigation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/216283v1?rss=1">
<title>
<![CDATA[
Reactivating vocabularies in the elderly 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/216283v1?rss=1"
</link>
<description><![CDATA[
Quality of memory and sleep decline with age, but the mechanistic interactions underlying the memory function of sleep in older adults are still unknown. It is widely assumed that the beneficial effect of sleep on memory relies on reactivation during Non-rapid eye movement (NREM) sleep, and targeting these reactivations by cue re-exposure reliably improves memory in younger participants. Here we tested whether the reactivation mechanism during sleep is still functional in old age by applying targeted memory reactivation (TMR) during NREM sleep in healthy adults over 60 years. In contrast to previous studies in young participants, older adults memories do not generally benefit from TMR during NREM sleep. On an individual level, a subgroup of older adults still profited from cueing during sleep. These improvers tended to have a better sleep efficiency than non-improvers. In addition, the oscillatory results resembled those obtained in younger participants, involving increases in theta (~6Hz) and spindle (~13 Hz) power for remembered and gained words in a later time windows. In contrast, non-improvers showed no increases in theta activity and even strongly reduced spindle power for later gained vs. lost words. Our results suggest that reactivations during sleep might lose their functionality for memory in some older adults, while this mechanism is still intact in a subgroup of participants. Further studies need to examine more closely the determinants of preserving the memory function of sleep during healthy aging.nnGrant informationThe study was supported by grant of the Swiss National Science Foundation (SNSF) No. 100014_162388. T.S. is supported by a grant of the Swiss National Science Foundation (SNSF) No. P2ZHP1_164994.nnAbbreviations
]]></description>
<dc:creator>Cordi, M.</dc:creator>
<dc:creator>Schreiner, T.</dc:creator>
<dc:creator>Rasch, B.</dc:creator>
<dc:date>2017-11-08</dc:date>
<dc:identifier>doi:10.1101/216283</dc:identifier>
<dc:title><![CDATA[Reactivating vocabularies in the elderly]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-11-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/097873v1?rss=1">
<title>
<![CDATA[
The contribution of striatal pseudo-reward prediction errors to value-based decision-making 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/097873v1?rss=1"
</link>
<description><![CDATA[
Most studies that have investigated the brain mechanisms underlying learning have focused on the ability to learn simple stimulus-response associations. However, in everyday life, outcomes are often obtained through complex behavioral patterns involving a series of actions. In such scenarios, parallel learning systems are important to reduce the complexity of the learning problem, as proposed in the framework of hierarchical reinforcement learning (HRL). One of the key features of HRL is the computation of pseudo-reward prediction errors (PRPEs) which allow the reinforcement of actions that led to a sub-goal before the final goal itself is achieved. Here we wanted to test the hypothesis that, despite not carrying any rewarding value per se, pseudo-rewards might generate a bias in choice behavior when reward contingencies are not well-known or uncertain. Second, we also hypothesized that this bias might be related to the strength of PRPE striatal representations. In order to test these ideas, we developed a novel decision-making paradigm to assess reward prediction errors (RPEs) and PRPEs in two studies (fMRI study: n = 20; behavioural study: n = 19). Our results show that overall participants developed a preference for the most pseudo-rewarding option throughout the task, even though it did not lead to more monetary rewards. fMRI analyses revealed that this preference was predicted by individual differences in the relative striatal sensitivity to PRPEs vs RPEs. Together, our results indicate that pseudo-rewards generate learning signals in the striatum and subsequently bias choice behavior despite their lack of association with actual reward.
]]></description>
<dc:creator>Mas-Herrero, E.</dc:creator>
<dc:creator>Sescousse, G.</dc:creator>
<dc:creator>Cools, R.</dc:creator>
<dc:creator>Marco-Pallares, J.</dc:creator>
<dc:date>2017-01-03</dc:date>
<dc:identifier>doi:10.1101/097873</dc:identifier>
<dc:title><![CDATA[The contribution of striatal pseudo-reward prediction errors to value-based decision-making]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-01-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/211862v1?rss=1">
<title>
<![CDATA[
A neuronal mechanism underlying decision-making deficits during hyperdopaminergic states 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/211862v1?rss=1"
</link>
<description><![CDATA[
Hyperdopaminergic states in mental disorders are associated with disruptive deficits in decision-making. However, the precise contribution of topographically distinct mesencephalic dopamine pathways to decision-making processes remains elusive. Here we show, using a multidisciplinary approach, how hyperactivity of ascending projections from the ventral tegmental area (VTA) contributes to faulty decision-making in rats. Activation of the VTA-nucleus accumbens pathway leads to insensitivity to loss and punishment due to impaired processing of negative reward prediction errors. In contrast, activation of the VTA-prefrontal cortex pathway promotes risky decision-making without affecting the ability to choose the economically most beneficial option. Together, these findings show how malfunction of ascending VTA projections affects value-based decision-making, providing a mechanistic understanding of the reckless behaviors seen in substance abuse, mania, and after dopamine replacement therapy in Parkinsons disease.
]]></description>
<dc:creator>Verharen, J. P. H.</dc:creator>
<dc:creator>de Jong, J. W.</dc:creator>
<dc:creator>Roelofs, T. J. M.</dc:creator>
<dc:creator>Huffels, C. F. M.</dc:creator>
<dc:creator>van Zessen, R.</dc:creator>
<dc:creator>Luijendijk, M. C. M.</dc:creator>
<dc:creator>Hamelink, R.</dc:creator>
<dc:creator>Willuhn, I.</dc:creator>
<dc:creator>den Ouden, H. E. M.</dc:creator>
<dc:creator>van der Plasse, G.</dc:creator>
<dc:creator>Adan, R. A. H.</dc:creator>
<dc:creator>Vanderschuren, L. J. M. J.</dc:creator>
<dc:date>2017-10-31</dc:date>
<dc:identifier>doi:10.1101/211862</dc:identifier>
<dc:title><![CDATA[A neuronal mechanism underlying decision-making deficits during hyperdopaminergic states]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/158139v1?rss=1">
<title>
<![CDATA[
Immuno-Detection by sequencing (ID-seq) enables large-scale high-dimensional phenotyping in cells. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/158139v1?rss=1"
</link>
<description><![CDATA[
Cell-based small molecule screening is an effective strategy leading to new medicines. Scientists in the pharmaceutical industry as well as in academia have made tremendous progress in developing both large-scale and smaller-scale screening assays. However, an accessible and universal technology for measuring large numbers of molecular and cellular phenotypes in many samples in parallel is not available. Here, we present the Immuno-Detection by sequencing (ID-seq) technology that combines antibody-based protein detection and DNA-sequencing via DNA-tagged antibodies. We used ID-seq to simultaneously measure 84 (phospho-)proteins in hundreds of samples and screen the effects of ~300 kinase inhibitor probes on primary human epidermal stem cells to characterise the role of 225 kinases. Our work highlighted a previously unrecognized downregulation of mTOR signaling during differentiation and uncovered 13 kinases regulating epidermal renewal through distinct mechanisms.
]]></description>
<dc:creator>van Buggenum, J. A.</dc:creator>
<dc:creator>Gerlach, J. P.</dc:creator>
<dc:creator>Tanis, S. E. J.</dc:creator>
<dc:creator>Hogeweg, M.</dc:creator>
<dc:creator>Jansen, P. W. T. C.</dc:creator>
<dc:creator>Middelwijk, J.</dc:creator>
<dc:creator>van der Steen, R.</dc:creator>
<dc:creator>Vermeulen, M.</dc:creator>
<dc:creator>Albers, C. A.</dc:creator>
<dc:creator>Mulder, K. W.</dc:creator>
<dc:date>2017-06-30</dc:date>
<dc:identifier>doi:10.1101/158139</dc:identifier>
<dc:title><![CDATA[Immuno-Detection by sequencing (ID-seq) enables large-scale high-dimensional phenotyping in cells.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-06-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/210195v1?rss=1">
<title>
<![CDATA[
The relationship between spatial configuration and functional connectivity of brain regions 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/210195v1?rss=1"
</link>
<description><![CDATA[
Brain connectivity is often considered in terms of the communication between functionally distinct brain regions. Many studies have investigated the extent to which patterns of coupling strength between multiple neural populations relates to behavior. For example, studies have used "functional connectivity fingerprints" to characterise individuals' brain activity. Here, we investigate the extent to which the exact spatial arrangement of cortical regions interacts with measures of brain connectivity. We find that the shape and exact location of brain regions interact strongly with the modelling of brain connectivity, and present evidence that the spatial arrangement of functional regions is strongly predictive of non-imaging measures of behaviour and lifestyle. We believe that, in many cases, cross-subject variations in the spatial configuration of functional brain regions are being interpreted as changes in functional connectivity. Therefore, a better understanding of these effects is important when interpreting the relationship between functional imaging data and cognitive traits.
]]></description>
<dc:creator>Bijsterbosch, J. D.</dc:creator>
<dc:creator>Woolrich, M. W.</dc:creator>
<dc:creator>Glasser, M. F.</dc:creator>
<dc:creator>Robinson, E. C.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>Van Essen, D. C.</dc:creator>
<dc:creator>Harrison, S. J.</dc:creator>
<dc:creator>Smith, S. M.</dc:creator>
<dc:date>2017-10-27</dc:date>
<dc:identifier>doi:10.1101/210195</dc:identifier>
<dc:title><![CDATA[The relationship between spatial configuration and functional connectivity of brain regions]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/196634v1?rss=1">
<title>
<![CDATA[
Mapping Cortical Brain Asymmetry in 17,141 Healthy Individuals Worldwide via the ENIGMA Consortium 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/196634v1?rss=1"
</link>
<description><![CDATA[
Hemispheric asymmetry is a cardinal feature of human brain organization. Altered brain asymmetry has also been linked to some cognitive and neuropsychiatric disorders. Here the ENIGMA consortium presents the largest ever analysis of cerebral cortical asymmetry and its variability across individuals. Cortical thickness and surface area were assessed in MRI scans of 17,141 healthy individuals from 99 datasets worldwide. Results revealed widespread asymmetries at both hemispheric and regional levels, with a generally thicker cortex but smaller surface area in the left hemisphere relative to the right. Regionally, asymmetries of cortical thickness and/or surface area were found in the inferior frontal gyrus, transverse temporal gyrus, parahippocampal gyrus, and entorhinal cortex. These regions are involved in lateralized functions, including language and visuospatial processing. In addition to population-level asymmetries, variability in brain asymmetry was related to sex, age, and brain size (indexed by intracranial volume). Interestingly, we did not find significant associations between asymmetries and handedness. Finally, with two independent pedigree datasets (N = 1,443 and 1,113, respectively), we found several asymmetries showing modest but highly reliable heritability. The structural asymmetries identified, and their variabilities and heritability provide a reference resource for future studies on the genetic basis of brain asymmetry and altered laterality in cognitive, neurological, and psychiatric disorders.nnSignificance StatementLeft-right asymmetry is a key feature of the human brain's structure and function. It remains unclear which cortical regions are asymmetrical on average in the population, and how biological factors such as age, sex and genetic variation affect these asymmetries. Here we describe by far the largest ever study of cerebral cortical brain asymmetry, based on data from 17,141 participants. We found a global anterior-posterior 'torque' pattern in cortical thickness, together with various regional asymmetries at the population level, which have not been previously described, as well as effects of age, sex, and heritability estimates. From these data, we have created an on-line resource that will serve future studies of human brain anatomy in health and disease.
]]></description>
<dc:creator>Kong, X.-Z.</dc:creator>
<dc:creator>Mathias, S.</dc:creator>
<dc:creator>Guadalupe, T.</dc:creator>
<dc:creator>Abe, C.</dc:creator>
<dc:creator>Agartz, I.</dc:creator>
<dc:creator>Akudjedu, T. N.</dc:creator>
<dc:creator>Aleman, A.</dc:creator>
<dc:creator>Alhusaini, S.</dc:creator>
<dc:creator>Allen, N. B.</dc:creator>
<dc:creator>Ames, D.</dc:creator>
<dc:creator>Andreassen, O. A.</dc:creator>
<dc:creator>Armstrong, N. J.</dc:creator>
<dc:creator>Bergo, F.</dc:creator>
<dc:creator>Bastin, M. E.</dc:creator>
<dc:creator>Batalla, A.</dc:creator>
<dc:creator>Bauer, J.</dc:creator>
<dc:creator>Baune, B.</dc:creator>
<dc:creator>Baur, R.</dc:creator>
<dc:creator>Biederman, J.</dc:creator>
<dc:creator>Blaine, S. K.</dc:creator>
<dc:creator>Boedhoe, P.</dc:creator>
<dc:creator>Boen, E.</dc:creator>
<dc:creator>Bose, A.</dc:creator>
<dc:creator>Bralten, J.</dc:creator>
<dc:creator>Brandeis, D.</dc:creator>
<dc:creator>Brem, S.</dc:creator>
<dc:creator>Brodaty, H.</dc:creator>
<dc:creator>Bröhl, H.</dc:creator>
<dc:creator>Buitelaar, J.</dc:creator>
<dc:creator>Bürger, C.</dc:creator>
<dc:creator>Bülow, R.</dc:creator>
<dc:creator>Calhoun, V.</dc:creator>
<dc:creator>Calvo, A.</dc:creator>
<dc:creator>Canales-Rodriguez, E. J.</dc:creator>
<dc:creator>Canive, J. M.</dc:creator>
<dc:creator>Cannon, D. M.</dc:creator>
<dc:creator>Caparelli, E. C.</dc:creator>
<dc:creator>Castellanos, F. X.</dc:creator>
<dc:creator>Cavalleri, G. L.</dc:creator>
<dc:creator>Cendes, F.</dc:creator>
<dc:creator>Chaim-Avancini, T. M.</dc:creator>
<dc:creator>Chant</dc:creator>
<dc:date>2017-10-01</dc:date>
<dc:identifier>doi:10.1101/196634</dc:identifier>
<dc:title><![CDATA[Mapping Cortical Brain Asymmetry in 17,141 Healthy Individuals Worldwide via the ENIGMA Consortium]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/206003v1?rss=1">
<title>
<![CDATA[
Signposts in the fog: Objects facilitate scene representations in left scene-selective cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/206003v1?rss=1"
</link>
<description><![CDATA[
We internally represent the structure of our surroundings even when there is little layout information available in the visual image, such as when walking through fog or darkness. One way in which we disambiguate such scenes is through object cues; for example, seeing a boat supports the inference that the foggy scene is a lake. Recent studies have investigated the neural mechanisms by which object and scene processing interact to support object perception. The current study examines the reverse interaction, by which objects facilitate the neural representation of scene layout. Photographs of indoor (closed) and outdoor (open) real-world scenes were blurred such that they were difficult to categorize on their own, but easily disambiguated by the inclusion of an object. fMRI decoding was used to measure scene representations in scene-selective parahippocampal place area (PPA) and occipital place area (OPA). Classifiers were trained to distinguish response patterns to fully visible indoor and outdoor scenes, presented in an independent experiment. Testing these classifiers on blurred scenes revealed a strong improvement in classification in left PPA and OPA when objects were present, despite the reduced low-level visual feature overlap with the training set in this condition. These findings were specific to left PPA/OPA, with no evidence for object-driven facilitation in right PPA/OPA, object-selective areas, and early visual cortex. These findings demonstrate separate roles for left and right scene-selective cortex in scene representation, whereby left PPA/OPA represents inferred scene layout, influenced by contextual object cues, and right PPA/OPA represents a scenes visual features.
]]></description>
<dc:creator>Brandman, T.</dc:creator>
<dc:creator>Peelen, M. V.</dc:creator>
<dc:date>2017-10-19</dc:date>
<dc:identifier>doi:10.1101/206003</dc:identifier>
<dc:title><![CDATA[Signposts in the fog: Objects facilitate scene representations in left scene-selective cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/202143v1?rss=1">
<title>
<![CDATA[
Theta phase coordinated memory reactivation reoccurs in a slow-oscillatory rhythm during NREM sleep 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/202143v1?rss=1"
</link>
<description><![CDATA[
It has been proposed that sleeps contribution to memory consolidation is to reactivate prior encoded information. To elucidate the neural mechanisms carrying reactivation-related mnemonic information, we investigated whether content-specific memory signatures associated with memory reactivation during wakefulness reoccur during subsequent sleep. We show that theta oscillations orchestrate the reactivation of memories, irrespective of the physiological state. Reactivation patterns during sleep autonomously re-emerged at a rate of 1 Hz, indicating a coordination by slow oscillatory activity.
]]></description>
<dc:creator>Schreiner, T.</dc:creator>
<dc:creator>Doeller, C. F.</dc:creator>
<dc:creator>Jensen, O.</dc:creator>
<dc:creator>Rasch, B.</dc:creator>
<dc:creator>Staudigl, T.</dc:creator>
<dc:date>2017-10-12</dc:date>
<dc:identifier>doi:10.1101/202143</dc:identifier>
<dc:title><![CDATA[Theta phase coordinated memory reactivation reoccurs in a slow-oscillatory rhythm during NREM sleep]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/202424v1?rss=1">
<title>
<![CDATA[
Across-subjects classification of stimulus modality from human MEG high frequency activity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/202424v1?rss=1"
</link>
<description><![CDATA[
Single-trial analyses have the potential to uncover meaningful brain dynamics that are obscured when averaging across trials. However, low signal-to-noise ratio (SNR) can impede the use of single-trial analyses and decoding methods. In this study, we investigate the applicability of a single-trial approach to decode stimulus modality from magnetoencephalography (MEG) high frequency activity. In order to classify the auditory versus visual presentation of words, we combine beamformer source reconstruction with the random forest classification method. To enable group level inference, the classification is embedded in an across-subjects framework.nnWe show that single-trial gamma SNR allows for good classification performance (accuracy across subjects: 66.44 %). This implies that the characteristics of high frequency activity have a high consistency across trials and subjects. The random forest classifier assigned informational value to activity in both auditory and visual cortex with high spatial specificity. Across time, gamma power was most informative during stimulus presentation. Among all frequency bands, the 75-95 Hz band was the most informative frequency band in visual as well as in auditory areas. Especially in visual areas, a broad range of gamma frequencies (55-125 Hz) contributed to the successful classification.nnThus, we demonstrate the feasibility of single-trial approaches for decoding the stimulus modality across subjects from high frequency activity and describe the discriminative gamma activity in time, frequency, and space.nnAuthor SummaryAveraging brain activity across trials is a powerful way to increase signal-to-noise ratio in MEG data. This approach, however, potentially obscures meaningful brain dynamics that unfold on the single-trial level. Single-trial analyses have been successfully applied to time domain or low frequency oscillatory activity; its application to MEG high frequency activity is hindered by the low amplitude of these signals. In the present study, we show that stimulus modality (visual versus auditory presentation of words) can successfully be decoded from single-trial MEG high frequency activity by combining source reconstruction with a random forest classification algorithm. This approach reveals patterns of activity above 75 Hz in both visual and auditory cortex, highlighting the importance of high frequency activity for the processing of domain-specific stimuli. Thereby, our results extend prior findings by revealing high-frequency activity in auditory cortex related to auditory word stimuli in MEG data. The adopted across-subjects framework furthermore suggests a high inter-individual consistency in the high frequency activity patterns.
]]></description>
<dc:creator>Westner, B. U.</dc:creator>
<dc:creator>Dalal, S. S.</dc:creator>
<dc:creator>Hanslmayr, S.</dc:creator>
<dc:creator>Staudigl, T.</dc:creator>
<dc:date>2017-10-12</dc:date>
<dc:identifier>doi:10.1101/202424</dc:identifier>
<dc:title><![CDATA[Across-subjects classification of stimulus modality from human MEG high frequency activity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/117432v1?rss=1">
<title>
<![CDATA[
Transformation From Independent To Integrative Coding Of Multi-Object Arrangements In Human Visual Cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/117432v1?rss=1"
</link>
<description><![CDATA[
To optimize processing, the human visual system utilizes regularities present in naturalistic visual input. One of these regularities is the relative position of objects in a scene (e.g., a sofa in front of a television), with behavioral research showing that regularly positioned objects are easier to perceive and to remember. Here we use fMRI to test how positional regularities are encoded in the visual system. Participants viewed pairs of objects that formed minimalistic two-object scenes (e.g., a "living room" consisting of a sofa and television) presented in their regularly experienced spatial arrangement or in an irregular arrangement (with interchanged positions). Additionally, single objects were presented centrally and in isolation. Multi-voxel activity patterns evoked by the object pairs were modeled as the average of the response patterns evoked by the two single objects forming the pair. In two experiments, this approximation in object-selective cortex was significantly less accurate for the regularly than the irregularly positioned pairs, indicating integration of individual object representations. More detailed analysis revealed a transition from independent to integrative coding along the posterior-anterior axis of the visual cortex, with the independent component (but not the integrative component) being almost perfectly predicted by object selectivity across the visual hierarchy. These results reveal a transitional stage between individual object and multi-object coding in visual cortex, providing a possible neural correlate of efficient processing of regularly positioned objects in natural scenes.
]]></description>
<dc:creator>Kaiser, D.</dc:creator>
<dc:creator>Peelen, M. V.</dc:creator>
<dc:date>2017-03-16</dc:date>
<dc:identifier>doi:10.1101/117432</dc:identifier>
<dc:title><![CDATA[Transformation From Independent To Integrative Coding Of Multi-Object Arrangements In Human Visual Cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-03-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/200998v1?rss=1">
<title>
<![CDATA[
A multi-modal approach to decomposing standard neuropsychological test performance: Symbol Search 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/200998v1?rss=1"
</link>
<description><![CDATA[
Neuropsychological test batteries provide normed assessments of cognitive performance across multiple functional domains. Although each test emphasizes a certain component of cognition, a poor score can reflect many possible processing deficits. Here we explore the use of simultaneous eye tracking and EEG to decompose test performance into interpretable, components of cognitive processing. We examine the specific case of Symbol Search, a "processing speed" subtest of the WISC, which involves searching for the presence of either of two target symbols among five search symbols. To characterize the signatures of effective performance of the test, we asked 26 healthy adults to perform a computerized version of it while recording continuous EEG and eye tracking. We first established basic gaze-shifting patterns in the task, such as more frequent and prolonged fixation of each target than each search symbol, and longer search symbol fixations and overall trial duration for target-absent trials. We then entered multiple such metrics into a least absolute shrinkage and selection operator (LASSO) analysis, which revealed that short trial completion times were mainly predicted by longer initial fixations on the targets and fewer subsequent confirmatory saccades directed back to the targets. Further, the tendency to make confirmatory saccades was associated with stronger gamma-amplitude modulation by mid-frontal theta-phase in the EEG during initial target symbol encoding. Taken together, these findings indicate that efficient Symbol Search performance depends more on effective memory encoding than on general "processing speed".
]]></description>
<dc:creator>Langer, N.</dc:creator>
<dc:creator>Ho, E. J.</dc:creator>
<dc:creator>Pedroni, A.</dc:creator>
<dc:creator>Alexander, L. M.</dc:creator>
<dc:creator>Marcelle, E. T.</dc:creator>
<dc:creator>Schuster, K.</dc:creator>
<dc:creator>Milham, M. P.</dc:creator>
<dc:creator>Kelly, S. P.</dc:creator>
<dc:date>2017-10-11</dc:date>
<dc:identifier>doi:10.1101/200998</dc:identifier>
<dc:title><![CDATA[A multi-modal approach to decomposing standard neuropsychological test performance: Symbol Search]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/187344v1?rss=1">
<title>
<![CDATA[
Porcupine: a visual pipeline tool for neuroimaging analysis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/187344v1?rss=1"
</link>
<description><![CDATA[
The field of neuroimaging is rapidly adopting a more reproducible approach to data acquisition and analysis. Data structures and formats are being standardised and data analyses are getting more automated. However, as data analysis becomes more complicated, researchers often have to write longer analysis scripts, spanning different tools across multiple programming languages. This makes it more difficult to share or recreate code, reducing the reproducibility of the analysis. We present a tool, Porcupine, that constructs ones analysis visually and automatically produces analysis code. The graphical representation improves understanding of the performed analysis, while retaining the flexibility of modifying the produced code manually to custom needs. Not only does Porcupine produce the analysis code, it also creates a shareable environment for running the code, in the form of a Docker image. Together, this forms a reproducible way of constructing, visualising and sharing ones analysis. Currently, Porcupine links to Nipype functionalities, which in turn accesses most standard neuroimaging analysis tools. With Porcupine, we bridge the gap between a conceptual and an implementational level of analysis and thus create reproducible and shareable science. We give the researcher a better oversight of their pipeline, both while developing and communicating their work. This will reduce the threshold at which less expert users can generate reusable pipelines. We provide a wide range of examples and documentation, as well as installer files for all platforms on our website: https://timvanmourik.github.io/Porcupine. Porcupine is free, open source, andreleased under the GNU General Public License v3.0.nnAuthor SummaryThe neuroimaging community is fervently debating that its reproducibility and transparency should be improved, but it is a challenging problem as to how to accomplish this. We here propose a tool, Porcupine, to aid in this process by more easily creating shareable workflows for analysing neuroimaging data. The conceptual understanding of a pipeline is improved by means of the graphical interface, and it automatically produces the code to perform the analysis and to create a sharing environment. This retains full flexibility to modify the script afterwards but in principle produces readily executable code for an end-to-end analysis. Porcupine currently links to all Nipype functionality, but is designed to be extendable to other workflow packages in neuroimaging and beyond. Porcupine is free and is released under the GNU General Public License.
]]></description>
<dc:creator>van Mourik, T.</dc:creator>
<dc:creator>Snoek, L.</dc:creator>
<dc:creator>Knapen, T.</dc:creator>
<dc:creator>Norris, D.</dc:creator>
<dc:date>2017-09-12</dc:date>
<dc:identifier>doi:10.1101/187344</dc:identifier>
<dc:title><![CDATA[Porcupine: a visual pipeline tool for neuroimaging analysis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/200931v1?rss=1">
<title>
<![CDATA[
Neocortical microdissection at columnar and laminar resolution for molecular interrogation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/200931v1?rss=1"
</link>
<description><![CDATA[
The heterogeneous organization of the mammalian neocortex poses a challenge to elucidate the molecular mechanisms underlying its physiological processes. Although high-throughput molecular methods are increasingly deployed in neuroscience, their anatomical specificity is often lacking. Here we introduce a targeted microdissection technique that enables extraction of high-quality RNA and proteins at high anatomical resolution from acutely prepared brain slices. We exemplify its utility by isolating single cortical columns and laminae from the mouse primary somatosensory (barrel) cortex. Tissues can be isolated from living slices in minutes, and the extracted RNA and protein are of sufficient quantity and quality to be used for RNA-sequencing and mass spectrometry. This technique will help to increase the anatomical specificity of molecular studies of the neocortex, and the brain in general as it is applicable to any brain structure that can be identified using optical landmarks in living slices.
]]></description>
<dc:creator>Kole, K.</dc:creator>
<dc:creator>Celikel, T.</dc:creator>
<dc:date>2017-10-10</dc:date>
<dc:identifier>doi:10.1101/200931</dc:identifier>
<dc:title><![CDATA[Neocortical microdissection at columnar and laminar resolution for molecular interrogation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/199265v1?rss=1">
<title>
<![CDATA[
Top-down expectation effects of food labels on motivation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/199265v1?rss=1"
</link>
<description><![CDATA[
When we buy our food, the information on the package informs us about the properties of the product, such as its taste and healthiness. These beliefs can influence the processing of food rewards and impact decision making beyond objective sensory properties. However, no studies, within or beyond the food domain, have assessed how written information, such as food labels, affect implicit motivation to obtain rewards, even though choices in daily life might be strongly driven by implicit motivational biases. We investigated how written information affects implicit motivation to obtain food rewards. We used food labels (high- and low-calorie), associated with an identical lemonade, to study motivation for food rewards during fMRI. In a joystick task, hungry participants (N=31) were instructed to make fast approach or avoid movements to earn the cued drinks. Behaviorally, we found a general approach bias, which was stronger for the drink that was most preferred during a subsequent choice test, i.e. the one labeled as low-calorie. This behavioral effect was accompanied by increased BOLD signal in the sensorimotor cortex during the response phase of the task for the preferred, low-calorie drink compared with the non-preferred, high-calorie drink. During the anticipation phase, the non-preferred, high-calorie drink label elicited stronger fMRI signal in the right ventral anterior insula, a region associated with aversion and taste intensity, than the preferred, low-calorie label. Together, these data suggest that high-calorie labeling can increase avoidance of drinks and reduce neural activity in brain regions associated with motor control. In conclusion, we show effects of food labeling on fMRI responses during anticipation and subsequent motivated action and on behavior, in the absence of objective taste differences, demonstrating the influence of written information on implicit biases. These findings contribute to our understanding of implicit biases in real-life eating behavior.
]]></description>
<dc:creator>Wegman, J.</dc:creator>
<dc:creator>van Loon, I.</dc:creator>
<dc:creator>Smeets, P.</dc:creator>
<dc:creator>Cools, R.</dc:creator>
<dc:creator>Aarts, E.</dc:creator>
<dc:date>2017-10-06</dc:date>
<dc:identifier>doi:10.1101/199265</dc:identifier>
<dc:title><![CDATA[Top-down expectation effects of food labels on motivation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-10-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/195461v1?rss=1">
<title>
<![CDATA[
Induction and Relief of Curiosity Elicit Parietal and Frontal Activity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/195461v1?rss=1"
</link>
<description><![CDATA[
Curiosity is a basic biological drive, but little is known about its behavioral and neural mechanisms. We can be curious about several types of information. On the one hand, curiosity is a function of the expected value of information, serving primarily to help us maximize reward. On the other hand, curiosity can be a function of the uncertainty of information, helping us to update what we know. In the current studies, we aimed to disentangle the contribution of information uncertainty and expected value of rewards to curiosity in humans of either sex. To this end, we designed a lottery task in which uncertainty and expected value of trial outcomes were manipulated independently, and examined how neural activity and behavioral measures of curiosity were modulated by these factors. Curiosity increased linearly with increased outcome uncertainty, both when curiosity was explicitly probed as well as when it was implicitly tested by peoples willingness to wait. Increased expected value, however, did not strongly relate to these curiosity measures. Neuroimaging results showed greater BOLD response with increasing outcome uncertainty in parietal cortex at the time of curiosity induction. Outcome updating when curiosity was relieved resulted in an increased signal in the insula, orbitofrontal cortex and parietal cortex. Furthermore, the insula showed a linear increase corresponding to the size of the information update. These results suggest that curiosity is monotonically related to the uncertainty about ones current world model, the induction and relief of which are associated with activity in parietal and insular cortices respectively.nnSignificance statementHumans are curious by nature. When you hear your phone beep, you probably feel the urge to check the message right away, even though the message itself likely doesnt give you a direct reward. In this study, we demonstrated that curiosity can be driven by outcome uncertainty, irrespective of reward. The induction of curiosity was accompanied by increased activity in the parietal cortex, whereas the information update at the time of curiosity relief was associated with activity in insular cortex. These findings advance our understanding of the behavioral and neural underpinnings of curiosity, which lies at the core of human information-seeking and serves to optimize the individuals current world-model.
]]></description>
<dc:creator>van Lieshout, L. L. F.</dc:creator>
<dc:creator>Vandenbroucke, A. R. E.</dc:creator>
<dc:creator>Müller, N. C. J.</dc:creator>
<dc:creator>Cools, R.</dc:creator>
<dc:creator>de Lange, F. P.</dc:creator>
<dc:date>2017-09-29</dc:date>
<dc:identifier>doi:10.1101/195461</dc:identifier>
<dc:title><![CDATA[Induction and Relief of Curiosity Elicit Parietal and Frontal Activity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/193342v1?rss=1">
<title>
<![CDATA[
2D:4D and spatial abilities: From rats to humans 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/193342v1?rss=1"
</link>
<description><![CDATA[
Variance in spatial abilities are thought to be determined by in utero levels of testosterone and oestrogen, measurable in adults by the length ratio of the 2nd and 4th digit (2D:4D). We confirmed the relationship between 2D:4D and spatial performance using rats in two different tasks (paired-associate task and watermaze) and replicated this in humans. We further clarified anatomical and functional brain correlates of the association between 2D:4D and spatial performance in humans.
]]></description>
<dc:creator>Muller, N.</dc:creator>
<dc:creator>Campbell, S.</dc:creator>
<dc:creator>Nonaka, M.</dc:creator>
<dc:creator>Rost, T.</dc:creator>
<dc:creator>Pipa, G.</dc:creator>
<dc:creator>Konrad, B.</dc:creator>
<dc:creator>Steiger, A.</dc:creator>
<dc:creator>Czisch, M.</dc:creator>
<dc:creator>Fernandez, G.</dc:creator>
<dc:creator>Dresler, M.</dc:creator>
<dc:creator>Genzel, L.</dc:creator>
<dc:date>2017-09-24</dc:date>
<dc:identifier>doi:10.1101/193342</dc:identifier>
<dc:title><![CDATA[2D:4D and spatial abilities: From rats to humans]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/192518v1?rss=1">
<title>
<![CDATA[
Stimulus familiarity and expectation jointly modulate neural activity in the visual ventral stream 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/192518v1?rss=1"
</link>
<description><![CDATA[
Prior knowledge about the visual world can change how a visual stimulus is processed. Two forms of prior knowledge are often distinguished: stimulus familiarity (i.e., whether a stimulus has been seen before) and stimulus expectation (i.e., whether a stimulus is expected to occur, based on the context). Neurophysiological studies in monkeys have shown suppression of spiking activity both for expected and for familiar items in object-selective inferotemporal cortex (IT). It is an open question, however, if and how these types of knowledge interact in their modulatory effects on the sensory response. In order to address this issue and to examine whether previous findings generalize to non-invasively measured neural activity in humans of both sexes, we separately manipulated stimulus familiarity and expectation, while non-invasively recording human brain activity using magnetoencephalography (MEG). We observed independent suppression of neural activity by familiarity and expectation, specifically in the lateral occipital complex (LOC), the putative human homologue of monkey IT. Familiarity also led to sharpened response dynamics, which was predominantly observed in early visual cortex. Together, these results show that distinct types of sensory knowledge jointly determine the amount of neural resources dedicated to object processing in the visual ventral stream.
]]></description>
<dc:creator>Manahova, M. E.</dc:creator>
<dc:creator>Mostert, P.</dc:creator>
<dc:creator>Kok, P.</dc:creator>
<dc:creator>Schoffelen, J.-M.</dc:creator>
<dc:creator>de Lange, F. P.</dc:creator>
<dc:date>2017-09-22</dc:date>
<dc:identifier>doi:10.1101/192518</dc:identifier>
<dc:title><![CDATA[Stimulus familiarity and expectation jointly modulate neural activity in the visual ventral stream]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/191916v1?rss=1">
<title>
<![CDATA[
Changes in alpha activity reveal that social opinion modulates attention allocation during face processing 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/191916v1?rss=1"
</link>
<description><![CDATA[
AbstractParticipants performance differs when conducting a task in the presence of a secondary individual, moreover the opinion the participant has of this individual also plays a role. Using EEG, we investigated how previous interactions with, and evaluations of, an avatar in virtual reality subsequently influenced attentional allocation to the face of that avatar. We focused on changes in the alpha activity as an index of attentional allocation. We found that the onset of an avatars face whom the participant had developed a rapport with induced greater alpha suppression. This suggests greater attentional resources allocated to the interacted-with avatars. The evaluative ratings of the avatar induced a U-shaped change in alpha suppression, such that participants paid most attention when the avatar was rated as average. These results suggest that attentional allocation is thus an important element of how behaviour is altered in the presence of a secondary individual.
]]></description>
<dc:creator>Heyselaar, E.</dc:creator>
<dc:creator>Mazaheri, A.</dc:creator>
<dc:creator>Hagoort, P.</dc:creator>
<dc:creator>Segaert, K.</dc:creator>
<dc:date>2017-09-21</dc:date>
<dc:identifier>doi:10.1101/191916</dc:identifier>
<dc:title><![CDATA[Changes in alpha activity reveal that social opinion modulates attention allocation during face processing]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/191775v1?rss=1">
<title>
<![CDATA[
Impaired hippocampal representation of place in the Fmr1-knockout mouse model of Fragile X syndrome 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/191775v1?rss=1"
</link>
<description><![CDATA[
Fragile X syndrome (FXS) is an X-chromosome linked intellectual disability and the most common genetic cause of autism spectrum disorder (ASD). Building upon demonstrated deficits in neuronal plasticity and spatial memory in FXS, we investigated how spatial information processing is affected in vivo in an FXS mouse model (Fmr1-KO). Healthy hippocampal neurons (so-called place cells) exhibit place-related activity during spatial exploration, and the stability of these spatial representations can be taken as an index of memory function. We find impaired stability and reduced specificity of Fmr1-KO spatial representations. This is a potential biomarker for the cognitive dysfunction observed in FXS, informative on the ability to integrate sensory information into an abstract representation and successfully retain this conceptual memory. Our results provide key insight into the biological mechanisms underlying cognitive disabilities in FXS and ASD, paving the way for a targeted approach to remedy these.
]]></description>
<dc:creator>Arbab, T.</dc:creator>
<dc:creator>Pennartz, C. M.</dc:creator>
<dc:creator>Battaglia, F. P.</dc:creator>
<dc:date>2017-09-20</dc:date>
<dc:identifier>doi:10.1101/191775</dc:identifier>
<dc:title><![CDATA[Impaired hippocampal representation of place in the Fmr1-knockout mouse model of Fragile X syndrome]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/191015v1?rss=1">
<title>
<![CDATA[
Catecholaminergic modulation of the avoidance of cognitive control 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/191015v1?rss=1"
</link>
<description><![CDATA[
The catecholamines have long been associated with cognitive control and value-based decision-making. More recently, we proposed that the catecholamines might modulate value-based decision-making about whether or not to engage in cognitive control. We test this hypothesis by assessing effects of a catecholamine challenge in a large sample of young, healthy adults (n = 100) on the avoidance of a cognitively demanding control process: task switching. Prolonging catecholamine transmission by blocking reuptake with methylphenidate altered the avoidance, but not the execution of cognitive control. Crucially, these effects could be isolated by taking into account individual differences in trait impulsivity, so that participants with higher trait impulsivity became more avoidant of cognitive control, despite faster task performance. One implication of these findings is that performance-enhancing effects of methylphenidate may be accompanied by an undermining effect on the willingness to exert cognitive control. Taken together, these findings integrate hitherto segregated literatures on catecholamines roles in value-based learning/choice and cognitive control.
]]></description>
<dc:creator>Frobose, M. I.</dc:creator>
<dc:creator>Swart, J. C.</dc:creator>
<dc:creator>Cook, J. L.</dc:creator>
<dc:creator>Geurts, D. E.</dc:creator>
<dc:creator>den Ouden, H. E.</dc:creator>
<dc:creator>Cools, R.</dc:creator>
<dc:date>2017-09-20</dc:date>
<dc:identifier>doi:10.1101/191015</dc:identifier>
<dc:title><![CDATA[Catecholaminergic modulation of the avoidance of cognitive control]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/191361v1?rss=1">
<title>
<![CDATA[
Controlling striatal function via anterior frontal cortex stimulation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/191361v1?rss=1"
</link>
<description><![CDATA[
Motivational, cognitive and action goals are processed by distinct, topographically organized, corticostriatal circuits. We aimed to test whether processing in the striatum is und er causal control by cortical regions in the human brain by investigating the effects of offline transcranial magnetic stimulation (TMS) over distinct frontal regions associated with motivational, cognitive and action goal processing. Using a three-session counterbalanced within-subject crossover design, continuous theta burst stimulation was applied over the anterior prefrontal cortex (aPFC), dorsolateral prefrontal cortex, or premotor cortex, immediately after which participants (N=27) performed a paradigm assessing reward anticipation (motivation), task (cognitive) switching, and response (action) switching. Using task-related functional magnetic resonance imaging (fMRI), we assessed the effects of stimulation on processing in distinct regions of the striatum. To account for non-specific effects, each session consisted of a baseline (no-TMS) and a stimulation (post-TMS) fMRI run. Stimulation of the aPFC tended to decrease reward-related processing in the caudate nucleus, while stimulation of the other sites was unsuccessful. A follow-up analysis revealed that aPFC stimulation also decreased processing in the putamen as a function of the interaction between all factors (reward, cognition and action), suggesting stimulation modulated the transfer of motivational information to cortico-striatal circuitry associated with action control.
]]></description>
<dc:creator>van Holstein, M</dc:creator>
<dc:creator>Froböse, M</dc:creator>
<dc:creator>O'Shea, J</dc:creator>
<dc:creator>Aarts, E</dc:creator>
<dc:creator>Cools, R</dc:creator>
<dc:date>2017-09-20</dc:date>
<dc:identifier>doi:10.1101/191361</dc:identifier>
<dc:title><![CDATA[Controlling striatal function via anterior frontal cortex stimulation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/187963v1?rss=1">
<title>
<![CDATA[
Towards a neuro-computational account of prism adaptation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/187963v1?rss=1"
</link>
<description><![CDATA[
Prism adaptation has a long history as an experimental paradigm used to investigate the functional and neural processes that underlie sensorimotor control. In the neuropsychology literature, functional explanations of prism adaptation are typically framed within a traditional cognitive psychology  box-and-arrow framework that distinguishes putative component functions thought to give rise to behaviour (i.e.  strategic control versus  spatial realignment). However, this kind of theoretical framework lacks precision and explanatory power. Here, we advocate for a computational framework that offers several advantages: 1) an algorithmic explanatory account of the computations and operations that drive behaviour; 2) expressed in quantitative mathematical terms; 3) embedded within a principled theoretical framework (Bayesian decision theory, state-space modelling); 4) that offers a means to generate and test quantitative behavioural predictions. This computational framework offers a route toward mechanistic explanations of prism adaptation behaviour. Thus it constitutes a conceptual advance compared to the traditional theoretical framework. In this paper, we illustrate how Bayesian decision theory and state-space models offer principled explanations for a range of behavioural phenomena in the field of prism adaptation (e.g. visual capture, magnitude of visual versus proprioceptive realignment, spontaneous recovery and dynamics of adaptation memory). We argue that this explanatory framework offers to advance understanding of the functional and neural mechanisms that implement prism adaptation behaviour, by enabling quantitative tests of hypotheses that go beyond mere descriptive mapping claims that  brain area X is (somehow) involved in psychological process Y.
]]></description>
<dc:creator>Petitet, P.</dc:creator>
<dc:creator>O'Reilly, J. X.</dc:creator>
<dc:creator>O'Shea, J.</dc:creator>
<dc:date>2017-09-12</dc:date>
<dc:identifier>doi:10.1101/187963</dc:identifier>
<dc:title><![CDATA[Towards a neuro-computational account of prism adaptation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/184192v1?rss=1">
<title>
<![CDATA[
Genetic markers of ADHD-related variations in intracranial volume 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/184192v1?rss=1"
</link>
<description><![CDATA[
Attention-Deficit/Hyperactivity Disorder (ADHD) is a common and highly heritable neurodevelopmental disorder with a complex pathophysiology, where genetic risk is hypothesized to be mediated by alterations in structure and function of diverse brain networks. We tested one aspect of this hypothesis by investigating the genetic overlap between ADHD (n=55,374) and (mainly subcortical) brain volumes (n=11,221-24,704), using the largest publicly available studies. At the level of common variant genetic architecture, we discovered a significant negative genetic correlation between ADHD and intracranial volume (ICV). Meta-analysis of individual variants found significant loci associated with both ADHD risk and ICV; additional loci were identified for ADHD and amygdala, caudate nucleus, and putamen volumes. Gene-set analysis in the ADHD-ICV meta-analytic data showed significant association with variation in neurite outgrowth-related genes. In summary, our results suggest new hypotheses about biological mechanisms involved in ADHD etiology and highlight the need to study additional brain parameters.
]]></description>
<dc:creator>Klein, M.</dc:creator>
<dc:creator>Walters, R. K.</dc:creator>
<dc:creator>Demontis, D.</dc:creator>
<dc:creator>Stein, J. L.</dc:creator>
<dc:creator>Hibar, D. P.</dc:creator>
<dc:creator>Adams, H. H.</dc:creator>
<dc:creator>Bralten, J.</dc:creator>
<dc:creator>Roth Mota, N.</dc:creator>
<dc:creator>Schachar, R.</dc:creator>
<dc:creator>Sonuga-Barke, E.</dc:creator>
<dc:creator>Mattheisen, M.</dc:creator>
<dc:creator>Neale, B. M.</dc:creator>
<dc:creator>Thompson, P. M.</dc:creator>
<dc:creator>Medland, S. E.</dc:creator>
<dc:creator>Borglum, A. D.</dc:creator>
<dc:creator>Faraone, S. V.</dc:creator>
<dc:creator>Arias-Vasquez, A.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:date>2017-09-12</dc:date>
<dc:identifier>doi:10.1101/184192</dc:identifier>
<dc:title><![CDATA[Genetic markers of ADHD-related variations in intracranial volume]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/185611v1?rss=1">
<title>
<![CDATA[
Cued reactivation during slow-wave sleep induces connectivity changes related to memory stabilization. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/185611v1?rss=1"
</link>
<description><![CDATA[
Memory reprocessing following acquisition enhances memory consolidation. Specifically, neural activity during encoding is thought to be  replayed during subsequent slow-wave sleep (SWS). This natural tendency of memory replay can be induced by external cueing, known as "targeted memory reactivation". Here, we analyzed data from a published study (van Dongen, Takashima, et al. 2012), where auditory cues reactivated learned visual object-location memories during SWS. Memory replay during sleep presumably involves a shift in connectivity across the brain. Therefore, we characterized the effects of memory reactivation on brain network connectivity using graph-theory. We found that cue presentation during SWS introduced increased network integration of the occipital cortex, a visual region that was also active during the object retrieval task. Importantly, enhanced network integration of the occipital cortex showed a behavioural benefit and predicted overnight memory stabilization. Furthermore, occipital cortex displayed enhanced connectivity with mnemonic regions, namely the hippocampus, parahippocampal gyrus, thalamus and medial prefrontal cortex during cue versus control sound presentation. Finally, network integration of early occipital cortex during cueing in SWS was related to increased activation of the bilateral parahippocampal gyrus, a region involved in coding for spatial associative information, at the post-sleep test. Together, these results support a neural mechanism where cue-induced replay during sleep promotes memory consolidation by increased integration of task-relevant perceptual regions with mnemonic regions.
]]></description>
<dc:creator>Berkers, R. M. W. J.</dc:creator>
<dc:creator>Ekman, M.</dc:creator>
<dc:creator>van Dongen, E. V.</dc:creator>
<dc:creator>Takashima, A.</dc:creator>
<dc:creator>Barth, M.</dc:creator>
<dc:creator>Paller, K.</dc:creator>
<dc:creator>Fernandez, G.</dc:creator>
<dc:date>2017-09-07</dc:date>
<dc:identifier>doi:10.1101/185611</dc:identifier>
<dc:title><![CDATA[Cued reactivation during slow-wave sleep induces connectivity changes related to memory stabilization.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/164707v1?rss=1">
<title>
<![CDATA[
Polygenic selection underlies evolution of human brain structure and behavioral traits 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/164707v1?rss=1"
</link>
<description><![CDATA[
Seemingly paradoxical characteristics of psychiatric disorders, including moderate to high prevalence, reduced fecundity, and high heritability have motivated explanations for the persistence of common risk alleles for severe psychiatric phenotypes throughout human evolution. Proposed mechanisms include balancing selection, drift, and weak polygenic adaptation acting either directly, or indirectly through selection on correlated traits. While many mechanisms have been proposed, few have been empirically tested. Leveraging publicly available data of unprecedented sample size, we studied twenty-five traits (i.e., ten neuropsychiatric disorders, three personality traits, total intracranial volume, seven subcortical brain structure volume traits, and four complex traits without neuropsychiatric associations) for evidence of several different signatures of selection over a range of evolutionary time scales. Consistent with the largely polygenic architecture of neuropsychiatric traits, we found no enrichment of trait-associated single-nucleotide polymorphisms (SNPs) in regions of the genome that underwent classical selective sweeps (i.e., events which would have driven selected alleles to near fixation). However, we discovered that SNPs associated with some, but not all, behaviors and brain structure volumes are enriched in genomic regions under selection since divergence from Neanderthals ~600,000 years ago, and show further evidence for signatures of ancient and recent polygenic adaptation. Individual subcortical brain structure volumes demonstrate genome-wide evidence in support of a mosaic theory of brain evolution while total intracranial volume and height appear to share evolutionary constraints consistent with concerted evolution. We further characterized the biological processes potentially targeted by selection, through expression Quantitative Trait Locus (eQTL) and Gene Ontology (GO) enrichment analyses and found evidence for the role of regulatory functions among selected SNPs in immune and brain tissues. Taken together, our results suggest that alleles associated with neuropsychiatric, behavioral, and brain volume phenotypes have experienced both ancient and recent polygenic adaptation in human evolution, acting through neurodevelopmental and immune-mediated pathways.
]]></description>
<dc:creator>Beiter, E. R.</dc:creator>
<dc:creator>Khramtsova, E. A.</dc:creator>
<dc:creator>van der Merwe, C.</dc:creator>
<dc:creator>Chimusa, E. R.</dc:creator>
<dc:creator>Simonti, C.</dc:creator>
<dc:creator>Stein, J.</dc:creator>
<dc:creator>Thompson, P.</dc:creator>
<dc:creator>Fisher, S.</dc:creator>
<dc:creator>Stein, D. J.</dc:creator>
<dc:creator>Capra, J. A.</dc:creator>
<dc:creator>Knowles, J. A.</dc:creator>
<dc:creator>Stranger, B. E.</dc:creator>
<dc:creator>Davis, L. K.</dc:creator>
<dc:date>2017-09-09</dc:date>
<dc:identifier>doi:10.1101/164707</dc:identifier>
<dc:title><![CDATA[Polygenic selection underlies evolution of human brain structure and behavioral traits]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/185264v1?rss=1">
<title>
<![CDATA[
Cueing memory during sleep is optimal during slow-oscillatory up-states 
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</title>
<link>
https://biorxiv.org/cgi/content/short/185264v1?rss=1"
</link>
<description><![CDATA[
Slow oscillations play a major role in neural plasticity. It is assumed that slow oscillatory up-states represent crucial time windows for memory reactivation and consolidation during sleep. Here we experimentally tested this assumption by utilizing closed-loop targeted memory reactivation (closed-loop TMR): Healthy participants were re-exposed to prior learned foreign vocabulary during up- and down-states of slow oscillations, respectively, in a within-subject design. We show that presenting memory cues during slow oscillatory up-states robustly improves recall performance, whereas memory cueing during down-states did not result in a clear behavioral benefit. On a neural basis successful memory reactivation during up-states was associated with a characteristic power increase in the theta and sleep spindle band. Such increases were completely absent for down-state memory cues. Our findings provide experimental support for the assumption that slow oscillatory up-states represent privileged time windows for memory reactivation, while the interplay of slow oscillations, theta and sleep spindle activity promote successful memory consolidation during sleep.
]]></description>
<dc:creator>Göldi, M.</dc:creator>
<dc:creator>van Poppel, E.</dc:creator>
<dc:creator>Rasch, B.</dc:creator>
<dc:creator>Schreiner, T.</dc:creator>
<dc:date>2017-09-07</dc:date>
<dc:identifier>doi:10.1101/185264</dc:identifier>
<dc:title><![CDATA[Cueing memory during sleep is optimal during slow-oscillatory up-states]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/185132v1?rss=1">
<title>
<![CDATA[
Individual alpha peak frequency predicts 10 Hz flicker effects on selective attention 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/185132v1?rss=1"
</link>
<description><![CDATA[
Rhythmic visual stimulation ("flicker") is primarily used to "tag" processing of low-level visual and high-level cognitive phenomena. However, preliminary evidence suggests that flicker may also entrain endogenous brain oscillations, thereby modulating cognitive processes supported by those brain rhythms. Here we tested the interaction between 10 Hz flicker and endogenous alpha-band (~10 Hz) oscillations during a selective visuospatial attention task. We recorded EEG from human participants (both genders) while they performed a modified Eriksen flanker task in which distractors and targets flickered within (10 Hz) or outside (7.5 or 15 Hz) the alpha band. By using a combination of EEG source separation, time-frequency, and single-trial linear mixed effects modeling, we demonstrate that 10 Hz flicker interfered with stimulus processing more on incongruent than congruent trials (high vs. low selective attention demands). Crucially, the effect of 10 Hz flicker on task performance was predicted by the distance between 10 Hz and individual alpha peak frequency (estimated during the task). Finally, the flicker effect on task performance was more strongly predicted by EEG flicker responses during stimulus processing than during preparation for the upcoming stimulus, suggesting that 10 Hz flicker interfered more with reactive than proactive selective attention. These findings are consistent with our hypothesis that visual flicker entrained endogenous alpha-band networks, which in turn impaired task performance. Our findings also provide novel evidence for frequency-dependent exogenous modulation of cognition that is determined by the correspondence between the exogenous flicker frequency and the endogenous brain rhythms.nnSignificanceHere we provide novel evidence that the interaction between exogenous rhythmic visual stimulation and endogenous brain rhythms can have frequency-specific behavioral effects. We show that alpha-band (10 Hz) flicker impairs stimulus processing in a selective attention task when the stimulus flicker rate matches individual alpha peak frequency. The effect of sensory flicker on task performance was stronger when selective attention demands were high, and was stronger during stimulus processing and response selection compared to the pre-stimulus anticipatory period. These findings provide novel evidence that frequency-specific sensory flicker affects online attentional processing, and also demonstrate that the correspondence between exogenous and endogenous rhythms is an overlooked prerequisite when testing for frequency-specific cognitive effects of flicker.
]]></description>
<dc:creator>Gulbinaite, R.</dc:creator>
<dc:creator>van Viegen, T.</dc:creator>
<dc:creator>Wieling, M.</dc:creator>
<dc:creator>Cohen, M. X.</dc:creator>
<dc:creator>VanRullen, R.</dc:creator>
<dc:date>2017-09-06</dc:date>
<dc:identifier>doi:10.1101/185132</dc:identifier>
<dc:title><![CDATA[Individual alpha peak frequency predicts 10 Hz flicker effects on selective attention]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-09-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/173831v1?rss=1">
<title>
<![CDATA[
Genetic Architecture of Subcortical Brain Structures in Over 40,000 Individuals Worldwide 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/173831v1?rss=1"
</link>
<description><![CDATA[
Subcortical brain structures are integral to motion, consciousness, emotions, and learning. We identified common genetic variation related to the volumes of nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen, and thalamus, using genome-wide association analyses in over 40,000 individuals from CHARGE, ENIGMA and the UK-Biobank. We show that variability in subcortical volumes is heritable, and identify 25 significantly associated loci (20 novel). Annotation of these loci utilizing gene expression, methylation, and neuropathological data identified 62 candidate genes implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.
]]></description>
<dc:creator>Satizabal, C. L.</dc:creator>
<dc:creator>Adams, H. H. H.</dc:creator>
<dc:creator>Hibar, D. P.</dc:creator>
<dc:creator>White, C. C.</dc:creator>
<dc:creator>Stein, J. L.</dc:creator>
<dc:creator>Scholz, M.</dc:creator>
<dc:creator>Sargurupremraj, M.</dc:creator>
<dc:creator>Jahanshad, N.</dc:creator>
<dc:creator>Smith, A. V.</dc:creator>
<dc:creator>Bis, J. C.</dc:creator>
<dc:creator>Jian, X.</dc:creator>
<dc:creator>Luciano, M.</dc:creator>
<dc:creator>Hofer, E.</dc:creator>
<dc:creator>Teumer, A.</dc:creator>
<dc:creator>van der Lee, S. J.</dc:creator>
<dc:creator>Yang, J.</dc:creator>
<dc:creator>Yanek, L. R.</dc:creator>
<dc:creator>Lee, T. V.</dc:creator>
<dc:creator>Li, S.</dc:creator>
<dc:creator>Hu, Y.</dc:creator>
<dc:creator>Koh, J. Y.</dc:creator>
<dc:creator>Eicher, J. D.</dc:creator>
<dc:creator>Desrivieres, S.</dc:creator>
<dc:creator>Arias-Vasquez, A.</dc:creator>
<dc:creator>Chauhan, G.</dc:creator>
<dc:creator>Athanasiu, L.</dc:creator>
<dc:creator>Renteria, M. E.</dc:creator>
<dc:creator>Kim, S.</dc:creator>
<dc:creator>Hohn, D.</dc:creator>
<dc:creator>Armstrong, N. J.</dc:creator>
<dc:creator>Chen, Q.</dc:creator>
<dc:creator>Holmes, A. J.</dc:creator>
<dc:creator>den Braber, A.</dc:creator>
<dc:creator>Kloszewska, I.</dc:creator>
<dc:creator>Andersson, M.</dc:creator>
<dc:creator>Espeseth, T.</dc:creator>
<dc:creator>Grimm, O.</dc:creator>
<dc:creator>Abramovic, L.</dc:creator>
<dc:creator>Alhusaini, S.</dc:creator>
<dc:creator>Milaneschi, Y.</dc:creator>
<dc:creator>Papmeyer, M.</dc:creator>
<dc:creator>Axelsson, T.</dc:creator>
<dc:creator>Ehrlich, S.</dc:creator>
<dc:creator>Roi</dc:creator>
<dc:date>2017-08-28</dc:date>
<dc:identifier>doi:10.1101/173831</dc:identifier>
<dc:title><![CDATA[Genetic Architecture of Subcortical Brain Structures in Over 40,000 Individuals Worldwide]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-08-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/179978v1?rss=1">
<title>
<![CDATA[
Developmental changes within the genetic architecture of social communication behaviour: A multivariate study of genetic variance in unrelated individuals 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/179978v1?rss=1"
</link>
<description><![CDATA[
BackgroundRecent analyses of trait-disorder overlap suggest that psychiatric dimensions may relate to distinct sets of genes that exert their maximum influence during different periods of development. This includes analyses of social-communciation difficulties that share, depending on their developmental stage, stronger genetic links with either Autism Spectrum Disorder or schizophrenia. Here we developed a multivariate analysis framework in unrelated individuals to model directly the developmental profile of genetic influences contributing to complex traits, such as social-communication difficulties, during a [~]10-year period spanning childhood and adolescence.nnMethodsLongitudinally assessed quantitative social-communication problems (N[&le;] 5,551) were studied in participants from a UK birth cohort (ALSPAC, 8 to 17 years). Using standardised measures, genetic architectures were investigated with novel multivariate genetic-relationship-matrix structural equation models (GSEM) incorporating whole-genome genotyping information. Analogous to twin research, GSEM included Cholesky decomposition, common pathway and independent pathway models.nnResultsA 2-factor Cholesky decomposition model described the data best. One genetic factor was common to SCDC measures across development, the other accounted for independent variation at 11 years and later, consistent with distinct developmental profiles in trait-disorder overlap. Importantly, genetic factors operating at 8 years explained only [~]50% of the genetic variation at 17 years.nnConclusionUsing latent factor models, we identified developmental changes in the genetic architecture of social-communication difficulties that enhance the understanding of ASD and schizophrenia-related dimensions. More generally, GSEM present a framework for modelling shared genetic aetiologies between phenotypes and can provide prior information with respect to patterns and continuity of trait-disorder overlap.
]]></description>
<dc:creator>St. Pourcain, B.</dc:creator>
<dc:creator>Eaves, L. J.</dc:creator>
<dc:creator>Ring, S. M.</dc:creator>
<dc:creator>Fisher, S. E.</dc:creator>
<dc:creator>Medland, S.</dc:creator>
<dc:creator>Evans, D. M.</dc:creator>
<dc:creator>Davey Smith, G.</dc:creator>
<dc:date>2017-08-23</dc:date>
<dc:identifier>doi:10.1101/179978</dc:identifier>
<dc:title><![CDATA[Developmental changes within the genetic architecture of social communication behaviour: A multivariate study of genetic variance in unrelated individuals]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-08-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/171660v1?rss=1">
<title>
<![CDATA[
Serial representation of items during working memory maintenance at letter-selective cortical sites 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/171660v1?rss=1"
</link>
<description><![CDATA[
We used intracranial recordings to study brain oscillations during a working memory task. To analyze sites involved in working memory, we focused on sites at which the elevation of the broadband gamma signal depended on which letter was presented. We tested a previously proposed model according to which different items are active at different phases of the theta cycle (in different gamma cycles within the theta cycle). Consistent with this model, the theta phase of letter-induced gamma elevation during maintenance reflected the order of letter presentation. These results suggest that working memory is organized by a theta-gamma code and provide strong support for the serial representation of items held in working memory.
]]></description>
<dc:creator>Bahramisharif, A.</dc:creator>
<dc:creator>Jensen, O.</dc:creator>
<dc:creator>Jacobs, J.</dc:creator>
<dc:creator>Lisman, J.</dc:creator>
<dc:date>2017-08-02</dc:date>
<dc:identifier>doi:10.1101/171660</dc:identifier>
<dc:title><![CDATA[Serial representation of items during working memory maintenance at letter-selective cortical sites]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-08-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/150748v1?rss=1">
<title>
<![CDATA[
Evidence for a causal link between left posterior alpha-beta power decreases and context-driven word production. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/150748v1?rss=1"
</link>
<description><![CDATA[
Different frequency bands in the electroencephalogram are postulated to support distinct language functions. Studies have suggested that alpha-beta power decreases may index word-retrieval processes. In context-driven word retrieval, participants hear lead-in sentences that either constrain the final word ("He locked the door with the") or not ("She walked in here with the"). The last word is shown as a picture to be named. Previous studies have consistently found alpha-beta power decreases prior to picture onset for constrained relative to unconstrained sentences, localised to the left lateral-temporal and lateral-frontal lobes. However, the relative contribution of temporal versus frontal areas to alpha-beta power decreases is unknown. We recorded the electroencephalogram from patients with stroke lesions encompassing the left-lateral temporal and inferior parietal regions or left-lateral frontal lobe and from matched controls. Individual-participant analyses revealed a behavioural sentence context facilitation effect in all participants, except for in the two patients with extensive lesions to temporal and inferior-parietal lobes. We replicated the alpha-beta power decreases prior to picture onset in all participants, except for in the two same patients with extensive posterior lesions. Thus, whereas posterior lesions eliminated the behavioural and oscillatory context effect, frontal lesions did not. Hierarchical clustering analyses of the patients lesion profiles, and behavioural and electrophysiological effects identified P7 and P9 as having a unique combination of lesion distribution and context effects. These results indicate a critical role for the left lateral-temporal and inferior parietal lobes, but not frontal cortex, in generating the alpha-beta power decreases underlying context-driven word production.
]]></description>
<dc:creator>Piai, V.</dc:creator>
<dc:creator>Rommers, J.</dc:creator>
<dc:creator>Knight, R. T.</dc:creator>
<dc:date>2017-06-15</dc:date>
<dc:identifier>doi:10.1101/150748</dc:identifier>
<dc:title><![CDATA[Evidence for a causal link between left posterior alpha-beta power decreases and context-driven word production.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-06-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/130195v1?rss=1">
<title>
<![CDATA[
Dorsal Anterior Cingulate-Midbrain Ensemble As A Reinforcement Meta-Learner 
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</title>
<link>
https://biorxiv.org/cgi/content/short/130195v1?rss=1"
</link>
<description><![CDATA[
The dorsal anterior cingulate cortex (dACC) is central in higher-order cognition and behavioural flexibility. The computational nature of this region, however, has remained elusive. Here we propose a new model - the Reinforcement Meta Learner (RML) - based on the bidirectional anatomical connections of the ACC with midbrain catecholamine nuclei (VTA and LC). In this circuit, dACC learns which actions are valuable and acts accordingly. Crucially, this mechanism is optimized by recurrent connectivity with the midbrain: Midbrain catecholamines provide modulatory signals to dACC, controlling its internal parameters (e.g. learning rate), while these parameter modulations are in turn optimized by dACC afferents to the midbrain. This closed-loop system generates emergent (i.e., homunculus-free) control and supports learning to solve hierarchical decision problems without having an intrinsic hierarchical structure itself. Further, it can be combined with other cortical modules to optimize the processing of these modules. We outline how the RML solves the current theoretical stalemate on dACC by assimilating various previous proposals on ACC functioning, and how it captures critical empirical findings from an unprecedented range of domains (stability/plasticity balance, effort processing, working memory, and higher-order classical and instrumental conditioning).
]]></description>
<dc:creator>Silvetti, M.</dc:creator>
<dc:creator>Vassena, E.</dc:creator>
<dc:creator>Verguts, T.</dc:creator>
<dc:date>2017-04-24</dc:date>
<dc:identifier>doi:10.1101/130195</dc:identifier>
<dc:title><![CDATA[Dorsal Anterior Cingulate-Midbrain Ensemble As A Reinforcement Meta-Learner]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-04-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/140954v1?rss=1">
<title>
<![CDATA[
An Amino Acid Motif In HLA-DRB1 Distinguishes Patients With Uveitis In Juvenile Idiopathic Arthritis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/140954v1?rss=1"
</link>
<description><![CDATA[
ObjectivesUveitis is a visually-debilitating disorder that affects up to 30% of children with the most common forms of juvenile idiopathic arthritis (JIA). The disease mechanisms predisposing only a subgroup of children to uveitis are unknown. To identify genetic susceptibility loci for uveitis in JIA, we conducted a genome-wide association study totalling 522 JIA cases.nnMethodsTwo cohorts of JIA patients with ophthalmological follow-up were separately genotyped and then imputed using a genome-wide imputation reference panel, and an HLA-specific reference panel used for imputing amino acids and HLA types in the major histocompatibility complex (MHC). After imputation, we performed genome-wide and MHC-specific analyses. We used a reverse immunology approach to model antigen presentation at 13 common HLA-DRB1 allotypes.nnResultsWe identified the amino acid serine at position 11 (serine-11) in HLA-DRB1 as associated to increased risk of uveitis (OR = 2.60, p = 5.43 x 10-10). We found the serine-11 signal to be specific to females (pfemales = 7.61 x 10-10, pmales = 0.18). Serine-11 resides in the YST-motif in the peptide binding groove of the HLA-DRB1 protein; all three amino acids are in perfect linkage disequilibrium and show identical association to disease. Quantitative prediction of binding affinity revealed that discernable peptide-binding preferences distinguish HLA-DRB1 allotypes with the YST-motif.nnConclusionOur findings highlight a genetically distinct, sexually-dimorphic feature of JIA-uveitis compared to JIA without uveitis in HLA-DRB1. The association indicates the potential involvement for antigen presentation by HLA-DRB1 in the development of uveitis in JIA.
]]></description>
<dc:creator>Haasnoot, A. J. W.</dc:creator>
<dc:creator>Schilham, M. W.</dc:creator>
<dc:creator>Kamphuis, S. S. M.</dc:creator>
<dc:creator>Hissink Muller, P. C. E.</dc:creator>
<dc:creator>Heiligenhaus, A.</dc:creator>
<dc:creator>Foll, D.</dc:creator>
<dc:creator>Ophoff, R. A.</dc:creator>
<dc:creator>Minden, K.</dc:creator>
<dc:creator>Radstake, T. R. D. J.</dc:creator>
<dc:creator>Den Hollander, A. I.</dc:creator>
<dc:creator>Reinards, T. H. C. M.</dc:creator>
<dc:creator>Hiddingh, S.</dc:creator>
<dc:creator>Schalij-Delfos, N.</dc:creator>
<dc:creator>Hoppenreijs, E. P. A. H.</dc:creator>
<dc:creator>van Rossum, M. A. J.</dc:creator>
<dc:creator>Wouters, C.</dc:creator>
<dc:creator>Saurenmann, R. K.</dc:creator>
<dc:creator>Wulffraat, N.</dc:creator>
<dc:creator>ICON-JIA Study Group,</dc:creator>
<dc:creator>ten Cate, R.</dc:creator>
<dc:creator>de Boer, J. H.</dc:creator>
<dc:creator>Pulit, S. L.</dc:creator>
<dc:creator>Kuiper, J. J. W.</dc:creator>
<dc:date>2017-05-22</dc:date>
<dc:identifier>doi:10.1101/140954</dc:identifier>
<dc:title><![CDATA[An Amino Acid Motif In HLA-DRB1 Distinguishes Patients With Uveitis In Juvenile Idiopathic Arthritis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-05-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/172684v1?rss=1">
<title>
<![CDATA[
MEG-BIDS: an extension to the Brain Imaging Data Structure for magnetoencephalography 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/172684v1?rss=1"
</link>
<description><![CDATA[
We present a significant extension of the Brain Imaging Data Structure (BIDS) to support the specific aspects of magnetoencephalography (MEG) data. MEG provides direct measurement of brain activity with millisecond temporal resolution and unique source imaging capabilities. So far, BIDS has provided a solution to structure the organization of magnetic resonance imaging (MRI) data, which nature and acquisition parameters are different. Despite the lack of standard data format for MEG, MEG-BIDS is a principled solution to store, organize and share the typically-large data volumes produced. It builds on BIDS for MRI, and therefore readily yields a multimodal data organization by construction. This is particularly valuable for the anatomical and functional registration of MEG source imaging with MRI. With MEG-BIDS and a growing range of software adopting the standard, the MEG community has a solution to minimize curation overheads, reduce data handling errors and optimize usage of computational resources for analytics. The standard also includes well-defined metadata, to facilitate future data harmonization and sharing efforts.
]]></description>
<dc:creator>Niso Galan, J. G.</dc:creator>
<dc:creator>Gorgolewski, K. J.</dc:creator>
<dc:creator>Bock, E.</dc:creator>
<dc:creator>Brooks, T. L.</dc:creator>
<dc:creator>Flandin, G.</dc:creator>
<dc:creator>Gramfort, A.</dc:creator>
<dc:creator>Henson, R. N.</dc:creator>
<dc:creator>Jas, M.</dc:creator>
<dc:creator>Litvak, V.</dc:creator>
<dc:creator>Moreau, J.</dc:creator>
<dc:creator>Oostenveld, R.</dc:creator>
<dc:creator>Schoffelen, J.-M.</dc:creator>
<dc:creator>Tadel, F.</dc:creator>
<dc:creator>Wexler, J.</dc:creator>
<dc:creator>Baillet, S.</dc:creator>
<dc:date>2017-08-08</dc:date>
<dc:identifier>doi:10.1101/172684</dc:identifier>
<dc:title><![CDATA[MEG-BIDS: an extension to the Brain Imaging Data Structure for magnetoencephalography]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-08-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/171637v1?rss=1">
<title>
<![CDATA[
Predicting motivation: computational models of PFC can explain neural coding of motivation and effort-based decision-making in health and disease 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/171637v1?rss=1"
</link>
<description><![CDATA[
Human behavior is strongly driven by the pursuit of rewards. In daily life, however, benefits mostly come at a cost, often requiring that effort be exerted in order to obtain potential benefits. Medial prefrontal cortex (MPFC) and dorsolateral prefrontal cortex (DLPFC) are frequently implicated in the expectation of effortful control, showing increased activity as a function of predicted task difficulty. Such activity partially overlaps with expectation of reward, and has been observed both during decision-making and during task preparation. Recently, novel computational frameworks have been developed to explain activity in these regions during cognitive control, based on the principle of prediction and prediction error (PRO model, Alexander and Brown, 2011, HER Model, Alexander and Brown, 2015). Despite the broad explanatory power of these models, it is not clear whether they can also accommodate effects related to the expectation of effort observed in MPFC and DLPFC. Here, we propose a translation of these computational frameworks to the domain of effort-based behavior. First, we discuss how the PRO model, based on prediction error, can explain effort-related activity in MPFC, by reframing effort-based behavior in a predictive context. We propose that MPFC activity reflects monitoring of motivationally relevant variables (such as effort and reward), by coding expectations, and discrepancies from such expectations. Moreover, we derive behavioral and neural model-based predictions for healthy controls and clinical populations with impairments of motivation. Second, we illustrate the possible translation to effort-based behavior of the HER model, an extended version of PRO model based on hierarchical error prediction, developed to explain MPFC-DLPFC interactions. We derive behavioral predictions which describe how effort and reward information is coded in PFC, and how changing the configuration of such environmental information might affect decision-making and task-performance involving motivation.
]]></description>
<dc:creator>Vassena, E.</dc:creator>
<dc:creator>Deraeve, J.</dc:creator>
<dc:creator>Alexander, W.</dc:creator>
<dc:date>2017-08-02</dc:date>
<dc:identifier>doi:10.1101/171637</dc:identifier>
<dc:title><![CDATA[Predicting motivation: computational models of PFC can explain neural coding of motivation and effort-based decision-making in health and disease]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-08-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/169151v1?rss=1">
<title>
<![CDATA[
Functional corticostriatal connection topographies predict goal directed behaviour in humans 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/169151v1?rss=1"
</link>
<description><![CDATA[
Anatomical tracing studies in non-human primates have suggested that corticostriatal connectivity is topographically organized: nearby locations in striatum are connected with nearby locations in cortex. The topographic organization of corticostriatal connectivity is thought to underpin many goal-directed behaviours, but these topographies have not been completely characterised in humans and their relationship to uniquely human behaviours remains to be fully determined. Instead, the dominant approach employs parcellations that cannot model the continuous nature of the topography, nor accommodate overlapping cortical projections in the striatum. Here, we employ a different approach to studying human corticostriatal circuitry: we estimate smoothly-varying and spatially overlapping  connection topographies from resting state fMRI. These correspond exceptionally well with and extend the topographies predicted from primate tracing studies. We show that striatal topography is preserved in regions not previously known to have topographic connections with the striatum and that many goal-directed behaviours can be mapped precisely onto individual variations in the spatial layout of striatal connectivity.
]]></description>
<dc:creator>Marquand, A. F.</dc:creator>
<dc:creator>Haak, K. V.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:date>2017-07-27</dc:date>
<dc:identifier>doi:10.1101/169151</dc:identifier>
<dc:title><![CDATA[Functional corticostriatal connection topographies predict goal directed behaviour in humans]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/168161v1?rss=1">
<title>
<![CDATA[
Probabilistic language models in cognitive neuroscience: promises and pitfalls 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/168161v1?rss=1"
</link>
<description><![CDATA[
Cognitive neuroscientists of language comprehension study how neural computations relate to cognitive computations during comprehension. On the cognitive part of the equation, it is important that the computations and processing complexity are explicitly defined. Probabilistic language models can be used to give a computationally explicit account of language complexity during comprehension. Whereas such models have so far predominantly been evaluated against behavioral data, only recently have the models been used to explain neurobiological signals. Measures obtained from these models emphasize the probabilistic, information-processing view of language understanding and provide a set of tools that can be used for testing neural hypotheses about language comprehension. Here, we provide a cursory review of the theoretical foundations and example neuroimaging studies employing probabilistic language models. We high-light the advantages and potential pitfalls of this approach and indicate avenues for future research.
]]></description>
<dc:creator>Armeni, K.</dc:creator>
<dc:creator>Willems, R. M.</dc:creator>
<dc:creator>Frank, S.</dc:creator>
<dc:date>2017-07-25</dc:date>
<dc:identifier>doi:10.1101/168161</dc:identifier>
<dc:title><![CDATA[Probabilistic language models in cognitive neuroscience: promises and pitfalls]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/166785v1?rss=1">
<title>
<![CDATA[
Computational Foundations of Natural Intelligence 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/166785v1?rss=1"
</link>
<description><![CDATA[
New developments in AI and neuroscience are revitalizing the quest to understanding natural intelligence, offering insight about how to equip machines with human-like capabilities. This paper reviews some of the computational principles relevant for understanding natural intelligence and, ultimately, achieving strong AI. After reviewing basic principles, a variety of computational modeling approaches is discussed. Subsequently, I concentrate on the use of artificial neural networks as a framework for modeling cognitive processes. This paper ends by outlining some of the challenges that remain to fulfill the promise of machines that show human-like intelligence.
]]></description>
<dc:creator>van Gerven, M.</dc:creator>
<dc:date>2017-07-21</dc:date>
<dc:identifier>doi:10.1101/166785</dc:identifier>
<dc:title><![CDATA[Computational Foundations of Natural Intelligence]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/165845v1?rss=1">
<title>
<![CDATA[
The effect of an 8-week mindful eating intervention on anticipatory reward responses in the midbrain 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/165845v1?rss=1"
</link>
<description><![CDATA[
Obesity is a highly prevalent disease, usually resulting from chronic overeating. Accumulating evidence suggests that increased neural responses during the anticipation of high-calorie food play an important role in overeating. A promising method for counteracting enhanced food anticipation in overeating might be mindfulness-based interventions (MBIs). However, the neural mechanisms by which MBIs can affect food reward anticipation are unclear. In this randomized, actively controlled study, the primary objective was to investigate the effect of an 8-week mindful eating intervention on reward anticipation. On the neural level, we hypothesized that mindful eating would decrease striatal reward anticipation responses. Additionally, responses in the midbrain - from which the reward pathways originate - were explored. Using functional magnetic resonance imaging (fMRI), we tested 58 healthy participants with a wide body mass index range (BMI: 19-35 kg/m2), motivated to change their eating behavior. During scanning they performed an incentive delay task, measuring neural reward anticipation responses to caloric and monetary cues before and after 8 weeks of mindful eating or educational cooking (active control). Compared with the educational cooking intervention, mindful eating affected neural reward anticipation responses, with relatively reduced caloric versus monetary reward responses. This effect was, however, not seen in the striatum, but only in the midbrain. The secondary objective was to assess temporary and long-lasting (one year follow-up) intervention effects on self-reported eating behavior and anthropometric measures (BMI, waist circumference, waist-to-hip-ratio (WHR)). We did not observe effects of the mindful eating intervention on eating behavior. Instead, the control intervention showed temporary beneficial effects on BMI, waist circumference, and diet quality, but not on WHR or self-reported eating behavior, as well as long-lasting increases in knowledge about healthy eating. These results suggest that an 8-week mindful eating intervention may have decreased the relative salience of food cues by affecting midbrain but not striatal reward responses. However, these exploratory results should be verified in confirmatory research.

The primary and secondary objectives of the study were registered in the Dutch Trial Register (NTR): NL4923 (NTR5025).
]]></description>
<dc:creator>Janssen, L. K.</dc:creator>
<dc:creator>Duif, I.</dc:creator>
<dc:creator>Speckens, A. E.</dc:creator>
<dc:creator>van Loon, I.</dc:creator>
<dc:creator>de Vries, J. H.</dc:creator>
<dc:creator>Cools, R.</dc:creator>
<dc:creator>Aarts, E.</dc:creator>
<dc:date>2017-07-21</dc:date>
<dc:identifier>doi:10.1101/165845</dc:identifier>
<dc:title><![CDATA[The effect of an 8-week mindful eating intervention on anticipatory reward responses in the midbrain]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/158758v1?rss=1">
<title>
<![CDATA[
Saccades phase-locked to alpha oscillations in the occipital and medial temporal lobe enhance memory encoding 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/158758v1?rss=1"
</link>
<description><![CDATA[
Efficient sampling of visual information requires a coordination of eye movements and ongoing brain oscillations. Using intracranial and MEG recordings, we show that saccades are locked to the phase of visual alpha oscillations, and that this coordination supports mnemonic encoding of visual scenes. Furthermore, parahippocampal and retrosplenial cortex involvement in this coordination reflects effective vision-to-memory mapping, highlighting the importance of neural oscillations for the interaction between visual and memory domains.
]]></description>
<dc:creator>Staudigl, T.</dc:creator>
<dc:creator>Hartl, E.</dc:creator>
<dc:creator>Noachtar, S.</dc:creator>
<dc:creator>Doeller, C. F.</dc:creator>
<dc:creator>Jensen, O.</dc:creator>
<dc:date>2017-07-03</dc:date>
<dc:identifier>doi:10.1101/158758</dc:identifier>
<dc:title><![CDATA[Saccades phase-locked to alpha oscillations in the occipital and medial temporal lobe enhance memory encoding]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-07-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/092569v1?rss=1">
<title>
<![CDATA[
In vivo magnetic recording of neuronal activity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/092569v1?rss=1"
</link>
<description><![CDATA[
Neuronal activity generates ionic flows and thereby both magnetic fields and electric potential differences, i.e. voltages. Voltage measurements are widely used, but suffer from isolating and smearing properties of tissue between source and sensor, are blind to ionic flow direction, and reflect the difference between two electrodes, complicating interpretation. Magnetic field measurements could overcome these limitations, but have been essentially limited to magnetoencephalography (MEG), using centimeter-sized, helium-cooled extracranial sensors. Here, we report on in vivo magnetic recordings of neuronal activity from visual cortex of cats with magnetrodes, specially developed needle-shaped probes carrying micron-sized, non-cooled magnetic sensors based on spin electronics. Event-related magnetic fields inside the neuropil were on the order of several nanoteslas, informing MEG source models and efforts for magnetic field measurements through MRI. Though the signal-to-noise ratio is still inferior to electrophysiology, this proof of concept demonstrates the potential to exploit the fundamental advantages of magnetophysiology.nnHIGHLIGHTSO_LISpin-electronics based probes achieve local magnetic recordings inside the neuropilnC_LIO_LIMagnetic field recordings were performed in vivo, in anesthetized cat visual cortexnC_LIO_LIEvent-related fields (ERFs) to visual stimuli were up to several nanoteslas in sizenC_LIO_LIERFs could be detected after averaging less than 20 trialsnC_LInnIN BRIEFCaruso et al. report in vivo, intra-cortical recordings of magnetic fields that reflect neuronal activity, using magnetrodes, i.e. micron size magnetic sensors based on spin electronics.
]]></description>
<dc:creator>Caruso, L.</dc:creator>
<dc:creator>Wunderle, T.</dc:creator>
<dc:creator>Lewis, C. M.</dc:creator>
<dc:creator>Valadeiro, J.</dc:creator>
<dc:creator>Trauchessec, V.</dc:creator>
<dc:creator>Trejo-Rosillo, J.</dc:creator>
<dc:creator>Amaral, J. P.</dc:creator>
<dc:creator>Ni, J.</dc:creator>
<dc:creator>Fermon, C.</dc:creator>
<dc:creator>Cardoso, S.</dc:creator>
<dc:creator>Freitas, P. P.</dc:creator>
<dc:creator>Fries, P.</dc:creator>
<dc:creator>Pannetier-Lecoeur, M.</dc:creator>
<dc:date>2016-12-09</dc:date>
<dc:identifier>doi:10.1101/092569</dc:identifier>
<dc:title><![CDATA[In vivo magnetic recording of neuronal activity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-12-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/154088v1?rss=1">
<title>
<![CDATA[
A genetic investigation of sex bias in the prevalence of attention deficit hyperactivity disorder 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/154088v1?rss=1"
</link>
<description><![CDATA[
Attention-deficit/hyperactivity disorder (ADHD) shows substantial heritability and is 2-7 times more common in males than females. We examined two putative genetic mechanisms underlying this sex bias: sex-specific heterogeneity and higher burden of risk in female cases. We analyzed genome-wide common variants from the Psychiatric Genomics Consortium and iPSYCH Project (20,183 cases, 35,191 controls) and Swedish population-registry data (N=77,905 cases, N=1,874,637 population controls). We find strong genetic correlation for ADHD across sex and no mean difference in polygenic burden across sex. In contrast, siblings of female probands are at an increased risk of ADHD, compared to siblings of male probands. The results also suggest that females with ADHD are at especially high risk of comorbid developmental conditions. Overall, this study supports a greater familial burden of risk in females with ADHD and some clinical and etiological heterogeneity. However, autosomal common variants largely do not explain the sex bias in ADHD prevalence.
]]></description>
<dc:creator>Martin, J.</dc:creator>
<dc:creator>Walters, R. K.</dc:creator>
<dc:creator>Demontis, D.</dc:creator>
<dc:creator>Mattheisen, M.</dc:creator>
<dc:creator>Lee, S. H.</dc:creator>
<dc:creator>Robinson, E.</dc:creator>
<dc:creator>Brikell, I.</dc:creator>
<dc:creator>Ghirardi, L.</dc:creator>
<dc:creator>Larsson, H.</dc:creator>
<dc:creator>Lichtenstein, P.</dc:creator>
<dc:creator>Eriksson, N.</dc:creator>
<dc:creator>- 23andMe Research Team,</dc:creator>
<dc:creator>- Psychiatric Genomics Consortium: ADHD Subgroup,</dc:creator>
<dc:creator>- iPSYCH-Broad ADHD Workgroup,</dc:creator>
<dc:creator>Werge, T.</dc:creator>
<dc:creator>Bo Mortensen, P.</dc:creator>
<dc:creator>Giortz Pedersen, M.</dc:creator>
<dc:creator>Mors, O.</dc:creator>
<dc:creator>Nordentoft, M.</dc:creator>
<dc:creator>Hougaard, D. M.</dc:creator>
<dc:creator>Bybjerg-Grauholm, J.</dc:creator>
<dc:creator>Wray, N.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Faraone, S. V.</dc:creator>
<dc:creator>O'Donovan, M. C.</dc:creator>
<dc:creator>Thapar, A.</dc:creator>
<dc:creator>Borglum, A. D.</dc:creator>
<dc:creator>Neale, B. M.</dc:creator>
<dc:date>2017-06-23</dc:date>
<dc:identifier>doi:10.1101/154088</dc:identifier>
<dc:title><![CDATA[A genetic investigation of sex bias in the prevalence of attention deficit hyperactivity disorder]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-06-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/151019v1?rss=1">
<title>
<![CDATA[
Dynamic interactions between top-down expectations and conscious awareness 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/151019v1?rss=1"
</link>
<description><![CDATA[
It is well known that top-down expectations affect perceptual processes. Yet, remarkably little is known about the relationship between expectations and conscious awareness We address three crucial questions that are outstanding: 1) How do predictions affect the likelihood of conscious stimulus perception?; 2) Does the brain register violations of predictions nonconsciously?; and 3) Do predictions need to be conscious to influence perceptual decisions? We performed three experiments in which we manipulated stimulus predictability within the attentional blink paradigm, while combining visual psychophysics with electrophysiological recordings. We found that valid stimulus expectations increase the likelihood of conscious access of stimuli. Furthermore, our findings suggest a clear dissociation in the interaction between expectations and consciousness: conscious awareness seems crucial for the implementation of top-down predictions, but not for the bottom-up generation of stimulus-evoked prediction errors. These results constrain and update influential theories about the role of consciousness in the predictive brain.
]]></description>
<dc:creator>Meijs, E.</dc:creator>
<dc:creator>Slagter, H. A.</dc:creator>
<dc:creator>de Lange, F. P.</dc:creator>
<dc:creator>van Gaal, S.</dc:creator>
<dc:date>2017-06-16</dc:date>
<dc:identifier>doi:10.1101/151019</dc:identifier>
<dc:title><![CDATA[Dynamic interactions between top-down expectations and conscious awareness]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-06-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/145581v1?rss=1">
<title>
<![CDATA[
Discovery Of The First Genome-Wide Significant Risk Loci For ADHD 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/145581v1?rss=1"
</link>
<description><![CDATA[
Attention-Deficit/Hyperactivity Disorder (ADHD) is a highly heritable childhood behavioral disorder affecting 5% of school-age children and 2.5% of adults. Common genetic variants contribute substantially to ADHD susceptibility, but no individual variants have been robustly associated with ADHD. We report a genome-wide association meta-analysis of 20,183 ADHD cases and 35,191 controls that identifies variants surpassing genome-wide significance in 12 independent loci, revealing new and important information on the underlying biology of ADHD. Associations are enriched in evolutionarily constrained genomic regions and loss-of-function intolerant genes, as well as around brain-expressed regulatory marks. These findings, based on clinical interviews and/or medical records are supported by additional analyses of a self-reported ADHD sample and a study of quantitative measures of ADHD symptoms in the population. Meta-analyzing these data with our primary scan yielded a total of 16 genome-wide significant loci. The results support the hypothesis that clinical diagnosis of ADHD is an extreme expression of one or more continuous heritable traits.
]]></description>
<dc:creator>Demontis, D.</dc:creator>
<dc:creator>Walters, R. K.</dc:creator>
<dc:creator>Martin, J.</dc:creator>
<dc:creator>Mattheisen, M.</dc:creator>
<dc:creator>Als, T. D.</dc:creator>
<dc:creator>Agerbo, E.</dc:creator>
<dc:creator>Belliveau, R.</dc:creator>
<dc:creator>Bybjerg-Grauholm, J.</dc:creator>
<dc:creator>Baekved-Hansen, M.</dc:creator>
<dc:creator>Cerrato, F.</dc:creator>
<dc:creator>Chambert, K.</dc:creator>
<dc:creator>Churchhouse, C.</dc:creator>
<dc:creator>Dumont, A.</dc:creator>
<dc:creator>Eriksson, N.</dc:creator>
<dc:creator>Gandal, M.</dc:creator>
<dc:creator>Goldstein, J.</dc:creator>
<dc:creator>Grove, J.</dc:creator>
<dc:creator>Hansen, C. S.</dc:creator>
<dc:creator>Hauberg, M.</dc:creator>
<dc:creator>Hollegaard, M.</dc:creator>
<dc:creator>Howrigan, D. P.</dc:creator>
<dc:creator>Huang, H.</dc:creator>
<dc:creator>Maller, J.</dc:creator>
<dc:creator>Martin, A. R.</dc:creator>
<dc:creator>Moran, J.</dc:creator>
<dc:creator>Pallesen, J.</dc:creator>
<dc:creator>Palmer, D. S.</dc:creator>
<dc:creator>Pedersen, C. B.</dc:creator>
<dc:creator>Pedersen, M. G.</dc:creator>
<dc:creator>Poterba, T.</dc:creator>
<dc:creator>Poulsen, J. B.</dc:creator>
<dc:creator>Ripke, S.</dc:creator>
<dc:creator>Robinson, E. B.</dc:creator>
<dc:creator>Satterstrom, F. K.</dc:creator>
<dc:creator>Stevens, C.</dc:creator>
<dc:creator>Turley, P.</dc:creator>
<dc:creator>Won, H.</dc:creator>
<dc:creator>- ADHD Working Group of the Psychiatric Genomics Con,</dc:creator>
<dc:creator>- Early Life</dc:creator>
<dc:date>2017-06-03</dc:date>
<dc:identifier>doi:10.1101/145581</dc:identifier>
<dc:title><![CDATA[Discovery Of The First Genome-Wide Significant Risk Loci For ADHD]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-06-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/142091v1?rss=1">
<title>
<![CDATA[
Human Resting-State Electrophysiological Networks In The Alpha Frequency Band: Evidence From Magnetoencephalographic Source Imaging 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/142091v1?rss=1"
</link>
<description><![CDATA[
In the resting-state, extended regions of the human cortex engage in electrical oscillations within the alpha-frequency band (7-14 Hz) that can be measured outside the head by magnetoencephalography (MEG). Given the accumulating evidence that alpha oscillations play a fundamental role in attentional processing and working memory, it becomes increasingly important to characterize their cortical organization. Event-related studies have demonstrated that attentional allocation can modulate alpha power selectively within the visual, auditory, and somatosensory cortices, as well as in higher-level regions. Such studies demonstrate the existence of multiple generators by exploiting experimental contrasts and trial-averaging. The identification of alpha generators from resting-state data alone has proven much harder and, consequently, relatively little is known about their organization: Apart from the classical visual, somatosensory, and auditory rhythms, it is unclear how many more generators can be observed with MEG and how they are organized into functional networks. Such knowledge, however, possibly enables to delineate separate cognitive, perceptual, and motor processes that co-occur in the resting-state and is therefore important. In this study we use the resting-state MEG data-set provided by the Human Connectome Project to identify cortical alpha generators and to characterize their organization into functional networks. The large number of subjects (N = 94), multiple scans per subject, and state-of-the-art surface-based cortical registration enable a detailed characterization of alpha in human cortex. By applying non-negative matrix factorization to source-projected power fluctuations, we identify 16 reliable cortical generators in each hemisphere. These include the classical sensory alpha rhythms as well as several additional ones in the lateral occipital and temporal lobes and in inferior parietal cortex. We show that the generators are coordinated across hemispheres and hence form resting-state networks (RSNs), two of which are the default mode network (DMN) and the ventral attention network (VAN). Our study hence provides a further subdivision of RSNs within the alpha frequency band and shows that these RSNs are supported by alpha generators. As such, it links the classical literature on human alpha with more recent research into electrophysiological RNSs.
]]></description>
<dc:creator>Hindriks, R.</dc:creator>
<dc:creator>Micheli, C.</dc:creator>
<dc:creator>Mantini, D.</dc:creator>
<dc:creator>Deco, G.</dc:creator>
<dc:date>2017-05-25</dc:date>
<dc:identifier>doi:10.1101/142091</dc:identifier>
<dc:title><![CDATA[Human Resting-State Electrophysiological Networks In The Alpha Frequency Band: Evidence From Magnetoencephalographic Source Imaging]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-05-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/054288v1?rss=1">
<title>
<![CDATA[
Top-down modulation of stimulus drive via beta-gamma cross-frequency interaction. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/054288v1?rss=1"
</link>
<description><![CDATA[
AbstractSeveral recent studies have demonstrated that the bottom-up signaling of a visual stimulus is subserved by interareal gamma-band synchronization, whereas top-down influences are mediated by alpha-beta band synchronization. These processes may implement top-down control of stimulus processing if top-down and bottom-up mediating rhythms are coupled via cross-frequency interaction. To test this possibility, we investigated Granger-causal influences among awake male macaque primary visual area V1, higher visual area V4 and parietal control area 7a during attentional task performance. Top-down 7a-to-V1 beta-band influences enhanced visually driven V1-to-V4 gamma-band influences. This enhancement was spatially specific and largest when beta-band activity preceded gamma-band activity by [~]0.1 s, suggesting a causal effect of top-down processes on bottom-up processes. We propose that this cross-frequency interaction mechanistically subserves the attentional control of stimulus selection.nnSignificance StatementContemporary research indicates that the alpha-beta frequency band underlies top-down control, while the gamma-band mediates bottom-up stimulus processing. This arrangement inspires an attractive hypothesis, which posits that top-down beta-band influences directly modulate bottom-up gamma band influences via cross-frequency interaction. We evaluate this hypothesis determining that beta-band top-down influences from parietal area 7a to visual area V1 are correlated with bottom-up gamma frequency oscillations from V1 to area V4, in a spatially specific manner, and that this correlation is maximal when top-down activity precedes bottom-up activity. These results show that for top-down processes such as spatial attention, elevated top-down beta-band influences directly enhance feedforward stimulus induced gamma-band processing, leading to enhancement of the selected stimulus.
]]></description>
<dc:creator>Craig Geoffrey Richter</dc:creator>
<dc:creator>William Hedley Thompson</dc:creator>
<dc:creator>Conrado A Bosman</dc:creator>
<dc:creator>Pascal Fries</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-05-19</dc:date>
<dc:identifier>doi:10.1101/054288</dc:identifier>
<dc:title><![CDATA[Top-down modulation of stimulus drive via beta-gamma cross-frequency interaction.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-05-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/135467v1?rss=1">
<title>
<![CDATA[
Gamma-Band Resonance Of Visual Cortex To Optogenetic Stimulation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/135467v1?rss=1"
</link>
<description><![CDATA[
Activated visual cortex typically engages in neuronal synchronization in the gamma-frequency band (30-90 Hz). Gamma-band synchronization is related to cognitive functioning, and its mechanisms have been extensively investigated, predominantly through in-vitro studies. To further elucidate its mechanisms in-vivo, we performed simultaneous optogenetic stimulation and electrophysiological recordings of visual cortical areas 17 and 21a in the anesthetized cat. Viral transfection with AAV1 or AAV9 under a CamKII promoter led to robust Channelrhodopsin-2 (ChR2) expression. Immunohistochemical analysis showed that all ChR2-expressing neurons were negative for Parvalbumin, consistent with predominant or exclusive expression in excitatory neurons. Optogenetic stimulation used primarily surface illumination directly above the transfected and recorded cells. Stimulation with constant light led to strong and sustained gamma-band synchronization with strength and bandwidth similar to visually induced gamma. Rhythmic stimulation with light-pulse trains or sinusoidal light modulation revealed strongest resonance for gamma-band frequencies. Gamma resonance was confirmed by optogenetic white-noise stimulation. White-noise stimulation allowed the quantification of the transfer function between the optogenetic stimulation and the local field potential response. This transfer function showed a dominant peak in the gamma band. Thus, we find that visual cortical circuits resonate most strongly to gamma-band components in their input. This resonance renders both the sensitivity to input, and the output of these circuits, selectively tuned to gamma.nnSignificance StatementActivated groups of cortical neurons often display rhythmic synchronization in the gamma-frequency band (30-90 Hz). Gamma-band synchronization is particularly well studied in visual cortex. We used optogenetics to control visual cortex neurons with light. Different optogenetic stimulation protocols, using constant light, rhythmically modulated light or white-noise modulated light, all demonstrated that the investigated circuits predominantly resonate to stimulation in the gamma band. The observed gamma-band resonance renders visual cortical circuits most sensitive to gamma-rhythmic synaptic inputs. This in turn renders their spike output and the ensuing interareal synchronization gamma rhythmic.nnThis work was supported by DFG (SPP 1665, FOR 1847, FR2557/5-1-CORNET to P.F.; EXC 1086, DI 1908/5-1, DI 1908/6-1 to I.D.), BMBF (01GQ1301 to I.D.), EU (HEALTH-F2-2008-200728-BrainSynch, FP7-604102-HBP, FP7-600730-Magnetrodes to P.F.; ERC Starting Grant OptoMotorPath to I.D.), a European Young Investigator Award to P.F., the FENS-Kavli Network of Excellence to I.D., National Institutes of Health (1U54MH091657-WU-Minn-Consortium-HCP to P.F.), the LOEWE program (NeFF to P.F. and I.D.). Present address of I.D.: Optophysiology, Bernstein Center and BrainLinks-BrainTools, University of Freiburg, Albertstrase 23, 79104 Freiburg, Germany.nnAuthor contributionsJ.N, C.M.L., T.W., P.F. designed research; J.N, C.M.L., T.W., P.J., I.D., P.F. performed experiments; J.N., C.M.L., T.W. analyzed data; J.N., P.F. wrote the paper.
]]></description>
<dc:creator>Ni, J.</dc:creator>
<dc:creator>Lewis, C.</dc:creator>
<dc:creator>Wunderle, T.</dc:creator>
<dc:creator>Jendritza, P.</dc:creator>
<dc:creator>Diester, I.</dc:creator>
<dc:creator>Fries, P.</dc:creator>
<dc:date>2017-05-08</dc:date>
<dc:identifier>doi:10.1101/135467</dc:identifier>
<dc:title><![CDATA[Gamma-Band Resonance Of Visual Cortex To Optogenetic Stimulation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-05-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/131516v1?rss=1">
<title>
<![CDATA[
10-Month-Old Infants Are Sensitive To The Time Course Of Perceived Actions: Evidence From A Study Combining Eye-tracking And EEG 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/131516v1?rss=1"
</link>
<description><![CDATA[
Research has shown that infants are able to track a moving target efficiently - even if it is transiently occluded from sight. This basic ability allows prediction of when and where events happen in everyday life. Yet, it is unclear whether, and how, infants internally represent the time course of ongoing movements to derive predictions. In this study, 10-month-old crawlers observed the video of a same-aged crawling baby that was transiently occluded and reappeared in either a temporally continuous or non-continuous manner (i.e., delayed by 500 ms vs. forwarded by 500 ms relative to the real-time movement). Eye movement and rhythmic neural brain activity (EEG) were measured simultaneously. Eye movement analyses showed that infants were sensitive to slight temporal shifts in movement continuation after occlusion. Furthermore, brain activity related to sensorimotor rather than mnemonic processing differed between observation of continuous and non-continuous movements. Early sensitivity to an actions timing may hence be explained within the internal real-time simulation account of action observation. Overall, the results support the hypothesis that 10-month-old infants are well prepared for internal representation of the time course of observed movements that are within the infants current motor repertoire.
]]></description>
<dc:creator>Bache, C.</dc:creator>
<dc:creator>Springer, A.</dc:creator>
<dc:creator>Noack, H.</dc:creator>
<dc:creator>Stadler, W.</dc:creator>
<dc:creator>Kopp, F.</dc:creator>
<dc:creator>Lindenberger, U.</dc:creator>
<dc:creator>Werkle-Bergner, M.</dc:creator>
<dc:date>2017-04-28</dc:date>
<dc:identifier>doi:10.1101/131516</dc:identifier>
<dc:title><![CDATA[10-Month-Old Infants Are Sensitive To The Time Course Of Perceived Actions: Evidence From A Study Combining Eye-tracking And EEG]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-04-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/057083v1?rss=1">
<title>
<![CDATA[
Can pornography be addictive? An fMRI study of men seeking treatment for problematic pornography use. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/057083v1?rss=1"
</link>
<description><![CDATA[
Pornography consumption is highly prevalent, particularly among young adult males. For some individuals, problematic pornography use (PPU) is a reason for seeking treatment. Despite the pervasiveness of pornography, PPU appears under-investigated, including with respect to the underlying neural mechanisms.nnUsing functional magnetic resonance imaging (fMRI), we examined ventral striatal responses to erotic and monetary stimuli, disentangling cue-related  wanting from reward-related  liking among 28 heterosexual males seeking treatment for PPU and 24 heterosexual males without PPU. Subjects engaged in an incentive delay task in the scanner, in which they received erotic or monetary rewards preceded by predictive cues. BOLD responses to erotic and monetary cues were analyzed and examined with respect to self-reported data on sexual activity collected over the 2 preceding months.nnMen with and without PPU differed in their striatal responses to cues predicting erotic pictures, but not in their responses to erotic pictures. PPU subjects when compared to control subjects showed increased activation of ventral striatum specifically for cues predicting erotic pictures but not for cues predicting monetary gains. Relative sensitivity to cues predicting erotic pictures versus monetary gains was significantly related to the increased behavioral motivation to view erotic images (suggestive of higher  wanting), severity of PPU, amount of pornography use per week and number of weekly masturbations.nnOur findings suggest that, similar to what is observed in substance and gambling addictions, the neural and behavioral mechanisms associated with the anticipatory processing of cues specifically predicting erotic rewards relate importantly to clinically relevant features of PPU. These findings suggest that PPU may represent a behavioral addiction and that interventions helpful in targeting behavioral and substance addictions warrant consideration for adaptation and use in helping men with PPU.
]]></description>
<dc:creator>Mateusz Gola</dc:creator>
<dc:creator>Malgorzata Wordecha</dc:creator>
<dc:creator>Guillaume Sescousse</dc:creator>
<dc:creator>Michal Lew-Starowicz</dc:creator>
<dc:creator>Bartosz Kossowski</dc:creator>
<dc:creator>Marek Wypych</dc:creator>
<dc:creator>Scott Makeig</dc:creator>
<dc:creator>Marc Potenza</dc:creator>
<dc:creator>Artur Marchewka</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-06-08</dc:date>
<dc:identifier>doi:10.1101/057083</dc:identifier>
<dc:title><![CDATA[Can pornography be addictive? An fMRI study of men seeking treatment for problematic pornography use.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-06-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/085670v1?rss=1">
<title>
<![CDATA[
Impaired lexical selection with competing distractors: Evidence from left temporal and left prefrontal lesions 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/085670v1?rss=1"
</link>
<description><![CDATA[
According to the competition account of lexical selection in word production, conceptually driven word retrieval involves the activation of a set of candidate words in left temporal cortex, and competitive selection of the intended word from this set, regulated by frontal cortical mechanisms. However, the relative contribution of these brain regions to competitive lexical selection is uncertain. In the present study, five patients with left prefrontal cortex lesions (overlapping in ventral and dorsal lateral cortex), eight patients with left lateral temporal cortex lesions (overlapping in middle temporal gyrus), and 13 matched controls performed a picture-word interference task. Distractor words were semantically related or unrelated to the picture, or the name of the picture (congruent condition). Semantic interference (related vs unrelated), tapping into competitive lexical selection, was examined. An overall semantic interference effect was observed for the control and left-temporal groups separately. The left-frontal patients did not show a reliable semantic interference effect as a group. The left-temporal patients had increased semantic interference in the error rates relative to controls. Error distribution analyses indicated that these patients had more hesitant responses for the related than for the unrelated condition. We propose that left middle temporal lesions affect the lexical activation component, making lexical selection more susceptible to errors.
]]></description>
<dc:creator>Piai, V.</dc:creator>
<dc:creator>Knight, R. T.</dc:creator>
<dc:date>2016-11-04</dc:date>
<dc:identifier>doi:10.1101/085670</dc:identifier>
<dc:title><![CDATA[Impaired lexical selection with competing distractors: Evidence from left temporal and left prefrontal lesions]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-11-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/123455v1?rss=1">
<title>
<![CDATA[
CiliaCarta: An Integrated And Validated Compendium Of Ciliary Genes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/123455v1?rss=1"
</link>
<description><![CDATA[
The cilium is an essential organelle at the surface of most mammalian cells whose dysfunction causes a wide range of genetic diseases collectively called ciliopathies. The current rate at which new ciliopathy genes are identified suggests that many ciliary components remain undiscovered. We generated and rigorously analyzed genomic, proteomic, transcriptomic and evolutionary data and systematically integrated these using Bayesian statistics into a predictive score for ciliary function. This resulted in 285 candidate ciliary genes. We found experimental evidence of ciliary associations for 24 out of 36 analyzed candidate proteins. In addition, we show that OSCP1, which has previously been implicated in two distinct non-ciliary functions, causes a cilium dysfunction phenotype when depleted in zebrafish. The candidate list forms the basis of CiliaCarta, a comprehensive ciliary compendium covering 836 genes. The resource can be used to objectively prioritize candidate genes in whole exome or genome sequencing of ciliopathy patients and can be accessed at http://bioinformatics.bio.uu.nl/john/syscilia/ciliacarta/.
]]></description>
<dc:creator>van Dam, T. J. P.</dc:creator>
<dc:creator>Kennedy, J.</dc:creator>
<dc:creator>van der Lee, R.</dc:creator>
<dc:creator>de Vrieze, E.</dc:creator>
<dc:creator>Wunderlich, K. A.</dc:creator>
<dc:creator>Rix, S.</dc:creator>
<dc:creator>Dougherty, G. W.</dc:creator>
<dc:creator>Lambacher, N. J.</dc:creator>
<dc:creator>Li, C.</dc:creator>
<dc:creator>Jensen, V. L.</dc:creator>
<dc:creator>Leroux, M. R.</dc:creator>
<dc:creator>Hjeij, R.</dc:creator>
<dc:creator>Horn, N.</dc:creator>
<dc:creator>Texier, Y.</dc:creator>
<dc:creator>Wissinger, Y.</dc:creator>
<dc:creator>van Reeuwijk, J.</dc:creator>
<dc:creator>Wheway, G.</dc:creator>
<dc:creator>Knapp, B.</dc:creator>
<dc:creator>Scheel, J. F.</dc:creator>
<dc:creator>Franco, B.</dc:creator>
<dc:creator>Mans, D. A.</dc:creator>
<dc:creator>van Wijk, E.</dc:creator>
<dc:creator>Kepes, F.</dc:creator>
<dc:creator>Slaats, G. G.</dc:creator>
<dc:creator>Toedt, G.</dc:creator>
<dc:creator>Kremer, H.</dc:creator>
<dc:creator>Omran, H.</dc:creator>
<dc:creator>Szymanska, K.</dc:creator>
<dc:creator>Koutroumpas, K.</dc:creator>
<dc:creator>Ueffing, M.</dc:creator>
<dc:creator>Nguyen, T.-M. T.</dc:creator>
<dc:creator>Letteboer, S. J. F.</dc:creator>
<dc:creator>Oud, M. M.</dc:creator>
<dc:creator>van Beersum, S. E. C.</dc:creator>
<dc:creator>Schmidts, M.</dc:creator>
<dc:creator>Beales, P. L.</dc:creator>
<dc:creator>Lu, Q.</dc:creator>
<dc:creator>Giles, R. H.</dc:creator>
<dc:creator>Szklarczyk, R.</dc:creator>
<dc:creator>Russell, R. B.</dc:creator>
<dc:creator>Gibson, T. J.</dc:creator>
<dc:creator>Johnson, C. A.</dc:creator>
<dc:date>2017-04-03</dc:date>
<dc:identifier>doi:10.1101/123455</dc:identifier>
<dc:title><![CDATA[CiliaCarta: An Integrated And Validated Compendium Of Ciliary Genes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-04-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/119073v1?rss=1">
<title>
<![CDATA[
Prior expectations induce pre-stimulus sensory templates 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/119073v1?rss=1"
</link>
<description><![CDATA[
Perception can be described as a process of inference, integrating bottom-up sensory inputs and top-down expectations. However, it is unclear how this process is neurally implemented. It has been proposed that expectations lead to pre-stimulus baseline increases in sensory neurons tuned to the expected stimulus, which in turn affects the processing of subsequent stimuli. Recent fMRI studies have revealed stimulus-specific patterns of activation in sensory cortex as a result of expectation, but this method lacks the temporal resolution necessary to distinguish pre- from post-stimulus processes. Here, we combined human MEG with multivariate decoding techniques to probe the representational content of neural signals in a time-resolved manner. We observed a representation of expected stimuli in the neural signal well before they were presented, demonstrating that expectations indeed induce a pre-activation of stimulus templates. These results suggest a mechanism for how predictive perception can be neurally implemented.
]]></description>
<dc:creator>Kok, P.</dc:creator>
<dc:creator>Mostert, P.</dc:creator>
<dc:creator>De Lange, F. P.</dc:creator>
<dc:date>2017-03-21</dc:date>
<dc:identifier>doi:10.1101/119073</dc:identifier>
<dc:title><![CDATA[Prior expectations induce pre-stimulus sensory templates]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-03-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/107987v1?rss=1">
<title>
<![CDATA[
Do Candidate Genes Affect the Brain’s White Matter Microstructure? Large-Scale Evaluation of 6,165 Diffusion MRI Scans 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/107987v1?rss=1"
</link>
<description><![CDATA[
AbstractSusceptibility genes for psychiatric and neurological disorders - including APOE, BDNF, CLU,CNTNAP2, COMT, DISC1, DTNBP1, ErbB4, HFE, NRG1, NTKR3, and ZNF804A - have been reported to affect white matter (WM) microstructure in the healthy human brain, as assessed through diffusion tensor imaging (DTI). However, effects of single nucleotide polymorphisms (SNPs) in these genes explain only a small fraction of the overall variance and are challenging to detect reliably in single cohort studies. To date, few studies have evaluated the reproducibility of these results. As part of the ENIGMA-DTI consortium, we pooled regional fractional anisotropy (FA) measures for 6,165 subjects (CEU ancestry N=4,458) from 11 cohorts worldwide to evaluate effects of 15 candidate SNPs by examining their associations with WM microstructure. Additive association tests were conducted for each SNP. We used several meta-analytic and mega-analytic designs, and we evaluated regions of interest at multiple granularity levels. The ENIGMA-DTI protocol was able to detect single-cohort findings as originally reported. Even so, in this very large sample, no significant associations remained after multiple-testing correction for the 15 SNPs investigated. Suggestive associations (1.3x10-4 < p < 0.05, uncorrected) were found for BDNF, COMT, and ZNF804A in specific tracts. Meta-and mega-analyses revealed similar findings. Regardless of the approach, the previously reported candidate SNPs did not show significant associations with WM microstructure in this largest genetic study of DTI to date; the negative findings are likely not due to insufficient power. Genome-wide studies, involving large-scale meta-analyses, may help to discover SNPs robustly influencing WM microstructure.
]]></description>
<dc:creator>Jahanshad, N.</dc:creator>
<dc:creator>Ganjgahi, H.</dc:creator>
<dc:creator>Bralten, J.</dc:creator>
<dc:creator>den Braber, A.</dc:creator>
<dc:creator>Faskowitz, J.</dc:creator>
<dc:creator>Knodt, A.</dc:creator>
<dc:creator>Lemaitre, H.</dc:creator>
<dc:creator>Nir, T.</dc:creator>
<dc:creator>Patel, B.</dc:creator>
<dc:creator>Richie, S.</dc:creator>
<dc:creator>Sprooten, E.</dc:creator>
<dc:creator>van Hulzen, K.</dc:creator>
<dc:creator>Zavaliangos-Petropulu, A.</dc:creator>
<dc:creator>Zwiers, M.</dc:creator>
<dc:creator>Almasy, L.</dc:creator>
<dc:creator>Bastin, M.</dc:creator>
<dc:creator>Bernstein, M.</dc:creator>
<dc:creator>Blangero, J.</dc:creator>
<dc:creator>Curran, J.</dc:creator>
<dc:creator>Deary, I. J.</dc:creator>
<dc:creator>de Zubicary, G.</dc:creator>
<dc:creator>Duggirala, R.</dc:creator>
<dc:creator>Fisher, S.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Fox, P.</dc:creator>
<dc:creator>Goldman, D.</dc:creator>
<dc:creator>Haberg, A.</dc:creator>
<dc:creator>Hariri, A.</dc:creator>
<dc:creator>Hong, L. E.</dc:creator>
<dc:creator>Hoogman, M.</dc:creator>
<dc:creator>Huentelman, M.</dc:creator>
<dc:creator>Martin, N.</dc:creator>
<dc:creator>Martinot, J.-L.</dc:creator>
<dc:creator>McIntosh, A.</dc:creator>
<dc:creator>McMahon, K.</dc:creator>
<dc:creator>Medland, S.</dc:creator>
<dc:creator>Mitchell, B.</dc:creator>
<dc:creator>Munoz-Maniega, S.</dc:creator>
<dc:creator>Olvera, R.</dc:creator>
<dc:creator>Oosterlaan, J.</dc:creator>
<dc:creator>Peterson, C.</dc:creator>
<dc:creator>Royle, N.</dc:creator>
<dc:creator>Saykin, A.</dc:creator>
<dc:creator>Schumann, G</dc:creator>
<dc:date>2017-02-20</dc:date>
<dc:identifier>doi:10.1101/107987</dc:identifier>
<dc:title><![CDATA[Do Candidate Genes Affect the Brain’s White Matter Microstructure? Large-Scale Evaluation of 6,165 Diffusion MRI Scans]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-02-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/099184v1?rss=1">
<title>
<![CDATA[
Multivariate cross-frequency coupling via generalized eigendecomposition 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/099184v1?rss=1"
</link>
<description><![CDATA[
This paper presents a new framework for analyzing cross-frequency coupling in multichannel electrophysiological recordings. The generalized eigendecomposition-based cross-frequency coupling framework (gedCFC) is inspired by source separation algorithms combined with dynamics of mesoscopic neurophysiological processes. It is unaffected by factors that confound traditional CFC methods such as non-stationarities, non-sinusoidality, and non-uniform phase angle distributions--attractive properties considering that brain activity is neither stationary nor perfectly sinusoidal. The gedCFC framework opens new opportunities for conceptualizing CFC as network interactions with diverse spatial/topographical distributions. five specific methods within the gedCFC framework are detailed, with validations in simulated data and applications in several empirical datasets. gedCFC accurately recovers physiologically plausible CFC patterns embedded in noise where traditional CFC methods perform poorly. It is also demonstrated that spike-field coherence in multichannel local field potential data can be analyzed using the gedCFC framework, with significant advantages over traditional spike-field coherence analyses. Null-hypothesis testing is also discussed.
]]></description>
<dc:creator>Cohen, M.</dc:creator>
<dc:date>2017-01-09</dc:date>
<dc:identifier>doi:10.1101/099184</dc:identifier>
<dc:title><![CDATA[Multivariate cross-frequency coupling via generalized eigendecomposition]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2017-01-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/097402v1?rss=1">
<title>
<![CDATA[
Comparison of linear spatial filters for identifying oscillatory activity in multichannel data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/097402v1?rss=1"
</link>
<description><![CDATA[
BackgroundLarge-scale synchronous neural activity produces electrical fields that can be measured by electrodes outside the head, and volume conduction ensures that neural sources can be measured by many electrodes. However, most data analyses in M/EEG research are univariate, meaning each electrode is considered as a separate measurement. Several multivariate linear spatial filtering techniques have been introduced to the cognitive electrophysiology literature, but these techniques are not commonly used; comparisons across filters would be beneficial to the field.nnNew methodThe purpose of this paper is to evaluate and compare the performance of several linear spatial filtering techniques, with a focus on those that use generalized eigendecomposition to facilitate dimensionality reduction and signal-to-noise ratio maximization.nnResultsSimulated and empirical data were used to assess the accuracy, signal-to-noise ratio, and interpretability of the spatial filter results. When the simulated signal is powerful, different spatial filters provide convergent results. However, more subtle signals require carefully selected analysis parameters to obtain optimal results.nnComparison with existing methodsLinear spatial filters can be powerful data analysis tools in cognitive electrophysiology, and should be applied more often; on the other hand, spatial filters can latch onto artifacts or produce uninterpretable results.nnConclusionsHypothesis-driven analyses, careful data inspection, and appropriate parameter selection are necessary to obtain high-quality results when using spatial filters.
]]></description>
<dc:creator>Cohen, M. X.</dc:creator>
<dc:date>2016-12-30</dc:date>
<dc:identifier>doi:10.1101/097402</dc:identifier>
<dc:title><![CDATA[Comparison of linear spatial filters for identifying oscillatory activity in multichannel data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-12-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/093724v1?rss=1">
<title>
<![CDATA[
Slice-sampled Bayesian PRF mapping 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/093724v1?rss=1"
</link>
<description><![CDATA[
Functional magnetic resonance imaging (FMRI) allows to non-invasively measure human brain activity at the millimeter scale. As such, it is widely used in computational neuroimaging studies that aim to build models to predict stimulus-induced neural responses in visual cortex. A popular method is population receptive field (PRF) mapping, which is able to characterize responses to a large range of stimuli. For each voxel, the PRF method estimates the best fitting receptive field properties (such as location and size in the visual field) using a coarse-to-fine approach which minimizes, but not eliminates, the risk of returning a local minimum. Here, we provide a Bayesian approach to the PRF method based on the slice sampler. Using this approach, we provide estimates of receptive field properties while at the same time being able to quantify their uncertainty. We test the performance of conventional and Bayesian approaches on simulated and empirical data.
]]></description>
<dc:creator>Quax, S. C.</dc:creator>
<dc:creator>van Koppen, T. C.</dc:creator>
<dc:creator>Jylanki, P.</dc:creator>
<dc:creator>Dumoulin, S. O.</dc:creator>
<dc:creator>van Gerven, M. A. J.</dc:creator>
<dc:date>2016-12-13</dc:date>
<dc:identifier>doi:10.1101/093724</dc:identifier>
<dc:title><![CDATA[Slice-sampled Bayesian PRF mapping]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-12-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/087817v1?rss=1">
<title>
<![CDATA[
Antenatal maternal anxiety modulates the BOLD response in 20-year old adolescents during an endogenous cognitive control task 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/087817v1?rss=1"
</link>
<description><![CDATA[
Evidence is building for an association between the level of anxiety experienced by a mother during pregnancy and the cognitive development of her offspring. The current study uses fMRI to examine whether there is an association between prenatal exposure to maternal anxiety and brain activity in 20 year old adolescents. In line with previous results of this follow-up study, it was found that adolescents of mothers reporting high levels of anxiety during weeks 12-22 of their pregnancy had a different pattern of decision making in a Gambling paradigm requiring endogenous cognitive control compared to adolescents of mothers reporting low to average levels of anxiety during pregnancy. Moreover, the blood oxygenation level dependent (BOLD) response in a number of prefrontal cortical areas was modulated by the level of antenatal maternal anxiety. In particular a number of right lateralized clusters including inferior frontal junction, that were modulated in the adolescents of mothers reporting low to average levels of anxiety during pregnancy by a task manipulation of cognitive control, were not modulated by this manipulation in the adolescents of mothers reporting high levels of anxiety during pregnancy. These results provide a neurobiological underpinning for our previous hypothesis of an association between a deficit in endogenous cognitive control in adolescence and exposure to maternal anxiety in the prenatal life period.
]]></description>
<dc:creator>Mennes, M.</dc:creator>
<dc:creator>Van den Bergh, B. R. H.</dc:creator>
<dc:creator>Sunaert, S.</dc:creator>
<dc:creator>Lagae, L.</dc:creator>
<dc:creator>Stiers, P.</dc:creator>
<dc:date>2016-11-15</dc:date>
<dc:identifier>doi:10.1101/087817</dc:identifier>
<dc:title><![CDATA[Antenatal maternal anxiety modulates the BOLD response in 20-year old adolescents during an endogenous cognitive control task]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-11-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/070672v1?rss=1">
<title>
<![CDATA[
Neuronal gamma-band synchronization regulated by instantaneous modulations of the oscillation frequency 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/070672v1?rss=1"
</link>
<description><![CDATA[
Neuronal gamma-band synchronization shapes information flow during sensory and cognitive processing. A common view is that a stable and shared frequency over time is required for robust and functional synchronization. To the contrary, we found that non-stationary instantaneous frequency modulations were essential for synchronization. First, we recorded gamma rhythms in monkey visual area V1, and found that they synchronized by continuously modulating their frequency difference in a phase-dependent manner. The frequency modulation properties regulated both the phase-locking and the preferred phase-relation between gamma rhythms. Second, our experimental observations were in agreement with a biophysical model of gamma rhythms and were accurately predicted by the theory of weakly coupled oscillators revealing the underlying theoretical principles that govern gamma synchronization. Thus, synchronization through instantaneous frequency modulations represents a fundamental principle of gamma-band neural coordination that is likely generalizable to other brain rhythms.
]]></description>
<dc:creator>Eric Lowet</dc:creator>
<dc:creator>Mark Roberts</dc:creator>
<dc:creator>Alina Peter</dc:creator>
<dc:creator>Bart Gips</dc:creator>
<dc:creator>Peter De Weerd</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-08-22</dc:date>
<dc:identifier>doi:10.1101/070672</dc:identifier>
<dc:title><![CDATA[Neuronal gamma-band synchronization regulated by instantaneous modulations of the oscillation frequency]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-08-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/069062v1?rss=1">
<title>
<![CDATA[
Reward learning deficits in Parkinson’s disease depend on depression 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/069062v1?rss=1"
</link>
<description><![CDATA[
BackgroundDepression is one of the most common and debilitating non-motor symptoms of Parkinsons disease (PD). The neurocognitive mechanisms underlying depression in PD are unclear and treatment is often suboptimal.nnMethodsWe investigated the role of striatal dopamine in reversal learning from reward and punishment by combining a controlled medication withdrawal procedure with functional magnetic resonance imaging (fMRI) in 22 non-depressed PD patients and 19 PD patients with past or present PD-related depression.nnResultsPD patients with a PD-related depression (history) exhibited impaired reward versus punishment reversal learning as well as reduced reward versus punishment-related BOLD signal in the striatum (putamen) compared with non-depressed PD patients. No effects of dopaminergic medication were observed.nnConclusionsThe present findings demonstrate that impairments in reversal learning from reward versus punishment and associated reward-related striatal signalling depend on the presence of (a history of) depression in PD.
]]></description>
<dc:creator>Monique HM Timmer</dc:creator>
<dc:creator>Guillaume Sescousse</dc:creator>
<dc:creator>Marieke E van der Schaaf</dc:creator>
<dc:creator>Rianne AJ Esselink</dc:creator>
<dc:creator>Roshan Cools</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-08-12</dc:date>
<dc:identifier>doi:10.1101/069062</dc:identifier>
<dc:title><![CDATA[Reward learning deficits in Parkinson’s disease depend on depression]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-08-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/069047v1?rss=1">
<title>
<![CDATA[
Dopaminergic drugs decrease loss aversion in Parkinson’s disease with but not without depression 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/069047v1?rss=1"
</link>
<description><![CDATA[
Depression, a common non-motor symptom of Parkinsons disease (PD), is accompanied by impaired decision making and an enhanced response to aversive outcomes. Current strategies to treat depression in PD include dopaminergic medication. However, their use can be accompanied by detrimental side effects, such as enhanced risky choice. The mechanisms underlying dopamine-induced increases in risky choice are unclear. In the current study we adopt a clinical-neuroeconomic approach to investigate the effects of dopaminergic medication on loss aversion during risky choice in depressed and non-depressed PD. Twenty-three healthy controls, 21 depressed and 22 non-depressed PD patients were assessed using a well-established gambling task measuring loss aversion during risky choice. Patients were tested on two occasions, after taking their normal dopaminergic medication (ON) and after withdrawal of their medication (OFF). Dopaminergic medication decreased loss aversion to a greater extent in depressed than non-depressed PD patients. Moreover, we show that the degree to which dopaminergic medication decreases loss aversion correlated with current depression severity and with drug effects on depression scores. These findings demonstrate that dopamine-induced changes in loss aversion depend on the presence of depressive symptoms in PD.nnSignificance statementDopaminergic medication that is used to treat motor and non-motor symptoms in patients with Parkinsons disease is known to contribute to risky decision-making. The underlying mechanisms are unclear. The present study demonstrates that dopaminergic medication in Parkinsons disease decreases loss aversion during risky choice, but only in depressed and not in non-depressed patients with Parkinsons disease. These results advance our understanding of the mechanisms underlying dopamine-induced risky choice, while also identifying depression as an important factor that confers vulnerability to such dopamine-induced risky choice.nnConflict of InterestThe authors declare no competing financial interests.
]]></description>
<dc:creator>Monique HM Timmer</dc:creator>
<dc:creator>Guillaume Sescousse</dc:creator>
<dc:creator>Rianne AJ Esselink</dc:creator>
<dc:creator>Payam Piray</dc:creator>
<dc:creator>Roshan Cools</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-08-11</dc:date>
<dc:identifier>doi:10.1101/069047</dc:identifier>
<dc:title><![CDATA[Dopaminergic drugs decrease loss aversion in Parkinson’s disease with but not without depression]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-08-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/067579v1?rss=1">
<title>
<![CDATA[
Local expectation violations result in global activity gain in primary visual cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/067579v1?rss=1"
</link>
<description><![CDATA[
During natural perception, we often form expectations about upcoming input. These expectations are usually multifaceted - we expect a particular object at a particular location. However, expectations about spatial location and stimulus features have mostly been studied in isolation, and it is unclear whether feature-based expectation can be spatially specific. Interestingly, feature-based attention automatically spreads to unattended locations. It is still an open question whether the neural mechanisms underlying feature-based expectation differ from those underlying feature-based attention. Therefore, establishing whether the effects of feature-based expectation are spatially specific may inform this debate. Here, we investigated this by inducing expectations of a specific stimulus feature at a specific location, and probing the effects on sensory processing across the visual field using fMRI. We found an enhanced sensory response for unexpected stimuli, which was elicited only when there was a violation of expectation at the specific location where participants formed a stimulus expectation. The neural consequences of this expectation violation, however, spread to cortical locations processing the stimulus in the opposite hemifield. This suggests that an expectation violation at one location in the visual world can lead to a spatially non-specific gain increase across the visual field.
]]></description>
<dc:creator>Peter Kok</dc:creator>
<dc:creator>Lieke L.F. van Lieshout</dc:creator>
<dc:creator>Floris P. de Lange</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-08-03</dc:date>
<dc:identifier>doi:10.1101/067579</dc:identifier>
<dc:title><![CDATA[Local expectation violations result in global activity gain in primary visual cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-08-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/063867v1?rss=1">
<title>
<![CDATA[
The Missing Link: Predicting Connectomes from Noisy and Partially Observed Tract Tracing Data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/063867v1?rss=1"
</link>
<description><![CDATA[
Our understanding of the wiring map of the brain, known as the connectome, has increased greatly in the last decade, mostly due to technological advancements in neuroimaging techniques and improvements in computational tools to interpret the vast amount of available data. Despite this, with the exception of the C. elegans roundworm, no definitive connectome has been established for any species. In order to obtain this, tracer studies are particularly appealing, as these have proven highly reliable. The downside of tract tracing is that it is costly to perform, and can only be applied ex vivo. In this paper, we suggest that instead of probing all possible connections, hitherto unknown connections may be predicted from the data that is already available. Our approach uses a  latent space model that embeds the connectivity in an abstract physical space. Regions that are close in the latent space have a high chance of being connected, while regions far apart are most likely disconnected in the connectome. After learning the latent embedding from the connections that we did observe, the latent space allows us to predict connections that have not been probed previously. We apply the methodology to two connectivity data sets of the macaque and we demonstrate that the latent space model is successful in predicting unobserved connectivity, outperforming two alternative baselines in nearly all cases. Furthermore, we show how the latent spatial embedding may be used to integrate multimodal observations (i.e. anterograde and retrograde tracers) for the mouse neocortex. Finally, our probabilistic approach enables us to make explicit which connections are easy to predict and which prove difficult, allowing for informed follow-up studies.
]]></description>
<dc:creator>Max Hinne</dc:creator>
<dc:creator>Annet Meijers</dc:creator>
<dc:creator>Rembrandt Bakker</dc:creator>
<dc:creator>Paul H.E. Tiesinga</dc:creator>
<dc:creator>Morten Mørup</dc:creator>
<dc:creator>Marcel A.J. van Gerven</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-07-14</dc:date>
<dc:identifier>doi:10.1101/063867</dc:identifier>
<dc:title><![CDATA[The Missing Link: Predicting Connectomes from Noisy and Partially Observed Tract Tracing Data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-07-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/036897v1?rss=1">
<title>
<![CDATA[
A high-quality reference panel reveals the complexity and distribution of structural genome changes in a human population 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/036897v1?rss=1"
</link>
<description><![CDATA[
Structural variation (SV) represents a major source of differences between individual human genomes and has been linked to disease phenotypes. However, the majority of studies provide neither a global view of the full spectrum of these variants nor integrate them into reference panels of genetic variation.nnHere, we analyse whole genome sequencing data of 769 individuals from 250 Dutch families, and provide a haplotype-resolved map of 1.9 million genome variants across 9 different variant classes, including novel forms of complex indels, and retrotransposition-mediated insertions of mobile elements and processed RNAs. A large proportion are previously under reported variants sized between 21 and 100bp. We detect 4 megabases of novel sequence, encoding 11 new transcripts. Finally, we show 191 known, trait-associated SNPs to be in strong linkage disequilibrium with SVs and demonstrate that our panel facilitates accurate imputation of SVs in unrelated individuals. Our findings are essential for genome-wide association studies.
]]></description>
<dc:creator>Jayne Hehir-Kwa</dc:creator>
<dc:creator>Tobias Marschall</dc:creator>
<dc:creator>Wigard P Kloosterman</dc:creator>
<dc:creator>Laurent C Francioli</dc:creator>
<dc:creator>Jasmijn A Baaijens</dc:creator>
<dc:creator>Louis Dijkstra</dc:creator>
<dc:creator>Abdel Abdellaoui</dc:creator>
<dc:creator>Vyacheslav Koval</dc:creator>
<dc:creator>Djie Tjwan Thung</dc:creator>
<dc:creator>Rene Wardenaar</dc:creator>
<dc:creator>Ivo Renkens</dc:creator>
<dc:creator>Bradley Coe</dc:creator>
<dc:creator>Patrick Deelen</dc:creator>
<dc:creator>Joep de Ligt</dc:creator>
<dc:creator>Eric-Wubbo Lameijer</dc:creator>
<dc:creator>Freerk van Dijk</dc:creator>
<dc:creator>Fereydoun Hormozdiari</dc:creator>
<dc:creator>Andre G Uitterlinden</dc:creator>
<dc:creator>Evan E Eichler</dc:creator>
<dc:creator>Paul de Bakker</dc:creator>
<dc:creator>Morris Swertz</dc:creator>
<dc:creator>Cisca Wijmenga</dc:creator>
<dc:creator>Gert-Jan van Ommen</dc:creator>
<dc:creator>Eline Slagboom</dc:creator>
<dc:creator>Dorret Boomsma</dc:creator>
<dc:creator>Genome of the Netherlands</dc:creator>
<dc:creator>Alexander Schoenhuth</dc:creator>
<dc:creator>Kai Ye</dc:creator>
<dc:creator>Victor Guryev</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-01-18</dc:date>
<dc:identifier>doi:10.1101/036897</dc:identifier>
<dc:title><![CDATA[A high-quality reference panel reveals the complexity and distribution of structural genome changes in a human population]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-01-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/060582v1?rss=1">
<title>
<![CDATA[
Gamma-rhythmic Gain Modulation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/060582v1?rss=1"
</link>
<description><![CDATA[
Cognition requires the dynamic modulation of effective connectivity, i.e. the modulation of the postsynaptic neuronal response to a given input. If postsynaptic neurons are rhythmically active, this might entail rhythmic gain modulation, such that inputs synchronized to phases of high gain benefit from enhanced effective connectivity. We show that visually induced gamma-band activity in awake macaque area V4 rhythmically modulates responses to unpredictable stimulus events. This modulation exceeded a simple additive superposition of a constant response onto ongoing gamma-rhythmic firing, demonstrating the modulation of multiplicative gain. Gamma phases leading to strongest neuronal responses also led to shortest behavioral reaction times, suggesting functional relevance of the effect. Furthermore, we find that constant optogenetic stimulation of anesthetized cat area 21a produces gamma-band activity entailing a similar gain modulation. As the gamma rhythm in area 21a did not spread backwards to area 17, this suggests that postsynaptic gamma is sufficient for gain modulation.
]]></description>
<dc:creator>Jianguang Ni</dc:creator>
<dc:creator>Thomas Wunderle</dc:creator>
<dc:creator>Christopher M. Lewis</dc:creator>
<dc:creator>Robert Desimone</dc:creator>
<dc:creator>Ilka Diester</dc:creator>
<dc:creator>Pascal Fries</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-06-24</dc:date>
<dc:identifier>doi:10.1101/060582</dc:identifier>
<dc:title><![CDATA[Gamma-rhythmic Gain Modulation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-06-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/060301v1?rss=1">
<title>
<![CDATA[
Next-generation sequencing identifies novel gene variants and pathways involved in specific language impairment 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/060301v1?rss=1"
</link>
<description><![CDATA[
A significant proportion of children suffer from unexplained problems acquiring proficient linguistic skills despite adequate intelligence and opportunity. These developmental speech and language disorders are highly heritable and have a substantial impact on society. Molecular studies have begun to identify candidate loci, but much of the underlying genetic architecture remains undetermined. Here, we performed whole exome sequencing of 43 unrelated probands affected by severe forms of specific language impairment, followed by independent validations with Sanger sequencing, and analyses of segregation patterns in parents and siblings, to try to shed new light on the aetiology of the disorder. By first focusing on a pre-defined set of known candidates from the literature, we identified potentially pathogenic variants in genes already implicated in diverse language-related syndromes, including ERC1, GRIN2A, and SRPX2. Complementary analyses suggested novel putative candidate genes carrying validated variants which were predicted to have functional effects, such as OXR1, SCN9A and KMT2D. We also searched for potential "multiple-hit" cases; one proband carried a rare AUTS2 variant in combination with a rare inherited haplotype affecting STARD9, while another carried a novel nonsynonymous variant in SEMA6D together with a rare stop-gain in SYNPR. When we broadened our scope to all rare and novel variants throughout the exomes, we identified several biological themes that were enriched for such variants, most notably microtubule transport and cytoskeletal regulation.
]]></description>
<dc:creator>Xiaowei Sylvia Chen</dc:creator>
<dc:creator>Rose H Reader</dc:creator>
<dc:creator>Alexander Hoischen</dc:creator>
<dc:creator>Joris A Veltman</dc:creator>
<dc:creator>Nuala H Simpson</dc:creator>
<dc:creator>SLI Consortium</dc:creator>
<dc:creator>Clyde Francks</dc:creator>
<dc:creator>Dianne F Newbury</dc:creator>
<dc:creator>Simon E Fisher</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-06-23</dc:date>
<dc:identifier>doi:10.1101/060301</dc:identifier>
<dc:title><![CDATA[Next-generation sequencing identifies novel gene variants and pathways involved in specific language impairment]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-06-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/060285v1?rss=1">
<title>
<![CDATA[
Finding functional disease-associated non-coding variation using next-generation sequencing 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/060285v1?rss=1"
</link>
<description><![CDATA[
Next generation sequencing has opened the way for the large scale interrogation of cohorts at the whole exome, or whole genome level. Currently, the field largely focuses on potential disease causing variants that fall within coding sequences and that are predicted to cause protein sequence changes, generally discarding non-coding variants. However non-coding DNA makes up ~98% of the genome and contains a range of sequences essential for controlling the expression of protein coding genes. Thus, potentially causative non-coding variation is currently being overlooked. To address this, we have designed an approach to assess variation in one class of non-coding regulatory DNA; the 3'UTRome. Variants in the 3'UTR region of genes are of particular interest because 3'UTRs are responsible for modulating protein expression levels via their interactions with microRNAs. Furthermore they are amenable to large scale analysis as 3'UTR-microRNA interactions are based on complementary base pairing and as such can be predicted in silico at the genome-wide level. We report a strategy for identifying and functionally testing variants in microRNA binding sites within the 3'UTRome and demonstrate the efficacy of this pipeline in a cohort of language impaired children. Using whole exome sequence data from 43 probands, we extracted variants that lay within 3'UTR microRNA binding sites. We identified a common variant (SNP) in a microRNA binding site and found this SNP to be associated with an endophenotype of language impairment (non-word repetition). We showed that this variant disrupted microRNA regulation in cells and was linked to altered gene expression in the brain, suggesting it may represent a risk factor contributing to SLI. This work demonstrates that biologically relevant variants are currently being under-investigated despite the wealth of next-generation sequencing data available and presents a simple strategy for interrogating non-coding regions of the genome. We propose that this strategy should be routinely applied to whole exome and whole genome sequence data in order to broaden our understanding of how non-coding genetic variation underlies complex phenotypes such as neurodevelopmental disorders.
]]></description>
<dc:creator>Paolo Devanna</dc:creator>
<dc:creator>Xiaowei Sylvia Chen</dc:creator>
<dc:creator>Joses Ho</dc:creator>
<dc:creator>Dario Gajewski</dc:creator>
<dc:creator>Alessandro Gialluisi</dc:creator>
<dc:creator>Clyde Francks</dc:creator>
<dc:creator>Simon E Fisher</dc:creator>
<dc:creator>Dianne F Newbury</dc:creator>
<dc:creator>Sonja C Vernes</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-06-22</dc:date>
<dc:identifier>doi:10.1101/060285</dc:identifier>
<dc:title><![CDATA[Finding functional disease-associated non-coding variation using next-generation sequencing]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-06-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/056671v1?rss=1">
<title>
<![CDATA[
Functional connectivity in neuromuscular system underlying bimanual muscle synergies 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/056671v1?rss=1"
</link>
<description><![CDATA[
Neural synchrony has been suggested as mechanism for integrating distributed sensorimotor systems involved in coordinated movement. To test the role of corticomuscular and intermuscular coherence in the formation of bimanual muscle synergies, we experimentally manipulated the degree of coordination between hand muscles by varying the sensitivity of the visual feedback to differences in bilateral force. In 16 healthy participants, cortical activity was measured using 64-channel electroencephalography (EEG) and muscle activity of the flexor pollicis brevis muscle of both hands using 8x8-channel high-density electromyography (HDsEMG). Using the uncontrolled manifold framework, coordination between bilateral forces was quantified by the synergy index RV in the time and frequency domain. Functional connectivity was assed using corticomuscular coherence between muscle activity and cortical source activity and intermuscular coherence between bilateral EMG activity. As expected, bimanual synergies were stronger in the high coordination condition. RV was higher in the high coordination condition in frequencies between 0 and 0.5 Hz, and above 2 Hz. For the 0.5-2 Hz frequency band this pattern was inverted. Corticomuscular coherence in the beta band (16-30 Hz) was maximal in the contralateral motor cortex and was reduced in the high coordination condition. In contrast, intermuscular coherence was observed at 5-12 Hz and increased with bimanual coordination. Within-subject comparisons revealed a negative correlation between RV and corticomuscular coherence and a positive correlation between RV and intermuscular coherence. Our findings suggest two distinct neural pathways: (1) Corticomuscular coherence reflects direct corticospinal projections involved in controlling individual muscles; (2) intermuscular coherence reflects diverging pathways involved in the coordination of multiple muscles.
]]></description>
<dc:creator>Ingmar E. J. de Vries</dc:creator>
<dc:creator>Andreas Daffertshofer</dc:creator>
<dc:creator>Dick F. Stegeman</dc:creator>
<dc:creator>Tjeerd W. Boonstra</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-06-02</dc:date>
<dc:identifier>doi:10.1101/056671</dc:identifier>
<dc:title><![CDATA[Functional connectivity in neuromuscular system underlying bimanual muscle synergies]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-06-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/049718v1?rss=1">
<title>
<![CDATA[
Two frequency bands contain the most stimulus-related information in visual cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/049718v1?rss=1"
</link>
<description><![CDATA[
Sensory cortices represent the world through the activity of diversely tuned cells. How the activity of single cells is coordinated within populations and across sensory hierarchies is largely unknown. Cortical oscillations may coordinate local and distributed neuronal groups. Using datasets from intracortical multi-electrode recordings and from large-scale electrocorticography (ECoG) grids, we investigated how visual features could be extracted from the local field potential (LFP) and how this compared with the information available from multi-unit activity (MUA). MUA recorded from macaque V1 contained comparable amounts of information as simultaneously recorded LFP power in two frequency bands, one in the alpha-beta band and the other in the gamma band. ECoG-LFP contained information in the same bands as microelectrode-LFP, even when identifying natural scenes. The fact that information was contained in the same bands in both intracortical and ECoG recordings suggests that oscillatory activity could play similar roles at both spatial scales.
]]></description>
<dc:creator>Christopher M Lewis</dc:creator>
<dc:creator>Conrado A Bosman</dc:creator>
<dc:creator>Nicolas M Brunet</dc:creator>
<dc:creator>Bruss Lima</dc:creator>
<dc:creator>Mark J. Roberts</dc:creator>
<dc:creator>Thilo Womelsdorf</dc:creator>
<dc:creator>Peter de Weerd</dc:creator>
<dc:creator>Sergio Neuenschwander</dc:creator>
<dc:creator>Wolf Singer</dc:creator>
<dc:creator>Pascal Fries</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-04-26</dc:date>
<dc:identifier>doi:10.1101/049718</dc:identifier>
<dc:title><![CDATA[Two frequency bands contain the most stimulus-related information in visual cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-04-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/052670v1?rss=1">
<title>
<![CDATA[
Meta-analysis of 2,104 trios provides support for 10 novel candidate genes for intellectual disability 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/052670v1?rss=1"
</link>
<description><![CDATA[
To identify novel candidate intellectual disability genes, we performed a meta-analysis on 2,637 de novo mutations, identified from the exomes of 2,104 ID trios. Statistical analyses identified 10 novel candidate ID genes, including DLG4, PPM1D, RAC1, SMAD6, SON, SOX5, SYNCRIP, TCF20, TLK2 and TRIP12. In addition, we show that these genes are intolerant to non-synonymous variation, and that mutations in these genes are associated with specific clinical ID phenotypes.
]]></description>
<dc:creator>Stefan H. Lelieveld</dc:creator>
<dc:creator>Margot R.F. Reijnders</dc:creator>
<dc:creator>Rolph Pfundt</dc:creator>
<dc:creator>Helger G. Yntema</dc:creator>
<dc:creator>Erik-Jan Kamsteeg</dc:creator>
<dc:creator>Petra de Vries</dc:creator>
<dc:creator>Bert B.A. de Vries</dc:creator>
<dc:creator>Marjolein H. Willemsen</dc:creator>
<dc:creator>Tjitske Kleefstra</dc:creator>
<dc:creator>Katharina Löhner</dc:creator>
<dc:creator>Maaike Vreeburg</dc:creator>
<dc:creator>Servi Stevens</dc:creator>
<dc:creator>Ineke van der Burgt</dc:creator>
<dc:creator>Ernie M.H.F. Bongers</dc:creator>
<dc:creator>Alexander P.A. Stegmann</dc:creator>
<dc:creator>Patrick Rump</dc:creator>
<dc:creator>Tuula Rinne</dc:creator>
<dc:creator>Marcel R. Nelen</dc:creator>
<dc:creator>Joris A. Veltman</dc:creator>
<dc:creator>Lisenka E.L.M. Vissers</dc:creator>
<dc:creator>Han G. Brunner</dc:creator>
<dc:creator>Christian Gilissen</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-05-11</dc:date>
<dc:identifier>doi:10.1101/052670</dc:identifier>
<dc:title><![CDATA[Meta-analysis of 2,104 trios provides support for 10 novel candidate genes for intellectual disability]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-05-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/040576v1?rss=1">
<title>
<![CDATA[
Explaining Missing Heritability Using Gaussian Process Regression 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/040576v1?rss=1"
</link>
<description><![CDATA[
For many traits and common human diseases, causal loci uncovered by genetic association studies account for little of the known heritable variation. Such  missing heritability may be due to the effect of non-additive interactions between multiple loci, but this has been little explored and difficult to test using existing parametric approaches. We propose a Bayesian non-parametric Gaussian Process Regression model, for identifying associated loci in the presence of interactions of arbitrary order. We analysed 46 quantitative yeast phenotypes and found that over 70% of the total known missing heritability could be explained using common genetic variants, many without significant marginal effects. Additional analysis of an immunological rat phenotype identified a three SNP interaction model providing a significantly better fit (p-value 9.0e-11) than the null model incorporating only the single marginally significant SNP. This new approach, called GPMM, represents a significant advance in approaches to understanding the missing heritability problem with potentially important implications for studies of complex, quantitative traits.
]]></description>
<dc:creator>Kevin Sharp</dc:creator>
<dc:creator>Wim Wiegerinck</dc:creator>
<dc:creator>Alejandro Arias-Vasquez</dc:creator>
<dc:creator>Barbara Franke</dc:creator>
<dc:creator>Jonathan Marchini</dc:creator>
<dc:creator>Cornelis A Albers</dc:creator>
<dc:creator>Hilbert J Kappen</dc:creator>
<dc:creator></dc:creator>
<dc:date>2016-02-22</dc:date>
<dc:identifier>doi:10.1101/040576</dc:identifier>
<dc:title><![CDATA[Explaining Missing Heritability Using Gaussian Process Regression]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2016-02-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/034363v1?rss=1">
<title>
<![CDATA[
Characterisation of CASPR2 deficiency disorder - a syndrome involving autism, epilepsy and language impairment 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/034363v1?rss=1"
</link>
<description><![CDATA[
BackgroundHeterozygous mutations in CNTNAP2 have been identified in patients with a range of complex phenotypes including intellectual disability, autism and schizophrenia. However heterozygous CNTNAP2 mutations are also common in the normal population. Conversely, homozygous mutations are rare and have not been found in unaffected individuals.nnCase presentationWe describe a consanguineous family carrying a deletion in CNTNAP2 predicted to abolish function of its protein product, CASPR2. Affected family members show epilepsy, facial dysmorphisms, severe intellectual disability and impaired language. We compared these patients with previously reported individuals carrying homozygous mutations in CNTNAP2 and identified a highly recognisable phenotype.nnConclusionsWe propose that CASPR2 loss produces a syndrome involving early-onset refractory epilepsy, intellectual disability, language impairment and autistic features that can be recognized as CASPR2 deficiency disorder. Further screening for homozygous patients meeting these criteria, together with detailed phenotypic investigations will be crucial for understanding the contribution of CNTNAP2 to normal and disrupted development.
]]></description>
<dc:creator>Pedro Rodenas-Cuadrado</dc:creator>
<dc:creator>Nicola Pietrafusa</dc:creator>
<dc:creator>Teresa Francavilla</dc:creator>
<dc:creator>Angela La Neve</dc:creator>
<dc:creator>Pasquale Striano</dc:creator>
<dc:creator>Sonja Vernes</dc:creator>
<dc:creator></dc:creator>
<dc:date>2015-12-20</dc:date>
<dc:identifier>doi:10.1101/034363</dc:identifier>
<dc:title><![CDATA[Characterisation of CASPR2 deficiency disorder - a syndrome involving autism, epilepsy and language impairment]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2015-12-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/028316v1?rss=1">
<title>
<![CDATA[
Inferred Model of the Prefrontal Cortex Activity Unveils Cell Assemblies and Memory Replay 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/028316v1?rss=1"
</link>
<description><![CDATA[
Cell assemblies are thought to be the units of information representation in the brain, yet their detection from experimental data is arduous. Here, we propose to infer effective coupling networks and model distributions for the activity of simultaneously recorded neurons in prefrontal cortex, during the performance of a decision-making task, and during preceding and following sleep epochs. Our approach, inspired from statistical physics, allows us to define putative cell assemblies as the groups of co-activated neurons in the models of the three recorded epochs. It reveals the existence of task-related changes of the effective couplings between the sleep epochs. The assemblies which strongly coactivate during the task epoch are found to replay during subsequent sleep, in correspondence to the changes of the inferred network. Across sessions, a variety of different network scenarios is observed, providing insight in cell assembly formation and replay.nnAuthor SummaryMemories are thought to be represented in the brain through groups of coactivating neurons, the so-called cell assemblies. We propose an approach to identify cell assemblies from multi-electrode recordings of neural activity in vivo, and apply it to the prefrontal cortex activity of a behaving rat. Our statistical physics inspired approach consists in inferring effective interactions between the recorded cells, which reproduce the correlations in their spiking activities. The analysis of the effective interaction networks and of the model distributions allows us to identify cell assemblies, which strongly co-activate when the rat is learning, and also during subsequent sleep. Our approach is thus capable of providing detailed insights in cell-assembly formation and replay, crucial for memory consolidation.
]]></description>
<dc:creator>Gaia Tavoni</dc:creator>
<dc:creator>Ulisse Ferrari</dc:creator>
<dc:creator>Francesco Paolo Battaglia</dc:creator>
<dc:creator>Simona Cocco</dc:creator>
<dc:creator>Rémi Monasson</dc:creator>
<dc:creator></dc:creator>
<dc:date>2015-10-03</dc:date>
<dc:identifier>doi:10.1101/028316</dc:identifier>
<dc:title><![CDATA[Inferred Model of the Prefrontal Cortex Activity Unveils Cell Assemblies and Memory Replay]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2015-10-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/021055v1?rss=1">
<title>
<![CDATA[
Stimulus induced visual cortical networks are recapitulated by spontaneous local and inter-areal synchronization 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/021055v1?rss=1"
</link>
<description><![CDATA[
Intrinsic covariation of brain activity has been studied across many levels of brain organization. Between visual areas, neuronal activity covaries primarily among portions with similar retinotopic selectivity. We hypothesized that spontaneous inter-areal co-activation is subserved by neuronal synchronization. We performed simultaneous high-density electrocorticographic recordings across several visual areas in awake monkeys to investigate spatial patterns of local and inter-areal synchronization. We show that stimulation-induced patterns of inter-areal co-activation were reactivated in the absence of stimulation. Reactivation occurred through both, inter-areal co-fluctuation of local activity and inter-areal phase synchronization. Furthermore, the trial-by-trial covariance of the induced responses recapitulated the pattern of inter-areal coupling observed during stimulation, i.e. the signal correlation. Reactivation-related synchronization showed distinct peaks in the theta, alpha and gamma frequency bands. During passive states, this rhythmic reactivation was augmented by specific patterns of arrhythmic correspondence. These results suggest that networks of intrinsic covariation observed at multiple levels and with several recording techniques are related to synchronization and that behavioral state may affect the structure of intrinsic dynamics.
]]></description>
<dc:creator>Christopher Lewis</dc:creator>
<dc:creator>Conrado Bosmann</dc:creator>
<dc:creator>Thilo Womelsdorf</dc:creator>
<dc:creator>Pascal Fries</dc:creator>
<dc:creator></dc:creator>
<dc:date>2015-06-16</dc:date>
<dc:identifier>doi:10.1101/021055</dc:identifier>
<dc:title><![CDATA[Stimulus induced visual cortical networks are recapitulated by spontaneous local and inter-areal synchronization]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2015-06-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/004804v1?rss=1">
<title>
<![CDATA[
Visual areas exert feedforward and feedback influences through distinct frequency channels 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/004804v1?rss=1"
</link>
<description><![CDATA[
Visual cortical areas are thought to form a hierarchy and to subserve cognitive functions by interacting in both feedforward and feedback directions. While feedforward influences convey sensory signals, feedback influences modulate brain responses to a given sensory stimulus according to the current behavioural context. Many studies have demonstrated effects of feedback influences on feedforward driven responses and on behaviour. Also, anatomical projections in both directions have been identified. However, although these studies have revealed the anatomical paths and the neurophysiological consequences of influences in both directions, the neurophysiological mechanisms through which these influences are exerted remain largely elusive. Here we show that in the primate visual system, feedforward influences are carried by theta-band (~4 Hz) and gamma-band (~60-80 Hz) synchronization, and feedback influences by beta-band (~14-18 Hz) synchronization. These frequency-specific asymmetries in directed influences were revealed by simultaneous local field potential recordings from eight visual areas and an analysis of Granger-causal influences across all 28 pairs of areas. The asymmetries in directed influences correlated directly with asymmetries in anatomy and enabled us to build a visual cortical hierarchy from the influence asymmetries alone. Across different task periods, most areas stayed at their hierarchical position, whereas particularly frontal areas moved dynamically. Our results demonstrate that feedforward and feedback signalling use different frequency channels, which might subserve their differential communication requirements and lead to differential local consequences. The possibility to infer hierarchical relationships through functional data alone might make it possible to derive a cortical hierarchy in the living human brain.
]]></description>
<dc:creator>Andre M Bastos</dc:creator>
<dc:creator>Julien Vezoli</dc:creator>
<dc:creator>Conrado A Bosman</dc:creator>
<dc:creator>Jan-Mathijs Schoffelen</dc:creator>
<dc:creator>Robert Oostenveld</dc:creator>
<dc:creator>Jarrod R Dowdall</dc:creator>
<dc:creator>Peter De Weerd</dc:creator>
<dc:creator>Henry Kennedy</dc:creator>
<dc:creator>Pascal Fries</dc:creator>
<dc:creator></dc:creator>
<dc:date>2014-05-06</dc:date>
<dc:identifier>doi:10.1101/004804</dc:identifier>
<dc:title><![CDATA[Visual areas exert feedforward and feedback influences through distinct frequency channels]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2014-05-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.05.20.106666v1?rss=1">
<title>
<![CDATA[
Arterial blood contrast (ABC) enabled by magnetization transfer (MT): a novel MRI technique for enhancing the measurement of brain activation changes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.05.20.106666v1?rss=1"
</link>
<description><![CDATA[
Functional brain imaging in humans is almost exclusively performed using blood oxygenation level dependent (BOLD) contrast. This typically requires a period of tens of milliseconds after excitation of the spin system to achieve maximum contrast, leading to inefficient use of acquisition time, reduced image quality, and inhomogeneous sensitivity throughout the cortex. We utilise magnetisation transfer to suppress the signal differentially from grey matter relative to blood so that the local increase in blood volume associated with brain activation (mainly occurring in the arterioles and capillaries) will increase the measured signal. Arterial blood contrast (ABC) is additive to the residual BOLD effect, but will have its maximum value at the time of excitation. We measured brain activation using combined ABC and residual BOLD contrast at different times post-excitation and compared this to BOLD data acquired under otherwise identical conditions. We conclude that using ABC and measuring shortly after excitation gives comparable sensitivity to standard BOLD but will provide greater efficiency, spatial specificity, improved image quality, and lower inter-subject variability. ABC offers new perspectives for performing functional MRI.
]]></description>
<dc:creator>Schulz, J.</dc:creator>
<dc:creator>Fazal, Z.</dc:creator>
<dc:creator>Metere, R.</dc:creator>
<dc:creator>Marques, J.</dc:creator>
<dc:creator>Norris, D.</dc:creator>
<dc:date>2020-05-23</dc:date>
<dc:identifier>doi:10.1101/2020.05.20.106666</dc:identifier>
<dc:title><![CDATA[Arterial blood contrast (ABC) enabled by magnetization transfer (MT): a novel MRI technique for enhancing the measurement of brain activation changes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-05-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.05.22.110833v1?rss=1">
<title>
<![CDATA[
Towards complete and error-free genome assemblies of all vertebrate species 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.05.22.110833v1?rss=1"
</link>
<description><![CDATA[
High-quality and complete reference genome assemblies are fundamental for the application of genomics to biology, disease, and biodiversity conservation. However, such assemblies are only available for a few non-microbial species1-4. To address this issue, the international Genome 10K (G10K) consortium5,6 has worked over a five-year period to evaluate and develop cost-effective methods for assembling the most accurate and complete reference genomes to date. Here we summarize these developments, introduce a set of quality standards, and present lessons learned from sequencing and assembling 16 species representing major vertebrate lineages (mammals, birds, reptiles, amphibians, teleost fishes and cartilaginous fishes). We confirm that long-read sequencing technologies are essential for maximizing genome quality and that unresolved complex repeats and haplotype heterozygosity are major sources of error in assemblies. Our new assemblies identify and correct substantial errors in some of the best historical reference genomes. Adopting these lessons, we have embarked on the Vertebrate Genomes Project (VGP), an effort to generate high-quality, complete reference genomes for all ~70,000 extant vertebrate species and help enable a new era of discovery across the life sciences.
]]></description>
<dc:creator>Rhie, A.</dc:creator>
<dc:creator>McCarthy, S. A.</dc:creator>
<dc:creator>Fedrigo, O.</dc:creator>
<dc:creator>Damas, J.</dc:creator>
<dc:creator>Formenti, G.</dc:creator>
<dc:creator>Koren, S.</dc:creator>
<dc:creator>Uliano-Silva, M.</dc:creator>
<dc:creator>Chow, W.</dc:creator>
<dc:creator>Fungtammasan, A.</dc:creator>
<dc:creator>Gedman, G. L.</dc:creator>
<dc:creator>Cantin, L. J.</dc:creator>
<dc:creator>Thibaud-Nissen, F.</dc:creator>
<dc:creator>Haggerty, L.</dc:creator>
<dc:creator>Lee, C.</dc:creator>
<dc:creator>Ko, B. J.</dc:creator>
<dc:creator>Kim, J.</dc:creator>
<dc:creator>Bista, I.</dc:creator>
<dc:creator>Smith, M.</dc:creator>
<dc:creator>Haase, B.</dc:creator>
<dc:creator>Mountcastle, J.</dc:creator>
<dc:creator>Winkler, S.</dc:creator>
<dc:creator>Paez, S.</dc:creator>
<dc:creator>Howard, J.</dc:creator>
<dc:creator>Vernes, S. C.</dc:creator>
<dc:creator>Lama, T. M.</dc:creator>
<dc:creator>Grutzner, F. C.</dc:creator>
<dc:creator>Warren, W. C.</dc:creator>
<dc:creator>Balakrishnan, C.</dc:creator>
<dc:creator>Burt, D.</dc:creator>
<dc:creator>George, J. M.</dc:creator>
<dc:creator>Biegler, M.</dc:creator>
<dc:creator>Iorns, D.</dc:creator>
<dc:creator>Digby, A.</dc:creator>
<dc:creator>Eason, D.</dc:creator>
<dc:creator>Edwards, T.</dc:creator>
<dc:creator>Wilkinson, M.</dc:creator>
<dc:creator>Turner, G. F.</dc:creator>
<dc:creator>Meyer, A.</dc:creator>
<dc:creator>Kautt, A. F.</dc:creator>
<dc:creator>Franchini, P.</dc:creator>
<dc:creator>Detrich, H. W.</dc:creator>
<dc:creator>Svardal, H.</dc:creator>
<dc:creator>Wagner, M.</dc:creator>
<dc:creator>Naylor, G. J. P.</dc:creator>
<dc:creator>Pippel, M</dc:creator>
<dc:date>2020-05-23</dc:date>
<dc:identifier>doi:10.1101/2020.05.22.110833</dc:identifier>
<dc:title><![CDATA[Towards complete and error-free genome assemblies of all vertebrate species]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-05-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.05.20.106070v1?rss=1">
<title>
<![CDATA[
Contextual and spatial associations between objects interactively modulate visual processing 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.05.20.106070v1?rss=1"
</link>
<description><![CDATA[
Much of what we know about object recognition arises from the study of isolated objects. In the real world, however, we commonly encounter groups of contextually-associated objects (e.g., teacup, saucer), often in stereotypical spatial configurations (e.g., teacup above saucer). Here we used EEG to test whether identity-based associations between objects (e.g., teacup-saucer vs. teacup-stapler) are encoded jointly with their typical relative positioning (e.g., teacup above saucer vs. below saucer). Observers viewed a 2.5Hz image stream of contextually-associated object pairs intermixed with non-associated pairs as every fourth image. The differential response to non-associated pairs (measurable at 0.625Hz in 28/37 participants), served as an index of contextual integration, reflecting the association of object identities in each pair. Over right occipitotemporal sites, this signal was larger for typically-positioned object streams, indicating that spatial configuration facilitated the extraction of the objects contextual association. This high-level influence of spatial configuration on object identity integration arose [~]320ms post stimulus onset, with lower-level perceptual grouping (shared with inverted displays) present at [~]130ms. These results demonstrate that contextual and spatial associations between objects interactively influence object processing. We interpret these findings as reflecting the high-level perceptual grouping of objects that frequently co-occur in highly stereotyped relative positions.
]]></description>
<dc:creator>Quek, G. L.</dc:creator>
<dc:creator>Peelen, M. V.</dc:creator>
<dc:date>2020-05-22</dc:date>
<dc:identifier>doi:10.1101/2020.05.20.106070</dc:identifier>
<dc:title><![CDATA[Contextual and spatial associations between objects interactively modulate visual processing]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-05-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.05.21.094912v1?rss=1">
<title>
<![CDATA[
Comparison of induced neurons reveals slower structural and functional maturation in humans than in apes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.05.21.094912v1?rss=1"
</link>
<description><![CDATA[
We generated induced excitatory sensory neurons (iNeurons, iNs) from chimpanzee, bonobo and human stem cells by expressing the transcription factor neurogenin-2 (NGN2). Single cell-RNA sequencing showed that genes involved in dendrite and synapse development are expressed earlier during iNs maturation in the chimpanzee than the human cells. In accordance, during the first two weeks of differentiation, chimpanzee and bonobo iNs showed repetitive action potentials and more spontaneous excitatory activity than human iNs, and extended neurites of higher total length. However, the axons of human iNs were slightly longer at 5 weeks of differentiation. The timing of the establishment of neuronal polarity did not differ between the species. Chimpanzee, bonobo and human neurites eventually reached the same level of structural complexity. Thus, human iNs develop slower than chimpanzee and bonobo iNs and this difference in timing likely depends on functions downstream of NGN2.
]]></description>
<dc:creator>Schoernig, M.</dc:creator>
<dc:creator>Ju, X.</dc:creator>
<dc:creator>Fast, L.</dc:creator>
<dc:creator>Weigert, A.</dc:creator>
<dc:creator>Schaffer, T.</dc:creator>
<dc:creator>Ebert, S.</dc:creator>
<dc:creator>Treutlein, B.</dc:creator>
<dc:creator>Nadif Kasri, N.</dc:creator>
<dc:creator>Peter, B.</dc:creator>
<dc:creator>Hevers, W.</dc:creator>
<dc:creator>Taverna, E.</dc:creator>
<dc:date>2020-05-24</dc:date>
<dc:identifier>doi:10.1101/2020.05.21.094912</dc:identifier>
<dc:title><![CDATA[Comparison of induced neurons reveals slower structural and functional maturation in humans than in apes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-05-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/496117v1?rss=1">
<title>
<![CDATA[
Not Just A Number: Age-Related Modulations of Oscillatory Patterns Underlying Top-Down and Bottom-Up Attention. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/496117v1?rss=1"
</link>
<description><![CDATA[
Attention operates through top-down (TD) and bottom-up (BU) mechanisms. Recently, it has been shown that slow (alpha) frequencies index facilitatory and suppressive mechanisms of TD attention and faster (gamma) frequencies signal BU attentional capture. Ageing is characterized by increased behavioral distractibility, resulting from either a reduced efficiency of TD attention or an enhanced triggering of BU attention. However, only few studies have investigated the impact of ageing upon the oscillatory activities involved in TD and BU attention. MEG data were collected from 14 elderly and 14 matched young healthy human participants while performing the Competitive Attention Task. Elderly participants displayed (1) exacerbated behavioral distractibility, (2) altered TD suppressive mechanisms, indexed by a reduced alpha synchronization in task-irrelevant regions, (3) less prominent alpha peak-frequency differences between cortical regions, (4) a similar BU system activation indexed by gamma activity, and (5) a reduced activation of lateral prefrontal inhibitory control regions. These results show that the ageing-related increased distractibility is of TD origin.
]]></description>
<dc:creator>ElShafei, H.</dc:creator>
<dc:creator>Fornoni, L.</dc:creator>
<dc:creator>Bertrand, O.</dc:creator>
<dc:creator>Bidet-Caulet, A.</dc:creator>
<dc:date>2018-12-13</dc:date>
<dc:identifier>doi:10.1101/496117</dc:identifier>
<dc:title><![CDATA[Not Just A Number: Age-Related Modulations of Oscillatory Patterns Underlying Top-Down and Bottom-Up Attention.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2018-12-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.05.26.113324v1?rss=1">
<title>
<![CDATA[
Dynamics of mutual inhibition between two visual cortical neurons compared to human perceptual competition 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.05.26.113324v1?rss=1"
</link>
<description><![CDATA[
Neural competition plays an essential role in active selection processes of noisy and ambiguous input signals and it is assumed to underlie emergent properties of brain functioning such as perceptual organization and decision making. Despite ample theoretical research on neural competition, experimental tools to allow neurophysiological investigation of competing neurons have not been available. We developed a "hybrid" system where real-life neurons and a computer-simulated neural circuit interacted. It enabled us to construct a mutual inhibition circuit between two real life pyramidal neurons. We then asked what dynamics this minimal unit of neural competition exhibits and compared them to the known behavioral-level dynamics of neural competition. We found that the pair of neurons shows bi-stability when activated simultaneously by current injections. The addition of modelled noise and changes in the activation strength showed that the dynamics of the circuit are strikingly similar to the known properties of bi-stable visual perception.
]]></description>
<dc:creator>Kogo, N.</dc:creator>
<dc:creator>Kern, F. B.</dc:creator>
<dc:creator>Nowotny, T.</dc:creator>
<dc:creator>van Ee, R.</dc:creator>
<dc:creator>van Wezel, R.</dc:creator>
<dc:creator>Aihara, T.</dc:creator>
<dc:date>2020-05-27</dc:date>
<dc:identifier>doi:10.1101/2020.05.26.113324</dc:identifier>
<dc:title><![CDATA[Dynamics of mutual inhibition between two visual cortical neurons compared to human perceptual competition]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-05-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.05.28.121137v1?rss=1">
<title>
<![CDATA[
Overlapping connectivity gradients in the anterior temporal lobe underlie semantic cognition 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.05.28.121137v1?rss=1"
</link>
<description><![CDATA[
Convergent evidence from neuroimaging, computational, and clinical research has shown that the anterior temporal lobe (ATL) is critically involved in two key aspects of semantic cognition: the representation of semantic knowledge, and the executive regulation of this knowledge. Both are necessary for integrating features to understand concepts, and to integrate concepts to understand discourse. Here, we tested the hypothesis that these differential aspects of integration map onto different patterns of ATL connectivity. Specifically, we hypothesized that there are two overlapping modes of functional connectivity of the ATL that each predict distinct aspects of semantic cognition on an individual level. We used a novel analytical approach (connectopic mapping) to identify the first two dominant modes connection topographies (i.e. maps of spatially varying connectivity) in the ATL in 766 participants (Human Connectome Project), and summarized these into 16 parameters that reflect inter-individual differences in their functional organization. If these connection topographies reflect the ATLs functional multiplicity, then we would expect to find a dissociation where one mode (but not the other) correlates with cross-modal matching of verbal and visual information (picture vocabulary naming), and the other (but not the former) correlates with how quickly and accurately relevant semantic information is retrieved (story comprehension). Our analysis revealed a gradient of spatially varying connectivity along the inferior-superior axis, and secondly, an anterior to posterior gradient. Multiple regression analyses revealed a double dissociation such that individual differences in the inferior-superior gradient are predictive of differences in story comprehension, whereas the anterior-posterior gradient maps onto differences in picture vocabulary naming, but not vice versa. These findings indicate that overlapping gradients of functional connectivity in the ATL are related to differential behaviors, which is important for understanding how its functional organization underlies its multiple functions.
]]></description>
<dc:creator>Faber, M.</dc:creator>
<dc:creator>Przezdzik, I.</dc:creator>
<dc:creator>Fernandez, G.</dc:creator>
<dc:creator>Haak, K. V.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:date>2020-05-30</dc:date>
<dc:identifier>doi:10.1101/2020.05.28.121137</dc:identifier>
<dc:title><![CDATA[Overlapping connectivity gradients in the anterior temporal lobe underlie semantic cognition]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-05-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.05.07.082743v1?rss=1">
<title>
<![CDATA[
Diverse deep neural networks all predict human IT well, after training and fitting 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.05.07.082743v1?rss=1"
</link>
<description><![CDATA[
Deep neural networks (DNNs) trained on object recognition provide the best current models of high-level visual areas in the brain. What remains unclear is how strongly network design choices, such as architecture, task training, and subsequent fitting to brain data contribute to the observed similarities. Here we compare a diverse set of nine DNN architectures on their ability to explain the representational geometry of 62 isolated object images in human inferior temporal (hIT) cortex, as measured with functional magnetic resonance imaging. We compare untrained networks to their task-trained counterparts, and assess the effect of fitting them to hIT using a cross-validation procedure. To best explain hIT, we fit a weighted combination of the principal components of the features within each layer, and subsequently a weighted combination of layers. We test all models across all stages of training and fitting for their correlation with the hIT representational dissimilarity matrix (RDM) using an independent set of images and subjects. We find that trained models significantly outperform untrained models (accounting for 57% more of the explainable variance), suggesting that features representing natural images are important for explaining hIT. Model fitting further improves the alignment of DNN and hIT representations (by 124%), suggesting that the relative prevalence of different features in hIT does not readily emerge from the particular ImageNet object-recognition task used to train the networks. Finally, all DNN architectures tested achieved equivalent high performance once trained and fitted. Similar ability to explain hIT representations appears to be shared among deep feedforward hierarchies of nonlinear features with spatially restricted receptive fields.
]]></description>
<dc:creator>Storrs, K. R.</dc:creator>
<dc:creator>Kietzmann, T. C.</dc:creator>
<dc:creator>Walther, A.</dc:creator>
<dc:creator>Mehrer, J.</dc:creator>
<dc:creator>Kriegeskorte, N.</dc:creator>
<dc:date>2020-05-08</dc:date>
<dc:identifier>doi:10.1101/2020.05.07.082743</dc:identifier>
<dc:title><![CDATA[Diverse deep neural networks all predict human IT well, after training and fitting]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-05-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.03.131573v1?rss=1">
<title>
<![CDATA[
A geometry of spike sequences: Fast, unsupervised discovery of high-dimensional neural spiking patterns based on optimal transport theory 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.03.131573v1?rss=1"
</link>
<description><![CDATA[
Neural coding and memory formation depend on temporal spiking sequences that span high-dimensional neural ensembles. The unsupervised discovery and characterization of these spiking sequences requires a suitable dissimilarity measure to spiking patterns, which can then be used for clustering and decoding. Here, we present a new dissimilarity measure based on optimal transport theory called SpikeShip, which compares multineuron spiking patterns based on all the relative spike-timing relationships among neurons. SpikeShip computes the optimal transport cost to make all the relative spike-timing relationships (across neurons) identical between two spiking patterns. We show that this transport cost can be decomposed into a temporal rigid translation term, which captures global latency shifts, and a vector of neuron-specific transport flows, which reflect inter-neuronal spike timing differences. SpikeShip can be effectively computed for high-dimensional neuronal ensembles, has a low (linear) computational cost that has the same order as the spike count, and is sensitive to higher-order correlations. Furthermore SpikeShip is binless, can handle any form of spike time distributions, is not affected by firing rate fluctuations, can detect patterns with a low signal-to-noise ratio, and can be effectively combined with a sliding window approach. We compare the advantages and differences between SpikeShip and other measures like SPIKE and Victor-Purpura distance. We applied SpikeShip to large-scale Neuropixel recordings during spontaneous activity and visual encoding. We show that high-dimensional spiking sequences detected via SpikeShip reliably distinguish between different natural images and different behavioral states. These spiking sequences carried complementary information to conventional firing rate codes. SpikeShip opens new avenues for studying neural coding and memory consolidation by rapid and unsupervised detection of temporal spiking patterns in high-dimensional neural ensembles.
]]></description>
<dc:creator>Sotomayor-Gomez, B.</dc:creator>
<dc:creator>Battaglia, F. P.</dc:creator>
<dc:creator>Vinck, M.</dc:creator>
<dc:date>2020-06-04</dc:date>
<dc:identifier>doi:10.1101/2020.06.03.131573</dc:identifier>
<dc:title><![CDATA[A geometry of spike sequences: Fast, unsupervised discovery of high-dimensional neural spiking patterns based on optimal transport theory]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.04.129569v1?rss=1">
<title>
<![CDATA[
Improving emotional-action control by targeting long-range phase-amplitude neuronal coupling. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.04.129569v1?rss=1"
</link>
<description><![CDATA[
Control over emotional action tendencies is essential for every-day interactions. This cognitive function can fail during socially challenging situations, and is chronically attenuated in social psychopathologies such as social anxiety and aggression. Previous studies have shown that control over social-emotional action tendencies depends on phase-amplitude coupling between prefrontal theta-band (6 Hz) rhythmic activity and broadband gamma-band activity in sensorimotor areas. Here, we delivered dual-site phase-coupled brain stimulation to facilitate theta-gamma phase-amplitude coupling between frontal regions known to implement that form of control, while participants were challenged to control their automatic action tendencies in a social-emotional approach/avoidance-task. Participants had increased control over their emotional action tendencies, depending on the relative phase and dose of the intervention. Concurrently measured fMRI effects of task and stimulation, and estimated changes in effective connectivity, indicated that the intervention improved control by increasing the efficacy of anterior prefrontal inhibition over sensorimotor cortex. This enhancement of emotional action control provides causal evidence for a phase-amplitude coupling mechanism guiding action selection during emotional-action control. More generally, the finding illustrates the potential of physiologically-grounded interventions aimed at reducing neural noise in cerebral circuits where communication relies on phase-amplitude coupling.
]]></description>
<dc:creator>Bramson, B.</dc:creator>
<dc:creator>den Ouden, H.</dc:creator>
<dc:creator>Toni, I.</dc:creator>
<dc:creator>Roelofs, K.</dc:creator>
<dc:date>2020-06-05</dc:date>
<dc:identifier>doi:10.1101/2020.06.04.129569</dc:identifier>
<dc:title><![CDATA[Improving emotional-action control by targeting long-range phase-amplitude neuronal coupling.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.06.137976v1?rss=1">
<title>
<![CDATA[
Striatal dopamine synthesis capacity reflects smartphone social activity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.06.137976v1?rss=1"
</link>
<description><![CDATA[
Striatal dopamine has been implicated in social behavior across humans, rodents, and non-human primates in artificial laboratory settings with highly-practiced tasks and fixed reward contingencies. Whether striatal dopamine drives naturalistic, spontaneous social behavior remains unclear. Here, we leverage day-to-day logs of unconstrained smartphone behavior and establish a novel link between smartphone social activity and individual differences in striatal dopamine synthesis capacity using [18F]-DOPA PET in (N=22) healthy adult humans. We find a strong relationship such that a higher proportion of social app interactions correlates with lower dopamine synthesis capacity in the bi-lateral putamen. Permutation tests and penalized regressions provide evidence that this link between dopamine synthesis capacity and social versus non-social smartphone taps is specific. These observations provide a key empirical grounding for current speculations about dopamines role in digital social behavior.
]]></description>
<dc:creator>Westbrook, A.</dc:creator>
<dc:creator>Ghosh, A.</dc:creator>
<dc:creator>van den Bosch, R.</dc:creator>
<dc:creator>Cools, R.</dc:creator>
<dc:date>2020-06-08</dc:date>
<dc:identifier>doi:10.1101/2020.06.06.137976</dc:identifier>
<dc:title><![CDATA[Striatal dopamine synthesis capacity reflects smartphone social activity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.08.139923v1?rss=1">
<title>
<![CDATA[
Amount of fiction reading correlates with higher connectivity between cortical areas for language and mentalizing 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.08.139923v1?rss=1"
</link>
<description><![CDATA[
Behavioral evidence suggests that engaging with fiction is positively correlated with social abilities. The rationale behind this link is that engaging with fiction and fictional characters may offer a  training mode for mentalizing and empathizing with sentient agents in the real world, analogous to a flight simulator for pilots. In this study, we explored the relationship between reading fiction and mentalizing by looking at brain network dynamics in 57 participants who varied on how much fiction they read in their daily lives. The hypothesis was that if reading fiction indeed trains mentalizing, a task that requires mentalizing -Like immersing in a fictional story and engaging with a protagonist-should elicit differences in brain network dynamics depending on how much people read. More specifically, more frequent readers should show increased connectivity within the theory of mind network (ToM) or between the ToM network and other brain networks. While brain activation was measured with fMRI, participants listened to two literary narratives. We computed time-course correlations between brain regions and compared the correlation values from listening to narratives to listening to an auditory baseline condition. The between-region correlations were then related to individual differences measures including the amount of fiction that participants consume in their daily lives. Our results show that there is a linear relationship between how much people read and the functional connectivity in areas known to be involved in language and mentalizing. This adds neurobiological credibility to the  fiction influences mentalizing abilities hypothesis as suggested on the basis of conceptual analysis.
]]></description>
<dc:creator>Hartung, F.</dc:creator>
<dc:creator>Willems, R. M.</dc:creator>
<dc:date>2020-06-09</dc:date>
<dc:identifier>doi:10.1101/2020.06.08.139923</dc:identifier>
<dc:title><![CDATA[Amount of fiction reading correlates with higher connectivity between cortical areas for language and mentalizing]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.10.142398v1?rss=1">
<title>
<![CDATA[
Entraining corticocortical plasticity changes oscillatory activity in action control and inhibition 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.10.142398v1?rss=1"
</link>
<description><![CDATA[
Oscillatory activity may reflect interactions between brain areas[1]. Here we tested whether inducing corticocortical plasticity in a specific set of connections changes oscillatory activity and cortico-cortical interactions and, if this is the case, whether the changes manifest in a manner that is behaviour state-dependent. We either increased or decreased the influence of activity in human ventral premotor cortex (PMv) over activity in primary motor cortex (M1) using cortico-cortical paired associative stimulation (ccPAS)[2, 3]. Before and after stimulation participants performed a Go/No-Go task. While M1 TMS pulses revealed the excitatory state of the motor system at specific time points, the electroencephalogram (EEG) revealed the evolution of oscillatory activity dynamics in the motor system over several hundreds of milliseconds before, during, and after each movement. Augmenting cortical connectivity between PMv and M1, by evoking synchronous pre- and postsynaptic activity in the PMv-M1 pathways, led to a state-dependent modulation of the causal influence of PMv over M1, and at the same time, enhanced oscillatory beta and theta rhythms in Go and No-Go trials, respectively. No changes were observed in the alpha rhythm. The plasticity induction effect was dependent on PMv-M1 stimulation order; the opposite patterns of results were observed after an equal amount of stimulation of PMv and M1 but applied in a temporal pattern that did not augment PMvs influence over M1. These results are consistent with Hebbian principles of synaptic plasticity[4] and show that artificial manipulation of cortico-cortical connectivity produces state-dependent functional changes in the spectral fingerprints of the motor circuit.
]]></description>
<dc:creator>Sel, A.</dc:creator>
<dc:creator>Verhagen, L.</dc:creator>
<dc:creator>Angerer, K.</dc:creator>
<dc:creator>David, R.</dc:creator>
<dc:creator>Klein-Flugge, M.</dc:creator>
<dc:creator>Rushworth, M. F.</dc:creator>
<dc:date>2020-06-11</dc:date>
<dc:identifier>doi:10.1101/2020.06.10.142398</dc:identifier>
<dc:title><![CDATA[Entraining corticocortical plasticity changes oscillatory activity in action control and inhibition]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.09.142471v1?rss=1">
<title>
<![CDATA[
Towards robust and replicable sex differences in the intrinsic brain function of autism 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.09.142471v1?rss=1"
</link>
<description><![CDATA[
BackgroundMarked sex differences in autism prevalence accentuate the need to understand the role of biological sex-related factors in autism. Efforts to unravel sex differences in the brain organization of autism have, however, been challenged by the limited availability of female data.

MethodsWe addressed this gap by using a large sample of males and females with autism and neurotypical (NT) control individuals (ABIDE; Autism: 362 males, 82 females; NT: 409 males, 166 females; 7-18 years). Discovery analyses examined main effects of diagnosis, sex and their interaction across five resting-state fMRI (R-fMRI) metrics (voxel-level Z > 3.1, cluster-level P < 0.01, gaussian random field corrected). Secondary analyses assessed the robustness of the results to different pre-processing approaches and their replicability in two independent samples: the EU-AIMS Longitudinal European Autism Project (LEAP) and the Gender Explorations of Neurogenetics and Development to Advance Autism Research (GENDAAR).

ResultsDiscovery analyses in ABIDE revealed significant main effects across the intrinsic functional connectivity (iFC) of the posterior cingulate cortex, regional homogeneity and voxel-mirrored homotopic connectivity (VMHC) in several cortical regions, largely converging in the default network midline. Sex-by-diagnosis interactions were confined to the dorsolateral occipital cortex, with reduced VMHC in females with autism. All findings were robust to different pre-processing steps. Replicability in independent samples varied by R-fMRI measures and effects with the targeted sex-by-diagnosis interaction being replicated in the larger of the two replication samples - EU-AIMS LEAP.

LimitationsGiven the lack of a priori harmonization among the discovery and replication datasets available to date, sample-related variation remained and may have affected replicability.

ConclusionsAtypical cross-hemispheric interactions are neurobiologically relevant to autism. They likely result from the combination of sex-dependent and sex-independent factors with a differential effect across functional cortical networks. Systematic assessments of the factors contributing to replicability are needed and necessitate coordinated large-scale data collection across studies.
]]></description>
<dc:creator>Floris, D. L.</dc:creator>
<dc:creator>Filho, J. O. A.</dc:creator>
<dc:creator>Lai, M.-C.</dc:creator>
<dc:creator>Giavasis, S.</dc:creator>
<dc:creator>Oldehinkel, M.</dc:creator>
<dc:creator>Mennes, M.</dc:creator>
<dc:creator>Charman, T.</dc:creator>
<dc:creator>Tillmann, J.</dc:creator>
<dc:creator>Dumas, G.</dc:creator>
<dc:creator>Ecker, C.</dc:creator>
<dc:creator>Dell'Acqua, F.</dc:creator>
<dc:creator>Banaschewski, T.</dc:creator>
<dc:creator>Moessnang, C.</dc:creator>
<dc:creator>Baron-Cohen, S.</dc:creator>
<dc:creator>Durston, S.</dc:creator>
<dc:creator>Loth, E.</dc:creator>
<dc:creator>Murphy, D. G.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Beckmann, C.</dc:creator>
<dc:creator>Milham, M.</dc:creator>
<dc:creator>Di Martino, A.</dc:creator>
<dc:date>2020-06-11</dc:date>
<dc:identifier>doi:10.1101/2020.06.09.142471</dc:identifier>
<dc:title><![CDATA[Towards robust and replicable sex differences in the intrinsic brain function of autism]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.09.142695v1?rss=1">
<title>
<![CDATA[
Causal evidence of network communication in whole-brain dynamics through a multiplexed neural code 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.09.142695v1?rss=1"
</link>
<description><![CDATA[
An important question in neuroscience is how local activity can be flexibly and selectively routed across the brain network. A proposed mechanism to flexibly route information is frequency division multiplexing: selective readout can be achieved by segregating the signal into non-overlapping frequency bands. Here, in wild-type mice and in a transgenic model (3xTgAD) of Alzheimers Disease (AD), we use optogenetic activation of the entorhinal cortex, concurrent whole-brain fMRI, and hidden Markov modeling. We demonstrate how inducing neuronal spiking with different theta frequencies causes spatially distinct states of brain network dynamics to emerge and to preferentially respond to one frequency, showing how selective information streams can arise from a single neuronal source of activity. This theta modulation mechanism, however, is impaired in the AD model. This work demonstrates that neuronal multiplexing is a sufficient mechanism to enable flexible brain network communication, and provides insight into the aberrant mechanisms underlying cognitive decline.
]]></description>
<dc:creator>Salvan, P.</dc:creator>
<dc:creator>Lazari, A.</dc:creator>
<dc:creator>Vidaurre, D.</dc:creator>
<dc:creator>Mandino, F.</dc:creator>
<dc:creator>Johansen-Berg, H.</dc:creator>
<dc:creator>Grandjean, J.</dc:creator>
<dc:date>2020-06-11</dc:date>
<dc:identifier>doi:10.1101/2020.06.09.142695</dc:identifier>
<dc:title><![CDATA[Causal evidence of network communication in whole-brain dynamics through a multiplexed neural code]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.12.143834v1?rss=1">
<title>
<![CDATA[
The genetic organization of subcortical volumetric change is stable throughout the lifespan 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.12.143834v1?rss=1"
</link>
<description><![CDATA[
While development and aging of the cerebral cortex show a similar topographic organization and are mainly governed by the same genes, it is unclear whether the same is true for subcortical structures, which follow fundamentally different ontogenetic and phylogenetic principles than the cerebral cortex. To test the hypothesis that genetically governed neurodevelopmental processes can be traced in subcortical structures throughout life, we analyzed a longitudinal magnetic resonance imaging dataset (n = 974, age 4-89 years), identifying five clusters of longitudinal change in development. With some exceptions, these clusters followed placement along the cranial axis in embryonic brain development, suggesting continuity in the pattern of change from prenatal stages. Developmental change patterns were conserved through the lifespan and predicted general cognitive function in an age-invariant manner. The results were replicated in longitudinal data from the Lifebrain consortium (n = 756, age 19-83 years). Genetic contributions to longitudinal brain changes were calculated from the Vietnam Era Twin Study of Aging (n = 331 male twins, age 51-60 years), revealing that distinct sets of genes tended to govern change for each developmental cluster. This finding was confirmed with single nucleotide polymorphisms and cross-sectional MRI data from the UK Biobank (n = 20,588, age 40-69), demonstrating significantly higher co-heritability among structures belonging to the same developmental clusters. Together, these results suggest that coordination of subcortical change adheres to fundamental principles of lifespan continuity, genetic organization and age-invariant relationships to cognitive function.

Significance statementHere we show that subcortical change during childhood development is organized in clusters. These clusters tend to follow the main gradient of embryonic brain development, and are stable across life. This means that subcortical regions changing together in childhood also change together throughout the rest of life, in accordance with a lifespan perspective on brain development and aging. Twin and single nucleotide polymorphism-based heritability analyses in middle-aged and older adults showed that volume and volume change of regions within each developmental cluster tended to be governed by the same sets of genes. Thus, volumetric changes across subcortical regions are tightly organized, and the coordinated change can be described in a lifespan perspective according to ontogenetic and genetic influences.
]]></description>
<dc:creator>Fjell, A.</dc:creator>
<dc:creator>Grydeland, H.</dc:creator>
<dc:creator>Wang, Y.</dc:creator>
<dc:creator>Amlien, I. K.</dc:creator>
<dc:creator>Bartres-Faz, D.</dc:creator>
<dc:creator>Brandmaier, A.</dc:creator>
<dc:creator>Duzel, S.</dc:creator>
<dc:creator>Elman, J.</dc:creator>
<dc:creator>Franz, C.</dc:creator>
<dc:creator>Haberg, A.</dc:creator>
<dc:creator>Kietzmann, T. C.</dc:creator>
<dc:creator>Kievit, R. A.</dc:creator>
<dc:creator>Kremen, W.</dc:creator>
<dc:creator>Krogsrud, S. K.</dc:creator>
<dc:creator>Kuhn, S. A.</dc:creator>
<dc:creator>Lindenberger, U.</dc:creator>
<dc:creator>Macia, D.</dc:creator>
<dc:creator>Mowinckel, A. M.</dc:creator>
<dc:creator>Nyberg, L.</dc:creator>
<dc:creator>Panizzon, M.</dc:creator>
<dc:creator>Sole-Padulles, C.</dc:creator>
<dc:creator>Sorensen, O.</dc:creator>
<dc:creator>Westerhausen, R.</dc:creator>
<dc:creator>Walhovd, K. B.</dc:creator>
<dc:date>2020-06-12</dc:date>
<dc:identifier>doi:10.1101/2020.06.12.143834</dc:identifier>
<dc:title><![CDATA[The genetic organization of subcortical volumetric change is stable throughout the lifespan]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.15.151795v1?rss=1">
<title>
<![CDATA[
Efficient population coding depends on stimulus convergence and source of noise 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.15.151795v1?rss=1"
</link>
<description><![CDATA[
Sensory organs transmit information to downstream brain circuits using a neural code comprised of spikes from multiple neurons. According to the prominent efficient coding framework, the properties of sensory populations have evolved to encode maximum information about stimuli given biophysical constraints. How information coding depends on the way sensory signals from multiple channels converge downstream is still unknown, especially in the presence of noise which corrupts the signal at different points along the pathway. Here, we calculated the optimal information transfer of a population of nonlinear neurons under two scenarios. First, a lumped-coding channel where the information from different inputs converges to a single channel, thus reducing the number of neurons. Second, an independent-coding channel when different inputs contribute independent information without convergence. In each case, we investigated information loss when the sensory signal was corrupted by two sources of noise. We determined critical noise levels at which the optimal number of distinct thresholds of individual neurons in the population changes. Comparing our system to classical physical systems, these changes correspond to first- or second-order phase transitions for the lumped- or the independent-coding channel, respectively. We relate our theoretical predictions to coding in a population of auditory nerve fibers recorded experimentally, and find signatures of efficient coding. Our results yield important insights into the diverse coding strategies used by neural populations to optimally integrate sensory stimuli in the presence of distinct sources of noise.
]]></description>
<dc:creator>Roeth, K.</dc:creator>
<dc:creator>Shao, S.</dc:creator>
<dc:creator>Gjorgjieva, J.</dc:creator>
<dc:date>2020-06-15</dc:date>
<dc:identifier>doi:10.1101/2020.06.15.151795</dc:identifier>
<dc:title><![CDATA[Efficient population coding depends on stimulus convergence and source of noise]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.15.151969v1?rss=1">
<title>
<![CDATA[
Beta2 oscillations in the hippocampal-cortical novelty detection circuit 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.15.151969v1?rss=1"
</link>
<description><![CDATA[
Novelty detection is a core feature of behavioral adaptation, and involves cascades of neuronal responses - from initial evaluation of the stimulus to the encoding of new representations - resulting in the behavioral ability to respond to unexpected inputs. In the past decade, a new important novelty detection feature, beta2 (~20 - 30 Hz) oscillations, has been described in the hippocampus. However, the interactions between beta2 and the hippocampal network are unknown, as well as the role - or even the presence - of beta2 in other areas involved with novelty detection. In this work, we used behavioral tasks that modulate novelty in combination with multisite local field potential (LFP) recordings targeting regions involved with novelty detection processing in mice - the CA1 region of the hippocampus, parietal cortex and mid-prefrontal cortex - to describe the oscillatory dynamics associated with novelty. We found that transient beta2 power increases were observed only during interaction with novel contexts and objects, but not with familiar contexts and objects. Also, robust theta-gamma phase-amplitude coupling was observed during the exploration of novel environments. Surprisingly, bursts of beta2 power had strong coupling with the phase of delta-range oscillations. Finally, the parietal and mid-frontal cortices had strong coherence with the hippocampus in both theta and beta2. These results highlight the importance of beta2 oscillations in a larger hippocampal-cortical circuit, suggesting that beta2 is a mechanism for detecting and modulating behavioral adaptation to novelty.
]]></description>
<dc:creator>Franca, A. S. C.</dc:creator>
<dc:creator>Borgegius, N.</dc:creator>
<dc:creator>Cohen, M.</dc:creator>
<dc:date>2020-06-15</dc:date>
<dc:identifier>doi:10.1101/2020.06.15.151969</dc:identifier>
<dc:title><![CDATA[Beta2 oscillations in the hippocampal-cortical novelty detection circuit]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.19.161190v1?rss=1">
<title>
<![CDATA[
Words in context: tracking context-processing during language comprehension using computational language models and MEG 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.19.161190v1?rss=1"
</link>
<description><![CDATA[
The meaning of a word depends on its lexical semantics and on the context in which it is embedded. At the basis of this lays the distinction between lexical retrieval and integration, two basic operations supporting language comprehension. In this paper, we investigate how lexical retrieval and integration are implemented in the brain by comparing MEG activity to word representations generated by computational language models. We test both non-contextualized embeddings, representing words independently from their context, and contextualized embeddings, which instead integrate contextual information in their representations. Using representational similarity analysis over cortical regions and over time, we observed that brain activity in the left anterior temporal pole and inferior frontal regions shows higher similarity with contextualized word embeddings compared to non-contextualized embeddings, between 300 and 500 ms after word presentation. On the other hand, non-contextualized word embeddings show higher similarity with brain activity in the left lateral and anterior temporal lobe at earlier latencies - areas and latencies related to lexical retrieval. Our results highlight how lexical retrieval and context integration can be tracked in the brain using word embeddings obtained with computational models. These results also suggest that the distinction between lexical retrieval and integration might be framed in terms of context-independent and contextualized representations.
]]></description>
<dc:creator>Lopopolo, A.</dc:creator>
<dc:creator>Schoffelen, J. M.</dc:creator>
<dc:creator>van den Bosch, A.</dc:creator>
<dc:creator>Willems, R. M.</dc:creator>
<dc:date>2020-06-19</dc:date>
<dc:identifier>doi:10.1101/2020.06.19.161190</dc:identifier>
<dc:title><![CDATA[Words in context: tracking context-processing during language comprehension using computational language models and MEG]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.20.162586v1?rss=1">
<title>
<![CDATA[
Low competitive status elicits aggression: behavioral and neural evidence 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.20.162586v1?rss=1"
</link>
<description><![CDATA[
Winners are commonly assumed to compete more aggressively than losers. Here, we find overwhelming evidence for the opposite. We first demonstrate that low-ranking teams commit more fouls than they receive in top-tier soccer, ice hockey, and basketball mens leagues. We replicate this effect in the laboratory, showing that male participants deliver louder sound blasts to a rival when placed in a low-status position. Using neuroimaging, we characterize brain activity patterns that encode competitive status as well as those that facilitate status-dependent aggression in healthy young men. These analyses reveal three key findings. First, anterior hippocampus and striatum contain multivariate representations of competitive status. Second, interindividual differences in status-dependent aggression are linked with a sharper status differentiation in the striatum and with greater reactivity to status-enhancing victories in the dorsal anterior cingulate cortex. Third, activity in ventromedial, ventrolateral, and dorsolateral prefrontal cortex is associated with trial-wise increases in status-dependent aggressive behavior. Taken together, our results run counter to narratives glorifying aggression in competitive situations. Rather, we show that those in the lower ranks of skill-based hierarchies are more likely to behave aggressively and identify the potential neural basis of this phenomenon.
]]></description>
<dc:creator>Buades-Rotger, M.</dc:creator>
<dc:creator>Goettlich, M.</dc:creator>
<dc:creator>Weiblen, R.</dc:creator>
<dc:creator>Petereit, P.</dc:creator>
<dc:creator>Scheidt, T.</dc:creator>
<dc:creator>Keevil, B. G.</dc:creator>
<dc:creator>Kraemer, U. M.</dc:creator>
<dc:date>2020-06-21</dc:date>
<dc:identifier>doi:10.1101/2020.06.20.162586</dc:identifier>
<dc:title><![CDATA[Low competitive status elicits aggression: behavioral and neural evidence]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.21.162628v1?rss=1">
<title>
<![CDATA[
Orbitofrontal lesion patients show an implicit approach bias to angry faces 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.21.162628v1?rss=1"
</link>
<description><![CDATA[
Damage to the ventromedial prefrontal cortex (VMPFC) can cause maladaptive social behavior, but the cognitive processes underlying these behavioral changes are still uncertain. Here, we tested whether patients with acquired VMPFC lesions show altered approach-avoidance tendencies to emotional facial expressions. Thirteen patients with focal VMPFC lesions and 31 age- and gender-matched healthy controls performed an implicit approach-avoidance task in which they either pushed or pulled a joystick depending on stimulus color. While controls avoided angry faces, VMPFC patients displayed an incongruent response pattern characterized by both increased approach and reduced avoidance of angry facial expressions. The approach bias was stronger in patients with higher self-reported impulsivity and disinhibition, and in those with larger lesions. We further used linear ballistic accumulator modelling to investigate latent parameters underlying approach-avoidance decisions. Controls displayed negative drift rates when approaching angry faces, whereas VMPFC lesions abolished this pattern. In addition, VMPFC patients had weaker response drifts than controls during avoidance. Finally, patients showed reduced drift rate variability and shorter non-decision times, indicating impulsive and rigid decision-making. Our findings thus suggest that VMPFC damage alters the pace of evidence accumulation in response to social signals, eliminating a default, protective avoidant bias and facilitating dysfunctional approach behavior.
]]></description>
<dc:creator>Buades-Rotger, M.</dc:creator>
<dc:creator>Solbakk, A.-K.</dc:creator>
<dc:creator>Liebrand, M.</dc:creator>
<dc:creator>Endestad, T.</dc:creator>
<dc:creator>Funderud, I.</dc:creator>
<dc:creator>Siegwardt, P.</dc:creator>
<dc:creator>Enter, D.</dc:creator>
<dc:creator>Roelofs, K.</dc:creator>
<dc:creator>Kraemer, U. M.</dc:creator>
<dc:date>2020-06-22</dc:date>
<dc:identifier>doi:10.1101/2020.06.21.162628</dc:identifier>
<dc:title><![CDATA[Orbitofrontal lesion patients show an implicit approach bias to angry faces]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.21.163915v1?rss=1">
<title>
<![CDATA[
Genetic influences on hub connectivity of the human connectome 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.21.163915v1?rss=1"
</link>
<description><![CDATA[
Brain network hubs are both highly connected and highly inter-connected, forming a critical communication backbone for coherent neural dynamics. The mechanisms driving this organization are poorly understood. Using diffusion-weighted imaging in twins, we identify a major role for genes, showing that they preferentially influence connectivity strength between network hubs of the human connectome. Using transcriptomic atlas data, we show that connected hubs demonstrate tight coupling of transcriptional activity related to metabolic and cytoarchitectonic similarity. Finally, comparing over thirteen generative models of network growth, we show that purely stochastic processes cannot explain the precise wiring patterns of hubs, and that model performance can be improved by incorporating genetic constraints. Our findings indicate that genes play a strong and preferential role in shaping the functionally valuable, metabolically costly connections between connectome hubs.
]]></description>
<dc:creator>Arnatkeviciute, A.</dc:creator>
<dc:creator>Fulcher, B. D.</dc:creator>
<dc:creator>Oldham, S.</dc:creator>
<dc:creator>Tiego, J.</dc:creator>
<dc:creator>Paquola, C.</dc:creator>
<dc:creator>Gerring, Z. F.</dc:creator>
<dc:creator>Aquino, K. M.</dc:creator>
<dc:creator>Hawi, Z.</dc:creator>
<dc:creator>Johnson, B.</dc:creator>
<dc:creator>Ball, G. M.</dc:creator>
<dc:creator>Klein, M.</dc:creator>
<dc:creator>Deco, G.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Bellgrove, M.</dc:creator>
<dc:creator>Fornito, A.</dc:creator>
<dc:date>2020-06-22</dc:date>
<dc:identifier>doi:10.1101/2020.06.21.163915</dc:identifier>
<dc:title><![CDATA[Genetic influences on hub connectivity of the human connectome]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.23.127258v1?rss=1">
<title>
<![CDATA[
White Matter microstructural property decoding from gradient echo data using realistic white matter models 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.23.127258v1?rss=1"
</link>
<description><![CDATA[
Multi-echo gradient echo (ME-GRE) magnetic resonance signal evolution in white matter has a strong dependence on the orientation of myelinated axons with respect to the main static field. Although analytical solutions have been able to predict some of the white matter (WM) signal behaviour of the hollow cylinder model, it has been shown that realistic models of WM offer a better description of the signal behaviour observed.

In this work, we present a pipeline to (i) generate realistic 2D WM models with their microstructure based on real axon morphology with adjustable fiber volume fraction (FVF) and g-ratio. We (ii) simulate their interaction with the static magnetic field to be able to simulate their MR signal. For the first time, we (iii) demonstrate that realistic 2D WM models can be used to simulate a MR signal that provides a good approximation of the signal obtained from a real 3D WM model derived from electron microscopy. We then (iv) demonstrate in silico that 2D WM models can be used to predict microstructural parameters in a robust way if ME-GRE multi-orientation data is available and the main fiber orientation in each pixel is known using DTI. A deep learning network was trained and characterized in its ability to recover the desired microstructural parameters such as FVF, g-ratio, free and bound water transverse relaxation and magnetic susceptibility. Finally, the network was trained to recover these micro-structural parameters from an ex vivo dataset acquired in 9 orientations with respect to the magnetic field and 12 echo times. We demonstrate that this is an overdetermined problem and that as few as 3 orientations can already provide comparable results for some of the decoded metrics.

[Highlights] - A pipeline to generate realistic white models of arbitrary fiber volume fraction and g-ratio is presented; - We present a methodology to simulated the gradient echo signal from segmented 2D and 3D models of white matter, which takes into account the interaction of the static magnetic field with the anisotropic susceptibility of the myelin phospholipids; - Deep Learning Networks can be used to decode microstructural white matter parameters from the signal of multi-echo multi-orientation data;
]]></description>
<dc:creator>Hedouin, R.</dc:creator>
<dc:creator>Metere, R.</dc:creator>
<dc:creator>Chan, K.-S.</dc:creator>
<dc:creator>Licht, C.</dc:creator>
<dc:creator>Mollink, J.</dc:creator>
<dc:creator>van Cappellen van Walsum, A.-M.</dc:creator>
<dc:creator>Marques, J. P.</dc:creator>
<dc:date>2020-06-24</dc:date>
<dc:identifier>doi:10.1101/2020.06.23.127258</dc:identifier>
<dc:title><![CDATA[White Matter microstructural property decoding from gradient echo data using realistic white matter models]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.23.168187v1?rss=1">
<title>
<![CDATA[
Visual mismatch responses index surprise signalling but not expectation suppression 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.23.168187v1?rss=1"
</link>
<description><![CDATA[
The ability to distinguish between commonplace and unusual sensory events is critical for efficient learning and adaptive behaviour. This has been investigated using oddball designs in which sequences of often-appearing (i.e. expected) stimuli are interspersed with rare (i.e. surprising) deviants. Resulting differences in electrophysiological responses following surprising compared to expected stimuli are known as visual mismatch responses (VMRs). VMRs are thought to index co-occurring contributions of stimulus repetition effects, expectation suppression (that occurs when ones expectations are fulfilled), and expectation violation (i.e. surprise) responses; however, these different effects have been conflated in existing oddball designs. To better isolate and quantify effects of expectation suppression and surprise, we adapted an oddball design based on Fast Periodic Visual Stimulation (FPVS) that controls for stimulus repetition effects. We recorded electroencephalography (EEG) while participants (N=48) viewed stimulation sequences in which a single face identity was periodically presented at 6 Hz. Critically, one of two different face identities (termed oddballs) appeared as every 7th image throughout the sequence. The presentation probabilities of each oddball image within a sequence varied between 10-90%, such that participants could form expectations about which oddball face identity was more likely to appear within each sequence. We also included  expectation neutral 50% probability sequences, whereby consistently biased expectations would not be formed for either oddball face identity. We found that VMRs indexed surprise responses, and effects of expectation suppression were absent. That is, ERPs were more negative-going at occipitoparietal electrodes for surprising compared to neutral oddballs, but did not differ between expected and neutral oddballs. Surprising oddball-evoked ERPs were also highly similar across the 10-40% appearance probability conditions. Our findings indicate that VMRs which are not accounted for by repetition effects are best described as an all-or-none surprise response, rather than a minimisation of prediction error responses associated with expectation suppression.

Highlights- We used a recently-developed oddball design that controls for repetition effects
- We found effects of surprise but not expectation suppression on ERPs
- Surprise responses did not vary by stimulus appearance probability
]]></description>
<dc:creator>Feuerriegel, D. C.</dc:creator>
<dc:creator>Yook, J.</dc:creator>
<dc:creator>Quek, G. L.</dc:creator>
<dc:creator>Hogendoorn, H.</dc:creator>
<dc:creator>Bode, S.</dc:creator>
<dc:date>2020-06-24</dc:date>
<dc:identifier>doi:10.1101/2020.06.23.168187</dc:identifier>
<dc:title><![CDATA[Visual mismatch responses index surprise signalling but not expectation suppression]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.25.170480v1?rss=1">
<title>
<![CDATA[
MeCP2 gates spatial learning-induced alternative splicing events in the mouse hippocampus 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.25.170480v1?rss=1"
</link>
<description><![CDATA[
Long-term memory formation is supported by functional and structural changes of neuronal networks, which rely on de novo gene transcription and protein synthesis. The modulation of the neuronal transcriptome in response to learning depends on transcriptional and post-transcriptional mechanisms. DNA methylation writers and readers regulate the activity-dependent genomic program required for memory consolidation. The most abundant DNA methylation reader, the Methyl CpG binding domain protein 2 (MeCP2), has been shown to regulate alternative splicing, but whether it establishes splicing events important for memory consolidation has not been investigated. In this study, we identified the alternative splicing profile of the mouse hippocampus in basal conditions and after a spatial learning experience, and investigated the requirement of MeCP2 for these processes. We observed that spatial learning triggers a wide-range of alternative splicing events in transcripts associated with structural remodeling and that virus-mediated knockdown of MeCP2 impairs learning-dependent post-transcriptional responses of mature hippocampal neurons. Furthermore, we found that MeCP2 preferentially affected the splicing modalities intron retention and exon skipping and guided the alternative splicing of distinct set of genes in baseline conditions and after learning. Lastly, comparative analysis of the MeCP2-regulated transcriptome with the alternatively spliced mRNA pool, revealed that MeCP2 disruption alters the relative abundance of alternatively spliced isoforms without affecting the overall mRNA levels. Overall our findings reveal that adult hippocampal MeCP2 is required to finetune alternative splicing events in basal conditions, as well as in response to spatial learning. This study provides new insight into how MeCP2 regulates brain function, particularly cognitive abilities, and sheds light onto the pathophysiological mechanisms of Rett syndrome, that is characterized by intellectual disability and caused by mutations in the Mecp2 gene.
]]></description>
<dc:creator>Brito, D. V. C.</dc:creator>
<dc:creator>Gulmez Karaca, K.</dc:creator>
<dc:creator>Oliveira, A. M. M.</dc:creator>
<dc:date>2020-06-25</dc:date>
<dc:identifier>doi:10.1101/2020.06.25.170480</dc:identifier>
<dc:title><![CDATA[MeCP2 gates spatial learning-induced alternative splicing events in the mouse hippocampus]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.25.171264v1?rss=1">
<title>
<![CDATA[
Crossing the Blood-Brain-Barrier: A bifunctional liposome for BDNF gene delivery - A Pilot Study 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.25.171264v1?rss=1"
</link>
<description><![CDATA[
To achieve their therapeutic effect on the brain, molecules need to pass the blood-brain-barrier (BBB). Many pharmacological treatments of neuropathologies encounter the BBB as a barrier, hindering their effective use. Pharmaceutical nanotechnology based on optimal physicochemical features and taking advantage of naturally occurring permeability mechanisms, nanocarriers such as liposomes offer an attractive alternative to allow drug delivery across the BBB. Liposomes are spherical bilayer lipid-based nanocapsules that can load hydrophilic molecules in their inner compartment and on their outer surface can be functionally modified by peptides, antibodies and polyethyleneglycol (PEG). When composed of cationic lipids, liposomes can serve as gene delivery devices, encapsulating and protecting genetic material from degradation and promoting nonviral cell transfection. In this study, we aimed to develop a liposomal formulation to encapsulate a plasmid harbouring brain-derived neurotrophic factor (BDNF) and infuse these liposomes via the peripheral bloodstream into the brain. To this end, liposomes were tagged with PEG, transferrin, and arginine and characterized regarding their physical properties, such as particle size, zeta-potential and polydispersity index (PDI). Moreover, we selected liposomes preparations for plasmid DNA (pDNA) encapsulation and checked for loading efficiency, in vitro cell uptake, and transfection. The preliminary results from this pilot study revealed that we were able to replicate the liposomes synthesis described in literature, achieving compatible size, charge, PDI, and loading efficiency. However, we could not properly determine whether the conjugation of the surface ligands transferrin and arginine to PEG worked and whether they were attached to the surface of the liposomes. Additionally, we were not able to see transfection in SH-SY5Y cells after 24 or 48 hours of incubation with the pDNA loaded liposomes. In conclusion, we synthesized liposomes encapsulation pBDNF, however, further research will be necessary to address the complete physicochemical characterization of the liposomes. Furthermore, preclinical studies will be helpful to verify transfection efficiency, cytotoxicity, and in the future, safe delivery of BDNF through the BBB.
]]></description>
<dc:creator>Diniz, D. M.</dc:creator>
<dc:creator>Franze, S.</dc:creator>
<dc:creator>Homberg, J. R.</dc:creator>
<dc:date>2020-06-26</dc:date>
<dc:identifier>doi:10.1101/2020.06.25.171264</dc:identifier>
<dc:title><![CDATA[Crossing the Blood-Brain-Barrier: A bifunctional liposome for BDNF gene delivery - A Pilot Study]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.26.173419v1?rss=1">
<title>
<![CDATA[
A neural surveyor in somatosensory cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.26.173419v1?rss=1"
</link>
<description><![CDATA[
Perhaps the most recognizable sensory map in all of neuroscience is the somatosensory homunculus. Though it seems straightforward, this simple representation belies the complex link between an activation in a somatotopic map and the associated touch location on the body. Any isolated activation is spatially ambiguous without a neural decoder that can read its position within the entire map, but how this is computed by neural networks is unknown. We propose that the somatosensory system implements multilateration, a common computation used by surveying and GPS systems to localize objects. Specifically, to decode touch location on the body, multilateration estimates the relative distance between the afferent input and the boundaries of a body part (e.g., the joints of a limb). We show that a simple feedforward neural network, which captures several fundamental receptive field properties of cortical somatosensory neurons, can implement a Bayes-optimal multilateral computation. Simulations demonstrated that this decoder produced a pattern of localization variability between two boundaries that was unique to multilateration. Finally, we identify this computational signature of multilateration in actual psychophysical experiments, suggesting that it is a candidate computational mechanism underlying tactile localization.
]]></description>
<dc:creator>Miller, L.</dc:creator>
<dc:creator>Fabio, C.</dc:creator>
<dc:creator>van Beers, R.</dc:creator>
<dc:creator>Farne, A.</dc:creator>
<dc:creator>Medendorp, W. P.</dc:creator>
<dc:date>2020-06-27</dc:date>
<dc:identifier>doi:10.1101/2020.06.26.173419</dc:identifier>
<dc:title><![CDATA[A neural surveyor in somatosensory cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.26.171827v1?rss=1">
<title>
<![CDATA[
Gray matter covariations and core symptoms of autism. The EU-AIMS Longitudinal European Autism Project 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.26.171827v1?rss=1"
</link>
<description><![CDATA[
BackgroundVoxel-based Morphometry (VBM) studies in Autism Spectrum Disorder (autism) have yielded diverging results. This might partly be attributed to structural alterations being associating with the combined influence of several regions rather than with a single region. Further, these structural covariation differences may relate to continuous measures of autism rather than with categorical case-control contrasts. The current study aimed to identify structural covariation alterations in autism, and assessed canonical correlations between brain covariation patterns and core autism symptoms.

MethodsWe studied 347 individuals with autism and 252 typically developing individuals, aged between 6 and 30 years, who have been deeply phenotyped in the Longitudinal European Autism Project (LEAP). All participants VBM maps were decomposed into spatially independent components using Independent Component Analysis. A Generalized Linear Model (GLM) was used to examine case-control differences. Next, Canonical Correlation Analysis (CCA) was performed to separately explore the integrated effects between all the brain sources of gray matter variation and two sets of core autism symptoms.

ResultsGLM analyses showed significant case-control differences for two independent components. The first component was primarily associated with decreased density of bilateral insula, inferior frontal gyrus, orbitofrontal cortex, and increased density of caudate nucleus in the autism group relative to typically developing individuals. The second component was related to decreased densities of the bilateral amygdala, hippocampus, and parahippocampal gyrus in the autism group relative to typically developing individuals. The CCA results showed significant correlations between components that involved variation of thalamus, putamen, precentral gyrus, frontal, parietal, and occipital lobes, and the cerebellum, and repetitive, rigid and stereotyped behaviors and abnormal sensory behaviors in autism individuals.

LimitationsOnly 55.9% of the participants with autism had complete questionnaire data on continuous parent-reported symptom measures.

ConclusionsCovaried areas associated with autism diagnosis and/or symptoms are scattered across the whole brain and include the limbic system, basal ganglia, thalamus, cerebellum, precentral gyrus, and parts of the frontal, parietal, and occipital lobes. Some of these areas potentially subserve social-communicative behavior whereas others may underpin sensory processing and integration, and motor behavior.
]]></description>
<dc:creator>Mei, T.</dc:creator>
<dc:creator>Llera, A.</dc:creator>
<dc:creator>Floris, D. L.</dc:creator>
<dc:creator>Forde, N. J.</dc:creator>
<dc:creator>Tillmann, J.</dc:creator>
<dc:creator>Durston, S.</dc:creator>
<dc:creator>Moessnang, C.</dc:creator>
<dc:creator>Banaschewski, T.</dc:creator>
<dc:creator>Holt, R. J.</dc:creator>
<dc:creator>Baron-Cohen, S.</dc:creator>
<dc:creator>Rausch, A.</dc:creator>
<dc:creator>Loth, E.</dc:creator>
<dc:creator>Dell'Acqua, F.</dc:creator>
<dc:creator>Charman, T.</dc:creator>
<dc:creator>Murphy, D. G. M.</dc:creator>
<dc:creator>Ecker, C.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>the EU-AIMS LEAP group,</dc:creator>
<dc:date>2020-06-27</dc:date>
<dc:identifier>doi:10.1101/2020.06.26.171827</dc:identifier>
<dc:title><![CDATA[Gray matter covariations and core symptoms of autism. The EU-AIMS Longitudinal European Autism Project]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.30.179721v1?rss=1">
<title>
<![CDATA[
The genetic architecture of structural left-right asymmetry of the human brain 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.30.179721v1?rss=1"
</link>
<description><![CDATA[
Left-right hemispheric asymmetry is an important aspect of healthy brain organization for many functions including language, and can be altered in cognitive and psychiatric disorders1-8. No mechanism has yet been identified for establishing the human brains left-right axis9. We performed multivariate genome-wide association scanning (mvGWAS) of cortical regional surface area and thickness asymmetries, and subcortical volume asymmetries, using data from 32,256 participants from the UK Biobank. There were 21 significant loci affecting different aspects of brain asymmetry, with functional enrichment involving microtubule-related genes and embryonic brain expression. These findings are consistent with a known role of the cytoskeleton in left-right axis determination in other organs of invertebrates and frogs10-12. Genetic variants affecting brain asymmetry overlapped with those influencing autism, educational attainment and schizophrenia.
]]></description>
<dc:creator>Sha, Z.</dc:creator>
<dc:creator>Schijven, D.</dc:creator>
<dc:creator>Carrion-Castillo, A.</dc:creator>
<dc:creator>Joliot, M.</dc:creator>
<dc:creator>Mazoyer, B.</dc:creator>
<dc:creator>Fisher, S.</dc:creator>
<dc:creator>Crivello, F.</dc:creator>
<dc:creator>Francks, C.</dc:creator>
<dc:date>2020-06-30</dc:date>
<dc:identifier>doi:10.1101/2020.06.30.179721</dc:identifier>
<dc:title><![CDATA[The genetic architecture of structural left-right asymmetry of the human brain]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.07.01.180604v1?rss=1">
<title>
<![CDATA[
BDNF Overexpression in the Prelimbic Cortex Does Not Reduce Anxiety- and Depression-like Behavior in Serotonin Knockout Rats 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.07.01.180604v1?rss=1"
</link>
<description><![CDATA[
Depressive disorders are one of the leading causes of non-fatal health loss in the last decade. Adding to the burden, the available treatments not always properly work for some individuals. There is, therefore, a constant effort from clinical and preclinical studies to bring forward a better understanding of the disease and look for novel alternative therapies. Two target systems very well explored are the serotonin and the brain-derived neurotrophic factor (BDNF) systems. Selective serotonin reuptake inhibitors (SSRIs), a commonly used class of antidepressants, target the serotonin transporter (SERT) and increase serotonin levels, which in turn also leads to an increase in BDNF. A rat model lacking SERT (SERT knockout) has been a useful tool to study the interplay between serotonin and BDNF. SERT-/- rats present increased extracellular levels of serotonin, yet BDNF levels are decreased, especially in the prefrontal cortex (PFC) and hippocampus. The animals further display anxiety- and depression-like behavior. Therefore, BDNF might mediate the phenotype expressed by the SERT-/- rats. In this study, we sought to investigate whether overexpression of BDNF in the brain of SERT-/- rats would rescue its anxious and depressive-like behavior. Through stereotaxic surgery, SERT-/- and wild-type (WT) rats received BDNF or GFP lentivirus microinfusions into the prelimbic cortex subregion of the mPFC and were submitted to the sucrose consumption, open field test, and forced swim tests. Additionally, we measured hypothalamus-pituitary-adrenal (HPA)-axis reactivity. The results revealed that SERT-/- rats presented decreased sucrose intake, decreased locomotor activity, and increased escape-oriented behavior in the forced swim test compared to WT rats. BDNF upregulation in WT rats caused alterations in the HPA-axis function, resulting in elevated basal plasma corticosterone levels and decreased plasma corticosterone upon stress. In conclusion, BDNF overexpression in the PrL, in general, did not rescue SERT-/- rats from its depression- and anxiety-like behavior, and in WT animals, it caused a malfunction in the HPA-axis.
]]></description>
<dc:creator>Diniz, D. M.</dc:creator>
<dc:creator>Bosch, K.</dc:creator>
<dc:creator>Calabrese, F.</dc:creator>
<dc:creator>Brivio, P.</dc:creator>
<dc:creator>Riva, M. A.</dc:creator>
<dc:creator>Grandjean, J.</dc:creator>
<dc:creator>Homberg, J. R.</dc:creator>
<dc:date>2020-07-01</dc:date>
<dc:identifier>doi:10.1101/2020.07.01.180604</dc:identifier>
<dc:title><![CDATA[BDNF Overexpression in the Prelimbic Cortex Does Not Reduce Anxiety- and Depression-like Behavior in Serotonin Knockout Rats]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-07-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.07.01.181966v1?rss=1">
<title>
<![CDATA[
BDNF overexpression in the ventral hippocampus promotes antidepressant- and anxiolytic-like activity in serotonin transporter knockout rats 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.07.01.181966v1?rss=1"
</link>
<description><![CDATA[
Brain-derived neurotrophic factor is one of the most studied proteins playing a pivotal role in neuroplasticity events and vulnerability and resilience to stress-related disorders. Most importantly, BDNF is decreased in depressive patients, and increased after antidepressant treatment. Additionally, BDNF was found to be reduced in a genetic subset of depression susceptible patients carrying the human polymorphism in the serotonin transporter promoter region (5-HTTLPR). The serotonin knockout rat (SERT-/-) is one of the animal models used to investigate the underlying molecular mechanisms behind the genetic susceptibility to depression in humans. SERT-/- rats present decreased BDNF levels, especially BDNF exon IV, in the prefrontal cortex (PFC) and ventral hippocampus (vHIP), and display anxiety- and depression-like behavior. To investigate whether upregulating BDNF in the vHIP would meliorate the phenotype of SERT-/- rats, we overexpressed BDNF locally into the rat brain by means of stereotaxic surgery and submitted the animals to behavioral challenges, including the sucrose consumption, the open field, and forced swim tests. Additionally, we measured hypothalamus-pituitary-adrenal (HPA)-axis reactivity. The results showed that lentivirus-induced BDNF IV overexpression in the vHIP of SERT-/- rats promoted higher sucrose preference and sucrose intake, on the first day of the sucrose consumption test, indicative for decreased anhedonia-like behavior. Moreover, it decreased immobility time in the forced swim test, suggesting adaptive passive coping. Additionally, BDNF upregulation increased the time spent in the center of a novel environment, implying decreased novel-induced anxiety-like behavior. Finally, it promoted a stronger decrease in plasma corticosterone levels 60 minutes after restraint stress. In conclusion, modulation of BDNF IV levels in the vHIP of SERT-/- rats led to a positive behavioral outcome placing BDNF upregulation in the vHIP as a potential candidate for the development new therapeutic approaches targeting the improvement of depressive symptoms.
]]></description>
<dc:creator>Diniz, D. M.</dc:creator>
<dc:creator>Calabrese, F.</dc:creator>
<dc:creator>Brivio, P.</dc:creator>
<dc:creator>Riva, M. A.</dc:creator>
<dc:creator>Grandjean, J.</dc:creator>
<dc:creator>Homberg, J. R.</dc:creator>
<dc:date>2020-07-01</dc:date>
<dc:identifier>doi:10.1101/2020.07.01.181966</dc:identifier>
<dc:title><![CDATA[BDNF overexpression in the ventral hippocampus promotes antidepressant- and anxiolytic-like activity in serotonin transporter knockout rats]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-07-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.07.01.168849v1?rss=1">
<title>
<![CDATA[
Hyperrealistic neural decoding: Linear reconstruction of face stimuli from fMRI measurements via the GAN latent space 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.07.01.168849v1?rss=1"
</link>
<description><![CDATA[
Neural decoding can be conceptualized as the problem of mapping brain responses back to sensory stimuli via a feature space. We introduce (i) a novel experimental paradigm which uses well-controlled yet highly naturalistic stimuli with a priori known feature representations and (ii) an implementation thereof for HYPerrealistic reconstruction of PERception (HYPER) of faces from brain recordings. To this end, we embrace the use of generative adversarial networks (GANs) at the earliest step of our neural decoding pipeline by acquiring fMRI data as subjects perceive face images synthesized by the generator network of a GAN. We show that the latent vectors used for generation effectively capture the same defining stimulus properties as the fMRI measurements. As such, GAN latent vectors can be used as features underlying the perceived images that can be predicted for (re-)generation, leading to the most accurate reconstructions of perception to date.
]]></description>
<dc:creator>Dado, T.</dc:creator>
<dc:creator>Gucluturk, Y.</dc:creator>
<dc:creator>Ambrogioni, L.</dc:creator>
<dc:creator>Ras, G.</dc:creator>
<dc:creator>Bosch, S. E.</dc:creator>
<dc:creator>van Gerven, M.</dc:creator>
<dc:creator>Guclu, U.</dc:creator>
<dc:date>2020-07-02</dc:date>
<dc:identifier>doi:10.1101/2020.07.01.168849</dc:identifier>
<dc:title><![CDATA[Hyperrealistic neural decoding: Linear reconstruction of face stimuli from fMRI measurements via the GAN latent space]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-07-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.07.04.188235v1?rss=1">
<title>
<![CDATA[
The dynamic transition between neural states is associated with the flexible use of memory 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.07.04.188235v1?rss=1"
</link>
<description><![CDATA[
Flexible behavior requires switching between different task conditions. It is known that such task- switching is associated with costs in terms of slowed reaction time, reduced accuracy, or both. The neural correlates of task-switching have usually been studied by requiring participants to switch between distinct task demands that recruit different brain networks. Here, we investigated the transition of neural states underlying switching between two opposite memory-related processes (i.e., memory retrieval and memory suppression) in a memory task. We investigated 26 healthy participants who performed a Think/No-Think task while being in the fMRI scanner. Behaviorally, we show that it was more difficult for participants to suppress unwanted memories when a No-Think was preceded by a Think trial instead of another No- Think trial. Neurally, we demonstrate that Think-to-No-Think switches were associated with an increase in control-related and a decrease in memory-related brain activity. Neural representations of task demand, assessed by decoding accuracy, were lower immediately after task switching compared to the non-switch transitions, suggesting a switch-induced delay in the neural transition towards the required task condition. This suggestion is corroborated by an association between condition-specific representational strength and condition-specific performance in switch trials. Taken together, we provided neural evidence from the time-resolved decoding approach to support the notion that carry-over of the previous task-set activation is associated with the switching cost leading to less successful memory suppression.

Significance statementOur brain can switch between multiple tasks but at the cost of less optimal performance during transition. One possible neuroscientific explanation is that the representation of the task condition is not easy to be updated immediately after switching. Thus, weak representations for the task at hand explain performance costs. To test this, we applied brain decoding approaches to human fMRI data when participants switched between successive trials of memory retrieval and suppression. We found that switching leads to a weaker representation of the current task. The remaining representation of the previous, opposite task is associated with inferior performance in the current task. Therefore, timely updating of task representations is critical for task switching in the service of flexible behaviors.
]]></description>
<dc:creator>Liu, W.</dc:creator>
<dc:creator>Kohn, N.</dc:creator>
<dc:creator>Fernandez, G.</dc:creator>
<dc:date>2020-07-05</dc:date>
<dc:identifier>doi:10.1101/2020.07.04.188235</dc:identifier>
<dc:title><![CDATA[The dynamic transition between neural states is associated with the flexible use of memory]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-07-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.07.06.186650v1?rss=1">
<title>
<![CDATA[
Attenuated Anticipation of Social and Monetary Rewards in Autism Spectrum Disorders 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.07.06.186650v1?rss=1"
</link>
<description><![CDATA[
BackgroundReward processing has been proposed to underpin atypical social behavior, a core feature of autism spectrum disorder (ASD). However, previous neuroimaging studies have yielded inconsistent results regarding the specificity of atypicalities for social rewards in ASD. Utilizing a large sample, we aimed to assess altered reward processing in response to reward type (social, monetary) and reward phase (anticipation, delivery) in ASD.

MethodsFunctional magnetic resonance imaging during social and monetary reward anticipation and delivery was performed in 212 individuals with ASD (7.6-30.5 years) and 181 typically developing (TD) participants (7.6-30.8 years).

ResultsAcross social and monetary reward anticipation, whole-brain analyses (p<0.05, family-wise error-corrected) showed hypoactivation of the right ventral striatum (VS) in ASD. Further, region of interest (ROI) analysis across both reward types yielded hypoactivation in ASD in both the left and right VS. Across delivery of social and monetary reward, hyperactivation of the VS in individuals with ASD did not survive correction for multiple comparisons. Reward type by diagnostic group interactions, and a dimensional analysis of autism trait scores were not significant during anticipation or delivery. Levels of attention-deficit/hyperactivity disorder (ADHD) symptoms did not affect reward processing in ASD.

ConclusionsOur results do not support current theories linking atypical social interaction in ASD to specific alterations in processing of social rewards. Instead, they point towards a generalized hypoactivity of VS in ASD during anticipation of both social and monetary rewards. We suggest that this indicates attenuated subjective reward value in ASD independent of social content and ADHD symptoms.
]]></description>
<dc:creator>Baumeister, S.</dc:creator>
<dc:creator>Moessnang, C.</dc:creator>
<dc:creator>Bast, N.</dc:creator>
<dc:creator>Hohmann, S.</dc:creator>
<dc:creator>Tillmann, J.</dc:creator>
<dc:creator>Goyard, D.</dc:creator>
<dc:creator>Charman, T.</dc:creator>
<dc:creator>Ambrosino, S.</dc:creator>
<dc:creator>Baron-Cohen, S.</dc:creator>
<dc:creator>Beckmann, C.</dc:creator>
<dc:creator>Boelte, S.</dc:creator>
<dc:creator>Bourgeron, T.</dc:creator>
<dc:creator>Rausch, A.</dc:creator>
<dc:creator>Crawley, D.</dc:creator>
<dc:creator>Dell'Acqua, F.</dc:creator>
<dc:creator>Dumas, G.</dc:creator>
<dc:creator>Durston, S.</dc:creator>
<dc:creator>Ecker, C.</dc:creator>
<dc:creator>Floris, D. L.</dc:creator>
<dc:creator>Frouin, V.</dc:creator>
<dc:creator>Hayward, H.</dc:creator>
<dc:creator>Holt, R.</dc:creator>
<dc:creator>Johnson, M. H.</dc:creator>
<dc:creator>Jones, E. J. H.</dc:creator>
<dc:creator>Lai, M.-C.</dc:creator>
<dc:creator>Lombardo, M. V.</dc:creator>
<dc:creator>Mason, L.</dc:creator>
<dc:creator>Oldehinkel, M.</dc:creator>
<dc:creator>Persico, T.</dc:creator>
<dc:creator>San Jos Caceres, A.</dc:creator>
<dc:creator>Wolfers, T.</dc:creator>
<dc:creator>Spooren, W.</dc:creator>
<dc:creator>Loth, E.</dc:creator>
<dc:creator>Murphy, D. G. M.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Tost, H.</dc:creator>
<dc:creator>Meyer-Lindenberg, A.</dc:creator>
<dc:creator>Banaschewski, T.</dc:creator>
<dc:creator>Brandeis, D.</dc:creator>
<dc:creator>AIMS-2-TRIALS group,</dc:creator>
<dc:date>2020-07-06</dc:date>
<dc:identifier>doi:10.1101/2020.07.06.186650</dc:identifier>
<dc:title><![CDATA[Attenuated Anticipation of Social and Monetary Rewards in Autism Spectrum Disorders]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-07-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.07.08.191304v1?rss=1">
<title>
<![CDATA[
The predictive brain in action: Involuntary actions reduce body prediction errors 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.07.08.191304v1?rss=1"
</link>
<description><![CDATA[
The perception of our body in space is flexible and manipulable. The predictive brain hypothesis explains this malleability as a consequence of the interplay between incoming sensory information and our body expectations. However, given the interaction between perception and action, we might also expect that actions would arise due to prediction errors, especially in conflicting situations. Here we describe a computational model, based on the free-energy principle, that forecasts involuntary movements in sensorimotor conflicts. We experimentally confirm those predictions in humans using a virtual reality rubber-hand illusion. Participants generated movements (forces) towards the virtual hand, regardless of its location with respect to the real arm, with little to no forces produced when the virtual hand overlaid their physical hand. The congruency of our model predictions and human observations indicates that the brain-body is generating actions to reduce the prediction error between the expected arm location and the new visual arm. This observed unconscious mechanism is an empirical validation of the perception-action duality in body adaptation to uncertain situations and evidence of the active component of predictive processing.
]]></description>
<dc:creator>Pablo Lanillos</dc:creator>
<dc:creator>Sae Franklin</dc:creator>
<dc:creator>David W. Franklin</dc:creator>
<dc:date>2020-07-08</dc:date>
<dc:identifier>doi:10.1101/2020.07.08.191304</dc:identifier>
<dc:title><![CDATA[The predictive brain in action: Involuntary actions reduce body prediction errors]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-07-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.07.09.196212v1?rss=1">
<title>
<![CDATA[
Examining the boundary sharpness coefficient as an index of cortical microstructure and its relationship to age and sex in autism spectrum disorder 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.07.09.196212v1?rss=1"
</link>
<description><![CDATA[
Autism spectrum disorder (ASD) is associated with atypical brain development. However, the phenotype of regionally specific increased cortical thickness observed in ASD may be driven by several independent biological processes that influence the gray/white matter boundary, such as synaptic pruning, myelination, or atypical migration. Here, we propose to use the boundary sharpness coefficient (BSC), a proxy for alterations in microstructure at the cortical gray/white matter boundary, to investigate brain differences in individuals with ASD, including factors that may influence ASD-related heterogeneity (age, sex, and intelligence quotient). Using a vertex-based meta-analysis and a large multi-center magnetic resonance structural imaging (MRI) dataset, with a total of 1136 individuals, 415 with ASD (112 female; 303 male) and 721 controls (283 female; 438 male), we observed that individuals with ASD had significantly greater BSC in the bilateral superior temporal gyrus and left inferior frontal gyrus indicating an abrupt transition (high contrast) between white matter and cortical intensities. Increases were observed in different brain regions in males and females, with larger effect sizes in females. Individuals with ASD under 18 had significantly greater BSC in the bilateral superior temporal gyrus and right postcentral gyrus; individuals with ASD over 18 had significantly increased BSC in the bilateral precuneus and superior temporal gyrus. BSC correlated with ADOS-2 CSS in individuals with ASD in the right medial temporal pole. Importantly, there was a significant spatial overlap between maps of the effect of diagnosis on BSC when compared to cortical thickness. These results invite studies to use BSC as a possible new measure of cortical development in ASD and to further examine the microstructural underpinnings of BSC-related differences and their impact on measures of cortical morphology.
]]></description>
<dc:creator>Emily Olafson</dc:creator>
<dc:creator>Saashi A Bedford</dc:creator>
<dc:creator>Gabriel A Devenyi</dc:creator>
<dc:creator>Raihaan Patel</dc:creator>
<dc:creator>Stephanie Tullo</dc:creator>
<dc:creator>Min Tae M Park</dc:creator>
<dc:creator>Evdokia Anagnostou</dc:creator>
<dc:creator>Simon Baron-Cohen</dc:creator>
<dc:creator>Edward T. Bullmore</dc:creator>
<dc:creator>Lindsay R. Chura</dc:creator>
<dc:creator>Michael C. Craig</dc:creator>
<dc:creator>Christine Ecker</dc:creator>
<dc:creator>Dorothea L. Floris</dc:creator>
<dc:creator>Rosemary J. Holt</dc:creator>
<dc:creator>Rhoshel Lenroot</dc:creator>
<dc:creator>Jason P. Lerch</dc:creator>
<dc:creator>Michael V. Lombardo</dc:creator>
<dc:creator>Declan G. M. Murphy</dc:creator>
<dc:creator>Armin Raznahan</dc:creator>
<dc:creator>Amber N. V. Ruigrok</dc:creator>
<dc:creator>Michael D. Spencer</dc:creator>
<dc:creator>John Suckling</dc:creator>
<dc:creator>Margot Taylor</dc:creator>
<dc:creator>The Medical Research Council Autism Imaging Multicentre Study Consortium</dc:creator>
<dc:creator>Meng-Chuan Lai</dc:creator>
<dc:creator>M. Mallar Chakravarty</dc:creator>
<dc:date>2020-07-10</dc:date>
<dc:identifier>doi:10.1101/2020.07.09.196212</dc:identifier>
<dc:title><![CDATA[Examining the boundary sharpness coefficient as an index of cortical microstructure and its relationship to age and sex in autism spectrum disorder]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-07-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.07.08.190405v1?rss=1">
<title>
<![CDATA[
The serotonin transporter modulates decisional anhedonia 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.07.08.190405v1?rss=1"
</link>
<description><![CDATA[
Serotonin transporter gene variance has long been considered an essential factor contributing to depression. However, meta-analyses yielded inconsistent findings recently, asking for further understanding of the link between the gene and depression-related symptoms. One key feature of depression is anhedonia. While data exist on the effect of serotonin transporter gene knockout (5-HTT-/-) in rodents on consummatory and anticipatory anhedonia, with mixed outcomes, the effect on decisional anhedonia has not been investigated thus far. Here, we tested whether 5-HTT-/- contributes to decisional anhedonia. To this end, we established a novel touchscreen-based "go/go" task of visual decision-making. During the learning of stimulus discrimination, 5-HTT+/+ rats performed more optimal decision-making compared to 5-HTT-/- rats at the beginning, but this difference did not persist throughout the learning period. During stimulus generalization, the generalization curves were similar between both genotypes and did not alter as the learning progress. Interestingly, the response time in 5-HTT+/+ rats increased as the session increased in general, while 5-HTT-/- rats tended to decrease. The response time difference might indicate that 5-HTT-/- rats altered willingness to exert cognitive effort to the categorization of generalization stimuli. These results suggest that the effect of 5-HTT ablation on decisional anhedonia is mild and interacts with learning, explaining the discrepant findings on the link between 5-HTT gene and depression.
]]></description>
<dc:creator>Chao Ciu-Gwok Guo</dc:creator>
<dc:creator>Michel MM Verheij</dc:creator>
<dc:creator>Judith R Homberg</dc:creator>
<dc:date>2020-07-09</dc:date>
<dc:identifier>doi:10.1101/2020.07.08.190405</dc:identifier>
<dc:title><![CDATA[The serotonin transporter modulates decisional anhedonia]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-07-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.07.11.198622v1?rss=1">
<title>
<![CDATA[
Sparse parallel independent component analysis and its application to identify linked genomic and gray matter alterations underlying working memory impairment in attention-deficit/hyperactivity disorder 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.07.11.198622v1?rss=1"
</link>
<description><![CDATA[
Most psychiatric disorders are highly heritable and associated with altered brain structural and functional patterns. Data fusion analyses on brain imaging and genetics, one of which is parallel independent component analysis (pICA), enable the link of genomic factors to brain patterns. Due to the small to modest effect sizes of common genetic variants in psychiatric disorders, it is usually challenging to reliably separate disorder-related genetic factors from the rest of the genome with the typical size of clinical samples. To alleviate this problem, we propose sparse parallel independent component analysis (spICA) to leverage the sparsity of individual genomic sources. The sparsity is enforced by performing Hoyer projection on the estimated independent sources. Simulation results demonstrate that the proposed spICA yields improved detection of independent sources and imaging-genomic associations compared to pICA. We applied spICA to gray matter volume (GMV) and single nucleotide polymorphism (SNP) data of 341 unrelated adults, including 127 controls, 167 attention-deficit/hyperactivity disorder (ADHD) cases, and 47 unaffected siblings. We identified one SNP source significantly and positively associated with a GMV source in superior/middle frontal regions. This association was replicated with a smaller effect size in 317 adolescents from ADHD families, including 188 individuals with ADHD and 129 unaffected siblings. The association was found to be more significant in ADHD families than controls, and stronger in adults and older adolescents than younger ones. The identified GMV source in superior/middle frontal regions was not correlated with head motion parameters and its loadings (expression levels) were reduced in adolescent (but not adult) individuals with ADHD. This GMV source was associated with working memory deficits in both adult and adolescent individuals with ADHD. The identified SNP component highlights SNPs in genes encoding long non-coding RNAs and SNPs in genes MEF2C, CADM2, and CADPS2, which have known functions relevant for modulating neuronal substrates underlying high-level cognition in ADHD.
]]></description>
<dc:creator>Kuaikuai Duan</dc:creator>
<dc:creator>Jiayu Chen</dc:creator>
<dc:creator>Vince D. Calhoun</dc:creator>
<dc:creator>Wenhao Jiang</dc:creator>
<dc:creator>Kelly Rootes-Murdy</dc:creator>
<dc:creator>Gido Schoenmacker</dc:creator>
<dc:creator>Rogers F. Silva</dc:creator>
<dc:creator>Barbara Franke</dc:creator>
<dc:creator>Jan K. Buitelaar</dc:creator>
<dc:creator>Martine Hoogman</dc:creator>
<dc:creator>Jaap Oosterlaan</dc:creator>
<dc:creator>Pieter J Hoekstra</dc:creator>
<dc:creator>Dirk Heslenfeld</dc:creator>
<dc:creator>Catharina A Hartman</dc:creator>
<dc:creator>Emma Sprooten</dc:creator>
<dc:creator>Alejandro Arias-Vasquez</dc:creator>
<dc:creator>Jessica A. Turner</dc:creator>
<dc:creator>Jingyu Liu</dc:creator>
<dc:date>2020-07-12</dc:date>
<dc:identifier>doi:10.1101/2020.07.11.198622</dc:identifier>
<dc:title><![CDATA[Sparse parallel independent component analysis and its application to identify linked genomic and gray matter alterations underlying working memory impairment in attention-deficit/hyperactivity disorder]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-07-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.07.13.200543v1?rss=1">
<title>
<![CDATA[
Beat gestures influence which speech sounds you hear 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.07.13.200543v1?rss=1"
</link>
<description><![CDATA[
Beat gestures - spontaneously produced biphasic movements of the hand - are among the most frequently encountered co-speech gestures in human communication. They are closely temporally aligned to the prosodic characteristics of the speech signal, typically occurring on lexically stressed syllables. Despite their prevalence across speakers of the worlds languages, how beat gestures impact spoken word recognition is unclear. Can these simple  flicks of the hand influence speech perception? Across six experiments, we demonstrate that beat gestures influence the explicit and implicit perception of lexical stress (e.g., distinguishing OBject from obJECT), and in turn, can influence what vowels listeners hear. Thus, we provide converging evidence for a manual McGurk effect: even the simplest  flicks of the hands influence which speech sounds we hear.

SIGNIFICANCE STATEMENTBeat gestures are very common in human face-to-face communication. Yet we know little about their behavioral consequences for spoken language comprehension. We demonstrate that beat gestures influence the explicit and implicit perception of lexical stress, and, in turn, can even shape what vowels we think we hear. This demonstration of a manual McGurk effect provides some of the first empirical support for a recent multimodal, situated psycholinguistic framework of human communication, while challenging current models of spoken word recognition that do not yet incorporate multimodal prosody. Moreover, it has the potential to enrich human-computer interaction and improve multimodal speech recognition systems.
]]></description>
<dc:creator>Bosker, H. R.</dc:creator>
<dc:creator>Peeters, D.</dc:creator>
<dc:date>2020-07-13</dc:date>
<dc:identifier>doi:10.1101/2020.07.13.200543</dc:identifier>
<dc:title><![CDATA[Beat gestures influence which speech sounds you hear]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-07-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.07.16.206383v1?rss=1">
<title>
<![CDATA[
An in-vivo study of BOLD laminar responses as a function of echo time and static magnetic field strength 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.07.16.206383v1?rss=1"
</link>
<description><![CDATA[
Layer specific functional MRI requires high spatial resolution data. An approach often used for compensating for the poor signal to noise ratio (SNR) associated with small voxel sizes consists of integrating the signal from voxels at a given cortical depth over a patch of cortex. After this integration, physiological noise is expected to be the dominant noise source in the signal. In this context, the sensitivity gain in moving to higher static field strengths is expected to be lower than when thermal noise dominates. In this work, activation profiles in response to the same visual stimulus are compared at 1.5 T, 3 T and 7 T using a multi-echo, gradient echo (GE) FLASH sequence, with a 0.75 mm isotropic voxel size and the cortical integration approach. The results show that after integrating over a patch of cortex between 40 and 100 mm3(at 7 T and 1.5 T, respectively), the signal is in the physiological noise dominated regime, and that the obtained activation profiles are similar at the three different field strengths for equivalent echo times. The evolution of the resting-state signal over echo time indicates that BOLD-like noise is the dominant source of physiological noise. Consequently, the functional contrast to noise ratio is not strongly echo-time or field-strength dependent. The results show that compared to 7T, the gold standard, laminar GE-BOLD fMRI at lower field strengths is feasible at the cost of poorer spatial resolution (larger cortical integration extensions) and lower efficiency.
]]></description>
<dc:creator>Markuerkiaga, I.</dc:creator>
<dc:creator>Marques, J. p.</dc:creator>
<dc:creator>Bains, L. J.</dc:creator>
<dc:creator>Norris, D.</dc:creator>
<dc:date>2020-07-17</dc:date>
<dc:identifier>doi:10.1101/2020.07.16.206383</dc:identifier>
<dc:title><![CDATA[An in-vivo study of BOLD laminar responses as a function of echo time and static magnetic field strength]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-07-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.07.22.215939v1?rss=1">
<title>
<![CDATA[
DNA methylation signatures of aggression and closely related constructs: A meta-analysis of epigenome-wide studies across the lifespan 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.07.22.215939v1?rss=1"
</link>
<description><![CDATA[
DNA methylation profiles of aggressive behavior may capture lifetime cumulative effects of genetic, stochastic, and environmental influences associated with aggression. Here, we report the first large meta-analysis of epigenome-wide association studies (EWAS) of aggressive behavior (N=15,324 participants). In peripheral blood samples of 14,434 participants from 18 cohorts with mean ages ranging from 7 to 68 years, 13 methylation sites were significantly associated with aggression (alpha=1.2x10-7; Bonferroni correction). In cord blood samples of 2,425 children from five cohorts with aggression assessed at mean ages ranging from 4 to 7 years, 83% of these sites showed the same direction of association with childhood aggression (r=0.74, p=0.006) but no epigenome-wide significant sites were found. Top-sites (48 at a false discovery rate of 5% in the peripherl blood meta-analysis or in a combined meta-analysis of peripheral blood and cord blood) have been associated with chemical exposures, smoking, cognition, metabolic traits, and genetic variation (mQTLs). Three genes whose expression levels were associated with top-sites were previously linked to schizophrenia and general risk tolerance. At six CpGs, DNA methylation variation in blood mirrors variation in the brain. On average 44% (range=3-82%) of the aggression-methylation association was explained by current and former smoking and BMI. These findings point at loci that are sensitive to chemical exposures with potential implications for neuronal functions. We hope these results to be a starting point for studies leading to applications as peripheral biomarkers and to reveal causal relationships with aggression and related traits.
]]></description>
<dc:creator>van Dongen, J.</dc:creator>
<dc:creator>Hagenbeek, F. A.</dc:creator>
<dc:creator>Suderman, M.</dc:creator>
<dc:creator>Roetman, P. J.</dc:creator>
<dc:creator>Sugden, K.</dc:creator>
<dc:creator>Chiocchetti, A. G.</dc:creator>
<dc:creator>Ismail, K.</dc:creator>
<dc:creator>Mulder, R. H.</dc:creator>
<dc:creator>Hafferty, J.</dc:creator>
<dc:creator>Adams, M. J.</dc:creator>
<dc:creator>Walker, R.</dc:creator>
<dc:creator>Morris, S.</dc:creator>
<dc:creator>Lahti, J.</dc:creator>
<dc:creator>Kupers, L. K.</dc:creator>
<dc:creator>Escaramis, G.</dc:creator>
<dc:creator>Alemany, S.</dc:creator>
<dc:creator>Bonder, M. J.</dc:creator>
<dc:creator>Meijer, M.</dc:creator>
<dc:creator>Ip, H. F.</dc:creator>
<dc:creator>Jansen, R.</dc:creator>
<dc:creator>Baselmans, B. M. L.</dc:creator>
<dc:creator>Parmar, P.</dc:creator>
<dc:creator>Lowry, E.</dc:creator>
<dc:creator>Streit, F.</dc:creator>
<dc:creator>Sirignano, L.</dc:creator>
<dc:creator>Send, T.</dc:creator>
<dc:creator>Frank, J.</dc:creator>
<dc:creator>Jylhava, J.</dc:creator>
<dc:creator>Wang, Y.</dc:creator>
<dc:creator>Mishra, P. P.</dc:creator>
<dc:creator>Colins, O. F.</dc:creator>
<dc:creator>Corcoran, D.</dc:creator>
<dc:creator>Poulton, R.</dc:creator>
<dc:creator>Mill, J.</dc:creator>
<dc:creator>Hannon, E.</dc:creator>
<dc:creator>Arseneault, L.</dc:creator>
<dc:creator>Korhonen, T.</dc:creator>
<dc:creator>Vuoksimaa, E.</dc:creator>
<dc:creator>Felix, J.</dc:creator>
<dc:creator>Bakermans-Kranenburg, M.</dc:creator>
<dc:creator>Campbell, A.</dc:creator>
<dc:creator>Czamara, D.</dc:creator>
<dc:creator>Binder, E.</dc:creator>
<dc:creator>Corpel</dc:creator>
<dc:date>2020-07-22</dc:date>
<dc:identifier>doi:10.1101/2020.07.22.215939</dc:identifier>
<dc:title><![CDATA[DNA methylation signatures of aggression and closely related constructs: A meta-analysis of epigenome-wide studies across the lifespan]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-07-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.07.23.217042v1?rss=1">
<title>
<![CDATA[
SEPIA - SuscEptibility mapping PIpeline tool for phAse images 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.07.23.217042v1?rss=1"
</link>
<description><![CDATA[
Quantitative susceptibility mapping (QSM) is a physics-driven computational technique that has a high sensitivity in quantifying iron deposition based on MRI phase images. Furthermore, it has a unique ability to distinguish paramagnetic and diamagnetic contributions such as haemorrhage and calcification based on image contrast. These properties have contributed to a growing interest to use QSM not only in research but also in clinical applications. However, it is challenging to obtain high quality susceptibility map because of its ill-posed nature, especially for researchers who have less experience with QSM and the optimisation of its pipeline. In this paper, we present an open-source processing pipeline tool called SuscEptibility mapping PIpeline tool for phAse images (SEPIA) dedicated to the post-processing of MRI phase images and QSM. SEPIA connects various QSM toolboxes freely available in the field to offer greater flexibility in QSM processing. It also provides an interactive graphical user interface to construct and execute a QSM processing pipeline, simplifying the workflow in QSM research. The extendable design of SEPIA also allows developers to deploy their methods in the framework, providing a platform for developers and researchers to share and utilise the state-of-the-art methods in QSM.
]]></description>
<dc:creator>Chan, K.-S.</dc:creator>
<dc:creator>Marques, J. P.</dc:creator>
<dc:date>2020-07-24</dc:date>
<dc:identifier>doi:10.1101/2020.07.23.217042</dc:identifier>
<dc:title><![CDATA[SEPIA - SuscEptibility mapping PIpeline tool for phAse images]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-07-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.07.24.220319v1?rss=1">
<title>
<![CDATA[
Interneuron Specific Gamma Synchronization Encodes Uncertain Cues and Prediction Errors in Lateral Prefrontal and Anterior Cingulate Cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.07.24.220319v1?rss=1"
</link>
<description><![CDATA[
Inhibitory interneurons are believed to realize critical gating functions in cortical circuits, but it has been difficult to ascertain the content of gated information for well characterized interneurons in primate cortex. Here, we address this question by characterizing putative interneurons in primate prefrontal and anterior cingulate cortex while monkeys engaged in attention demanding reversal learning. We find that subclasses of narrow spiking neurons have a relative suppressive effect on the local circuit indicating they are inhibitory interneurons. One of these interneuron subclasses showed prominent firing rate modulations and (35-45 Hz) gamma synchronous spiking during periods of uncertainty in both, lateral prefrontal cortex (LPFC) and in anterior cingulate cortex (ACC). In LPFC this interneuron subclass activated when the uncertainty of attention cues was resolved during flexible learning, whereas in ACC it fired and gamma-synchronized when outcomes were uncertain and prediction errors were high during learning. Computational modeling of this interneuron-specific gamma band activity in simple circuit motifs suggests it could reflect a soft winner-take-all gating of information having high degree of uncertainty. Together, these findings elucidate an electrophysiologically-characterized interneuron subclass in the primate, that forms gamma synchronous networks in two different areas when resolving uncertainty during adaptive goal-directed behavior.
]]></description>
<dc:creator>Banaie Boroujeni, K.</dc:creator>
<dc:creator>Tiesinga, P.</dc:creator>
<dc:creator>Womelsdorf, T.</dc:creator>
<dc:date>2020-07-25</dc:date>
<dc:identifier>doi:10.1101/2020.07.24.220319</dc:identifier>
<dc:title><![CDATA[Interneuron Specific Gamma Synchronization Encodes Uncertain Cues and Prediction Errors in Lateral Prefrontal and Anterior Cingulate Cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-07-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.07.24.219386v1?rss=1">
<title>
<![CDATA[
Causal evidence for a double dissociation between object- and scene-selective regions of visual cortex: A pre-registered TMS replication study 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.07.24.219386v1?rss=1"
</link>
<description><![CDATA[
Natural scenes are characterized by individual objects as well as by global scene properties such as spatial layout. Functional neuroimaging research has shown that this distinction between object and scene processing is one of the main organizing principles of human high-level visual cortex. For example, object-selective regions, including the lateral occipital complex (LOC), were shown to represent object content (but not scene layout), while scene-selective regions, including the occipital place area (OPA), were shown to represent scene layout (but not object content). Causal evidence for a double dissociation between LOC and OPA in representing objects and scenes is currently limited, however. One TMS experiment, conducted in a relatively small sample (N=13), reported an interaction between LOC and OPA stimulation and object and scene recognition performance (Dilks et al., 2013). Here, we present a high-powered pre-registered replication of this study (N=72, including male and female human participants), using group-average fMRI coordinates to target LOC and OPA. Results revealed unambiguous evidence for a double dissociation between LOC and OPA: Relative to vertex stimulation, TMS over LOC selectively impaired the recognition of objects, while TMS over OPA selectively impaired the recognition of scenes. Furthermore, we found that these effects were stable over time and consistent across individual objects and scenes. These results show that LOC and OPA can be reliably and selectively targeted with TMS, even when defined based on group-average fMRI coordinates. More generally, they support the distinction between object and scene processing as an organizing principle of human high-level visual cortex.

Significance StatementOur daily-life environments are characterized both by individual objects and by global scene properties. The distinction between object and scene processing features prominently in visual cognitive neuroscience, with fMRI studies showing that this distinction is one of the main organizing principles of human high-level visual cortex. However, causal evidence for the selective involvement of object- and scene-selective regions in processing their preferred category is less conclusive. Here, testing a large sample (N=72) using an established paradigm and a pre-registered protocol, we found that TMS over object-selective cortex (LOC) selectively impaired object recognition while TMS over scene-selective cortex (OPA) selectively impaired scene recognition. These results provide conclusive causal evidence for the distinction between object and scene processing in human visual cortex.
]]></description>
<dc:creator>Wischnewski, M.</dc:creator>
<dc:creator>Peelen, M. V.</dc:creator>
<dc:date>2020-07-26</dc:date>
<dc:identifier>doi:10.1101/2020.07.24.219386</dc:identifier>
<dc:title><![CDATA[Causal evidence for a double dissociation between object- and scene-selective regions of visual cortex: A pre-registered TMS replication study]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-07-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.07.24.219709v1?rss=1">
<title>
<![CDATA[
Spatial and temporal context jointly modulate the sensory response within the ventral visual stream 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.07.24.219709v1?rss=1"
</link>
<description><![CDATA[
Both spatial and temporal context play an important role in visual perception and behavior. Humans can extract statistical regularities from both forms of context to help processing the present and to construct expectations about the future. Numerous studies have found reduced neural responses to expected stimuli compared to unexpected stimuli, for both spatial and temporal regularities. However, it is largely unclear whether and how these forms of context interact. In the current fMRI study, thirty-three human volunteers were exposed to object stimuli that could be expected or surprising in terms of their spatial and temporal context. We found a reliable independent contribution of both spatial and temporal context in modulating the neural response. Specifically, neural responses to stimuli in expected compared to unexpected contexts were suppressed throughout the ventral visual stream. Interestingly, the modulation by spatial context was stronger in magnitude and more reliable than modulations by temporal context. These results suggest that while both spatial and temporal context serve as a prior that can modulate sensory processing in a similar fashion, predictions of spatial context may be a more powerful modulator in the visual system.

Significance StatementBoth temporal and spatial context can affect visual perception, however it is largely unclear if and how these different forms of context interact in modulating sensory processing. When manipulating both temporal and spatial context expectations, we found that they jointly affected sensory processing, evident as a suppression of neural responses for expected compared to unexpected stimuli. Interestingly, the modulation by spatial context was stronger than that by temporal context. Together, our results suggest that spatial context may be a stronger modulator of neural responses than temporal context within the visual system. Thereby, the present study provides new evidence how different types of predictions jointly modulate perceptual processing.
]]></description>
<dc:creator>He, T.</dc:creator>
<dc:creator>Richter, D.</dc:creator>
<dc:creator>Wang, Z.</dc:creator>
<dc:creator>de Lange, F. P.</dc:creator>
<dc:date>2020-07-26</dc:date>
<dc:identifier>doi:10.1101/2020.07.24.219709</dc:identifier>
<dc:title><![CDATA[Spatial and temporal context jointly modulate the sensory response within the ventral visual stream]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-07-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.08.17.255034v1?rss=1">
<title>
<![CDATA[
Controlling for effects of confounding variables on machine learning predictions 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.08.17.255034v1?rss=1"
</link>
<description><![CDATA[
Machine learning predictive models are being used in neuroimaging to predict information about the task or stimuli or to identify potentially clinically useful biomarkers. However, the predictions can be driven by confounding variables unrelated to the signal of interest, such as scanner effect or head motion, limiting the clinical usefulness and interpretation of machine learning models. The most common method to control for confounding effects is regressing out the confounding variables separately from each input variable before machine learning modeling. However, we show that this method is insufficient because machine learning models can learn information from the data that cannot be regressed out. Instead of regressing out confounding effects from each input variable, we propose controlling for confounds post-hoc on the level of machine learning predictions. This allows partitioning of the predictive performance into the performance that can be explained by confounds and performance independent of confounds. This approach is flexible and allows for parametric and non-parametric confound adjustment. We show in real and simulated data that this method correctly controls for confounding effects even when traditional input variable adjustment produces false-positive findings.
]]></description>
<dc:creator>Dinga, R.</dc:creator>
<dc:creator>Schmaal, L.</dc:creator>
<dc:creator>Penninx, B. W.</dc:creator>
<dc:creator>Veltman, D. J.</dc:creator>
<dc:creator>Marquand, A. F.</dc:creator>
<dc:date>2020-08-18</dc:date>
<dc:identifier>doi:10.1101/2020.08.17.255034</dc:identifier>
<dc:title><![CDATA[Controlling for effects of confounding variables on machine learning predictions]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-08-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.08.14.251199v1?rss=1">
<title>
<![CDATA[
The Multivariate Genetic Architecture of Literacy-, Language- and Working Memory-related Abilities as Captured by Genome-wide Variation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.08.14.251199v1?rss=1"
</link>
<description><![CDATA[
There is genetic overlap between many measures of literacy, language and phonological working memory (PWM) though our knowledge of multivariate genetic architectures is incomplete. Here, we directly modeled genetic trait interrelationships in unrelated UK youth (8-13 years, N=6,453), as captured by genome-wide relationship matrices, using novel structural equation modeling techniques. We identified, besides shared genetic factors across different domains (explaining 91-97% genetic variance in literacy-related measures such as passage reading fluency, spelling, phonemic awareness, 44% in oral language and 53% in PWM), evidence for distinct cognitive abilities; trait-specific genetic influences ranged between 47% for PWM to 56% for oral language. Among reading fluency measures (non-word, word and passage reading), single-word reading was genetically most diverse. Multivariate genetic and residual covariance patterns showed concordant effect directionality, except for near-zero residual correlations between oral language and literacy-related abilities. These findings suggest differences in etiological mechanisms and trait modifiability even among genetically highly correlated skills.
]]></description>
<dc:creator>Shapland, C. Y.</dc:creator>
<dc:creator>Verhoef, E.</dc:creator>
<dc:creator>Davey Smith, G.</dc:creator>
<dc:creator>Fisher, S. E.</dc:creator>
<dc:creator>Verhulst, B.</dc:creator>
<dc:creator>Dale, P. S.</dc:creator>
<dc:creator>St Pourcain, B.</dc:creator>
<dc:date>2020-08-14</dc:date>
<dc:identifier>doi:10.1101/2020.08.14.251199</dc:identifier>
<dc:title><![CDATA[The Multivariate Genetic Architecture of Literacy-, Language- and Working Memory-related Abilities as Captured by Genome-wide Variation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-08-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.08.12.247841v1?rss=1">
<title>
<![CDATA[
Relations between hemispheric asymmetries of grey matter and auditory processing of spoken syllables in 281 healthy adults 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.08.12.247841v1?rss=1"
</link>
<description><![CDATA[
Most people have a right-ear advantage for the perception of spoken syllables, consistent with left hemisphere dominance for speech processing. However, there is considerable variation, with some people showing left-ear advantage. The extent to which this variation is reflected in brain structure remains unclear. We tested for relations between hemispheric asymmetries of auditory processing and of grey matter in 281 adults, using dichotic listening and voxel-based morphometry. This was the largest study of this issue to date. Per-voxel asymmetry indexes were derived for each participant following registration of brain magnetic resonance images to a template that was symmetrized. The asymmetry index derived from dichotic listening was related to grey matter asymmetry in clusters of voxels corresponding to the amygdala and cerebellum lobule VI. There was also a smaller, non-significant cluster in the posterior superior temporal gyrus, a region of auditory cortex. These findings contribute to the mapping of asymmetrical structure-function links in the human brain, and suggest that subcortical structures should be investigated in relation to hemispheric dominance for speech processing, in addition to auditory cortex.
]]></description>
<dc:creator>Guadalupe, T.</dc:creator>
<dc:creator>Kong, X.-Z.</dc:creator>
<dc:creator>Akkermans, S. E. A.</dc:creator>
<dc:creator>Fisher, S. E.</dc:creator>
<dc:creator>Francks, C.</dc:creator>
<dc:date>2020-08-13</dc:date>
<dc:identifier>doi:10.1101/2020.08.12.247841</dc:identifier>
<dc:title><![CDATA[Relations between hemispheric asymmetries of grey matter and auditory processing of spoken syllables in 281 healthy adults]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-08-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.08.11.246140v1?rss=1">
<title>
<![CDATA[
Sonlicromanol improves neuronal network dysfunction and transcriptome changes linked to m.3243A > G heteroplasmy in iPSC-derived neurons 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.08.11.246140v1?rss=1"
</link>
<description><![CDATA[
Mitochondrial encephalomyopathy, lactic acidosis and stroke-like episodes (MELAS) is often caused by an adenine to guanine mutation at m.3243 (m.3243A>G) of the MT-TL1 gene (tRNAleu(UUR)). To understand how this mutation affects the nervous system, we differentiated human induced-pluripotent stem cells (iPSCs) into excitatory neurons with normal (low heteroplasmy) and impaired (high heteroplasmy) mitochondrial function from MELAS patients with the m.3243A>G mutation. We combined micro-electrode array (MEA) measurements with RNA sequencing (MEA-seq) and found that the m.3243A>G mutation affects expression of genes involved in mitochondrial respiration- and presynaptic function, as well as non-cell autonomous processes in co-cultured astrocytes. Finally, we show that the clinical II stage drug sonlicromanol (KH176) improved neuronal network activity in a patient-specific manner when treatment is initiated early in development. This was intricately linked with changes in the neural transcriptome. Overall, MEA-seq is a powerful approach to identify mechanisms underlying the m.3243A>G mutation and to study the effect of pharmacological interventions in iPSC-derived neurons.

Highlights- High m.3243A>G heteroplasmy leads to lower neuronal network activity and synchronicity
- High heteroplasmy affects expression of genes involved in mitochondrial ATP production and the synaptic function / the presynaptic vesicle cycle
- High neuronal heteroplasmy non cell autonomously affects gene expression in healthy co-cultured astrocytes
- Sonlicromanol partially rescues neuronal network activity and transcriptome changes induced by high heteroplasmy


eTOC BlurbUsing human inducible pluripotent stem cell-derived neurons with high levels of m.3243A>G heteroplasmy, Klein Gunnewiek et al. show transcriptome changes underlying the functional neuronal network phenotype, and how sonlicromanol can partially improve both this neuronal network phenotype, and the transcriptome changes, in a patient-specific manner.
]]></description>
<dc:creator>Klein Gunnewiek, T. M.</dc:creator>
<dc:creator>Verboven, A. H. A.</dc:creator>
<dc:creator>Hogeweg, M.</dc:creator>
<dc:creator>Schoenmaker, C.</dc:creator>
<dc:creator>Renkema, H.</dc:creator>
<dc:creator>Beyrath, J.</dc:creator>
<dc:creator>Smeitink, J.</dc:creator>
<dc:creator>De Vries, B. B. A.</dc:creator>
<dc:creator>Kozicz, T.</dc:creator>
<dc:creator>'t Hoen, P. A. C.</dc:creator>
<dc:creator>Nadif Kasri, N. M.</dc:creator>
<dc:date>2020-08-12</dc:date>
<dc:identifier>doi:10.1101/2020.08.11.246140</dc:identifier>
<dc:title><![CDATA[Sonlicromanol improves neuronal network dysfunction and transcriptome changes linked to m.3243A > G heteroplasmy in iPSC-derived neurons]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-08-12</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.08.10.242958v1?rss=1">
<title>
<![CDATA[
Predictability in natural images determines V1 firing rates and synchronization: A deep neural network approach 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.08.10.242958v1?rss=1"
</link>
<description><![CDATA[
Predictive coding is an important candidate theory of self-supervised learning in the brain. Its central idea is that neural activity results from an integration and comparison of bottom-up inputs with contextual predictions, a process in which firing rates and synchronization may play distinct roles. Here, we quantified stimulus predictability for natural images based on self-supervised, generative neural networks. When the precise pixel structure of a stimulus falling into the V1 receptive field (RF) was predicted by the spatial context, V1 exhibited characteristic{gamma} -synchronization (30-80Hz), despite no detectable modulation of firing rates. In contrast to{gamma} , {beta}-synchronization emerged exclusively for unpredictable stimuli. Natural images with high structural predictability were characterized by high compressibility and low dimensionality. Yet, perceptual similarity was mainly determined by higher-level features of natural stimuli, not by the precise pixel structure. When higher-level features of the stimulus in the receptive field were predicted by the context, neurons showed a strong reduction in firing rates and an increase in surround suppression that was dissociated from synchronization patterns. These findings reveal distinct roles of synchronization and firing rates in the predictive coding of natural images.
]]></description>
<dc:creator>Uran, C.</dc:creator>
<dc:creator>Peter, A. S.</dc:creator>
<dc:creator>Lazar, A.</dc:creator>
<dc:creator>Barnes, W.</dc:creator>
<dc:creator>Klon-Lipok, J.</dc:creator>
<dc:creator>Shapcott, K. A.</dc:creator>
<dc:creator>Roese, R.</dc:creator>
<dc:creator>Fries, P.</dc:creator>
<dc:creator>Singer, W.</dc:creator>
<dc:creator>Vinck, M.</dc:creator>
<dc:date>2020-08-10</dc:date>
<dc:identifier>doi:10.1101/2020.08.10.242958</dc:identifier>
<dc:title><![CDATA[Predictability in natural images determines V1 firing rates and synchronization: A deep neural network approach]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-08-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.08.07.241497v1?rss=1">
<title>
<![CDATA[
Hidden population modes in social brain morphology: Its parts are more than its sum 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.08.07.241497v1?rss=1"
</link>
<description><![CDATA[
The complexity of social interactions is a defining property of the human species. Many social neuroscience experiments have sought to map  perspective taking,  empathy, and other canonical psychological constructs to distinguishable brain circuits. This predominant research paradigm was seldom complemented by bottom-up studies of the unknown sources of variation that add up to measures of social brain structure; perhaps due to a lack of large population datasets. We aimed at a systematic de-construction of social brain morphology into its elementary building blocks in the UK Biobank cohort (n=~10,000). Coherent patterns of structural co-variation were explored within a recent atlas of social brain locations, enabled through translating autoencoder algorithms from deep learning. The artificial neural networks learned rich subnetwork representations that became apparent from social brain variation at population scale. The learned subnetworks carried essential information about the co-dependence configurations between social brain regions, with the nucleus accumbens, medial prefrontal cortex, and temporoparietal junction embedded at the core. Some of the uncovered subnetworks contributed to predicting examined social traits in general, while other subnetworks helped predict specific facets of social functioning, such as feelings of loneliness. Our population-level evidence indicates that hidden subsystems of the social brain underpin interindividual variation in dissociable aspects of social lifestyle.
]]></description>
<dc:creator>Kiesow, H.</dc:creator>
<dc:creator>Spreng, R. N.</dc:creator>
<dc:creator>Holmes, A. J.</dc:creator>
<dc:creator>Chakravarty, M. M.</dc:creator>
<dc:creator>Marquand, A. F.</dc:creator>
<dc:creator>Yeo, B. T. T.</dc:creator>
<dc:creator>Bzdok, D.</dc:creator>
<dc:date>2020-08-07</dc:date>
<dc:identifier>doi:10.1101/2020.08.07.241497</dc:identifier>
<dc:title><![CDATA[Hidden population modes in social brain morphology: Its parts are more than its sum]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-08-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.08.07.241257v1?rss=1">
<title>
<![CDATA[
KANSL1 Deficiency Causes Neuronal Dysfunction by Oxidative Stress-Induced Autophagy 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.08.07.241257v1?rss=1"
</link>
<description><![CDATA[
Autophagy is a finely tuned process of programmed degradation and recycling of proteins and cellular components, which is crucial in neuronal function and synaptic integrity. Mounting evidence implicates chromatin remodelling in fine-tuning autophagy pathways. However, this epigenetic regulation is poorly understood in neurons. Here, we investigate the role in autophagy of KANSL1, a member of the nonspecific lethal complex, which acetylates histone H4 on lysine 16 (H4K16ac) to facilitate transcriptional activation. Loss-of-function of KANSL1 is strongly associated with the neurodevelopmental disorder Koolen-de Vries Syndrome (KdVS).

Starting from KANSL1-deficient human induced-pluripotent stem cells, both from KdVS patients and genome-edited lines, we identified superoxide dismutase 1, an antioxidant enzyme, to be significantly decreased, leading to a subsequent increase in oxidative stress and autophagosome accumulation. In KANSL1-deficient neurons, autophagosome accumulation at excitatory synapses resulted in reduced synaptic density, reduced AMPA receptor-mediated transmission and impaired neuronal network activity. Furthermore, we found that increased oxidative stress-mediated autophagosome accumulation leads to increased mTOR activation and decreased lysosome function, further preventing the clearing of autophagosomes. Finally, by pharmacologically reducing oxidative stress, we could rescue the aberrant autophagosome formation as well as synaptic and neuronal network activity in KANSL1-deficient neurons. Our findings thus point towards an important relation between oxidative stress-induced autophagy and synapse function, and demonstrate the importance of H4K16ac-mediated changes in chromatin structure to balance reactive oxygen species- and mTOR-dependent autophagy.
]]></description>
<dc:creator>Linda, K.</dc:creator>
<dc:creator>Lewerissa, E.</dc:creator>
<dc:creator>Verboven, A. H. A.</dc:creator>
<dc:creator>Gabriele, M.</dc:creator>
<dc:creator>Frega, M.</dc:creator>
<dc:creator>Klein Gunnewiek, T. M.</dc:creator>
<dc:creator>Devilee, L.</dc:creator>
<dc:creator>Ulferts, E.</dc:creator>
<dc:creator>Oudakker, A.</dc:creator>
<dc:creator>Schoenmaker, C.</dc:creator>
<dc:creator>van Bokhoven, H.</dc:creator>
<dc:creator>Schubert, D.</dc:creator>
<dc:creator>Testa, G.</dc:creator>
<dc:creator>Koolen, D.</dc:creator>
<dc:creator>de Vries, B. B. A.</dc:creator>
<dc:creator>Nadif Kasri, N.</dc:creator>
<dc:date>2020-08-07</dc:date>
<dc:identifier>doi:10.1101/2020.08.07.241257</dc:identifier>
<dc:title><![CDATA[KANSL1 Deficiency Causes Neuronal Dysfunction by Oxidative Stress-Induced Autophagy]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-08-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.08.05.228700v1?rss=1">
<title>
<![CDATA[
Individualized characterization of volumetric development in the preterm brain 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.08.05.228700v1?rss=1"
</link>
<description><![CDATA[
The diverse cerebral consequences of preterm birth create significant challenges for understanding pathogenesis or predicting later outcome. Instead of focusing on describing effects common to the group, comparing individual infants against robust normative data offers a powerful alternative to study brain maturation. Here we used Gaussian process regression to create normative curves characterising brain volumetric development in 274 term-born infants, modelling for age at scan and sex. We then compared 89 preterm infants scanned at termequivalent age to these normative charts, relating individual deviations from typical volumetric development to perinatal risk factors and later neurocognitive scores. To test generalisability, we used a second independent dataset comprising of 253 preterm infants scanned using different acquisition parameters and scanner. We describe rapid, non-uniform brain growth during the neonatal period. In both preterm cohorts, cerebral atypicalities were widespread, often multiple, and varied highly between individuals. Deviations from normative development were associated with respiratory support, nutrition, birth weight, and later neurocognition, demonstrating their clinical relevance. Group-level understanding of the preterm brain disguise a large degree of individual differences. We provide a method and normative dataset that offer a more precise characterisation of the cerebral consequences of preterm birth by profiling the individual neonatal brain.
]]></description>
<dc:creator>Dimitrova, R.</dc:creator>
<dc:creator>Arulkumaran, S.</dc:creator>
<dc:creator>Carney, O.</dc:creator>
<dc:creator>Chew, A.</dc:creator>
<dc:creator>Falconer, S.</dc:creator>
<dc:creator>Ciarrusta, J.</dc:creator>
<dc:creator>Wolfers, T.</dc:creator>
<dc:creator>Batalle, D.</dc:creator>
<dc:creator>Cordero-Grande, L.</dc:creator>
<dc:creator>Price, A. N.</dc:creator>
<dc:creator>Teixeira, R. P.</dc:creator>
<dc:creator>Hughes, E.</dc:creator>
<dc:creator>Egloff, A.</dc:creator>
<dc:creator>Hutter, J.</dc:creator>
<dc:creator>Makropoulos, A.</dc:creator>
<dc:creator>Robinson, E. C.</dc:creator>
<dc:creator>Schuh, A.</dc:creator>
<dc:creator>Vecchiato, K.</dc:creator>
<dc:creator>Steinweg, J. K.</dc:creator>
<dc:creator>Macleod, R.</dc:creator>
<dc:creator>Marquand, A. F.</dc:creator>
<dc:creator>McAlonan, G.</dc:creator>
<dc:creator>Rutherford, M. A.</dc:creator>
<dc:creator>Counsell, S. J.</dc:creator>
<dc:creator>Smith, S. M.</dc:creator>
<dc:creator>Rueckert, D.</dc:creator>
<dc:creator>Hajnal, J. V.</dc:creator>
<dc:creator>O'Muircheartaigh, J.</dc:creator>
<dc:creator>Edwards, A. D.</dc:creator>
<dc:date>2020-08-05</dc:date>
<dc:identifier>doi:10.1101/2020.08.05.228700</dc:identifier>
<dc:title><![CDATA[Individualized characterization of volumetric development in the preterm brain]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-08-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.08.04.236109v1?rss=1">
<title>
<![CDATA[
Frequency-specific transcranial neuromodulation of oscillatory alpha power alters and predicts human visuospatial attention performance 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.08.04.236109v1?rss=1"
</link>
<description><![CDATA[
Unilateral transcranial alternating current stimulation (tACS) at alpha frequency modulates the locus of spatial attention. However, the neural mechanisms by which tACS influences spatial attention remain poorly understood. Here, we applied high-definition tACS at the individual alpha frequency (IAF), two control frequencies (IAF+/-2Hz) and sham to the left posterior parietal cortex and measured its effects on visuospatial attention performance as well as alpha power (using electroencephalography, EEG). Our results revealed a leftward lateralization of alpha power relative to sham. At a high value of leftward alpha lateralization, we also observed a leftward attention bias, which differed from sham. Moreover, the magnitude of the alpha lateralization effect predicted the attention bias. These effects occurred for tACS at IAF but not for the control frequencies. This suggests that tACS operates through oscillatory interactions with ongoing brain rhythms in line with the synchronization theory. Our results also highlight the importance of personalized stimulation protocols, especially in potential clinical settings.
]]></description>
<dc:creator>Kemmerer, S. K.</dc:creator>
<dc:creator>Sack, A. T.</dc:creator>
<dc:creator>de Graaf, T. A.</dc:creator>
<dc:creator>ten Oever, S.</dc:creator>
<dc:creator>De Weerd, P.</dc:creator>
<dc:creator>Schuhmann, T.</dc:creator>
<dc:date>2020-08-05</dc:date>
<dc:identifier>doi:10.1101/2020.08.04.236109</dc:identifier>
<dc:title><![CDATA[Frequency-specific transcranial neuromodulation of oscillatory alpha power alters and predicts human visuospatial attention performance]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-08-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.08.04.236190v1?rss=1">
<title>
<![CDATA[
Estimation of Laminar BOLD Activation Profiles using Deconvolution with a Physiological Point Spread Function 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.08.04.236190v1?rss=1"
</link>
<description><![CDATA[
BackgroundThe specificity of gradient echo (GE)-BOLD laminar fMRI activation profiles is degraded by intracortical veins that drain blood from lower to upper cortical layers, propagating activation signal in the same direction. This work describes an approach to obtain layer specific profiles by deconvolving the measured profiles with a physiological Point Spread Function (PSF).

New MethodIt is shown that the PSF can be characterised by a TE-dependent peak to tail (p2t) value that is independent of cortical depth and can be estimated by simulation. An experimental estimation of individual p2t values and the sensitivity of the deconvolved profiles to variations in p2t is obtained using laminar data measured with a multi-echo 3D-FLASH sequence. These profiles are echo time dependent, but the underlying neuronal response is the same, allowing a data-based estimation of the PSF.

ResultsThe deconvolved profiles are highly similar to the gold-standard obtained from extremely high resolution 3D-EPI data, for a range of p2t values of 5-9, which covers both the empirically determined value (7.1) and the value obtained by simulation (6.3).

Comparison with Existing Method(s)Corrected profiles show a flatter shape across the cortex and a high level of similarity with the gold-standard, defined as a subset of profiles that are unaffected by intracortical veins.

ConclusionsWe conclude that deconvolution is a robust approach for removing the effect of signal propagation through intracortical veins. This makes it possible to obtain profiles with high laminar specificity while benefitting from the higher sensitivity and efficiency of GE-BOLD sequences.
]]></description>
<dc:creator>Markuerkiaga, I.</dc:creator>
<dc:creator>Marques, J. P.</dc:creator>
<dc:creator>Gallagher, T. E.</dc:creator>
<dc:creator>Norris, D. G.</dc:creator>
<dc:date>2020-08-05</dc:date>
<dc:identifier>doi:10.1101/2020.08.04.236190</dc:identifier>
<dc:title><![CDATA[Estimation of Laminar BOLD Activation Profiles using Deconvolution with a Physiological Point Spread Function]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-08-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.07.31.230342v1?rss=1">
<title>
<![CDATA[
Home-EEG assessment of possible compensatory mechanisms for sleep disruption in highly irregular shift workers - The ANCHOR study 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.07.31.230342v1?rss=1"
</link>
<description><![CDATA[
Study objectivesWhile poor sleep quality has been related to increased risk of Alzheimers disease, long-time shift workers (maritime pilots) did not manifest evidence of early Alzheimers disease in a recent study. We explored two hypotheses of possible compensatory mechanisms for sleep disruption: Increased efficiency in generating deep sleep during workweeks (model 1) and rebound sleep during rest weeks (model 2).

MethodsWe used data from ten male maritime pilots (mean age: 51.6{+/-}2.4 years) with a history of approximately 18 years of irregular shift work. Subjective sleep quality was assessed with the Pittsburgh Sleep Quality Index (PSQI). A single lead EEG-device was used to investigate sleep in the home/work environment, quantifying total sleep time (TST), deep sleep time (DST), and deep sleep time percentage (DST%). Using multilevel models, we studied the sleep architecture of maritime pilots over time, at the transition of a workweek to a rest week.

ResultsMaritime pilots reported worse sleep quality in workweeks compared to rest weeks (PSQI=8.2{+/-}2.2 vs. 3.9{+/-}2.0; p<0.001). Model 1 showed a trend towards an increase in DST% of 0.6% per day during the workweek (p=0.08). Model 2 did not display an increase in DST% in the rest week (p=0.87).

ConclusionsOur findings indicated that increased efficiency in generating deep sleep during workweeks is a more likely compensatory mechanism for sleep disruption in the maritime pilot cohort than rebound sleep during rest weeks. Compensatory mechanisms for poor sleep quality might mitigate sleep disruption-related risk of developing Alzheimers disease. These results should be used as a starting point for future studies including larger, more diverse populations of shift workers.
]]></description>
<dc:creator>Mentink, L.</dc:creator>
<dc:creator>Thomas, J.</dc:creator>
<dc:creator>Melis, R.</dc:creator>
<dc:creator>Olde Rikkert, M.</dc:creator>
<dc:creator>Overeem, S.</dc:creator>
<dc:creator>Claassen, J.</dc:creator>
<dc:date>2020-07-31</dc:date>
<dc:identifier>doi:10.1101/2020.07.31.230342</dc:identifier>
<dc:title><![CDATA[Home-EEG assessment of possible compensatory mechanisms for sleep disruption in highly irregular shift workers - The ANCHOR study]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-07-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.07.31.230185v1?rss=1">
<title>
<![CDATA[
A collaborative resource platform for non-human primate neuroimaging 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.07.31.230185v1?rss=1"
</link>
<description><![CDATA[
Neuroimaging non-human primates (NHPs) is a growing, yet highly specialized field of neuroscience. Resources that were primarily developed for human neuroimaging often need to be significantly adapted for use with NHPs or other animals, which has led to an abundance of custom, in-house solutions. In recent years, the global NHP neuroimaging community has made significant efforts to transform the field towards more open and collaborative practices. Here we present the PRIMatE Resource Exchange (PRIME-RE), a new collaborative online platform for NHP neuroimaging. PRIME-RE is a dynamic community-driven hub for the exchange of practical knowledge, specialized analytical tools, and open data repositories, specifically related to NHP neuroimaging. PRIME-RE caters to both researchers and developers who are either new to the field, looking to stay abreast of the latest developments, or seeking to collaboratively advance the field.
]]></description>
<dc:creator>Messinger, A.</dc:creator>
<dc:creator>Sirmpilatze, N.</dc:creator>
<dc:creator>Heuer, K.</dc:creator>
<dc:creator>Loh, K. K.</dc:creator>
<dc:creator>Mars, R.</dc:creator>
<dc:creator>Sein, J.</dc:creator>
<dc:creator>Xu, T.</dc:creator>
<dc:creator>Glen, D.</dc:creator>
<dc:creator>Jung, B.</dc:creator>
<dc:creator>Seidlitz, J.</dc:creator>
<dc:creator>Taylor, P.</dc:creator>
<dc:creator>Toro, R.</dc:creator>
<dc:creator>Garza-Villareal, E.</dc:creator>
<dc:creator>Sponheim, C.</dc:creator>
<dc:creator>Wang, X.</dc:creator>
<dc:creator>Benn, A.</dc:creator>
<dc:creator>Cagna, B.</dc:creator>
<dc:creator>Dadarwal, R.</dc:creator>
<dc:creator>Evrard, H.</dc:creator>
<dc:creator>Garcia-Saldivar, P.</dc:creator>
<dc:creator>Giavasis, S.</dc:creator>
<dc:creator>Hartig, R.</dc:creator>
<dc:creator>Lepage, C.</dc:creator>
<dc:creator>Liu, C.</dc:creator>
<dc:creator>Majka, P.</dc:creator>
<dc:creator>Merchant, H.</dc:creator>
<dc:creator>Milham, M.</dc:creator>
<dc:creator>Rosa, M.</dc:creator>
<dc:creator>Tasserie, J.</dc:creator>
<dc:creator>Uhrig, L.</dc:creator>
<dc:creator>Margulies, D.</dc:creator>
<dc:creator>Klink, P. C.</dc:creator>
<dc:date>2020-07-31</dc:date>
<dc:identifier>doi:10.1101/2020.07.31.230185</dc:identifier>
<dc:title><![CDATA[A collaborative resource platform for non-human primate neuroimaging]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-07-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.08.27.270249v1?rss=1">
<title>
<![CDATA[
Dynamics of neural microstates in the VTA-striatal-prefrontal loop during novelty exploration in the rat 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.08.27.270249v1?rss=1"
</link>
<description><![CDATA[
EEG microstates refer to quasi-stable spatial patterns of scalp potentials, and their dynamics have been linked to cognitive and behavioral states. Neural activity at single and multiunit levels also exhibit spatiotemporal coordination, but this spatial scale is difficult to relate to EEG. Here, we translated EEG microstate analysis to triple-area local field potential (LFP) recordings from up to 192 electrodes in rats to investigate the mesoscopic dynamics of neural microstates within and across brain regions.

We performed simultaneous recordings from the prefrontal cortex (PFC), striatum (STR), and ventral tegmental area (VTA) during awake behavior (object novelty and exploration). We found that the LFP data can be accounted for by multiple, recurring, quasi-stable spatial activity patterns with an average period of stability of ~60-100 ms. The top four maps accounted for 60-80% of the total variance, compared to ~25% for shuffled data. Cross-correlation of the microstate time-series across brain regions revealed rhythmic patterns of microstate activations, which we interpret as a novel indicator of inter-regional, mesoscale synchronization. Furthermore, microstate features, and patterns of temporal correlations across microstates, were modulated by behavioural states such as movement and novel object exploration. These results support the existence of a functional mesoscopic organization across multiple brain areas, and open up the opportunity to investigate their relation to EEG microstates, of particular interest to the human research community.

Significance StatementThe coordination of neural activity across the entire brain has remained elusive. Here we combine large-scale neural recordings at fine spatial resolution with the analysis of microstates, i.e. short-lived, recurring spatial patterns of neural activity. We demonstrate that the local activity in different brain areas can be accounted for by only a few microstates per region. These microstates exhibited temporal dynamics that were correlated across regions in rhythmic patterns. We demonstrate that these microstates are linked to behavior and exhibit different properties in the frequency domain during different behavioural states. In summary, LFP microstates provide an insightful approach to studying both mesoscopic and large-scale brain activation within and across regions.
]]></description>
<dc:creator>Mishra, A.</dc:creator>
<dc:creator>Marzban, N.</dc:creator>
<dc:creator>Cohen, M. X.</dc:creator>
<dc:creator>Englitz, B.</dc:creator>
<dc:date>2020-08-28</dc:date>
<dc:identifier>doi:10.1101/2020.08.27.270249</dc:identifier>
<dc:title><![CDATA[Dynamics of neural microstates in the VTA-striatal-prefrontal loop during novelty exploration in the rat]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-08-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.08.26.264168v1?rss=1">
<title>
<![CDATA[
The cognitive effects of a promised bonus do not depend on dopamine synthesis capacity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.08.26.264168v1?rss=1"
</link>
<description><![CDATA[
Reward motivation is known to enhance cognitive control. However, detrimental effects have also been observed, which have been attributed to overdosing of already high baseline dopamine levels by further dopamine increases elicited by reward cues. Aarts et al. (2014) indeed demonstrated, in 14 individuals, that reward effects depended on striatal dopamine synthesis capacity, measured with [18F]FMT-PET: promised reward improved Stroop control in low-dopamine individuals, while impairing it in high-dopamine individuals. Here, we aimed to assess this same effect in 44 new participants, who had previously undergone an [18F]DOPA-PET scan to quantify dopamine synthesis capacity. This sample performed the exact same rewarded Stroop paradigm as in the prior study. However, we did not find any correlation between reward effects on cognitive control and striatal dopamine synthesis capacity. The discrepancy between the current and our previous findings might reflect the use of different radiotracers for indexing dopamine synthesis capacity.

STATEMENT OF RELEVANCEReward motivation is generally thought to enhance cognitive control, but paradoxical negative effects of rewards on cognitive control have also been observed. A previous PET study demonstrated that reward effects on Stroop control depended on baseline striatal dopamine synthesis capacity, indexed by uptake of the radiotracer [18F]FMT. The sample size is this study was very small for a between-subject correlational design. Replicating the exact same Stroop paradigm within a larger sample is therefore crucial to robustly establish the mechanistic link between incentive motivation and cognitive control and advancing our understanding of who chokes under pressure and why, a topic of great societal relevance today. The present study did not reveal any correlation between reward effects on cognitive control and striatal dopamine synthesis capacity, indexed with [18F]FDOPA-PET. Future studies might consider putative differential sensitivity of the radiotracer [18F]FMT and [18F]FDOPA, while also addressing other indices of dopamine transmission.
]]></description>
<dc:creator>Hofmans, L.</dc:creator>
<dc:creator>van den Bosch, R.</dc:creator>
<dc:creator>Määttä, J.</dc:creator>
<dc:creator>Verkes, R.-J.</dc:creator>
<dc:creator>Aarts, E.</dc:creator>
<dc:creator>Cools, R.</dc:creator>
<dc:date>2020-08-27</dc:date>
<dc:identifier>doi:10.1101/2020.08.26.264168</dc:identifier>
<dc:title><![CDATA[The cognitive effects of a promised bonus do not depend on dopamine synthesis capacity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-08-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.08.25.264382v1?rss=1">
<title>
<![CDATA[
Synchronization between keyboard typing and neural oscillations 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.08.25.264382v1?rss=1"
</link>
<description><![CDATA[
Rhythmic neural activity synchronizes with certain rhythmic behaviors, such as breathing, sniffing, saccades, and speech. The extent to which neural oscillations synchronize with higher-level and more complex behaviors is largely unknown. Here we investigated electrophysiological synchronization with keyboard typing, which is an omnipresent behavior daily engaged by an uncountably large number of people. Keyboard typing is rhythmic with frequency characteristics roughly the same as neural oscillatory dynamics associated with cognitive control, notably through midfrontal theta (4 -7 Hz) oscillations. We tested the hypothesis that synchronization occurs between typing and midfrontal theta, and breaks down when errors are committed. Thirty healthy participants typed words and sentences on a keyboard without visual feedback, while EEG was recorded. Typing rhythmicity was investigated by inter-keystroke interval analyses and by a kernel density estimation method. We used a multivariate spatial filtering technique to investigate frequency-specific synchronization between typing and neuronal oscillations. Our results demonstrate theta rhythmicity in typing (around 6.5 Hz) through the two different behavioral analyses. Synchronization between typing and neuronal oscillations occurred at frequencies ranging from 4 to 15 Hz, but to a larger extent for lower frequencies. However, peak synchronization frequency was idiosyncratic across subjects, therefore not specific to theta nor to midfrontal regions, and correlated somewhat with peak typing frequency. Errors and trials associated with stronger cognitive control were not associated with changes in synchronization at any frequency. As a whole, this study shows that brain-behavior synchronization does occur during keyboard typing but is not specific to midfrontal theta.

Significance statementEvery day, millions of people type on keyboards. Keyboard typing is a rhythmic behavior, with inter-keystroke-intervals of around 135 ms (~7 Hz), which is roughly the same frequency as the brain rhythm implicated in cognitive control ("theta" band, ~6 Hz). Here we investigated the hypothesis that the EEG signature of cognitive control is synchronized with keyboard typing. By recording EEG during typing in 30 healthy subjects we showed that keyboard typing indeed follows theta rhythmicity, and that synchronization between typing and neural oscillations occurs. However, synchronization was not limited to theta but occurred at frequencies ranging from 4 to 15 Hz, and in several regions. Brain-behavior synchronization during typing thus seems more nuanced and complex than we originally hypothesized.
]]></description>
<dc:creator>Duprez, J.</dc:creator>
<dc:creator>Mitchel, S.</dc:creator>
<dc:creator>Drijvers, L.</dc:creator>
<dc:creator>Cohen, M. X.</dc:creator>
<dc:date>2020-08-25</dc:date>
<dc:identifier>doi:10.1101/2020.08.25.264382</dc:identifier>
<dc:title><![CDATA[Synchronization between keyboard typing and neural oscillations]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-08-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.08.25.266122v1?rss=1">
<title>
<![CDATA[
Multivariate associative patterns between the gut microbiota and large-scale brain network connectivity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.08.25.266122v1?rss=1"
</link>
<description><![CDATA[
Research on the gut-brain axis has accelerated substantially over the course of the last years. Many reviews have outlined the important implications of understanding the relation of the gut microbiota with human brain function and behavior. One substantial drawback in integrating gut microbiome and brain data is the lack of integrative multivariate approaches that enable capturing variance in both modalities simultaneously. To address this issue, we applied a linked independent component analysis (LICA) to microbiota and brain connectivity data.

We analyzed data from 58 healthy females (mean age = 21.5 years). Magnetic Resonance Imaging data were acquired using resting state functional imaging data. The assessment of gut microbial composition from feces was based on sequencing of the V4 16S rRNA gene region. We used the LICA model to simultaneously factorize the subjects large-scale brain networks and microbiome relative abundance data into 10 independent components of spatial and abundance variation.

LICA decomposition resulted in four components with non-marginal contribution of the microbiota data. The default mode network featured strongly in three components, whereas the two-lateralized fronto-parietal attention networks contributed to one component. The executive-control (with the default mode) network was associated to another component. We found the abundance of Prevotella genus was associated to the strength of expression of all networks, whereas Bifidobacterium was associated with the default mode and frontoparietal-attention networks.

We provide the first exploratory evidence for multivariate associative patterns between the gut microbiota and brain network connectivity in healthy humans, taking into account the complexity of both systems.
]]></description>
<dc:creator>Kohn, N.</dc:creator>
<dc:creator>Szopinska-Tokov, J.</dc:creator>
<dc:creator>Llera Arenas, A.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>Arias-Vasquez, A.</dc:creator>
<dc:creator>Aarts, E.</dc:creator>
<dc:date>2020-08-25</dc:date>
<dc:identifier>doi:10.1101/2020.08.25.266122</dc:identifier>
<dc:title><![CDATA[Multivariate associative patterns between the gut microbiota and large-scale brain network connectivity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-08-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.08.25.265975v1?rss=1">
<title>
<![CDATA[
No exploitation of temporal predictive context during visual search 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.08.25.265975v1?rss=1"
</link>
<description><![CDATA[
The human visual system can rapidly extract regularities from our visual environment, generating predictive context. It has been shown that spatial predictive context can be used during visual search. We set out to see whether observers can additionally exploit temporal predictive context, using an extended version of a contextual cueing paradigm. Though we replicated the contextual cueing effect, repeating search scenes in a structured order versus a random order yielded no additional behavioural benefit. This was true both for participants who were sensitive to spatial predictive context, and for those who were not. We argue that spatial predictive context during visual search is more readily learned and subsequently exploited than temporal predictive context, potentially rendering the latter redundant. In conclusion, unlike spatial context, temporal context is not automatically extracted and used during visual search.
]]></description>
<dc:creator>Bouwkamp, F. G.</dc:creator>
<dc:creator>de Lange, F. P.</dc:creator>
<dc:creator>Spaak, E.</dc:creator>
<dc:date>2020-08-25</dc:date>
<dc:identifier>doi:10.1101/2020.08.25.265975</dc:identifier>
<dc:title><![CDATA[No exploitation of temporal predictive context during visual search]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-08-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.09.04.283002v1?rss=1">
<title>
<![CDATA[
Similarity of brain activity patterns during learning and subsequent resting state predicts memory consolidation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.09.04.283002v1?rss=1"
</link>
<description><![CDATA[
Long-term memory depends on memory consolidation that seems to rely on learning-induced changes in the brain activity. Here, we introduced a novel approach analyzing continuous EEG data to study learning-induced changes as well as trait-like characteristics in brain activity underlying consolidation. Thirty-one healthy young adults performed a learning task and their performance was retested after a short (~1h) delay, that enabled us to investigate the consolidation of serial-order and probability information simultaneously. EEG was recorded during a pre- and post-learning rest period and during learning. To investigate the brain activity associated with consolidation performance, we quantified similarities in EEG functional connectivity of learning and pre-learning rest (baseline similarity) as well as learning and post-learning rest (post-learning similarity). While comparable patterns of these two could indicate trait-like similarities, changes in similarity from baseline to post-learning could indicate learning-induced changes, possibly spontaneous reactivation. Individuals with higher learning-induced changes in alpha frequency connectivity (8.5-9.5 Hz) showed better consolidation of serial-order information. This effect was stronger for more distant channels, highlighting the role of long-range centro-parietal networks underlying the consolidation of serial-order information. The consolidation of probability information was associated with learning-induced changes in delta frequency connectivity (2.5-3 Hz) and seemed to be dependent on more local, short-range connections. Beyond these associations with learning-induced changes, we also found substantial overlap between the baseline and post-learning similarity and their associations with consolidation performance, indicating that stable (trait-like) differences in functional connectivity networks may also be crucial for memory consolidation.

Significance statementWe studied memory consolidation in humans by characterizing how similarity in neural oscillatory patterns during learning and rest periods supports consolidation. Previous studies on similarity focused on learning-induced changes (including reactivation) and neglected the stable individual characteristics that are present over resting periods and learning. Moreover, learning-induced changes are predominantly studied invasively in rodents or with neuroimaging or event-related electrophysiology techniques in humans. Here, we introduced a novel approach that enabled us 1) to reveal both learning-induced changes and trait-like individual differences in brain activity and 2) to study learning-induced changes in humans by analyzing continuous EEG. We investigated the consolidation of two types of information and revealed distinct learning-induced changes and trait-like characteristics underlying the different memory processes.
]]></description>
<dc:creator>Zavecz, Z.</dc:creator>
<dc:creator>Janacsek, K.</dc:creator>
<dc:creator>Simor, P.</dc:creator>
<dc:creator>Cohen, M. X.</dc:creator>
<dc:creator>Nemeth, D.</dc:creator>
<dc:date>2020-09-04</dc:date>
<dc:identifier>doi:10.1101/2020.09.04.283002</dc:identifier>
<dc:title><![CDATA[Similarity of brain activity patterns during learning and subsequent resting state predicts memory consolidation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-09-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.09.03.281162v1?rss=1">
<title>
<![CDATA[
Bayesian Connective Field Modeling: a Markov Chain Monte Carlo approach. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.09.03.281162v1?rss=1"
</link>
<description><![CDATA[
The majority of neurons in the human brain process signals from neurons elsewhere in the brain. Connective Field (CF) modeling is a biologically-grounded method to describe this essential aspect of the brains circuitry. It allows characterizing the response of a population of neurons in terms of the activity in another part of the brain. CF modeling translates the concept of the receptive field (RF) into the domain of connectivity by assessing the spatial dependency between signals in distinct cortical visual field areas. Standard CF model estimation has some intrinsic limitations in that it cannot estimate the uncertainty associated with each of its parameters. Obtaining the uncertainty will allow identification of model biases, e.g. related to an over- or under-fitting or a co-dependence of parameters, thereby improving the CF prediction. To enable this, here we present a Bayesian framework for the CF model. Using a Markov Chain Monte Carlo (MCMC) approach, we estimate the underlying posterior distribution of the CF parameters and consequently, quantify the uncertainty associated with each estimate. We applied the method and its new Bayesian features to characterize the cortical circuitry of the early human visual cortex of 12 healthy participants that were assessed using 3T fMRI. In addition, we show how the MCMC approach enables the use of effect size (beta) as a data-driven parameter to retain relevant voxels for further analysis. Finally, we demonstrate how our new method can be used to compare different CF models. Our results show that single Gaussian models are favoured over differences of Gaussians (i.e. center-surround) models, suggesting that the cortico-cortical connections of the early visual system do not possess center-surround organisation. We conclude that our new Bayesian CF framework provides a comprehensive tool to improve our fundamental understanding of the human cortical circuitry in health and disease.

Highlights{square} We present and validate a Bayesian CF framework based on a MCMC approach.
{square}The MCMC CF approach quantifies the model uncertainty associated with each CF parameter.
{square}We show how to use effect size beta as a data-driven threshold to retain relevant voxels.
{square}The cortical connective fields of the human early visual system are best described by a single, circular symmetric, Gaussian.
]]></description>
<dc:creator>Invernizzi, A.</dc:creator>
<dc:creator>Haak, K. V.</dc:creator>
<dc:creator>Carvalho, J.</dc:creator>
<dc:creator>Renken, R.</dc:creator>
<dc:creator>Cornelissen, F.</dc:creator>
<dc:date>2020-09-03</dc:date>
<dc:identifier>doi:10.1101/2020.09.03.281162</dc:identifier>
<dc:title><![CDATA[Bayesian Connective Field Modeling: a Markov Chain Monte Carlo approach.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-09-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.08.28.262550v1?rss=1">
<title>
<![CDATA[
Serotonergic Effects on Interoception 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.08.28.262550v1?rss=1"
</link>
<description><![CDATA[
Interoception is the signalling, perception, and interpretation of internal physiological states. Much of the psychopharmacology of interoception is still undiscovered. However, psychiatric disorders associated with changes of interoception, including depressive, anxiety, and eating disorders are often treated with selective serotonin reuptake inhibitors (SSRIs). The causal effect of acute changes of serotonin transmission on interoceptive cognition was tested by a within-participant, crossover, placebo-controlled study. Forty-seven healthy human volunteers (31 female, 16 male) were tested both on and off a 20mg oral dose of the commonly prescribed SSRI citalopram. For each randomly ordered session, participants made judgments on the synchrony of their heartbeat to auditory tones and expressed confidence in each of these judgments. Citalopram enhanced insight into the likelihood that ones interoceptive judgment had been correct, driven primarily by enhanced confidence for correct responses. This effect was independent of measured cardiac and subjective effects of the drug. This novel result is evidence that acute serotonin changes can alter metacognitive insight into the reliability of inferences based on interoceptive information, which is a foundation for considering effects of serotonin on cognition and emotion in terms of effective top-down regulation of interoceptive influence on mental states.
]]></description>
<dc:creator>Livermore, J. J. A.</dc:creator>
<dc:creator>Holmes, C. L.</dc:creator>
<dc:creator>Moga, G.</dc:creator>
<dc:creator>Adamatzky, K.</dc:creator>
<dc:creator>Critchley, H.</dc:creator>
<dc:creator>Garfinkel, S.</dc:creator>
<dc:creator>Campbell-Meiklejohn, D.</dc:creator>
<dc:date>2020-08-31</dc:date>
<dc:identifier>doi:10.1101/2020.08.28.262550</dc:identifier>
<dc:title><![CDATA[Serotonergic Effects on Interoception]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-08-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.09.04.282715v1?rss=1">
<title>
<![CDATA[
Phasic modulation of visual representations during sustained attention 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.09.04.282715v1?rss=1"
</link>
<description><![CDATA[
Sustained attention has long been thought to benefit perception in a continuous fashion, but recent evidence suggests that it affects perception in a discrete, rhythmic way. Periodic fluctuations in behavioral performance over time, and modulations of behavioral performance by the phase of spontaneous oscillatory brain activity point to an attentional sampling rate in the theta or alpha frequency range. We investigated whether such discrete sampling by attention is reflected in periodic fluctuations in the decodability of visual stimulus orientation from magnetoencephalographic (MEG) brain signals.

In this exploratory study, human subjects attended one of two grating stimuli while MEG was being recorded. We assessed the strength of the visual representation of the attended stimulus using a support vector machine (SVM) to decode the orientation of the grating (clockwise vs. counterclockwise) from the MEG signal. We tested whether decoder performance depended on the theta/alpha phase of local brain activity. While the phase of ongoing activity in visual cortex did not modulate decoding performance, theta/alpha phase of activity in the FEF and parietal cortex, contralateral to the attended stimulus did modulate decoding performance. These findings suggest that phasic modulations of visual stimulus representations in the brain are caused by frequency- specific top-down activity in the fronto-parietal attention network.
]]></description>
<dc:creator>van Es, M. W. J.</dc:creator>
<dc:creator>Marshall, T. R.</dc:creator>
<dc:creator>Spaak, E.</dc:creator>
<dc:creator>Jensen, O.</dc:creator>
<dc:creator>Schoffelen, J.-M.</dc:creator>
<dc:date>2020-09-04</dc:date>
<dc:identifier>doi:10.1101/2020.09.04.282715</dc:identifier>
<dc:title><![CDATA[Phasic modulation of visual representations during sustained attention]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-09-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.09.04.283655v1?rss=1">
<title>
<![CDATA[
Genome Methylation Predicts Age and Longevity of Bats 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.09.04.283655v1?rss=1"
</link>
<description><![CDATA[
Exceptionally long-lived species, including many bats, rarely show overt signs of aging, making it difficult to determine why species differ in lifespan. Here, we use DNA methylation (DNAm) profiles from 712 known-age bats, representing 26 species, to identify epigenetic changes associated with age and longevity. We demonstrate that DNAm accurately predicts chronological age. Across species, longevity is negatively associated with the rate of DNAm change at age-associated sites. Furthermore, analysis of several bat genomes reveals that hypermethylated age- and longevity-associated sites are disproportionately located in promoter regions of key transcription factors (TF) and enriched for histone and chromatin features associated with transcriptional regulation. Predicted TF binding site motifs and enrichment analyses indicate that age-related methylation change is influenced by developmental processes, while longevity-related DNAm change is associated with innate immunity or tumorigenesis genes, suggesting that bat longevity results from augmented immune response and cancer suppression.
]]></description>
<dc:creator>Wilkinson, G. S.</dc:creator>
<dc:creator>Adams, D. M.</dc:creator>
<dc:creator>Arnold, B. D.</dc:creator>
<dc:creator>Ball, H. C.</dc:creator>
<dc:creator>Breeze, C. E.</dc:creator>
<dc:creator>Carter, G. G.</dc:creator>
<dc:creator>Cooper, L. N.</dc:creator>
<dc:creator>Dechmann, D. K. N.</dc:creator>
<dc:creator>Devanna, P. S.</dc:creator>
<dc:creator>Fasel, N. J.</dc:creator>
<dc:creator>Galazyuk, A. V.</dc:creator>
<dc:creator>Gunther, L.</dc:creator>
<dc:creator>Haghani, A.</dc:creator>
<dc:creator>Li, C. Z.</dc:creator>
<dc:creator>Lu, A.</dc:creator>
<dc:creator>Hurme, E.</dc:creator>
<dc:creator>Jones, G.</dc:creator>
<dc:creator>Knornschild, M.</dc:creator>
<dc:creator>Lattenkamp, E. Z.</dc:creator>
<dc:creator>Mayer, F.</dc:creator>
<dc:creator>Medellin, R. A.</dc:creator>
<dc:creator>Nagy, M.</dc:creator>
<dc:creator>Pope, B.</dc:creator>
<dc:creator>Power, M. L.</dc:creator>
<dc:creator>Ransome, R. D.</dc:creator>
<dc:creator>Reinhardt, J. A.</dc:creator>
<dc:creator>Teeling, E. C.</dc:creator>
<dc:creator>Vernes, S. C.</dc:creator>
<dc:creator>Zamora-Mejias, D.</dc:creator>
<dc:creator>Zhang, J.</dc:creator>
<dc:creator>Zoller, J.</dc:creator>
<dc:creator>Horvath, S. C.</dc:creator>
<dc:date>2020-09-04</dc:date>
<dc:identifier>doi:10.1101/2020.09.04.283655</dc:identifier>
<dc:title><![CDATA[Genome Methylation Predicts Age and Longevity of Bats]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-09-04</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.09.17.299743v1?rss=1">
<title>
<![CDATA[
Dual strategies in human confidence judgments 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.09.17.299743v1?rss=1"
</link>
<description><![CDATA[
Although confidence is commonly believed to be an essential element in decision making, it remains unclear what gives rise to ones sense of confidence. Recent Bayesian theories propose that confidence is computed, in part, from the degree of uncertainty in sensory evidence. Alternatively, observers can use physical properties of the stimulus as a heuristic to confidence. In the current study, we developed ideal observer models for either hypothesis and compared their predictions against human data obtained from psychophysical experiments. Participants reported the orientation of a stimulus, and their confidence in this estimate, under varying levels of internal and external noise. As predicted by the Bayesian model, we found a consistent link between confidence and behavioral variability for a given stimulus orientation. Confidence was higher when orientation estimates were more precise, for both internal and external sources of noise. However, we observed the inverse pattern when comparing between stimulus orientations: although observers gave more precise orientation estimates for cardinal orientations (a phenomenon known as the oblique effect), they were more confident about oblique orientations. We show that these results are well explained by a strategy to confidence that is based on the perceived amount of noise in the stimulus. Altogether, our results suggest that confidence is not always computed from the degree of uncertainty in ones perceptual evidence, but can instead be based on visual cues that function as simple heuristics to confidence.
]]></description>
<dc:creator>Bertana, A.</dc:creator>
<dc:creator>Chetverikov, A.</dc:creator>
<dc:creator>van Bergen, R. S.</dc:creator>
<dc:creator>Ling, S.</dc:creator>
<dc:creator>Jehee, J.</dc:creator>
<dc:date>2020-09-19</dc:date>
<dc:identifier>doi:10.1101/2020.09.17.299743</dc:identifier>
<dc:title><![CDATA[Dual strategies in human confidence judgments]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-09-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.09.18.303263v1?rss=1">
<title>
<![CDATA[
Relating neural oscillations to laminar fMRI connectivity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.09.18.303263v1?rss=1"
</link>
<description><![CDATA[
Laminar fMRI holds the potential to study connectivity at the laminar level in humans. Here we analyze simultaneously recorded EEG and high resolution fMRI data to investigate how EEG power modulations, induced by a task with an attentional component, relate to changes in fMRI laminar connectivity between and within brain regions. Our results indicate that our task induced decrease in beta power relates to an increase in deep-to-deep layer coupling between regions and to an increase in deep/middle-to-superficial layer connectivity within brain regions. The attention-related alpha power decrease predominantly relates to reduced connectivity between deep and superficial layers within brain regions, since, unlike beta power, alpha power was found to be positively correlated to connectivity. We observed no strong relation between laminar connectivity and gamma band oscillations. These results indicate that especially beta band, and to a lesser extent alpha band oscillations relate to laminar specific fMRI connectivity. These differential effects for the alpha and beta bands suggest a complex picture of possibly co-occurring neural processes that can differentially affect laminar connectivity.
]]></description>
<dc:creator>Scheeringa, R.</dc:creator>
<dc:creator>Bonnefond, M.</dc:creator>
<dc:creator>van Mourik, T.</dc:creator>
<dc:creator>Jensen, O.</dc:creator>
<dc:creator>Norris, D. G.</dc:creator>
<dc:creator>Koopmans, P. J.</dc:creator>
<dc:date>2020-09-18</dc:date>
<dc:identifier>doi:10.1101/2020.09.18.303263</dc:identifier>
<dc:title><![CDATA[Relating neural oscillations to laminar fMRI connectivity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-09-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.09.24.311654v1?rss=1">
<title>
<![CDATA[
Associations between ADHD symptom remission and white matter microstructure: a longitudinal analysis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.09.24.311654v1?rss=1"
</link>
<description><![CDATA[
BackgroundAttention-deficit hyperactivity disorder (ADHD) is associated with white matter (WM) microstructure. Our objective was to investigate how WM microstructure is longitudinally related to symptom remission in adolescents and young adults with ADHD.

MethodsWe obtained diffusion-weighted imaging (DWI) data from 99 participants at two time points (mean age baseline: 16.91 years, mean age follow-up: 20.57 years). We used voxel-wise Tract-Based Spatial Statistics (TBSS) with permutation-based inference to investigate associations of inattention (IA) and hyperactivity-impulsivity (HI) symptom change with fractional anisotropy (FA) at baseline, follow-up, and change between time points.

ResultsRemission of combined HI and IA symptoms was significantly associated with reduced FA at follow-up in the left superior longitudinal fasciculus and the left corticospinal tract (CST) (PFWE=0.038 and PFWE=0.044, respectively), mainly driven by an association between HI remission and follow-up CST FA (PFWE=0.049). There was no significant association of combined symptom decrease with FA at baseline or with changes in FA between the two assessments.

ConclusionsIn this longitudinal DWI study of ADHD using dimensional symptom scores, we show that greater symptom decrease is associated with lower follow-up FA in specific WM tracts. Altered FA thus may appear to follow, rather than precede, changes in symptom remission. Our findings indicate divergent WM developmental trajectories between individuals with persistent and remittent ADHD, and support the role of prefrontal and sensorimotor tracts in the remission of ADHD.
]]></description>
<dc:creator>Damatac, C. G.</dc:creator>
<dc:creator>Leenders, A. E. M.</dc:creator>
<dc:creator>Soheili-Nezhad, S.</dc:creator>
<dc:creator>Chauvin, R. J. M.</dc:creator>
<dc:creator>Mennes, M. J. J.</dc:creator>
<dc:creator>Zwiers, M. P.</dc:creator>
<dc:creator>van Rooij, D.</dc:creator>
<dc:creator>Akkermans, S. E. A.</dc:creator>
<dc:creator>Naaijen, J.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>Sprooten, E.</dc:creator>
<dc:date>2020-09-25</dc:date>
<dc:identifier>doi:10.1101/2020.09.24.311654</dc:identifier>
<dc:title><![CDATA[Associations between ADHD symptom remission and white matter microstructure: a longitudinal analysis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-09-25</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.09.23.309526v1?rss=1">
<title>
<![CDATA[
Dorsal to ventral imbalance in the superior longitudinal fasciculus mediates methylphenidate's effect on beta oscillations in ADHD 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.09.23.309526v1?rss=1"
</link>
<description><![CDATA[
BackgroundWhile pharmacological treatment with Methylphenidate (MPH) is a first line intervention for ADHD, its mechanisms of action have yet to be elucidated. In a previous MEG study, we demonstrated that MPH in ADHD normalizes beta depression in preparation to motor responses (1). We here seek to identify the white matter tracts that mediate MPHs effect on beta oscillations.

MethodsWe implemented a double-blind placebo-controlled crossover design, where boys diagnosed with ADHD underwent behavioral and MEG measurements during a spatial attention task while on and off MPH. Results were compared with an age/IQ-matched typically developing (TD) group performing the same task. Estimates of white matter tracts were obtained through diffusion tensor imaging (DTI). Based on aprioristic selection model criteria, we sought to determine the fiber tracts associated with electrophysiological, behavioral and clinical features of attentional functions.

ResultsWe identified three main tracts: the anterior thalamic radiation (ATR), the Superior Longitudinal Fasciculus ( parietal endings) (SLFp) and Superior Longitudinal Fasciculus ( temporal endings) (SLFt). ADHD symptoms severity was associated with lower fractional anisotropy (FA) within the ATR. In addition, individuals with relatively higher FA in SLFp compared to SLFt showed faster and more accurate behavioral responses to MPH. Furthermore, the same parieto-temporal FA gradient explained the effects of MPH on beta modulation: subjects with ADHD exhibiting higher FA in SLFp compared to SLFt also displayed greater effects of MPH on beta power during response preparation.

ConclusionsBased on MPHs modulatory effects on striatal dopamine levels, our data suggest that the behavioral deficits and aberrant oscillatory modulations observed in ADHD depend on a structural connectivity imbalance within the SLF, caused by a diffusivity gradient in favor of temporal rather than parietal, fiber tracts.
]]></description>
<dc:creator>Mazzetti, C.</dc:creator>
<dc:creator>Gonzales Damatac, C.</dc:creator>
<dc:creator>Sprooten, E.</dc:creator>
<dc:creator>ter Huurne, N.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Jensen, O.</dc:creator>
<dc:date>2020-09-23</dc:date>
<dc:identifier>doi:10.1101/2020.09.23.309526</dc:identifier>
<dc:title><![CDATA[Dorsal to ventral imbalance in the superior longitudinal fasciculus mediates methylphenidate's effect on beta oscillations in ADHD]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-09-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.09.21.301325v1?rss=1">
<title>
<![CDATA[
Splitting sleep between the night and a daytime nap reduces homeostatic sleep pressure and enhances long-term memory 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.09.21.301325v1?rss=1"
</link>
<description><![CDATA[
Daytime naps have been linked with enhanced memory encoding and consolidation. It remains unclear how a daily napping schedule impacts learning throughout the day, and whether these effects are the same for well-rested and sleep restricted individuals. We compared memory in 112 adolescents who underwent two simulated school weeks containing 8 or 6.5 hour sleep opportunities each day. Sleep episodes were nocturnal or split between nocturnal sleep and a 90-min afternoon nap, creating four experimental groups: 8h-continuous, 8h-split, 6.5h-continuous and 6.5h-split. Declarative memory was assessed with picture encoding and an educationally realistic factual knowledge task. Splitting sleep significantly enhanced afternoon picture encoding and factual knowledge under both 6.5h and 8h durations. Splitting sleep also significantly reduced slow-wave activity during nocturnal sleep, suggesting lower homeostatic sleep pressure during the day. There was no negative impact of the split sleep schedule on morning performance, despite a reduction in nocturnal sleep duration. These findings suggest that naps could be incorporated into a daily sleep schedule that provides sufficient sleep and benefits learning.
]]></description>
<dc:creator>Cousins, J. N.</dc:creator>
<dc:creator>Leong, R. L. F.</dc:creator>
<dc:creator>Jamaluddin, S. A.</dc:creator>
<dc:creator>Ng, A. S. C.</dc:creator>
<dc:creator>Ong, J. L.</dc:creator>
<dc:creator>Chee, M. W. L.</dc:creator>
<dc:date>2020-09-22</dc:date>
<dc:identifier>doi:10.1101/2020.09.21.301325</dc:identifier>
<dc:title><![CDATA[Splitting sleep between the night and a daytime nap reduces homeostatic sleep pressure and enhances long-term memory]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-09-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.09.18.303727v1?rss=1">
<title>
<![CDATA[
Stochasticity explains differences in the number of de novo mutations between families 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.09.18.303727v1?rss=1"
</link>
<description><![CDATA[
The number of de novo mutations (DNMs) in the human germline is correlated with parental age at conception, but this explains only part of the observed variation. We investigated whether there is a family-specific contribution to the number of DNMs in offspring. The analysis of DNMs in 111 dizygotic twin pairs did not identify a significant family-specific contribution. This result was corroborated by comparing DNMs of 1669 siblings to those of age-matched unrelated offspring. In addition, by modeling DNM data from 1714 multi-offspring families we estimated that the family specific contribution explains approximately 5.2% of the variation in DNM number. Furthermore, we found no significant difference between the observed number of DNMs and those based on a stochastic Poisson process. We conclude that a family-specific contribution to DNMs is small and that stochasticity explains a large proportion of variation in DNM counts.
]]></description>
<dc:creator>Gilissen, C.</dc:creator>
<dc:creator>Hampstead, J. E.</dc:creator>
<dc:creator>Goldmann, J. M.</dc:creator>
<dc:creator>Wong, W. S. W.</dc:creator>
<dc:creator>Wilfert, A. B.</dc:creator>
<dc:creator>Turner, T.</dc:creator>
<dc:creator>Jonker, M. A.</dc:creator>
<dc:creator>Bernier, R.</dc:creator>
<dc:creator>Huynen, M. A.</dc:creator>
<dc:creator>Eichler, E. E.</dc:creator>
<dc:creator>Veltman, J. A.</dc:creator>
<dc:creator>Maxwell, G. L.</dc:creator>
<dc:date>2020-09-20</dc:date>
<dc:identifier>doi:10.1101/2020.09.18.303727</dc:identifier>
<dc:title><![CDATA[Stochasticity explains differences in the number of de novo mutations between families]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-09-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.09.29.316364v1?rss=1">
<title>
<![CDATA[
Allele-specific antisense oligonucleotide therapy for dominantly inherited hearing impairment DFNA9. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.09.29.316364v1?rss=1"
</link>
<description><![CDATA[
The c.151C>T founder mutation in COCH is a frequent cause of late onset, dominantly inherited hearing impairment and vestibular dysfunction (DFNA9) in the Dutch/Belgian population. The initial clinical symptoms only manifest between the 3rd and 5th decade of life, which leaves ample time for therapeutic intervention. The dominant inheritance pattern and established non-haploinsufficiency disease mechanism indicate that suppressing translation of mutant COCH transcripts has high therapeutic potential. Single-Molecule Real-Time (SMRT) sequencing resulted in the identification of 11 variants with a low population-frequency (< 10%), that are specific to the c.151C>T mutant COCH allele. Proof of concept was obtained that gapmer antisense oligonucleotides (AONs), directed against the c.151C>T mutation or mutant allele-specific intronic variants, are able to specifically induce mutant COCH transcript degradation when delivered to transgenic cells expressing COCH minigenes. Sequence optimization of the AONs against the c.151C>T mutation resulted in a lead molecule that reduced the levels of mutant COCH transcripts by ~60% in a transgenic cell model, without affecting wildtype COCH transcript levels. With the proven safety of AONs in humans, and rapid advancements in inner ear drug delivery, our in-vitro studies indicate that AONs offer a promising treatment modality for DFNA9.
]]></description>
<dc:creator>de Vrieze, E.</dc:creator>
<dc:creator>Peijenborg, J.</dc:creator>
<dc:creator>Canas Martin, J.</dc:creator>
<dc:creator>Martens, A.</dc:creator>
<dc:creator>van der Heuvel, S.</dc:creator>
<dc:creator>Neveling, K.</dc:creator>
<dc:creator>Pennings, R.</dc:creator>
<dc:creator>Kremer, H.</dc:creator>
<dc:creator>van Wijk, E.</dc:creator>
<dc:date>2020-09-30</dc:date>
<dc:identifier>doi:10.1101/2020.09.29.316364</dc:identifier>
<dc:title><![CDATA[Allele-specific antisense oligonucleotide therapy for dominantly inherited hearing impairment DFNA9.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-09-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.09.29.316836v1?rss=1">
<title>
<![CDATA[
QSM Reconstruction Challenge 2.0 Part 1: A Realistic in silico Head Phantom for MRI data simulation and evaluation of susceptibility mapping procedures 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.09.29.316836v1?rss=1"
</link>
<description><![CDATA[
PurposeTo create a realistic in-silico head phantom for the second Quantitative Susceptibility Mapping (QSM) Reconstruction Challenge and for future evaluations of processing algorithms for QSM.

MethodsWe created a digital whole-head tissue property phantom by segmenting and post-processing high-resolution (0.64mm isotropic), multi-parametric MRI data acquired at 7T from a healthy volunteer. We simulated the steady-state magnetization at 7T using a Bloch simulator and mimicked a Cartesian sampling scheme through Fourier-based processing. Computer code for generating the phantom and performing the MR simulation was designed to facilitate flexible modifications of the phantom in the future, such as the inclusion of pathologies, as well as the simulation of a wide range of acquisition protocols. Specifically, the following parameters and effects were implemented: repetition time and echo time, voxel size, background fields, and RF phase biases. Diffusion weighted imaging phantom data is provided allowing future investigations of tissue microstructure effects in phase and QSM algorithms.

ResultsThe brain-part of the phantom featured realistic morphology with spatial variations in relaxation and susceptibility values similar to the in vivo setting. We demonstrated some of the phantoms properties, including the possibility of generating phase data with non-linear evolution over echo time due to partial volume effects or complex distributions of frequency shifts within the voxel.

ConclusionThe presented phantom and computer programs are publicly available and may serve as a ground truth in future assessments of the faithfulness of quantitative susceptibility reconstruction algorithms.
]]></description>
<dc:creator>Marques, J. P.</dc:creator>
<dc:creator>Meineke, J.</dc:creator>
<dc:creator>Milovic, C.</dc:creator>
<dc:creator>Bilgic, B.</dc:creator>
<dc:creator>Chan, K.-S.</dc:creator>
<dc:creator>Hedouin, R.</dc:creator>
<dc:creator>vand der Zwaag, W.</dc:creator>
<dc:creator>Langkammer, C.</dc:creator>
<dc:creator>Schweser, F.</dc:creator>
<dc:date>2020-10-01</dc:date>
<dc:identifier>doi:10.1101/2020.09.29.316836</dc:identifier>
<dc:title><![CDATA[QSM Reconstruction Challenge 2.0 Part 1: A Realistic in silico Head Phantom for MRI data simulation and evaluation of susceptibility mapping procedures]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.09.30.320168v1?rss=1">
<title>
<![CDATA[
Scene context impairs perception of semantically congruent objects 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.09.30.320168v1?rss=1"
</link>
<description><![CDATA[
Visual scene context is well-known to facilitate the recognition of scene-congruent objects. Interestingly, however, according to the influential theory of predictive coding, scene congruency should lead to reduced (rather than enhanced) processing of congruent objects, compared to incongruent ones, since congruent objects elicit reduced prediction error responses. We tested this counterintuitive hypothesis in two online behavioural experiments with human participants (N = 300). We found clear evidence for impaired perception of congruent objects, both in a change detection task measuring response times as well as in a bias-free object discrimination task measuring accuracy. Congruency costs were related to independent subjective congruency ratings. Finally, we show that the reported effects cannot be explained by low-level stimulus confounds, response biases, or top-down strategy. These results provide convincing evidence for perceptual congruency costs during scene viewing, in line with predictive coding theory.

Statement of RelevanceThe theory of the  Bayesian brain, the idea that our brain is a hypothesis-testing machine, has become very influential over the past decades. A particularly influential formulation is the theory of predictive coding. This theory entails that stimuli that are expected, for instance because of the context in which they appear, generate a weaker neural response than unexpected stimuli. Scene context correctly  predicts congruent scene elements, which should result in lower prediction error. Our study tests this important, counterintuitive, and hitherto not fully tested, hypothesis. We find clear evidence in favour of it, and demonstrate that these  congruency costs are indeed evident in perception, and not limited to one particular task setting or stimulus set. Since perception in the real world is never of isolated objects, but always of entire scenes, these findings are important not just for the Bayesian brain hypothesis, but for our understanding of real-world visual perception in general.
]]></description>
<dc:creator>Spaak, E.</dc:creator>
<dc:creator>Peelen, M. V.</dc:creator>
<dc:creator>de Lange, F.</dc:creator>
<dc:date>2020-10-02</dc:date>
<dc:identifier>doi:10.1101/2020.09.30.320168</dc:identifier>
<dc:title><![CDATA[Scene context impairs perception of semantically congruent objects]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.01.321893v1?rss=1">
<title>
<![CDATA[
Aberrant ventral dentate gyrus structure and function in individuals susceptible to post-traumatic stress disorder 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.01.321893v1?rss=1"
</link>
<description><![CDATA[
Post-traumatic stress disorder (PTSD) is a psychiatric disorder vulnerable individuals can develop following a traumatic event, whereas others are resilient. Enhanced insight into the mechanistic underpinnings contributing to these inter-individual differences in PTSD susceptibility is key to improved treatment and prevention. Aberrant function of the hippocampal dentate gyrus (DG) may contribute to its psychopathology, with the dorsal DG potentially encoding trauma memory generalization and the ventral DG anxiety. Using a mouse model, we investigated the association between deviant DG structure and function and susceptibility to develop PTSD-like symptoms following trauma. Mice were exposed to a traumatic event (unpredictable, inescapable foot shocks) and tested for PTSD symptomatology following recovery. In three independent experiments, DG neuronal morphology, synaptic protein gene expression and neuronal activity during trauma encoding and recall were assessed. Behaviorally, PTSD-like animals displayed some increased anxiety-like behavior already prior to trauma, increased novelty-induced freezing, but no clear differences in remote trauma memory recall. Comparison of the ventral DG of PTSD-like vs resilient mice revealed lower spine density, reduced expression of the postsynaptic protein homer 1b/c gene, a larger population of neurons active during trauma encoding and a greater presence of somatostatin neurons to be associated with PTSD susceptibility. In contrast, the dorsal DG of PTSD-like animals did not differ in terms of spine density or gene expression, but displayed more active neurons during trauma encoding and a lower amount of somatostatin neurons. These data propose a critical role for -mainly the ventral-DG in establishing symptomatology addressed in this PTSD model.
]]></description>
<dc:creator>Dirven, B. C. J.</dc:creator>
<dc:creator>van der Geugten, D.</dc:creator>
<dc:creator>van Bodegom, M.</dc:creator>
<dc:creator>Madder, L.</dc:creator>
<dc:creator>van Agen, L.</dc:creator>
<dc:creator>Homberg, J. R.</dc:creator>
<dc:creator>Kozicz, T.</dc:creator>
<dc:creator>Henckens, M. J. A. G.</dc:creator>
<dc:date>2020-10-02</dc:date>
<dc:identifier>doi:10.1101/2020.10.01.321893</dc:identifier>
<dc:title><![CDATA[Aberrant ventral dentate gyrus structure and function in individuals susceptible to post-traumatic stress disorder]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.09.332700v1?rss=1">
<title>
<![CDATA[
Estimating intra-axonal axial diffusivity in the presence of fibre orientation dispersion 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.09.332700v1?rss=1"
</link>
<description><![CDATA[
To estimate microstructure-related parameters from diffusion MRI data, biophysical models make strong, simplifying assumptions about the underlying tissue. The extent to which many of these assumptions are valid remains an open research question. This study was inspired by the disparity between the estimated intra-axonal axial diffusivity from literature and that typically assumed by the Neurite Orientation Dispersion and Density Imaging (NODDI) model (d[boxV] = 1.7m2/ms). We first demonstrate how changing the assumed axial diffusivity results in considerably different NODDI parameter estimates. Second, we illustrate the ability to estimate axial diffusivity as a free parameter of the model using high b-value data and an adapted NODDI framework. Using both simulated and in vivo data we investigate the impact of fitting to either real-valued or magnitude data, with Gaussian and Rician noise characteristics respectively, and what happens if we get the noise assumptions wrong in this high b-value and thus low SNR regime. Our results from real-valued human data estimate intra-axonal axial diffusivities of ~ 2 - 2.5m2/ms, in line with current literature. Crucially, our results demonstrate the importance of accounting for both a rectified noise floor and/or a signal offset to avoid biased parameter estimates when dealing with low SNR data.
]]></description>
<dc:creator>Howard, A. F.</dc:creator>
<dc:creator>Lange, F. J.</dc:creator>
<dc:creator>Mollink, J.</dc:creator>
<dc:creator>Cottaar, M.</dc:creator>
<dc:creator>Drakesmith, M.</dc:creator>
<dc:creator>Rudrapatna, S. U.</dc:creator>
<dc:creator>Jones, D. K.</dc:creator>
<dc:creator>Miller, K. L.</dc:creator>
<dc:creator>Jbabdi, S.</dc:creator>
<dc:date>2020-10-10</dc:date>
<dc:identifier>doi:10.1101/2020.10.09.332700</dc:identifier>
<dc:title><![CDATA[Estimating intra-axonal axial diffusivity in the presence of fibre orientation dispersion]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.07.328765v1?rss=1">
<title>
<![CDATA[
Anterior cingulate cortex hypofunction causes anti-social aggression in mice 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.07.328765v1?rss=1"
</link>
<description><![CDATA[
Controlling aggression is a crucial skill in social species like rodents and humans, and has been associated with anterior cingulate cortex (ACC). Here, we demonstrate a causal link between ACC hypofunction and failed aggression control in BALB/cJ mice. We first show that ACC in BALB/cJ mice is structurally degraded: Neuron density is decreased, with pervasive neuron death and neuro-toxic astroglia. Gene-set enrichment analysis suggested that this process is driven by neuronal degeneration, which then causes toxic astrogliosis. cFos expression across ACC indicated functional consequences: During aggressive encounters, ACC was engaged in control mice, but not BALB/cJ mice. Chemogenetically activating ACC during aggressive encounters drastically suppressed anti-social aggression but left adaptive aggression intact. The network effects of our chemogenetic perturbation suggest that this behavioural rescue is mediated by suppression of amygdala and hypothalamus and activation of mediodorsal thalamus. Together, these findings highlight the causal role of ACC in curbing anti-social aggression.
]]></description>
<dc:creator>van Heukelum, S.</dc:creator>
<dc:creator>Tulva, K.</dc:creator>
<dc:creator>Geers, F.</dc:creator>
<dc:creator>van Dulm, S.</dc:creator>
<dc:creator>Ruisch, H.</dc:creator>
<dc:creator>Mill, J.</dc:creator>
<dc:creator>Viana, J. F.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>Buitelaar, J. K.</dc:creator>
<dc:creator>Poelmans, G.</dc:creator>
<dc:creator>Glennon, J. C.</dc:creator>
<dc:creator>Vogt, B. A.</dc:creator>
<dc:creator>Havenith, M. N.</dc:creator>
<dc:creator>Franca, A. S. C.</dc:creator>
<dc:date>2020-10-08</dc:date>
<dc:identifier>doi:10.1101/2020.10.07.328765</dc:identifier>
<dc:title><![CDATA[Anterior cingulate cortex hypofunction causes anti-social aggression in mice]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.05.325993v1?rss=1">
<title>
<![CDATA[
The developmental genetic architecture of vocabulary skills during the first three years of life: Capturing emerging associations with later-life reading and cognition 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.05.325993v1?rss=1"
</link>
<description><![CDATA[
Individual differences in early-life vocabulary measures are heritable and associated with subsequent reading and cognitive abilities, although the underlying mechanisms are little understood. Here, we (i) investigate the developmental genetic architecture of expressive and receptive vocabulary in toddlerhood and (ii) assess origin and developmental stage of emerging genetic associations with mid-childhood verbal and non-verbal skills.

Studying up to 6,524 unrelated children from the population-based Avon Longitudinal Study of Parents and Children (ALSPAC) cohort, we dissected the phenotypic variance of longitudinally assessed early-life vocabulary measures (15-38 months) and later-life reading and cognitive skills (7-8 years) into genetic and residual components, by fitting multivariate structural equation models to genome-wide genetic-relationship matrices.

Our findings show that the genetic architecture of early-life vocabulary is dynamic, involving multiple distinct genetic factors. Two of them are developmentally stable and contribute to genetic variation in mid-childhood skills: Genetic links with later-life verbal abilities (reading, verbal intelligence) emerged with expressive vocabulary at 24 months. The underlying genetic factor explained 10.1% variation (path coefficient: 0.32(SE=0.06)) in early language, but also 6.4% (path coefficient: 0.25(SE=0.12)) and 17.9% (path coefficient: 0.42(SE=0.13)) variation in mid-childhood reading and verbal intelligence, respectively. An independent stable genetic factor was identified for receptive vocabulary at 38 months, explaining 2.1% (path coefficient: 0.15(SE=0.07)) phenotypic variation. This genetic factor was also linked to both verbal and non-verbal cognitive abilities in mid-childhood, accounting for 24.7% of the variation in non-verbal intelligence (path coefficient: 0.50(SE=0.08)), 33.0% in reading (path coefficient: 0.57(SE=0.07)) and 36.1% in verbal intelligence (path coefficient: 0.60(0.10)), corresponding to the majority of genetic variance ([&ge;]66.4%).

Thus, the genetic foundations of mid-childhood reading and cognition are diverse. They involve at least two independent genetic factors that emerge at different developmental stages during early language development and may implicate differences in cognitive processes that are already detectable during toddlerhood.

Author summaryDifferences in the number of words young children produce (expressive vocabulary) and understand (receptive vocabulary) can be partially explained by genetic factors, and are related to reading and cognitive abilities later in life. Here, we studied genetic influences underlying word production and understanding during early development (15-38 months) and their genetic relationship with mid-childhood reading and cognitive skills (7-8 years), based on longitudinal phenotype measures and genome-wide genetic data from up to 6,524 unrelated children. We showed that vocabulary skills assessed at different stages during early development are influenced by distinct genetic factors, two of which also contribute to genetic variation in mid-childhood skills, suggesting developmental stability: Genetic sources emerging for word production skills at 24 months were linked to subsequent verbal abilities, including mid-childhood reading and verbal intelligence performance. A further independent genetic factor was identified that related to word comprehension at 38 months and also contributed to variation in later verbal as well as non-verbal abilities during mid-childhood. Thus, the genetic foundations of mid-childhood reading and cognition involve at least two independent genetic factors that emerge during early-life langauge development and may implicate differences in overarching cognitive mechanisms.
]]></description>
<dc:creator>Verhoef, E.</dc:creator>
<dc:creator>Shapland, C. Y.</dc:creator>
<dc:creator>Fisher, S. E.</dc:creator>
<dc:creator>Dale, P. S.</dc:creator>
<dc:creator>St Pourcain, B.</dc:creator>
<dc:date>2020-10-05</dc:date>
<dc:identifier>doi:10.1101/2020.10.05.325993</dc:identifier>
<dc:title><![CDATA[The developmental genetic architecture of vocabulary skills during the first three years of life: Capturing emerging associations with later-life reading and cognition]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.13.337436v1?rss=1">
<title>
<![CDATA[
A White Matter Atlas and Common Connectivity Space Facilitate the Pig as a Translational Model in Neuroscience 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.13.337436v1?rss=1"
</link>
<description><![CDATA[
Neuroimagings capability to quickly and rapidly phenotype the cortical organization of the whole brain brings with it the possibility to extend our understanding of cortical organization across the mammalian lineage. However, neuroimaging has thus far generally limited itself to a small number of species, with most animal studies being performed in either rodents or Non-Human Primates. Here we perform a first pass characterization of an animal which has recently seen its stock rise in the neuroscience community with the development of new models of neurological disease; the domestic pig. Characterizing the structural connectome of the pig, we create a white matter atlas, and an anatomical template which we use to build a horizontal translation between the pig and human based on a connectivity blueprint approach. We find that conserved trends of structural connectivity across species enabled spatial prediction of regions of interest between the pig and human, showing the potential horizontal translations have as a tool to assess the translational validity of porcine models of neurological disease. Releasing the anatomical template, white matter atlas, and connectivity blueprints, we hope to ease and promote the acceptance of the pig as an alternative large-animal model by the neuroimaging community.
]]></description>
<dc:creator>Benn, R. A.</dc:creator>
<dc:creator>Mars, R. B.</dc:creator>
<dc:creator>Xu, T.</dc:creator>
<dc:creator>Rodriguez-Esparragoza, L.</dc:creator>
<dc:creator>Montesinos, P.</dc:creator>
<dc:creator>Manzano-Patron, J. P.</dc:creator>
<dc:creator>Lopez-Martin, G.</dc:creator>
<dc:creator>Fuster, V.</dc:creator>
<dc:creator>Gonzalez-Sanchez, J.</dc:creator>
<dc:creator>Duff, E. P.</dc:creator>
<dc:creator>Ibanez, B.</dc:creator>
<dc:date>2020-10-14</dc:date>
<dc:identifier>doi:10.1101/2020.10.13.337436</dc:identifier>
<dc:title><![CDATA[A White Matter Atlas and Common Connectivity Space Facilitate the Pig as a Translational Model in Neuroscience]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.13.323618v1?rss=1">
<title>
<![CDATA[
DIMA: Data-driven selection of a suitable imputation algorithm 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.13.323618v1?rss=1"
</link>
<description><![CDATA[
MotivationImputation is a prominent strategy when dealing with missing values (MVs) in proteomics data analysis pipelines. However, the performance of different imputation methods is difficult to assess and varies strongly depending on data characteristics. To overcome this issue, we present the concept of a data-driven selection of a suitable imputation algorithm (DIMA).

ResultsThe performance and broad applicability of DIMA is demonstrated on 121 quantitative proteomics data sets from the PRIDE database and on simulated data consisting of 5 - 50% MVs with different proportions of missing not at random and missing completely at random values. DIMA reliably suggests a high-performing imputation algorithm which is always among the three best algorithms and results in a root mean square error difference ({Delta}RMSE) [&le;] 10% in 84% of the cases.

Availability and ImplementationSource code is freely available for download at github.com/clemenskreutz/OmicsData.
]]></description>
<dc:creator>Egert, J.</dc:creator>
<dc:creator>Warscheid, B.</dc:creator>
<dc:creator>Kreutz, C.</dc:creator>
<dc:date>2020-10-14</dc:date>
<dc:identifier>doi:10.1101/2020.10.13.323618</dc:identifier>
<dc:title><![CDATA[DIMA: Data-driven selection of a suitable imputation algorithm]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.13.337477v1?rss=1">
<title>
<![CDATA[
Does dopamine synthesis capacity predict individual variation in curiosity? 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.13.337477v1?rss=1"
</link>
<description><![CDATA[
Curiosity, which can be defined as "intrinsically motivated information-seeking", is an important driving force in our everyday lives. Based on previous evidence demonstrating a link between information prediction errors and dopamine neuronal firing rates, we asked whether the drive to seek information varies with individual differences in dopamine synthesis capacity. In order to investigate this, we let participants perform a lottery task in which we independently manipulated outcome uncertainty, outcome valence (gains versus losses) and expected value, and asked participants to indicate their curiosity for each presented lottery. In a separate session, participants underwent an [18F]DOPA PET scan to quantify their dopamine synthesis capacity. We replicate previous behavioral results, showing that curiosity is a function of outcome uncertainty as well as outcome valence (gain versus loss). However, we found no evidence that curiosity or the sensitivity to outcome uncertainty, outcome valence and expected value was related to participants dopamine synthesis capacity in the ventral striatum, the caudate nucleus or the putamen. These findings stress the need for further studies into the role of dopamine in (different types of) curiosity.
]]></description>
<dc:creator>van Lieshout, L. L. F.</dc:creator>
<dc:creator>van den Bosch, R.</dc:creator>
<dc:creator>Hofmans, L.</dc:creator>
<dc:creator>de Lange, F. P.</dc:creator>
<dc:creator>Cools, R.</dc:creator>
<dc:date>2020-10-14</dc:date>
<dc:identifier>doi:10.1101/2020.10.13.337477</dc:identifier>
<dc:title><![CDATA[Does dopamine synthesis capacity predict individual variation in curiosity?]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.09.28.316992v1?rss=1">
<title>
<![CDATA[
Multiple pathways of LRRK2-G2019S / Rab10 interaction in dopaminergic neurons 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.09.28.316992v1?rss=1"
</link>
<description><![CDATA[
BackgroundInherited mutations in the LRRK2 protein are the most common known cause of Parkinsons, but the mechanisms by which increased kinase activity of mutant LRRK2 leads to pathological events remain to be determined. In vitro assays (heterologous cell culture, phospho-protein mass spectrometry) suggest that several Rab proteins might be directly phosphorylated by LRRK2-G2019S. Which Rabs interact with LRRK2 in dopaminergic neurons to facilitate normal and pathological physiological responses remains to be determined. An in vivo screen of Rab expression in dopaminergic neurons in young adult Drosophila demonstrated a strong genetic interaction between LRRK2-G2019S and Rab10. We now ask if Rab10 is required for LRRK2-induced physiological responses in DA neurons.

MethodsLRRK2-G2019S was expressed in Drosophila dopaminergic neurons and the effects of Rab10 depletion on Proboscis Extension, vision, circadian activity pattern and courtship memory determined in aged flies.

ResultsRab10 loss-of-function rescued bradykinesia of the Proboscis Extension Response (PER) and visual defects of aged flies expressing LRRK2-G2019S in DA neurons. Rab10 knock-down however, did not rescue the marked sleep phenotype which results from dopaminergic expression of LRRK2-G2019S. Courtship memory is not affected by LRRK2 expression, but is markedly improved by Rab10 depletion. Anatomically, both LRRK2-G2019S and Rab10 are seen in the cytoplasm and at the synaptic endings of dopaminergic neurons.

ConclusionsWe conclude that, in Drosophila dopaminergic neurons, Rab10 is involved differentially in LRRK2-induced behavioral deficits. Therefore, variations in Rab expression may contribute to susceptibility of different dopaminergic nuclei to neurodegeneration seen in people with Parkinsons.

Graphical AbstractRab10 depletion ameliorates the proboscis extension bradykinesia and loss of synaptic signalling in the retina induced by LRRK2-G2019S expression (magenta arrows / orange crosses). Rab10 manipulation does not affect the  sleep phenotype from LRRK2-G2019S (magenta arrow). Reduction of Rab10 facilitates conditioned courtship memory, but LRRK2 has no effect (yellow arrow). All manipulations of Rab10 and G2019S in dopaminergic neurons, shown in the outline of the brain (filled cells have high levels of Rab10). We conclude that Rab10 and LRRK2 interact in some, but not all dopaminergic neurons. This may underlie differences in the susceptibility of different human striatal dopaminergic cells to Parkinsons and explain why different symptoms initiate particular ages.



O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=172 SRC="FIGDIR/small/316992v2_ufig1.gif" ALT="Figure 1">
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]]></description>
<dc:creator>Fellgett, A.</dc:creator>
<dc:creator>Middleton, C. A.</dc:creator>
<dc:creator>Munns, J.</dc:creator>
<dc:creator>Ugbode, C.</dc:creator>
<dc:creator>Jaciuch, D.</dc:creator>
<dc:creator>Wilson, L.</dc:creator>
<dc:creator>Chawla, S.</dc:creator>
<dc:creator>Elliott, C.</dc:creator>
<dc:date>2020-09-28</dc:date>
<dc:identifier>doi:10.1101/2020.09.28.316992</dc:identifier>
<dc:title><![CDATA[Multiple pathways of LRRK2-G2019S / Rab10 interaction in dopaminergic neurons]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-09-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.09.328609v1?rss=1">
<title>
<![CDATA[
Face neurons in human visual cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.09.328609v1?rss=1"
</link>
<description><![CDATA[
The exquisite capacity of primates to detect and recognize faces is crucial for social interactions. Although disentangling the neural basis of human face recognition remains a key goal in neuroscience, direct evidence at the single-neuron level is virtually nonexistent. We recorded from face-selective neurons in human visual cortex, in a region characterized by functional magnetic resonance imaging (fMRI) activations for faces compared to objects (i.e. the occipital face area, OFA). The majority of visually responsive neurons in this fMRI activation showed strong selectivity at short latencies for faces compared to objects. Feature scrambled faces and face-like objects could also drive these neurons, suggesting that the OFA is not tightly-tuned to the visual attributes that typically define whole human faces. These single-cell recordings within the human face processing system provide vital experimental evidence linking previous imaging studies in humans and invasive studies in animal models.
]]></description>
<dc:creator>Decramer, T.</dc:creator>
<dc:creator>Premereur, E.</dc:creator>
<dc:creator>Zhu, Q.</dc:creator>
<dc:creator>Van Paesschen, W.</dc:creator>
<dc:creator>van Loon, J.</dc:creator>
<dc:creator>Vanduffel, W.</dc:creator>
<dc:creator>Taubert, J.</dc:creator>
<dc:creator>Janssen, P.</dc:creator>
<dc:creator>Theys, T.</dc:creator>
<dc:date>2020-10-09</dc:date>
<dc:identifier>doi:10.1101/2020.10.09.328609</dc:identifier>
<dc:title><![CDATA[Face neurons in human visual cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.06.320499v1?rss=1">
<title>
<![CDATA[
Antisense oligonucleotide-based treatment of retinitis pigmentosa caused by USH2A exon 13 mutations 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.06.320499v1?rss=1"
</link>
<description><![CDATA[
Mutations in USH2A, encoding usherin, are the most common cause of syndromic and non-syndromic retinitis pigmentosa (RP). The two founder mutations in exon 13 (c.2299delG and c.2276G>T) collectively account for ~34% of USH2A-associated RP cases. Skipping of exon 13 from the USH2A transcript during pre-mRNA splicing presents a potential treatment modality in which the resulting transcript is predicted to encode a slightly shortened usherin protein. Morpholino-induced skipping of ush2a exon 13 in larvae of the previously published ush2a exon 13 zebrafish mutant resulted in the production of usherin{Delta}exon13 and completely restored retinal function. RNA antisense oligonucleotides were investigated for their potential to specifically induce human USH2A exon 13 skipping. Lead candidate QR-421a induced dose-dependent exon 13 skipping in iPSC-derived photoreceptor precursors from a patient homozygous for the USH2A c.2299delG mutation. Intravitreal delivery of QR-421a in non-human primates showed that QR-421a penetrates the retinal outer nuclear layer and induces detectable levels of exon 13 skipping until at least 3 months post injection. In conclusion, QR-421a-induced exon skipping proves to be a highly promising treatment for RP caused by mutations in exon 13 of the USH2A gene.
]]></description>
<dc:creator>Slijkerman, R.</dc:creator>
<dc:creator>van Diepen, H.</dc:creator>
<dc:creator>Dona, M.</dc:creator>
<dc:creator>Venselaar, H.</dc:creator>
<dc:creator>Zang, J.</dc:creator>
<dc:creator>Neuhauss, S.</dc:creator>
<dc:creator>Peters, T.</dc:creator>
<dc:creator>Broekman, S.</dc:creator>
<dc:creator>Pennings, R.</dc:creator>
<dc:creator>Kremer, H.</dc:creator>
<dc:creator>Adamson, P.</dc:creator>
<dc:creator>de Vrieze, E.</dc:creator>
<dc:creator>van Wijk, E.</dc:creator>
<dc:date>2020-10-07</dc:date>
<dc:identifier>doi:10.1101/2020.10.06.320499</dc:identifier>
<dc:title><![CDATA[Antisense oligonucleotide-based treatment of retinitis pigmentosa caused by USH2A exon 13 mutations]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.17.343442v1?rss=1">
<title>
<![CDATA[
Brain preparedness: The proactive role of the cortisol awakening response 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.17.343442v1?rss=1"
</link>
<description><![CDATA[
Upon awakening from nighttime sleep, the stress hormone cortisol exhibits a burst in the morning within 30-minutes in humans. This cortisol awakening response (CAR) is thought to prepare the brain for upcoming challenges. Yet, the neurobiological mechanisms underlying the CAR-mediated  preparation function remains unknown. Using blood-oxygen-level-dependent functional magnetic resonance imaging (BOLD-fMRI) with a dedicated prospective design and pharmacological manipulation, we investigated this proactive mechanism in humans across two fMRI studies. In Study 1, we found that a robust CAR was predictive of less hippocampal and prefrontal activity, though enhanced functional coupling between those regions and facilitated working memory performance, during a demanding task later in the afternoon. These results implicate the CAR in proactively promoting brain preparedness based on improved neural efficiency. To address the causality of this proactive effect, we conducted a second study (Study 2) in which we suppressed the CAR with a double blind, placebo controlled, randomized design using Dexamethasone. We found that pharmacological suppression of CAR mirrored the proactive effects from Study 1. Dynamic causal modeling analyses further revealed a reduction of prefrontal top-down modulation over hippocampal activity when performing a cognitively demanding task in the afternoon. These findings establish a causal link between the CAR and its proactive role in optimizing brain functional networks involved in neuroendocrine control and memory.
]]></description>
<dc:creator>Xiong, B.</dc:creator>
<dc:creator>Chen, C.</dc:creator>
<dc:creator>Tian, Y.</dc:creator>
<dc:creator>Zhang, S.</dc:creator>
<dc:creator>Liu, C.</dc:creator>
<dc:creator>Evans, T.</dc:creator>
<dc:creator>Fernandez, G.</dc:creator>
<dc:creator>Wu, J.</dc:creator>
<dc:creator>Qin, S.</dc:creator>
<dc:date>2020-10-17</dc:date>
<dc:identifier>doi:10.1101/2020.10.17.343442</dc:identifier>
<dc:title><![CDATA[Brain preparedness: The proactive role of the cortisol awakening response]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.18.344267v1?rss=1">
<title>
<![CDATA[
Architectural Affordance Impacts Human Sensorimotor Brain Dynamics 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.18.344267v1?rss=1"
</link>
<description><![CDATA[
Action is a medium of collecting sensory information about the environment, which in turn is shaped by architectural affordances. Affordances characterize the fit between the physical structure of the body and capacities for movement and interaction with the environment, thus relying on sensorimotor processes associated with exploring the surroundings. Central to sensorimotor brain dynamics, the attentional mechanisms directing the gating function of sensory signals share neuronal resources with motor-related processes necessary to inferring the external causes of sensory signals. Such a predictive coding approach suggests that sensorimotor dynamics are sensitive to architectural affordances that support or suppress specific kinds of actions for an individual. However, how architectural affordances relate to the attentional mechanisms underlying the gating function for sensory signals remains unknown. Here we demonstrate that event-related desynchronization of alpha-band oscillations in parieto-occipital and medio-temporal regions covary with the architectural affordances. Source-level time-frequency analysis of data recorded in a motor-priming Mobile Brain/Body Imaging experiment revealed strong event-related desynchronization of the alpha band to originate from the posterior cingulate complex and bilateral parahippocampal areas. Our results firstly contribute to the understanding of how the brain resolves architectural affordances relevant to behaviour. Second, our results indicate that the alpha-band originating from the posterior cingulate complex covaries with the architectural affordances before participants interact with the environment. During the interaction, the bilateral parahippocampal areas dynamically reflect the affordable behaviour as perceived through the visual system. We conclude that the sensorimotor dynamics are developed for processing behaviour-relevant features in the designed environment.
]]></description>
<dc:creator>Djebbara, Z.</dc:creator>
<dc:creator>Fich, L. B.</dc:creator>
<dc:creator>Gramann, K.</dc:creator>
<dc:date>2020-10-18</dc:date>
<dc:identifier>doi:10.1101/2020.10.18.344267</dc:identifier>
<dc:title><![CDATA[Architectural Affordance Impacts Human Sensorimotor Brain Dynamics]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.20.347005v1?rss=1">
<title>
<![CDATA[
Temporal prediction elicits rhythmic pre-activation of relevant sensory cortices 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.20.347005v1?rss=1"
</link>
<description><![CDATA[
Being able to anticipate events before they happen facilitates stimulus processing. The anticipation of the contents of events is thought to be implemented by the elicitation of prestimulus templates in sensory cortex. In contrast, the anticipation of the timing of events is typically associated with entrainment of neural oscillations. It is so far unknown whether and in which conditions temporal expectations interact with feature-based expectations, and, consequently, whether entrainment modulates the generation of content-specific sensory templates. In this study, we investigated the role of temporal expectations in a sensory discrimination task. We presented participants with rhythmically interleaved visual and auditory streams of relevant and irrelevant stimuli while measuring neural activity using magnetoencephalography. We found no evidence that rhythmic stimulation induced prestimulus feature templates. However, we did observe clear anticipatory rhythmic pre-activation of the relevant sensory cortices. This oscillatory activity peaked at behaviourally relevant, in-phase, intervals. Our results suggest that temporal expectations about stimulus features do not behave similarly to explicitly cued, non-rhythmic, expectations; yet elicit a distinct form of modality-specific pre-activation.

Graphical abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=165 SRC="FIGDIR/small/347005v3_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@fce8corg.highwire.dtl.DTLVardef@1c16c3corg.highwire.dtl.DTLVardef@1a90d62org.highwire.dtl.DTLVardef@1adaa17_HPS_FORMAT_FIGEXP  M_FIG C_FIG The brain extracts temporal regularities from the environment to anticipate upcoming events. Furthermore, with prior knowledge about their contents, the brain is thought to leverage this by instantiating anticipatory sensory templates. We investigated if sensory templates occur in response to a rhythmic stimulus stream with predictable temporal structure. We found that temporal rhythmic predictions did not induce sensory templates, but rather modulated the excitability in early sensory cortices.
]]></description>
<dc:creator>Barne, L. C.</dc:creator>
<dc:creator>Cravo, A. M.</dc:creator>
<dc:creator>de Lange, F. P.</dc:creator>
<dc:creator>Spaak, E.</dc:creator>
<dc:date>2020-10-21</dc:date>
<dc:identifier>doi:10.1101/2020.10.20.347005</dc:identifier>
<dc:title><![CDATA[Temporal prediction elicits rhythmic pre-activation of relevant sensory cortices]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.09.27.315432v1?rss=1">
<title>
<![CDATA[
Learning at variable attentional load requires cooperation between working memory, meta-learning and attention-augmented reinforcement learning 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.09.27.315432v1?rss=1"
</link>
<description><![CDATA[
Flexible learning of changing reward contingencies can be realized with different strategies. A fast learning strategy involves using working memory of recently rewarded objects to guide choices. A slower learning strategy uses prediction errors to gradually update value expectations to improve choices. How the fast and slow strategies work together in scenarios with real-world stimulus complexity is not well known. Here, we disentangle their relative contributions in rhesus monkeys while they learned the relevance of object features at variable attentional load. We found that learning behavior across six subjects is consistently best predicted with a model combining (i) fast working memory (ii) slower reinforcement learning from differently weighted positive and negative prediction errors, as well as (iii) selective suppression of non-chosen feature values and (iv) a meta-learning mechanism adjusting exploration rates based on a memory trace of recent errors. These mechanisms cooperate differently at low and high attentional loads. While working memory was essential for efficient learning at lower attentional loads, enhanced weighting of negative prediction errors and meta-learning were essential for efficient learning at higher attentional loads. Together, these findings pinpoint a canonical set of learning mechanisms and demonstrate how they cooperate when subjects flexibly adjust to environments with variable real-world attentional demands.

Significance statementLearning which visual features are relevant for achieving our goals is challenging in real-world scenarios with multiple distracting features and feature dimensions. It is known that in such scenarios learning benefits significantly from attentional prioritization. Here we show that beyond attention, flexible learning uses a working memory system, a separate learning gain for avoiding negative outcomes, and a meta-learning process that adaptively increases exploration rates whenever errors accumulate. These subcomponent processes of cognitive flexibility depend on distinct learning signals that operate at varying timescales, including the most recent reward outcome (for working memory), memories of recent outcomes (for adjusting exploration), and reward prediction errors (for attention augmented reinforcement learning). These results illustrate the specific mechanisms that cooperate during cognitive flexibility.
]]></description>
<dc:creator>Womelsdorf, T.</dc:creator>
<dc:creator>Watson, M. R.</dc:creator>
<dc:creator>Tiesinga, P.</dc:creator>
<dc:date>2020-09-28</dc:date>
<dc:identifier>doi:10.1101/2020.09.27.315432</dc:identifier>
<dc:title><![CDATA[Learning at variable attentional load requires cooperation between working memory, meta-learning and attention-augmented reinforcement learning]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-09-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.28.359224v1?rss=1">
<title>
<![CDATA[
Brunner syndrome associated MAOA dysfunction in human dopaminergic neurons results in NMDAR hyperfunction and increased network activity. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.28.359224v1?rss=1"
</link>
<description><![CDATA[
BackgroundMonoamine neurotransmitter abundance affects motor control, emotion, and cognitive function and is regulated by monoamine oxidases. Amongst these, monoamine oxidase A (MAOA) catalyzes the degradation of dopamine, norepinephrine, and serotonin into their inactive metabolites. Loss-of-function mutations in the X-linked MAOA gene cause Brunner syndrome, which is characterized by various forms of impulsivity, maladaptive externalizing behavior, and mild intellectual disability. Impaired MAOA activity in individuals with Brunner syndrome results in bioamine aberration, but it is currently unknown how this affects neuronal function.

MethodsWe generated human induced pluripotent stem cell (hiPSC)-derived dopaminergic (DA) neurons from three individuals with Brunner syndrome carrying different mutations, and used CRISPR/Cas9 mediated homologous recombination to rescue MAOA function. We used these lines to characterize morphological and functional properties of DA neuronal cultures at the single cell and neuronal network level in vitro.

ResultsBrunner syndrome DA neurons showed reduced synaptic density but hyperactive network activity. Intrinsic functional properties and -amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR)-mediated synaptic transmission were not affected by MAOA dysfunction. Instead, we show that the neuronal network hyperactivity is mediated by upregulation of the GRIN2A and GRIN2B subunits of the N-methyl-D-aspartate receptor (NMDAR), and rescue of MAOA results in normalization of NMDAR function as well as restoration of network activity.

ConclusionsOur data suggest that MAOA dysfunction in Brunner syndrome increases activity of dopaminergic neurons through upregulation of NMDAR function, which may contribute to Brunner syndrome associated phenotypes.
]]></description>
<dc:creator>Shi, Y.</dc:creator>
<dc:creator>van Rhijn, J.-R.</dc:creator>
<dc:creator>Bormann, M.</dc:creator>
<dc:creator>Mossink, B.</dc:creator>
<dc:creator>Frega, M.</dc:creator>
<dc:creator>Recaioglu, H.</dc:creator>
<dc:creator>Hakobjan, M.</dc:creator>
<dc:creator>Klein Gunnewiek, T. M.</dc:creator>
<dc:creator>Schoenmaker, C.</dc:creator>
<dc:creator>Palmer, E.</dc:creator>
<dc:creator>Faivre, L.</dc:creator>
<dc:creator>Kittel-Schneider, S.</dc:creator>
<dc:creator>Schubert, D.</dc:creator>
<dc:creator>Brunner, H.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Nadif Kasri, N.</dc:creator>
<dc:date>2020-10-29</dc:date>
<dc:identifier>doi:10.1101/2020.10.28.359224</dc:identifier>
<dc:title><![CDATA[Brunner syndrome associated MAOA dysfunction in human dopaminergic neurons results in NMDAR hyperfunction and increased network activity.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.30.361238v1?rss=1">
<title>
<![CDATA[
Head-free eye tracking, and efficient receptive field mapping in the marmoset 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.30.361238v1?rss=1"
</link>
<description><![CDATA[
The marmoset has emerged as a promising primate model system, in particular for visual neuroscience. Many common experimental paradigms rely on head fixation and an extended period of eye fixation during the presentation of salient visual stimuli. Both of these behavioral requirements can be challenging for marmosets. Here, we present two methodological developments, each addressing one of these difficulties. First, we show that it is possible to use a standard eye tracking system without head fixation to assess visual behavior in the marmoset. Eye tracking quality from head-free animals is sufficient to obtain precise psychometric functions from a visual acuity task. Secondly, we introduce a novel method for efficient receptive field mapping that does not rely on moving stimuli but uses fast flashing annuli and wedges. We present data recorded during head-fixation in areas V1 and V6 and show that receptive field locations are readily obtained within a short period of recording time. Thus, the methodological advancements presented in this work will contribute to establish the marmoset as a valuable model in neuroscience.
]]></description>
<dc:creator>Jendritza, P.</dc:creator>
<dc:creator>Klein, F. J.</dc:creator>
<dc:creator>Rohenkohl, G.</dc:creator>
<dc:creator>Fries, P.</dc:creator>
<dc:date>2020-10-30</dc:date>
<dc:identifier>doi:10.1101/2020.10.30.361238</dc:identifier>
<dc:title><![CDATA[Head-free eye tracking, and efficient receptive field mapping in the marmoset]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.11.02.365452v1?rss=1">
<title>
<![CDATA[
Assessing uncertainty in connective field estimations from resting state fMRI activity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.11.02.365452v1?rss=1"
</link>
<description><![CDATA[
Connective Field (CF) modeling estimates the local spatial integration between signals in distinct cortical visual field areas. As we have shown previously using 7T data, CF can reveal the visuotopic organization of visual cortical areas even when applied to BOLD activity recorded in the absence of external stimulation. This indicates that CF modeling can be used to evaluate cortical processing in participants in which the visual input may be compromised. Furthermore, by using Bayesian CF modelling it is possible to estimate the co-variability of the parameter estimates and therefore, apply CF modeling to single cases. However, no previous studies evaluated the (Bayesian) CF model using 3T resting-state fMRI data, although this is important since 3T scanners are much more abundant and more often used in clinical research than 7T ones. In this study, we investigate whether it is possible to obtain meaningful CF estimates from 3T resting state (RS) fMRI data. To do so, we applied the standard and Bayesian CF modeling approaches on two RS scans interleaved by the acquisition of visual stimulation in 12 healthy participants.

Our results show that both approaches reveal good agreement between RS- and visual field (VF)-based maps. Moreover, the 3T observations were similar to those previously reported at 7T. In addition, to quantify the uncertainty associated with each estimate in both RS and VF data, we applied our Bayesian CF framework to provide the underlying marginal distribution of the CF parameters. Finally, we show how an additional CF parameter, beta, can be used as a data-driven threshold on the RS data to further improve CF estimates. We conclude that Bayesian CF modeling can characterize local functional connectivity between visual cortical areas from RS data at 3T. In particular, we expect the ability to assess parameter uncertainty in individual participants will be important for future clinical studies.

HighlightsO_LILocal functional connectivity between visual cortical areas can be estimated from RS-fMRI data at 3T using both standard CF and Bayesian CF modelling.
C_LIO_LIBayesian CF modelling quantifies the model uncertainty associated with each CF parameter on RS and VF data, important in particular for future studies on clinical populations.
C_LIO_LI3T observations were qualitatively similar to those previously reported at 7T.
C_LI
]]></description>
<dc:creator>Invernizzi, A.</dc:creator>
<dc:creator>Gravel, N. G.</dc:creator>
<dc:creator>Haak, K. V.</dc:creator>
<dc:creator>Renken, R. J.</dc:creator>
<dc:creator>Cornelissen, F. W.</dc:creator>
<dc:date>2020-11-03</dc:date>
<dc:identifier>doi:10.1101/2020.11.02.365452</dc:identifier>
<dc:title><![CDATA[Assessing uncertainty in connective field estimations from resting state fMRI activity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-11-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.11.06.371252v1?rss=1">
<title>
<![CDATA[
Cortical representation of touch in silico 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.11.06.371252v1?rss=1"
</link>
<description><![CDATA[
With its six layers and ~12000 neurons, a cortical column is a complex network whose function is plausibly greater than the sum of its constituents. Functional characterization of its network components will require going beyond the brute-force modulation of the neural activity of a small group of neurons. Here we introduce an open-source, biologically inspired, computationally efficient network model of the somatosensory cortexs granular and supragranular layers after reconstructing the barrel cortex in soma resolution. Comparisons of the network activity to empirical observations showed that the in silico network replicates the known properties of touch representations and whisker deprivation-induced changes in synaptic strength induced in vivo. Simulations show that the history of the membrane potential acts as a spatial filter that determines the presynaptic population of neurons contributing to a post-synaptic action potential; this spatial filtering might be critical for synaptic integration of top-down and bottom-up information.
]]></description>
<dc:creator>Huang, C.</dc:creator>
<dc:creator>Zeldenrust, F.</dc:creator>
<dc:creator>Celikel, T.</dc:creator>
<dc:date>2020-11-07</dc:date>
<dc:identifier>doi:10.1101/2020.11.06.371252</dc:identifier>
<dc:title><![CDATA[Cortical representation of touch in silico]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-11-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.11.06.371658v1?rss=1">
<title>
<![CDATA[
Cell type specific information transfer for sparse coding 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.11.06.371658v1?rss=1"
</link>
<description><![CDATA[
Sensory neurons reconstruct the world from action potentials (spikes) impinging on them. To effectively transfer information about the stimulus to the next processing level, a neuron needs to be able to adapt its working range to the properties of the stimulus. Here, we focus on the intrinsic neural properties that influence information transfer in cortical neurons and how tightly their properties need to be tuned to the stimulus statistics for them to be effective. We start by measuring the intrinsic information encoding properties of putative excitatory and inhibitory neurons in L2/3 of the mouse barrel cortex. Excitatory neurons show high thresholds and strong adaptation, making them fire sparsely and resulting in a strong compression of information, whereas inhibitory neurons that favour fast spiking transfer more information. Next, we turn to computational modelling and ask how two properties influence information transfer: 1) spike-frequency adaptation and 2) the shape of the IV-curve. We find that a subthreshold (but not threshold) adaptation, the  h-current, and a properly tuned leak conductance can increase the information transfer of a neuron, whereas threshold adaptation can increase its working range. Finally, we verify the effect of the IV-curve slope in our experimental recordings and show that excitatory neurons form a more heterogeneous population than inhibitory neurons. These relationships between intrinsic neural features and neural coding that had not been quantified before will aid computational, theoretical and systems neuroscientists in understanding how neuronal populations can alter their coding properties, such as through the impact of neuromodulators. Why the variability of intrinsic properties of excitatory neurons is larger than that of inhibitory ones is an exciting question, for which future research is needed.

Author summaryIntracellular information transfer from synaptic input to output spike train is necessarily lossy. Here, we explicitly measure the mutual information between a neurons input and spike output and show that information transfer is more lossy and heterogeneous for excitatory than for inhibitory neurons. By using computational modelling we show that the shape of the input-output curve as well as how fast a neuron adapts to its input collectively determine the rate of information loss. These insights will help both experimentalists and modellers in designing and simulating experiments that investigate how network coding properties can adapt to the environment, for instance through the effects of neuromodulators.
]]></description>
<dc:creator>Zeldenrust, F.</dc:creator>
<dc:creator>Calcini, N.</dc:creator>
<dc:creator>Yan, X.</dc:creator>
<dc:creator>Bijlsma, A.</dc:creator>
<dc:creator>Celikel, T.</dc:creator>
<dc:date>2020-11-08</dc:date>
<dc:identifier>doi:10.1101/2020.11.06.371658</dc:identifier>
<dc:title><![CDATA[Cell type specific information transfer for sparse coding]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-11-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.11.09.373886v1?rss=1">
<title>
<![CDATA[
Serotonin transporter knockout in rats modulates category learning 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.11.09.373886v1?rss=1"
</link>
<description><![CDATA[
Lower function of the serotonin transporter (5-HTT) has a strong relationship with the development of autism spectrum disorder (ASD) in humans. One characteristic of ASD is the repetitive and restrictive behavior, which may form the basis for better memory and savant skills in some people with ASD. This characteristic in ASD may reflect a tendency towards an exploitation strategy rather than an exploration strategy during learning. Using a rat model, we developed a touchscreen-based task for testing 5-HTT knockout effects on stimulus category learning. By analyzing the data with a reinforcement learning drift diffusion model, we find that 5-HTT knockout rats show a lower learning rate and apply more of an exploitation versus exploration strategy compared to WT rats during category learning. The decision bound of decision-making during stimulus generalization indicates that more 5-HTT knockout rats than WT rats exploit irrelevant information to categorize stimuli. The touchscreen-based task we developed greatly increases the translational value from animals to humans and helps to understand the behavioral mechanisms underlying repetitive behavior in ASD.
]]></description>
<dc:creator>Guo, C. C.-G.</dc:creator>
<dc:creator>Minda, J. P.</dc:creator>
<dc:creator>Homberg, J.</dc:creator>
<dc:date>2020-11-09</dc:date>
<dc:identifier>doi:10.1101/2020.11.09.373886</dc:identifier>
<dc:title><![CDATA[Serotonin transporter knockout in rats modulates category learning]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-11-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.11.10.374538v1?rss=1">
<title>
<![CDATA[
Novelty Processing Depends on Medial Temporal Lobe Structures 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.11.10.374538v1?rss=1"
</link>
<description><![CDATA[
ObjectivesThe goal of the present study was to identify the role of the medial temporal lobe (MTL) in the detection and later processing of novelty stimuli.

MethodsTwenty-one epilepsy patients with unilateral MTL resection (10 left-sided; 11 right-sided) performed an adapted visual novelty oddball task. In this task two streams of stimuli were presented on the left and right of fixation while the patients electroencephalogram was measured. Patients responded to infrequent target stimuli, while ignoring frequent standard, and infrequent novel stimuli that could appear either contra- or ipsilateral to the resected side.

ResultsNovelty detection, as indexed by the N2 ERP component elicited by novels, was not affected by the MTL resections. Later processing of novels, however, as indexed by the novelty P3 ERP component, was reduced for novels presented contra-versus ipsilateral to the resected side. Target processing, as indexed by the P3b, was unaffected.

ConclusionsThe current results suggest that MTL structures play a role in novelty processing, but that the novelty signal may originate from a distinct neural source.
]]></description>
<dc:creator>Schomaker, J.</dc:creator>
<dc:creator>Grouls, M. M. E.</dc:creator>
<dc:creator>Rau, E.</dc:creator>
<dc:creator>Hendriks, M.</dc:creator>
<dc:creator>Colon, A.</dc:creator>
<dc:creator>Meeter, M.</dc:creator>
<dc:date>2020-11-10</dc:date>
<dc:identifier>doi:10.1101/2020.11.10.374538</dc:identifier>
<dc:title><![CDATA[Novelty Processing Depends on Medial Temporal Lobe Structures]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-11-10</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.11.10.376970v1?rss=1">
<title>
<![CDATA[
Optimising a Simple Fully Convolutional Network (SFCN) for accurate brain age prediction in the PAC 2019 challenge 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.11.10.376970v1?rss=1"
</link>
<description><![CDATA[
Brain age prediction from brain MRI scans not only helps improve brain ageing modelling generally, but also provides benchmarks for predictive analysis methods. Brain-age delta, which is the difference between a subjects predicted age and true age, has become a meaningful biomarker for the health of the brain. Here, we report the details of our brain age prediction models and results in the Predictive Analysis Challenge 2019. The aim of the challenge was to use T1-weighted brain MRIs to predict a subjects age in multicentre datasets. We apply a lightweight deep convolutional neural network architecture, Simple Fully Convolutional Neural Network (SFCN), and combined several techniques including data augmentation, transfer learning, model ensemble, and bias correction for brain age prediction. The model achieved first places in both of the two objectives in the PAC 2019 brain age prediction challenge: Mean absolute error (MAE) = 2.90 years without bias removal, and MAE = 2.95 years with bias removal.
]]></description>
<dc:creator>Gong, W.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>Vedaldi, A.</dc:creator>
<dc:creator>Smith, S. M.</dc:creator>
<dc:creator>Peng, H.</dc:creator>
<dc:date>2020-11-11</dc:date>
<dc:identifier>doi:10.1101/2020.11.10.376970</dc:identifier>
<dc:title><![CDATA[Optimising a Simple Fully Convolutional Network (SFCN) for accurate brain age prediction in the PAC 2019 challenge]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-11-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.08.14.250654v1?rss=1">
<title>
<![CDATA[
ERAP2 facilitates a subpeptidome of Birdshot Uveitis-associated HLA-A29 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.08.14.250654v1?rss=1"
</link>
<description><![CDATA[
Birdshot Uveitis (BU) is a blinding inflammatory eye condition that only affects HLA-A29-positive individuals. Genetic association studies linked ERAP2 with BU, an aminopeptidase which trims peptides before their presentation by HLA class I at the cell surface, which suggests that ERAP2-dependent peptide presentation by HLA-A29 drives the pathogenesis of BU. However, it remains poorly understood whether the effects of ERAP2 on the HLA-A29 peptidome are distinct from its effect on other HLA allotypes. To address this, we focused on the effects of ERAP2 on the immunopeptidome in patient-derived antigen presenting cells. Using complementary HLA-A29-based and pan-class I immunopurifications, isotope-labelled naturally processed and presented HLA-bound peptides were sequenced by mass spectrometry. We show that the effects of ERAP2 on the N-terminus of ligands of HLA-A29 are shared across endogenous HLA allotypes, but discover and replicate that one peptide motif generated in the presence of ERAP2 is specifically bound by HLA-A29. This motif can be found in the amino acid sequence of putative autoantigens. We further show evidence for internal sequence specificity for ERAP2 imprinted in the immunopeptidome. These results reveal that ERAP2 can generate an HLA-A29-specific antigen repertoire, which supports that antigen presentation is a key disease pathway in BU.
]]></description>
<dc:creator>Venema, W.</dc:creator>
<dc:creator>Hiddingh, S.</dc:creator>
<dc:creator>de Boer, J. H.</dc:creator>
<dc:creator>Claas, F.</dc:creator>
<dc:creator>Mulder, A.</dc:creator>
<dc:creator>Hollander, A. D.</dc:creator>
<dc:creator>Stratikos, E.</dc:creator>
<dc:creator>Sarkizova, S.</dc:creator>
<dc:creator>Janssen, G.</dc:creator>
<dc:creator>Veelen, P. v.</dc:creator>
<dc:creator>Kuiper, J. J.</dc:creator>
<dc:date>2020-08-14</dc:date>
<dc:identifier>doi:10.1101/2020.08.14.250654</dc:identifier>
<dc:title><![CDATA[ERAP2 facilitates a subpeptidome of Birdshot Uveitis-associated HLA-A29]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-08-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.11.13.381418v1?rss=1">
<title>
<![CDATA[
Stimulus-specific plasticity of macaque V1 spike rates and gamma 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.11.13.381418v1?rss=1"
</link>
<description><![CDATA[
When a visual stimulus is repeated, average neuronal responses typically decrease, yet they might maintain or even increase their impact through increased synchronization. Previous work has found that many repetitions of a grating lead to increasing gamma-band synchronization. Here we show in awake macaque area V1 that both, repetition-related reductions in firing rate and increases in gamma are specific to the repeated stimulus. These effects showed some persistence on the timescale of minutes. Further, gamma increases were specific to the presented stimulus location. Importantly, repetition effects on gamma and on firing rates generalized to natural images. These findings suggest that gamma-band synchronization subserves the adaptive processing of repeated stimulus encounters, both for generating efficient stimulus responses and possibly for memory formation.
]]></description>
<dc:creator>Peter, A. S.</dc:creator>
<dc:creator>Stauch, B. J.</dc:creator>
<dc:creator>Shapcott, K.</dc:creator>
<dc:creator>Kouroupaki, K.</dc:creator>
<dc:creator>Schmiedt, J. T.</dc:creator>
<dc:creator>Klein, L.</dc:creator>
<dc:creator>Klon-Lipok, J.</dc:creator>
<dc:creator>Dowdall, J. R.</dc:creator>
<dc:creator>Schoelvinck, M. L.</dc:creator>
<dc:creator>Vinck, M.</dc:creator>
<dc:creator>Singer, W.</dc:creator>
<dc:creator>Schmid, M. C.</dc:creator>
<dc:creator>Fries, P.</dc:creator>
<dc:date>2020-11-15</dc:date>
<dc:identifier>doi:10.1101/2020.11.13.381418</dc:identifier>
<dc:title><![CDATA[Stimulus-specific plasticity of macaque V1 spike rates and gamma]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-11-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.11.14.382051v1?rss=1">
<title>
<![CDATA[
Preferred auditory temporal processing regimes and auditory-motor interactions 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.11.14.382051v1?rss=1"
</link>
<description><![CDATA[
Decoding the rich temporal dynamics of complex sounds such as speech is constrained by the underlying neuronal processing mechanisms. Oscillatory theories suggest the existence of one optimal perceptual performance regime at auditory stimulation rates in the delta to theta range (<10 Hz), but reduced performance in the alpha range (10-14 Hz) is controversial. Additionally, the widely discussed motor system contribution to timing remains unclear. We measured rate discrimination thresholds between 4-15 Hz, and auditory-motor coupling strength was estimated through auditory-motor synchronization. In a Bayesian model comparison, high auditory-motor synchronizers showed a larger range of constant optimal temporal judgments than low synchronizers, with performance decreasing in the alpha range. This evidence for optimal auditory processing in the theta range is consistent with preferred oscillatory regimes in auditory cortex that compartmentalize stimulus encoding and processing. The findings suggest, remarkably, that increased auditory-motor interaction might extend such an optimal range towards faster rates.
]]></description>
<dc:creator>Kern, P.</dc:creator>
<dc:creator>Assaneo, M. F.</dc:creator>
<dc:creator>Endres, D.</dc:creator>
<dc:creator>Poeppel, D.</dc:creator>
<dc:creator>Rimmele, J. M.</dc:creator>
<dc:date>2020-11-15</dc:date>
<dc:identifier>doi:10.1101/2020.11.14.382051</dc:identifier>
<dc:title><![CDATA[Preferred auditory temporal processing regimes and auditory-motor interactions]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-11-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.11.13.381467v1?rss=1">
<title>
<![CDATA[
Stimulus-specific plasticity in human visual gamma-band activity and functional connectivity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.11.13.381467v1?rss=1"
</link>
<description><![CDATA[
Under natural conditions, the visual system often sees a given input repeatedly. This provides an opportunity to optimize processing of the repeated stimuli. Stimulus repetition has been shown to strongly modulate neuronal-gamma band synchronization, yet crucial questions remained open. Here we used magnetoencephalography in 30 human subjects and find that gamma decreases across ~10 repetitions and then increases across further repetitions, revealing plastic changes of the activated neuronal circuits. Crucially, changes induced by one stimulus did not affect responses to other stimuli, demonstrating stimulus specificity. Changes partially persisted when the inducing stimulus was repeated after 25 minutes of intervening stimuli. They were strongest in early visual cortex and increased interareal feedforward influences. Our results suggest that early visual cortex gamma synchronization enables adaptive neuronal processing of recurring stimuli. These and previously reported changes might be due to an interaction of oscillatory dynamics with established synaptic plasticity mechanisms.
]]></description>
<dc:creator>Stauch, B. J.</dc:creator>
<dc:creator>Peter, A.</dc:creator>
<dc:creator>Schuler, H.</dc:creator>
<dc:creator>Fries, P.</dc:creator>
<dc:date>2020-11-13</dc:date>
<dc:identifier>doi:10.1101/2020.11.13.381467</dc:identifier>
<dc:title><![CDATA[Stimulus-specific plasticity in human visual gamma-band activity and functional connectivity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-11-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.11.19.390393v1?rss=1">
<title>
<![CDATA[
Stress-sensitive brain computations of task controllability 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.11.19.390393v1?rss=1"
</link>
<description><![CDATA[
Estimating the controllability of the environment enables agents to better predict upcoming events and decide when to engage controlled action selection. How does the human brain estimate controllability? Trial-by-trial analysis of choices, decision times, and neural activity in an explore-and-predict task demonstrate that humans solve this problem by comparing the predictions of an "actor" model with those of a reduced "spectator" model of their environment. Neural BOLD responses within striatal and medial prefrontal areas tracked the instantaneous difference in the prediction errors generated by these two statistical learning models. BOLD activity in the posterior cingulate, temporoparietal, and prefrontal cortices covaried with changes in estimated controllability. Exposure to inescapable stressors biased controllability estimates downward and increased reliance on the spectator model in an anxiety-dependent fashion. Taken together, these findings provide a mechanistic account of controllability inference and its distortion by stress exposure.
]]></description>
<dc:creator>Ligneul, R.</dc:creator>
<dc:creator>Mainen, Z.</dc:creator>
<dc:creator>Ly, V.</dc:creator>
<dc:creator>Cools, R.</dc:creator>
<dc:date>2020-11-20</dc:date>
<dc:identifier>doi:10.1101/2020.11.19.390393</dc:identifier>
<dc:title><![CDATA[Stress-sensitive brain computations of task controllability]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-11-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.11.25.397695v1?rss=1">
<title>
<![CDATA[
QSM Reconstruction Challenge 2.0: Design and Report of Results 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.11.25.397695v1?rss=1"
</link>
<description><![CDATA[
PurposeThe aim of the second quantitative susceptibility mapping (QSM) reconstruction challenge (Oct 2019, Seoul, Korea) was to test the accuracy of QSM dipole inversion algorithms in simulated brain data.

MethodsA two-stage design was chosen for this challenge. The participants were provided with datasets of multi-echo gradient echo images synthesized from two realistic in silico head phantoms using an MR simulator. At the first stage, participants optimized QSM reconstructions without ground-truths available to mimic the clinical setting. At the second stage, ground-truths were provided for parameter optimization.Submissions were evaluated using eight numerical metrics and visual ratings.

ResultsA total of 98 reconstructions were submitted for stage 1 and 47 submissions for stage 2. Iterative methods had the best quantitative metric scores, followed by deep-learning and direct inversion methods. Priors derived from magnitude data improved the metric scores. Algorithms based on iterative approaches and Total Variation (and its derivatives) produced the best overall results. The reported results and analysis pipelines have been made public to allow researchers to compare new methods to the current state of the art.

ConclusionThe synthetic data provides a consistent framework to test the accuracy and robustness of QSM algorithms in the presence of noise, calcifications and minor voxel dephasing effects. Total Variation-based algorithmsproduced the best results along all metrics. Future QSM challenges should asses if this good performance with synthetic datasets translates to more realistic scenarios, where background fields and dipole-incompatible phase contributions are included.
]]></description>
<dc:creator>QSM Challenge 2.0 Organization Committee,</dc:creator>
<dc:creator>Bilgic, B.</dc:creator>
<dc:creator>Langkammer, C.</dc:creator>
<dc:creator>Marques, J. P.</dc:creator>
<dc:creator>Meineke, J.</dc:creator>
<dc:creator>Milovic, C.</dc:creator>
<dc:creator>Schweser, F.</dc:creator>
<dc:date>2020-11-26</dc:date>
<dc:identifier>doi:10.1101/2020.11.25.397695</dc:identifier>
<dc:title><![CDATA[QSM Reconstruction Challenge 2.0: Design and Report of Results]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-11-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.11.27.401489v1?rss=1">
<title>
<![CDATA[
Visual motion processing recruits regions selective for auditory motion in early deaf individuals 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.11.27.401489v1?rss=1"
</link>
<description><![CDATA[
In early deaf individuals, the auditory deprived temporal brain regions become engaged in visual processing. In our study we tested further the hypothesis that intrinsic functional specialization guides the expression of cross-modal responses in the deprived auditory cortex. We used functional MRI to characterize the brain response to horizontal, radial and stochastic visual motion in early deaf and hearing individuals matched for the use of oral or sign language. Visual motion showed enhanced response in the  deaf mid-lateral planum temporale, a region selective to auditory motion as demonstrated by a separate auditory motion localizer in hearing people. Moreover, multivariate pattern analysis revealed that this reorganized temporal region showed enhanced decoding of motion categories in the deaf group, while visual motion-selective region hMT+/V5 showed reduced decoding when compared to hearing people. Dynamic Causal Modelling revealed that the  deaf motion-selective temporal region shows a specific increase of its functional interactions with hMT+/V5 and is now part of a large-scale visual motion selective network. In addition, we observed preferential responses to radial, compared to horizontal, visual motion in the  deaf right superior temporal cortex region that also show preferential response to approaching/receding sounds in the hearing brain. Overall, our results suggest that the early experience of auditory deprivation interacts with intrinsic constraints and triggers a large-scale reallocation of computational load between auditory and visual brain regions that typically support the multisensory processing of motion information.

HighlightsO_LIAuditory motion-sensitive regions respond to visual motion in the deaf
C_LIO_LIReorganized auditory cortex can discriminate between visual motion trajectories
C_LIO_LIPart of the deaf auditory cortex shows preference for in-depth visual motion
C_LIO_LIDeafness might lead to computational reallocation between auditory/visual regions.
C_LI
]]></description>
<dc:creator>Benetti, S.</dc:creator>
<dc:creator>Zonca, J.</dc:creator>
<dc:creator>Ferrari, A.</dc:creator>
<dc:creator>Rezk, M.</dc:creator>
<dc:creator>Rabini, G.</dc:creator>
<dc:creator>Collignon, O.</dc:creator>
<dc:date>2020-11-27</dc:date>
<dc:identifier>doi:10.1101/2020.11.27.401489</dc:identifier>
<dc:title><![CDATA[Visual motion processing recruits regions selective for auditory motion in early deaf individuals]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-11-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.11.30.401323v1?rss=1">
<title>
<![CDATA[
MR-based camera-less eye tracking using deep neural networks 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.11.30.401323v1?rss=1"
</link>
<description><![CDATA[
Viewing behavior provides a window into many central aspects of human cognition and health, and it is an important variable of interest or confound in many fMRI studies. To make eye tracking freely and widely available for MRI research, we developed DeepMReye: a convolutional neural network that decodes gaze position from the MR-signal of the eyeballs. It performs camera-less eye tracking at sub-imaging temporal resolution in held-out participants with little training data and across a broad range of scanning protocols. Critically, it works even in existing datasets and when the eyes are closed. Decoded eye movements explain network-wide brain activity also in regions not associated with oculomotor function. This work emphasizes the importance of eye tracking for the interpretation of fMRI results and provides an open-source software solution that is widely applicable in research and clinical settings.
]]></description>
<dc:creator>Frey, M.</dc:creator>
<dc:creator>Nau, M.</dc:creator>
<dc:creator>Doeller, C. F.</dc:creator>
<dc:date>2020-12-01</dc:date>
<dc:identifier>doi:10.1101/2020.11.30.401323</dc:identifier>
<dc:title><![CDATA[MR-based camera-less eye tracking using deep neural networks]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-12-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.12.02.408468v1?rss=1">
<title>
<![CDATA[
Learning differentially shapes prefrontal and hippocampal activity patterns during classical conditioning 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.12.02.408468v1?rss=1"
</link>
<description><![CDATA[
The ability to use sensory cues to inform goal directed actions is a critical component of intelligent behavior. To study how sound cues are translated into anticipatory licking during classical appetitive conditioning, we employed high-density electrophysiological recordings from the hippocampal CA1 area and the prefrontal cortex (PFC). CA1 and PFC neurons undergo distinct learning dependent changes at the single cell level and maintain representations of cue identity during anticipatory behavior at the population level. In addition, reactivation of task-related neuronal assemblies during hippocampal awake Sharp-Wave Ripples (aSWR) changed within individual sessions in CA1 and over the course of multiple sessions in PFC. Despite both areas being highly engaged and synchronized during the task, we found no evidence for coordinated single cell or assembly activity during conditioning trials or aSWR.
]]></description>
<dc:creator>Klee, J. L.</dc:creator>
<dc:creator>Souza, B. C.</dc:creator>
<dc:creator>Battaglia, F. P.</dc:creator>
<dc:date>2020-12-03</dc:date>
<dc:identifier>doi:10.1101/2020.12.02.408468</dc:identifier>
<dc:title><![CDATA[Learning differentially shapes prefrontal and hippocampal activity patterns during classical conditioning]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-12-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.12.03.410399v1?rss=1">
<title>
<![CDATA[
A hierarchy of linguistic predictions during natural language comprehension 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.12.03.410399v1?rss=1"
</link>
<description><![CDATA[
Understanding spoken language requires transforming ambiguous acoustic streams into a hierarchy of representations, from phonemes to meaning. It has been suggested that the brain uses prediction to guide the interpretation of incoming input. However, the role of prediction in language processing remains disputed, with disagreement about both the ubiquity and representational nature of predictions. Here, we address both issues by analysing brain recordings of participants listening to audiobooks, and using a deep neural network (GPT-2) to precisely quantify contextual predictions. First, we establish that brain responses to words are modulated by ubiquitous, probabilistic predictions. Next, we disentangle model-based predictions into distinct dimensions, revealing dissociable signatures of syntactic, phonemic and semantic predictions. Finally, we show that high-level (word) predictions inform low-level (phoneme) predictions, supporting hierarchical predictive processing. Together, these results underscore the ubiquity of prediction in language processing, showing that the brain spontaneously predicts upcoming language at multiple levels of abstraction.
]]></description>
<dc:creator>Heilbron, M.</dc:creator>
<dc:creator>Armeni, K.</dc:creator>
<dc:creator>Schoffelen, J.-M.</dc:creator>
<dc:creator>Hagoort, P.</dc:creator>
<dc:creator>de Lange, F. P.</dc:creator>
<dc:date>2020-12-03</dc:date>
<dc:identifier>doi:10.1101/2020.12.03.410399</dc:identifier>
<dc:title><![CDATA[A hierarchy of linguistic predictions during natural language comprehension]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-12-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.12.15.422886v1?rss=1">
<title>
<![CDATA[
Quantitative Genetic Scoring, or how to put a number on an arbitrary genetic region 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.12.15.422886v1?rss=1"
</link>
<description><![CDATA[
MotivationWith the increasing availability of genome-wide genetic data, methods to combine genetic variables with other sources of data in statistical models are required. This paper introduces quantitative genetic scoring (QGS), a dimensionality reduction method to create quantitative genetic variables representing arbitrary genetic regions.

MethodsQGS is defined as the sum of absolute differences in the genetic sequence between a subject and a reference population. QGS properties such as distribution and sensitivity to region size were examined, and QGS was tested in six different existing genomic data sets of various sizes and various phenotypes.

ResultsQGS can reduce genetic information by >98% yet explain phenotypic variance at low, medium, and high level of granularity. Associations based on QGS are independent of both size and linkage disequilibrium structure of the underlying region. In combination with stability selection, QGS finds significant results where a traditional genome-wide association approaches struggle. In conclusion, QGS preserves phenotypically significant genetic variance while reducing dimensionality, allowing researchers to include quantitative genetic information in any type of statistical analysis.

Availabilityhttps://github.com/machine2learn/QGS

Contactgido.schoenmacker@radboudumc.nl

Supplemental informationSupplemental data are available online.
]]></description>
<dc:creator>Schoenmacker, G. H.</dc:creator>
<dc:creator>Vlaming, P.</dc:creator>
<dc:creator>Pallesen, J.</dc:creator>
<dc:creator>Pikulina, M. Y.</dc:creator>
<dc:creator>Ghamarian, A. H.</dc:creator>
<dc:creator>Demontis, D. H.</dc:creator>
<dc:creator>Borglum, A.</dc:creator>
<dc:creator>Galesloot, T. E.</dc:creator>
<dc:creator>Poelmans, G.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Claassen, T.</dc:creator>
<dc:creator>Heskes, T.</dc:creator>
<dc:creator>Buitelaar, J.</dc:creator>
<dc:creator>Arias Vasquez, A.</dc:creator>
<dc:date>2020-12-16</dc:date>
<dc:identifier>doi:10.1101/2020.12.15.422886</dc:identifier>
<dc:title><![CDATA[Quantitative Genetic Scoring, or how to put a number on an arbitrary genetic region]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-12-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.09.27.315614v1?rss=1">
<title>
<![CDATA[
Estimating Multiple Latencies in the Auditory System from Auditory Steady-State Responses on a Single EEG Channel 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.09.27.315614v1?rss=1"
</link>
<description><![CDATA[
The latency of the auditory steady-state response (ASSR) may provide valuable information regarding the integrity of the auditory system, as it could potentially reveal the presence of multiple intracerebral sources. To estimate multiple latencies from high-order ASSRs, we propose a novel two-stage procedure that consists of a nonparametric estimation method, called apparent latency from phase coherence (ALPC), followed by a heuristic sequential forward selection algorithm (SFS). Compared with existing methods, ALPC-SFS requires few prior assumptions, and is straightforward to implement for higher-order nonlinear responses to multi-cosine sound complexes with their initial phases set to zero. It systematically evaluates the nonlinear components of the ASSRs by estimating multiple latencies, automatically identifies involved ASSR components, and reports a latency consistency index (LCI). To verify the proposed method, we performed simulations for several scenarios: two nonlinear subsystems with different or overlapping outputs. We compared the results from our method with predictions from existing, parametric methods. We also recorded the EEG from ten normal-hearing adults by bilaterally presenting superimposed tones with four frequencies that evoke a unique set of ASSRs. From these ASSRs, two major latencies were found to be stable across subjects on repeated measurement days. The two latencies are dominated by low-frequency (LF) (near 40 Hz, at around 41-52 ms) and high-frequency (HF) (>80 Hz, at around 21-27 ms) ASSR components. The frontal-central (FC) brain region showed longer latencies on LF components, but shorter latencies on HF components, when compared with temporal-lobe regions. In conclusion, the proposed nonparametric ALPC-SFS method, applied to zero-phase, multi-cosine sound complexes is more suitable for evaluating embedded nonlinear systems underlying ASSRs than existing methods. It may therefore be a promising objective measure for hearing performance and auditory cortex (dys)function. The Matlab scripts for the ALPC-SFS method is available here: https://github.com/ieeeWang/ALPC-SFS-method-Matlab-scripts.
]]></description>
<dc:creator>Wang, L.</dc:creator>
<dc:creator>Noordanus, E.</dc:creator>
<dc:creator>van Opstal, J. A.</dc:creator>
<dc:date>2020-09-28</dc:date>
<dc:identifier>doi:10.1101/2020.09.27.315614</dc:identifier>
<dc:title><![CDATA[Estimating Multiple Latencies in the Auditory System from Auditory Steady-State Responses on a Single EEG Channel]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-09-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.12.23.424234v1?rss=1">
<title>
<![CDATA[
Postural effects on arm movement variability are idiosyncratic and feedback-dependent 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.12.23.424234v1?rss=1"
</link>
<description><![CDATA[
Reaching movements are subject to noise arising during the sensing, planning and execution phases of movement production, which contributes to movement variability. When vision of the moving hand is available, reaching variability appears to be strongly influenced by noise occurring during the specification and/or online updating of movement plans in visual coordinates. In contrast, when vision of the hand is unavailable, variability appears more dependent upon hand movement direction, suggesting a greater influence of execution noise. Given that execution noise acts in part at the muscular level, we hypothesized that reaching variability should depend not only on movement direction but initial arm posture as well. Moreover, given that the effects of execution noise are more apparent when movements are performed without vision of the hand, we reasoned that postural effects would be more evident when visual feedback was withheld. To test these hypotheses, subjects planned memory-guided reaching movements to three frontal plane targets, using either an "adducted" or "abducted" initial arm posture. Movements were then executed with and without hand vision. We found that the effects of initial arm posture on movement variability were idiosyncratic in both visual feedback conditions. In addition, without visual feedback, posture-dependent differences in variability varied with movement extent, growing abruptly larger in magnitude during the terminal phases of movement, and were moderately correlated with differences in mean endpoint positions. The results emphasize the role of factors other than noise (i.e. biomechanics and suboptimal sensorimotor integration) in constraining patterns of movement variability in 3D space.
]]></description>
<dc:creator>Phataraphruk, P.</dc:creator>
<dc:creator>Rahman, Q.</dc:creator>
<dc:creator>Lakshminarayanan, K.</dc:creator>
<dc:creator>Fruchtman, M.</dc:creator>
<dc:creator>Buneo, C.</dc:creator>
<dc:date>2020-12-24</dc:date>
<dc:identifier>doi:10.1101/2020.12.23.424234</dc:identifier>
<dc:title><![CDATA[Postural effects on arm movement variability are idiosyncratic and feedback-dependent]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-12-24</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.09.11.292870v1?rss=1">
<title>
<![CDATA[
Striatal BOLD and midfrontal theta power express motivation for action 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.09.11.292870v1?rss=1"
</link>
<description><![CDATA[
Action selection is biased by the valence of anticipated outcomes. To assess mechanisms by which these motivational biases are expressed and controlled, we measured simultaneous EEG-fMRI during a motivational Go/NoGo learning task (N=36), leveraging the temporal resolution of EEG and subcortical access of fMRI. VmPFC BOLD encoded cue valence, importantly predicting trial-by-trial valence-driven response speed differences and EEG theta power around cue onset. In contrast, striatal BOLD encoded selection of active Go responses and correlated with theta power around response time. Within trials, theta power ramped in the fashion of an evidence accumulation signal for the value of making a  Go response, capturing the faster responding to reward cues. Our findings reveal a dual nature of midfrontal theta power, with early components reflecting the vmPFC contribution to motivational biases, and late components reflecting their striatal translation into behavior, in line with influential recent "value of work" theories of striatal processing.
]]></description>
<dc:creator>Algermissen, J.</dc:creator>
<dc:creator>Swart, J. C.</dc:creator>
<dc:creator>Scheeringa, R.</dc:creator>
<dc:creator>Cools, R.</dc:creator>
<dc:creator>den Ouden, H. E. M.</dc:creator>
<dc:date>2020-09-11</dc:date>
<dc:identifier>doi:10.1101/2020.09.11.292870</dc:identifier>
<dc:title><![CDATA[Striatal BOLD and midfrontal theta power express motivation for action]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-09-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.12.21.423808v1?rss=1">
<title>
<![CDATA[
Schema-induced shifts in mice navigational strategies are unveiled by a minimal behavioral model of spatial exploration. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.12.21.423808v1?rss=1"
</link>
<description><![CDATA[
Shifts in spatial patterns produced during the execution of a navigational task can be used to track the effects of the accumulation of knowledge and the acquisition of structured information about the environment. Here we provide a quantitative analysis of mice behavior while performing a novel goal localization task in a large, modular arena, the HexMaze. To demonstrate the effects of different forms of previous knowledge we first obtain a precise statistical characterization of animals paths with sub-trial resolution and over different phases of learning. The emergence of a flexible representation of the task is accompanied by a progressive improvement of performance, mediated by multiple, multiplexed time scales. We then use a generative mathematical model of the animal behavior to isolate the specific contributions to the final navigational strategy. We find that animal behavior can be accurately reproduced by the combined effect of a goal-oriented component, becoming stronger with the progression of learning, and of a random walk component, producing choices unrelated to the task and only partially weakened in time.
]]></description>
<dc:creator>Vallianatou, C.-A.</dc:creator>
<dc:creator>Alonso, A.</dc:creator>
<dc:creator>Aleman, A.</dc:creator>
<dc:creator>Genzel, L.</dc:creator>
<dc:creator>Stella, F.</dc:creator>
<dc:date>2020-12-22</dc:date>
<dc:identifier>doi:10.1101/2020.12.21.423808</dc:identifier>
<dc:title><![CDATA[Schema-induced shifts in mice navigational strategies are unveiled by a minimal behavioral model of spatial exploration.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-12-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.12.19.423601v1?rss=1">
<title>
<![CDATA[
End-to-end optimization of prosthetic vision 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.12.19.423601v1?rss=1"
</link>
<description><![CDATA[
Neural prosthetics may provide a promising solution to restore visual perception in some forms of blindness. The restored prosthetic percept is rudimentary compared to normal vision and can be optimized with a variety of image preprocessing techniques to maximize relevant information transfer. Extracting the most useful features from a visual scene is a non-trivial task and optimal preprocessing choices strongly depend on the context. Despite rapid advancements in deep learning, research currently faces a difficult challenge in finding a general and automated preprocessing strategy that can be tailored to specific tasks or user requirements. In this paper we present a novel deep learning approach that explicitly addresses this issue by optimizing the entire process of phosphene generation in an end-to-end fashion. The proposed model is based on a deep auto-encoder architecture and includes a highly adjustable simulation module of prosthetic vision. In computational validation experiments we show that such an approach is able to automatically find a task-specific stimulation protocol. The presented approach is highly modular and could be extended to dynamically optimize prosthetic vision for everyday tasks and requirements of the end-user.
]]></description>
<dc:creator>de Ruyter van Steveninck, J.</dc:creator>
<dc:creator>Guclu, U.</dc:creator>
<dc:creator>van Wezel, R. J. A.</dc:creator>
<dc:creator>van Gerven, M. A. J.</dc:creator>
<dc:date>2020-12-21</dc:date>
<dc:identifier>doi:10.1101/2020.12.19.423601</dc:identifier>
<dc:title><![CDATA[End-to-end optimization of prosthetic vision]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-12-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.12.19.423580v1?rss=1">
<title>
<![CDATA[
Sleep leads to system-wide neural changes independent of allo- and egocentric spatial training in humans and rats 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.12.19.423580v1?rss=1"
</link>
<description><![CDATA[
Sleep is important for memory consolidation, especially the process of systems consolidation should occur during sleep. While a significant amount of research has been done in regards to the effect of sleep on behavior and certain mechanisms during sleep, until now evidence is lacking that sleep leads to consolidation across the system. Here, we investigated the role of sleep in consolidation of spatial memory in the watermaze in both rats and humans using allocentric and egocentric based training. Combining behavior with immediate early gene expression analysis in rodents and functional MR imaging in humans, elucidated similar behavioral and neural effects in both species. Rats and humans showed a benefit of sleep on behavior. Interestingly, sleep led to systems-wide retrieval network in both species in both training conditions. Thus, we provide cross-species evidence for memory consolidation on the system-level occurring during sleep.

Significance StatementProcesses occurring during sleep such as memory reactivations are proposed to lead to consolidation from the initial hippocampal memory representation to long-lasting cortical representations, this is known as systems consolidation. By combining behavioral measurements in the watermaze with immediate early gene expression analysis in rats and function magnetic resonance imaging in humans, we could show a benefit of sleep on behavioral memory performance. And, sleep lead to systems-wide changes in the retrieval network. These results are the first direct evidence supporting the role of sleep for systems-wide memory consolidation in both rats and humans.
]]></description>
<dc:creator>Samanta, A.</dc:creator>
<dc:creator>van Rongen, L. S.</dc:creator>
<dc:creator>Rossato, J. I.</dc:creator>
<dc:creator>Jacobse, J.</dc:creator>
<dc:creator>Schoenefeld, R.</dc:creator>
<dc:creator>Genzel, L.</dc:creator>
<dc:date>2020-12-21</dc:date>
<dc:identifier>doi:10.1101/2020.12.19.423580</dc:identifier>
<dc:title><![CDATA[Sleep leads to system-wide neural changes independent of allo- and egocentric spatial training in humans and rats]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-12-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.12.19.423579v1?rss=1">
<title>
<![CDATA[
Neuroanatomy of the grey seal brain: bringing pinnipeds into the neurobiological study of vocal learning 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.12.19.423579v1?rss=1"
</link>
<description><![CDATA[
Comparative studies of vocal learning and vocal non-learning animals can increase our understanding of the neurobiology and evolution of vocal learning and human speech. Mammalian vocal learning is understudied: most research has either focused on vocal learning in songbirds or its absence in non-human primates. Here we focus on a highly promising model species for the neurobiology of vocal learning: grey seals. We provide a neuroanatomical atlas (based on dissected brain slices and magnetic resonance images), a labelled MRI template, a 3D model with volumetric measurements of brain regions, and histological cortical stainings. Four main features of the grey seal brain stand out. (1) It is relatively big and highly convoluted. (2) It hosts a relatively large temporal lobe and cerebellum, structures which could support developed timing abilities and acoustic processing. (3) The cortex is similar to humans in thickness and shows the expected six-layered mammalian structure. (4) Expression of FoxP2 - a gene involved in vocal learning and spoken language - is present in deeper layers of the cortex. Our results could facilitate future studies targeting the neural and genetic underpinnings of mammalian vocal learning, thus bridging the research gap from songbirds to humans and non-human primates.
]]></description>
<dc:creator>Hoeksema, N.</dc:creator>
<dc:creator>Verga, L.</dc:creator>
<dc:creator>Mengede, J.</dc:creator>
<dc:creator>van Roessel, C.</dc:creator>
<dc:creator>Villanueva, S.</dc:creator>
<dc:creator>Salazar-Casals, A.</dc:creator>
<dc:creator>Rubio-Garcia, A.</dc:creator>
<dc:creator>Curcic-Blake, B.</dc:creator>
<dc:creator>Vernes, S.</dc:creator>
<dc:creator>Ravignani, A.</dc:creator>
<dc:date>2020-12-19</dc:date>
<dc:identifier>doi:10.1101/2020.12.19.423579</dc:identifier>
<dc:title><![CDATA[Neuroanatomy of the grey seal brain: bringing pinnipeds into the neurobiological study of vocal learning]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-12-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.12.18.423445v1?rss=1">
<title>
<![CDATA[
Meta-analytic evidence for downregulation of the amygdala during working memory maintenance 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.12.18.423445v1?rss=1"
</link>
<description><![CDATA[
The amygdala is a region critically implicated in affective processes. Downregulation of the amygdala is therefore one of the hallmarks of successful emotion regulation. Downregulation is thought to be established through top-down control of the executive control network over the amygdala. Such a reciprocal relationship, however, is not exclusive to cognitive regulation of emotion. It has recently been noted that any cognitively demanding task may downregulate the amygdala, including a standard working memory task. Here, using a coordinate-based meta-analysis based on an activation likelihood estimation (ALE), we examined whether a standard working memory task (i.e., a 2-back task) downregulates the amygdala similarly to a cognitive reappraisal task. Following the PRISMA guidelines, we included a total of 66 studies using a 2-back working memory task and 65 studies using a cognitive reappraisal task. We found that a standard 2-back working memory task indeed systematically downregulates the amygdala, and that deactivated clusters strongly overlap with those observed during a cognitive reappraisal task. This finding has important consequences for the interpretation of the underlying mechanism of the effects of cognitive reappraisal on amygdala activity: downregulation of amygdala during cognitive reappraisal might be due to the cognitively demanding nature of the task and not per se by the act of the reappraisal itself. Moreover, it raises the possibility of applying working memory tasks in a clinical setting as an alternative emotion regulation strategy.
]]></description>
<dc:creator>de Voogd, L. D.</dc:creator>
<dc:creator>Hermans, E. J.</dc:creator>
<dc:date>2020-12-19</dc:date>
<dc:identifier>doi:10.1101/2020.12.18.423445</dc:identifier>
<dc:title><![CDATA[Meta-analytic evidence for downregulation of the amygdala during working memory maintenance]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-12-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.06.26.173724v1?rss=1">
<title>
<![CDATA[
Genetics of human gut microbiome composition 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.06.26.173724v1?rss=1"
</link>
<description><![CDATA[
To study the effect of host genetics on gut microbiome composition, the MiBioGen consortium curated and analyzed genome-wide genotypes and 16S fecal microbiome data from 18,340 individuals (24 cohorts). Microbial composition showed high variability across cohorts: only 9 out of 410 genera were detected in more than 95% samples. A genome-wide association study (GWAS) of host genetic variation in relation to microbial taxa identified 31 loci affecting microbiome at a genome-wide significant (P<5x10-8) threshold. One locus, the lactase (LCT) gene locus, reached study-wide significance (GWAS signal P=1.28x10-20), and it showed an age-dependent association with Bifidobacterium abundance. Other associations were suggestive (1.95x10-10<P<5x10-8) but enriched for taxa showing high heritability and for genes expressed in the intestine and brain. A phenome-wide association study and Mendelian randomization identified enrichment of microbiome trait loci in the metabolic, nutrition and environment domains and suggested the microbiome has causal effects in ulcerative colitis and rheumatoid arthritis.
]]></description>
<dc:creator>Kurilshikov, A.</dc:creator>
<dc:creator>Medina-Gomez, C.</dc:creator>
<dc:creator>Bacigalupe, R.</dc:creator>
<dc:creator>Radjabzadeh, D.</dc:creator>
<dc:creator>Wang, J.</dc:creator>
<dc:creator>Demirkan, A.</dc:creator>
<dc:creator>Le Roy, C. I.</dc:creator>
<dc:creator>Raygoza Garay, J. A.</dc:creator>
<dc:creator>Finnicum, C.</dc:creator>
<dc:creator>Liu, X.</dc:creator>
<dc:creator>Zhernakova, D.</dc:creator>
<dc:creator>Bonder, M. J.</dc:creator>
<dc:creator>Hansen, T. H.</dc:creator>
<dc:creator>Frost, F.</dc:creator>
<dc:creator>Ruhlemann, M. C.</dc:creator>
<dc:creator>Turpin, W.</dc:creator>
<dc:creator>Moon, J.-Y.</dc:creator>
<dc:creator>Kim, H.-N.</dc:creator>
<dc:creator>Lull, K.</dc:creator>
<dc:creator>Barkan, E.</dc:creator>
<dc:creator>Shah, S. A.</dc:creator>
<dc:creator>Fornage, M.</dc:creator>
<dc:creator>Szopinska-Tokov, J.</dc:creator>
<dc:creator>Wallen, Z.</dc:creator>
<dc:creator>Borisevich, D.</dc:creator>
<dc:creator>Agreus, L.</dc:creator>
<dc:creator>Andreasson, A.</dc:creator>
<dc:creator>Bang, C.</dc:creator>
<dc:creator>Bedrani, L.</dc:creator>
<dc:creator>Bell, J. T.</dc:creator>
<dc:creator>Bisgaard, H.</dc:creator>
<dc:creator>Boehnke, M.</dc:creator>
<dc:creator>Boomsma, D. I.</dc:creator>
<dc:creator>Burk, R. D.</dc:creator>
<dc:creator>Claringbould, A.</dc:creator>
<dc:creator>Croitoru, K.</dc:creator>
<dc:creator>Davies, G.</dc:creator>
<dc:creator>Van Duijn, C.</dc:creator>
<dc:creator>Duijts, L.</dc:creator>
<dc:creator>Falony, G.</dc:creator>
<dc:creator>Fu, J.</dc:creator>
<dc:creator>van der Graaf, A.</dc:creator>
<dc:creator>Hansen, T</dc:creator>
<dc:date>2020-06-28</dc:date>
<dc:identifier>doi:10.1101/2020.06.26.173724</dc:identifier>
<dc:title><![CDATA[Genetics of human gut microbiome composition]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-06-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.12.15.422902v1?rss=1">
<title>
<![CDATA[
The role of anatomical connection strength for interareal communication in macaque cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.12.15.422902v1?rss=1"
</link>
<description><![CDATA[
What is the relationship between anatomical connection strength and rhythmic synchronization? Simultaneous recordings of 15 cortical areas in two macaque monkeys show that interareal networks are functionally organized in spatially distinct modules with specific synchronization frequencies, i.e. frequency-specific functional connectomes. We relate the functional interactions between 91 area pairs to their anatomical connection strength defined in a separate cohort of twenty six subjects. This reveals that anatomical connection strength predicts rhythmic synchronization and vice-versa, in a manner that is specific for frequency bands and for the feedforward versus feedback direction, even if interareal distances are taken into account. These results further our understanding of structure-function relationships in large-scale networks covering different modality-specific brain regions and provide strong constraints on mechanistic models of brain function. Because this approach can be adapted to non-invasive techniques, it promises to open new perspectives on the functional organization of the human brain.
]]></description>
<dc:creator>Vezoli, J.</dc:creator>
<dc:creator>Vinck, M.</dc:creator>
<dc:creator>Bosman, C. A.</dc:creator>
<dc:creator>Bastos, A. M.</dc:creator>
<dc:creator>Lewis, C. M.</dc:creator>
<dc:creator>Kennedy, H.</dc:creator>
<dc:creator>Fries, P.</dc:creator>
<dc:date>2020-12-15</dc:date>
<dc:identifier>doi:10.1101/2020.12.15.422902</dc:identifier>
<dc:title><![CDATA[The role of anatomical connection strength for interareal communication in macaque cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-12-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.12.08.415729v1?rss=1">
<title>
<![CDATA[
Information transfer and recovery for the sense of touch 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.12.08.415729v1?rss=1"
</link>
<description><![CDATA[
Transformation of postsynaptic potentials (PSPs) into action potentials (APs) is the rate-limiting step of communication in neural networks. The efficiency of this intracellular information transfer also powerfully shapes stimulus representations in sensory cortices. Using whole-cell recordings and information-theoretic measures, we show herein that somatic PSPs accurately represent stimulus location on a trial-by-trial basis in single neurons even 4 synapses away from the sensory periphery in the whisker system. This information is largely lost during AP generation but can be rapidly (<20 ms) recovered using complementary information in local populations in a cell-type-specific manner. These results show that as sensory information is transferred from one neural locus to another, the circuits reconstruct the stimulus with high fidelity so that sensory representations of single neurons faithfully represent the stimulus in the periphery, but only in their PSPs, resulting in lossless information processing for the sense of touch in the primary somatosensory cortex.
]]></description>
<dc:creator>Huang, C.</dc:creator>
<dc:creator>Englitz, B.</dc:creator>
<dc:creator>Reznik, A.</dc:creator>
<dc:creator>Zeldenrust, F.</dc:creator>
<dc:creator>Celikel, T.</dc:creator>
<dc:date>2020-12-09</dc:date>
<dc:identifier>doi:10.1101/2020.12.08.415729</dc:identifier>
<dc:title><![CDATA[Information transfer and recovery for the sense of touch]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-12-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.12.15.422826v1?rss=1">
<title>
<![CDATA[
Heterogeneous relationships between white matter and behaviour 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.12.15.422826v1?rss=1"
</link>
<description><![CDATA[
Several studies have established specific relationships between White Matter (WM) and behaviour. However, these studies have typically focussed on fractional anisotropy (FA), a neuroimaging metric that is sensitive to multiple tissue properties, making it difficult to identify what biological aspects of WM may drive such relationships. Here, we carry out a pre-registered assessment of WM-behaviour relationships in 50 healthy individuals across multiple behavioural and anatomical domains, and complementing FA with myelin-sensitive quantitative MR modalities (MT, R1, R2*).

Surprisingly, we only find support for predicted relationships between FA and behaviour in one of three pre-registered tests. For one behavioural domain, where we failed to detect an FA-behaviour correlation, we instead find evidence for a correlation between behaviour and R1. This hints that multimodal approaches are able to identify a wider range of WM-behaviour relationships than focusing on FA alone.

To test whether a common biological substrate such as myelin underlies WM-behaviour relationships, we then ran joint multimodal analyses, combining across all MRI parameters considered. No significant multimodal signatures were found and power analyses suggested that sample sizes of 40 to 200 may be required to detect such joint multimodal effects, depending on the task being considered.

These results demonstrate that FA-behaviour relationships from the literature can be replicated, but may not be easily generalisable across domains. Instead, multimodal microstructural imaging may be best placed to detect a wider range of WM-behaviour relationships, as different MRI modalities provide distinct biological sensitivities. Our findings highlight a broad heterogeneity in WMs relationship with behaviour, suggesting that variable biological effects may be shaping their interaction.

HighlightsO_LIPre-registered testing of microstructural imaging across modalities (FA, MT, R1, R2*) to test WM-behaviour relationships.
C_LIO_LIPartial support for FA-behaviour relationships hypothesised based on previous literature.
C_LIO_LIMultimodal approaches can help detect WM-behaviour relationships that are not detected with FA alone.
C_LIO_LISample sizes of 40 to 200 may be needed to detect myelin-behaviour relationships in joint multimodal analyses.
C_LIO_LIVariable biological effects may be shaping WM-behaviour relationships.
C_LI
]]></description>
<dc:creator>Lazari, A.</dc:creator>
<dc:creator>Salvan, P.</dc:creator>
<dc:creator>Cottaar, M.</dc:creator>
<dc:creator>Papp, D.</dc:creator>
<dc:creator>van der Werf, O. J.</dc:creator>
<dc:creator>Johnstone, A.</dc:creator>
<dc:creator>Sanders, Z.-B.</dc:creator>
<dc:creator>Sampaio-Baptista, C.</dc:creator>
<dc:creator>Eichert, N.</dc:creator>
<dc:creator>Miyamoto, K.</dc:creator>
<dc:creator>Winkler, A.</dc:creator>
<dc:creator>Callaghan, M. F.</dc:creator>
<dc:creator>Nichols, T. E.</dc:creator>
<dc:creator>Stagg, C. J.</dc:creator>
<dc:creator>Rushworth, M.</dc:creator>
<dc:creator>Verhagen, L.</dc:creator>
<dc:creator>Johansen-Berg, H.</dc:creator>
<dc:date>2020-12-15</dc:date>
<dc:identifier>doi:10.1101/2020.12.15.422826</dc:identifier>
<dc:title><![CDATA[Heterogeneous relationships between white matter and behaviour]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-12-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.01.06.425535v1?rss=1">
<title>
<![CDATA[
Independent Genomic Sources of Brain Structure and Function 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.01.06.425535v1?rss=1"
</link>
<description><![CDATA[
IntroductionThe last decade has seen a surge in well powered genome-wide association studies (GWASs) of complex behavioural traits, disorders, and more recently, of brain structural and functional neuroimaging features. However, the extreme polygenicity of these complex traits makes it difficult to translate the GWAS signal into mechanistic biological insights. We postulate that the covariance of SNP-effects across many brain features, as be captured by latent genomic components of SNP effect sizes. These may partly reflect the concerted multi-locus genomic effects through known molecular pathways and protein-protein interactions. Here, we test the feasibility of a new data-driven method to derive such latent components of genome-wide effects on more than thousand neuroimaging derived traits, and investigate their utility in interpreting the complex biological processes that shape the GWAS signal.

MethodsWe downloaded the GWAS summary statistics of 3,143 brain imaging-derived phenotypes (IDPs) from the UK Biobank, provided by the Oxford Brain Imaging Genetics (BIG) Server (Elliott et al. 2018). Probabilistic independent component analysis (ICA) was used to extract two hundred independent genomic components from the matrix of SNP-effect sizes. We qualitatively describe the distribution of the latent components loadings in the neuroimaging and the genomic dimensions. Gene-wide statistics were calculated for each genomic component. We tested the genomic components enrichment for molecular pathways using MSigDB, and for single-cell RNA-sequencing of adult and foetal brain cells.

Results200 components explained 80% of the variance in SNP-effects sizes. Each MRI modality and data processing method projected the imaging data into a clearly distinct cluster in the genomic component embedded space. Among the 200 genomic components, 157 were clearly driven by a single locus, while 39 were highly polygenic. Together, these 39 components were significantly enriched for 2,274 MSigDB gene sets (fully corrected for multiple testing across gene-sets and components). Several components were sensitive to molecular pathways, single cell expression profiles, and brain traits in patterns consistent with knowledge across these biological levels. To illustrate this, we highlight a component that implicated axonal regeneration pathways, which was specifically enriched for gene expression in oligodendrocyte precursors, microglia and astrocytes, and loaded highly on white matter neuroimaging traits. We highlight a second component that implicated synaptic function and neuron projection organization pathways that was specifically enriched for neuronal cell transcriptomes.

ConclusionWe propose genomic ICA as a new method to identify latent genetic factors influencing brain structure and function by multimodal MRI. The derived latent genomic dimensions are highly sensitive to known molecular pathways and cell-specific gene expression profiles. Genomic ICA may help to disentangle the many different biological routes by which the genome defines the inter-individual variation of the brain. Future research is aimed at using this method to profile individual subjects genomic data along the new latent dimensions and evaluating the utility of these dimensions in stratifying heterogeneous patient populations.
]]></description>
<dc:creator>Soheili-Nezhad, S.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>Sprooten, E.</dc:creator>
<dc:date>2021-01-07</dc:date>
<dc:identifier>doi:10.1101/2021.01.06.425535</dc:identifier>
<dc:title><![CDATA[Independent Genomic Sources of Brain Structure and Function]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-01-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.01.05.425205v1?rss=1">
<title>
<![CDATA[
Corticospinal correlates of hand preference for reaching during whole-body motion 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.01.05.425205v1?rss=1"
</link>
<description><![CDATA[
Behavioral studies have shown that humans account for inertial acceleration in their decisions of hand choice when reaching during body motion. Physiologically, it is unclear at what stage of movement preparation information about body motion is integrated in the process of hand selection. Here, we addressed this question by applying transcranial magnetic stimulation over motor cortex (M1) of human participants who performed a preferential reach task while they were sinusoidally translated on a linear motion platform. If M1 only represents a read-out of the final hand choice, we expect the body motion not to affect the MEP amplitude. If body motion biases the hand selection process prior to target onset, we expect corticospinal excitability to modulate with the phase of the motion, with larger MEP amplitudes for phases that show a bias to using the right hand. Behavioral results replicate our earlier findings of a sinusoidal modulation of hand choice bias with motion phase. MEP amplitudes also show a sinusoidal modulation with motion phase, suggesting that body motion influences corticospinal excitability which may ultimately reflect changes of hand preference. The modulation being present prior to target onset suggests that competition between hands is represented throughout the corticospinal tract. Its phase relationship with the motion profile suggests that other processes after target onset take up time until the hand selection process has been completely resolved, and the reach is initiated. We conclude that the corticospinal correlates of hand preference are modulated by body motion.
]]></description>
<dc:creator>Oostwoud Wijdenes, L.</dc:creator>
<dc:creator>Wynn, S. C.</dc:creator>
<dc:creator>Roesink, B. S.</dc:creator>
<dc:creator>Schutter, D. J. L. G.</dc:creator>
<dc:creator>Selen, L. P. J.</dc:creator>
<dc:creator>Medendorp, W. P.</dc:creator>
<dc:date>2021-01-05</dc:date>
<dc:identifier>doi:10.1101/2021.01.05.425205</dc:identifier>
<dc:title><![CDATA[Corticospinal correlates of hand preference for reaching during whole-body motion]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-01-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.01.20.427439v1?rss=1">
<title>
<![CDATA[
Human neuronal networks on micro-electrode arrays are a highly robust tool to study disease-specific genotype-phenotype correlations in vitro 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.01.20.427439v1?rss=1"
</link>
<description><![CDATA[
Micro-electrode arrays (MEAs) are increasingly used to characterize neuronal network activity of human induced pluripotent stem-cell (hiPSC)-derived neurons. Despite their gain in popularity, MEA recordings from hiPSC-derived neuronal networks are not always used to their full potential in respect to experimental design, execution and data analysis. Therefore, we benchmarked the robustness and sensitivity of MEA-derived neuronal activity patterns derived from ten healthy individual control lines. We provide recommendations on experimental design and analysis to achieve standardization. With such standardization, MEAs can be used as a reliable platform to distinguish (disease-specific) network phenotypes. In conclusion, we show that MEAs are a powerful and robust tool to uncover functional neuronal network phenotypes from hiPSC-derived neuronal networks, and provide an important resource to advance the hiPSC field towards the use of MEAs for disease-phenotyping and drug discovery.
]]></description>
<dc:creator>Mossink, B.</dc:creator>
<dc:creator>Verboven, A. H. A.</dc:creator>
<dc:creator>van Hugte, E. J. H.</dc:creator>
<dc:creator>Klein Gunnewiek, T. M.</dc:creator>
<dc:creator>Parodi, G.</dc:creator>
<dc:creator>Linda, K.</dc:creator>
<dc:creator>Schoenmaker, C.</dc:creator>
<dc:creator>Kleefstra, T.</dc:creator>
<dc:creator>Kozicz, T.</dc:creator>
<dc:creator>van Bokhoven, H.</dc:creator>
<dc:creator>Schubert, D.</dc:creator>
<dc:creator>Nadif Kasri, N.</dc:creator>
<dc:creator>Frega, M.</dc:creator>
<dc:date>2021-01-21</dc:date>
<dc:identifier>doi:10.1101/2021.01.20.427439</dc:identifier>
<dc:title><![CDATA[Human neuronal networks on micro-electrode arrays are a highly robust tool to study disease-specific genotype-phenotype correlations in vitro]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-01-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.01.22.427803v1?rss=1">
<title>
<![CDATA[
Social prediction modulates activity of macaque superior temporal cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.01.22.427803v1?rss=1"
</link>
<description><![CDATA[
The ability to attribute thoughts to others, also called theory of mind (TOM), has been extensively studied. Computationally, the basis of TOM in humans has been interpreted within the predictive coding framework and associated with activity in the temporo-parietal junction (TPJ). However, the evolutionary origins of these human mindreading abilities have been challenged since the concept was coined. Here we identify a brain region in the Rhesus macaque that shares computational properties with the human TPJ. We revealed, using a non-linguistic task and functional magnetic resonance imaging, that activity in a region of the macaque middle superior temporal cortex was specifically modulated by the predictability of social interactions. As in human TPJ, this region could be distinguished from other temporal regions involved in face processing. Our result suggests the existence of a precursor for the theory of mind ability in the last common ancestor of human and old-world monkeys.
]]></description>
<dc:creator>Roumazeilles, L.</dc:creator>
<dc:creator>Schurz, M.</dc:creator>
<dc:creator>Lojkiewiez, M.</dc:creator>
<dc:creator>Verhagen, L.</dc:creator>
<dc:creator>Schuffelgen, U.</dc:creator>
<dc:creator>Marche, K.</dc:creator>
<dc:creator>Mahmoodi, A.</dc:creator>
<dc:creator>Emberton, A.</dc:creator>
<dc:creator>Simpson, K.</dc:creator>
<dc:creator>Joly, O.</dc:creator>
<dc:creator>Khamassi, M.</dc:creator>
<dc:creator>Rushworth, M. F.</dc:creator>
<dc:creator>Mars, R. B.</dc:creator>
<dc:creator>Sallet, J.</dc:creator>
<dc:date>2021-01-23</dc:date>
<dc:identifier>doi:10.1101/2021.01.22.427803</dc:identifier>
<dc:title><![CDATA[Social prediction modulates activity of macaque superior temporal cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-01-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.02.05.429165v1?rss=1">
<title>
<![CDATA[
A nested cortical hierarchy of neural states underlies event segmentation in the human brain 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.02.05.429165v1?rss=1"
</link>
<description><![CDATA[
A fundamental aspect of human experience is that it is segmented into discrete events. This may be underpinned by transitions between distinct neural states. Using an innovative data-driven state segmentation method, we investigate how neural states are organized across the cortical hierarchy and where in the cortex neural state boundaries and perceived event boundaries overlap. Our results show that neural state boundaries are organized in a temporal cortical hierarchy, with short states in primary sensory regions, and long states in lateral and medial prefrontal cortex. State boundaries are shared within and between groups of brain regions that resemble well-known functional networks. Perceived event boundaries overlap with neural state boundaries across large parts of the cortical hierarchy, particularly when those state boundaries demarcate a strong transition or are shared between brain regions. Taken together, these findings suggest that a partially nested cortical hierarchy of neural states forms the basis of event segmentation.
]]></description>
<dc:creator>Geerligs, L.</dc:creator>
<dc:creator>van Gerven, M.</dc:creator>
<dc:creator>Campbell, K.</dc:creator>
<dc:creator>Güclü, U.</dc:creator>
<dc:date>2021-02-05</dc:date>
<dc:identifier>doi:10.1101/2021.02.05.429165</dc:identifier>
<dc:title><![CDATA[A nested cortical hierarchy of neural states underlies event segmentation in the human brain]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-02-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.02.02.429430v1?rss=1">
<title>
<![CDATA[
Brain2Pix: Fully convolutional naturalistic video reconstruction from brain activity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.02.02.429430v1?rss=1"
</link>
<description><![CDATA[
Reconstructing complex and dynamic visual perception from brain activity remains a major challenge in machine learning applications to neuroscience. Here we present a new method for reconstructing naturalistic images and videos from very large single-participant functional magnetic resonance imaging data that leverages the recent success of image-to-image transformation networks. This is achieved by exploiting spatial information obtained from retinotopic mappings across the visual system. More specifically, we first determine what position each voxel in a particular region of interest would represent in the visual field based on its corresponding receptive field location. Then, the 2D image representation of the brain activity on the visual field is passed to a fully convolutional image-to-image network trained to recover the original stimuli using VGG feature loss with an adversarial regularizer. In our experiments, we show that our method offers a significant improvement over existing video reconstruction techniques.
]]></description>
<dc:creator>Le, L.</dc:creator>
<dc:creator>Ambrogioni, L.</dc:creator>
<dc:creator>Seeliger, K.</dc:creator>
<dc:creator>Güclütürk, Y.</dc:creator>
<dc:creator>van Gerven, M.</dc:creator>
<dc:creator>Güclü, U.</dc:creator>
<dc:date>2021-02-03</dc:date>
<dc:identifier>doi:10.1101/2021.02.02.429430</dc:identifier>
<dc:title><![CDATA[Brain2Pix: Fully convolutional naturalistic video reconstruction from brain activity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-02-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.02.02.429418v1?rss=1">
<title>
<![CDATA[
Alpha oscillations shape sensory representation and perceptual accuracy 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.02.02.429418v1?rss=1"
</link>
<description><![CDATA[
Alpha activity (8-14 Hz) is the dominant rhythm in the awake brain, and thought to play an important role in setting the brains internal state. Previous work has associated states of decreased alpha power with enhanced neural excitability. However, evidence is mixed on whether and how such excitability enhancement modulates sensory signals of interest versus noise differently, and what, if any, the consequences are for subsequent perception. Here, human subjects (male and female) performed a visual detection task in which we manipulated their decision criteria in a block-wise manner. While our manipulation led to substantial criterion shifts, these shifts were not reflected in pre-stimulus alpha-band changes. Rather, lower pre-stimulus alpha power in occipital-parietal areas improved perceptual sensitivity and enhanced information content decodable from neural activity patterns. Additionally, oscillatory alpha phase immediately before stimulus presentation modulated accuracy. Together, our results suggest that alpha-band dynamics modulate sensory signals of interest more strongly than noise.

Significance statementThe internal state of our brain fluctuates, giving rise to variability in perception and action. Neural oscillations, most prominently in the alpha-band, have been suggested to play a role in setting this internal state. Here, we show that ongoing alpha-band activity in occipital-parietal regions predicts the quality of visual information decodable in neural activity patterns, and subsequently human observers sensitivity in a visual detection task. Our results provide comprehensive evidence that visual representation is modulated by ongoing alpha-band activity, and advance our understanding on how, when faced with unchanging external stimuli, internal neural fluctuations influence perception and behavior.
]]></description>
<dc:creator>Zhou, Y. J.</dc:creator>
<dc:creator>Iemi, L.</dc:creator>
<dc:creator>Schoffelen, J.-M.</dc:creator>
<dc:creator>de Lange, F. P.</dc:creator>
<dc:creator>Haegens, S.</dc:creator>
<dc:date>2021-02-03</dc:date>
<dc:identifier>doi:10.1101/2021.02.02.429418</dc:identifier>
<dc:title><![CDATA[Alpha oscillations shape sensory representation and perceptual accuracy]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-02-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.02.01.429143v1?rss=1">
<title>
<![CDATA[
Cortico-amygdalar connectivity and externalizing/internalizing behavior in children with neurodevelopmental disorders 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.02.01.429143v1?rss=1"
</link>
<description><![CDATA[
BackgroundExternalizing and internalizing behaviors are common and contribute to impairment in children with neurodevelopmental disorders (NDDs). Associations between externalizing or internalizing behaviors and cortico-amygdalar connectivity have been found in children with and without clinically significant internalizing/externalizing behaviors. This study examined whether such associations are present across children with different NDDs.

MethodsMulti-modal neuroimaging and behavioral data from the Province of Ontario Neurodevelopmental Disorders (POND) Network were used. POND participants aged 6-18 years with a primary diagnosis of autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD) or obsessive-compulsive disorder (OCD), as well as typically developing children (TDC) with T1-weighted, resting-state fMRI or diffusion weighted imaging and parent-report Child Behavioral Checklist (CBCL) data available, were analyzed (n range=157-346). Associations between externalizing or internalizing behavior and cortico-amygdalar structural and functional connectivity indices were examined using linear regressions, controlling for age, gender, and image-modality specific covariates. Behavior-by-diagnosis interaction effects were also examined.

ResultsNo significant linear associations (or diagnosis-by-behavior interaction effects) were found between CBCL-measured externalizing or internalizing behaviors and any of the connectivity indices examined. Post-hoc bootstrapping analyses indicated stability and reliability of these null results.

ConclusionsThe current study provides evidence in favour of the absence of a shared linear relationship between internalizing or externalizing behaviors and cortico-amygdalar connectivity properties across a transdiagnostic sample of children with various NDDs and TDC. Detecting shared brain-behavior relationships in children with NDDs may benefit from the use of different methodological approaches, including incorporation of multi-dimensional behavioral data (i.e. behavioral assessments, neurocognitive tasks, task-based fMRI) or clustering approaches to delineate whether subgroups of individuals with different brain-behavior profiles are present within heterogeneous cross-disorder samples.
]]></description>
<dc:creator>Nakua, H.</dc:creator>
<dc:creator>Hawco, C.</dc:creator>
<dc:creator>Forde, N. J.</dc:creator>
<dc:creator>Jacobs, G. R.</dc:creator>
<dc:creator>Joseph, M.</dc:creator>
<dc:creator>Voineskos, A.</dc:creator>
<dc:creator>Wheeler, A. L.</dc:creator>
<dc:creator>Lai, M.-C.</dc:creator>
<dc:creator>Szatmari, P.</dc:creator>
<dc:creator>Kelley, E.</dc:creator>
<dc:creator>Liu, X.</dc:creator>
<dc:creator>Georgiades, S.</dc:creator>
<dc:creator>Nicolson, R.</dc:creator>
<dc:creator>Schachar, R.</dc:creator>
<dc:creator>Crosbie, J.</dc:creator>
<dc:creator>Anagnostou, E.</dc:creator>
<dc:creator>Lerch, J. P.</dc:creator>
<dc:creator>Arnold, P. D.</dc:creator>
<dc:creator>Ameis, S. H.</dc:creator>
<dc:date>2021-02-02</dc:date>
<dc:identifier>doi:10.1101/2021.02.01.429143</dc:identifier>
<dc:title><![CDATA[Cortico-amygdalar connectivity and externalizing/internalizing behavior in children with neurodevelopmental disorders]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-02-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.01.29.428809v1?rss=1">
<title>
<![CDATA[
Defensive freezing and its relation to approach-avoidance decision-making under threat 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.01.29.428809v1?rss=1"
</link>
<description><![CDATA[
Successful responding to acutely threatening situations requires adequate approach-avoidance decisions. However, it is unclear how threat-induced states-like freezing-related bradycardia-impact the weighing of the potential outcomes of such value-based decisions. Insight into the underlying computations is essential, not only to improve our models of decision-making but also to improve interventions for maladaptive decisions, for instance in anxiety patients and first-responders who frequently have to make decisions under acute threat. Forty-two participants made passive and active approach-avoidance decisions under threat-of-shock when confronted with mixed outcome-prospects (i.e., varying money and shock amounts). Choice behavior was best predicted by a model including individual action-tendencies and bradycardia, beyond the subjective value of the outcome. Moreover, threat-related bradycardia interacted with subjective value, depending on the action-context (i.e., passive vs. active). Specifically, in action-contexts incongruent with participants intrinsic action-tendencies, strong freezers showed diminished effects of subjective value on choice. These findings illustrate the relevance of testing approach-avoidance decisions in relatively ecologically valid conditions of acute and primarily reinforced threat. These mechanistic insights into approach-avoidance conflict-resolution may inspire biofeedback-related techniques to optimize decision-making under threat. Critically, the findings demonstrate the relevance of incorporating internal psychophysiological states and external action-contexts into models of approach-avoidance decision-making.
]]></description>
<dc:creator>Klaassen, F. H.</dc:creator>
<dc:creator>Held, L.</dc:creator>
<dc:creator>Figner, B.</dc:creator>
<dc:creator>O'Reilly, J. X.</dc:creator>
<dc:creator>Klumpers, F.</dc:creator>
<dc:creator>de Voogd, L. D.</dc:creator>
<dc:creator>Roelofs, K.</dc:creator>
<dc:date>2021-02-01</dc:date>
<dc:identifier>doi:10.1101/2021.01.29.428809</dc:identifier>
<dc:title><![CDATA[Defensive freezing and its relation to approach-avoidance decision-making under threat]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-02-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.11.15.383869v1?rss=1">
<title>
<![CDATA[
Bridging brain and cognition: A multilayer network analysis of brain structural covariance and general intelligence in a developmental sample of struggling learners 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.11.15.383869v1?rss=1"
</link>
<description><![CDATA[
Network analytic methods that are ubiquitous in other areas, such as systems neuroscience, have recently been used to test network theories in psychology, including intelligence research. The network or mutualism theory of intelligence proposes that the statistical associations among cognitive abilities (e.g., specific abilities such as vocabulary or memory) stem from causal relations among them throughout development. In this study, we used network models (specifically LASSO) of cognitive abilities and brain structural covariance (grey and white matter) to simultaneously model brain-behavior relationships essential for general intelligence in a large (behavioral, N=805; cortical volume, N=246; fractional anisotropy, N=165), developmental (ages 5-18) cohort of struggling learners (CALM). We found that mostly positive, small partial correlations pervade our cognitive, neural, and multilayer networks. Moreover, using community detection (Walktrap algorithm) and calculating node centrality (absolute strength and bridge strength), we found convergent evidence that subsets of both cognitive and neural nodes play an intermediary role  between brain and behavior. We discuss implications and possible avenues for future studies.
]]></description>
<dc:creator>Simpson-Kent, I. L.</dc:creator>
<dc:creator>Fried, E. I.</dc:creator>
<dc:creator>Akarca, D.</dc:creator>
<dc:creator>Mareva, S.</dc:creator>
<dc:creator>Bullmore, E. T.</dc:creator>
<dc:creator>The CALM Team,</dc:creator>
<dc:creator>Kievit, R. A.</dc:creator>
<dc:date>2020-11-17</dc:date>
<dc:identifier>doi:10.1101/2020.11.15.383869</dc:identifier>
<dc:title><![CDATA[Bridging brain and cognition: A multilayer network analysis of brain structural covariance and general intelligence in a developmental sample of struggling learners]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-11-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.02.19.431732v1?rss=1">
<title>
<![CDATA[
Individual variation in brain microstructural-cognition relationships in aging 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.02.19.431732v1?rss=1"
</link>
<description><![CDATA[
The sources of inter- and intra-individual variability in age-related cognitive decline remain poorly understood. We examined the association between 20-year trajectories of cognitive decline and multimodal brain structure and morphology in older age. We used the Whitehall II Study, an extensively characterised cohort with 3T brain magnetic resonance images acquired at older age (mean age = 69.52{+/-} 4.9) and 5 repeated cognitive performance assessments between mid-life (mean age = 53.2 {+/-}4.9 years) and late-life (mean age = 67.7 {+/-}4.9). Using non-negative matrix factorization, we identified 10 brain components integrating cortical thickness, surface area, fractional anisotropy, and mean and radial diffusivities. We observed two latent variables describing distinct brain-cognition associations. The first describes variations in 5 structural components associated with low mid-life performance across multiple cognitive domains, decline in reasoning, but maintenance of fluency abilities. The second describes variations in 6 structural components associated with low mid-life performance in fluency and memory, but retention of multiple abilities. Expression of latent variables predicts future cognition 3.2 years later (mean age = 70.87 {+/-}4.9). This data-driven approach highlights brain-cognition relationships wherein individuals degrees of cognitive decline and maintenance across diverse cognitive functions that are both positively and negatively associated with cortical structure.
]]></description>
<dc:creator>Patel, R.</dc:creator>
<dc:creator>Mackay, C. E.</dc:creator>
<dc:creator>Jansen, M. G.</dc:creator>
<dc:creator>Devenyi, G.</dc:creator>
<dc:creator>O'Donoghue, M. C.</dc:creator>
<dc:creator>Kivimäki, M.</dc:creator>
<dc:creator>Singh-Manoux, A.</dc:creator>
<dc:creator>Zsoldos, E.</dc:creator>
<dc:creator>Ebmeier, K. P.</dc:creator>
<dc:creator>Chakravarty, M.</dc:creator>
<dc:creator>Suri, S.</dc:creator>
<dc:date>2021-02-20</dc:date>
<dc:identifier>doi:10.1101/2021.02.19.431732</dc:identifier>
<dc:title><![CDATA[Individual variation in brain microstructural-cognition relationships in aging]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-02-20</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.02.19.431945v1?rss=1">
<title>
<![CDATA[
MVPA does not reveal neural representations of hierarchical linguistic structure in MEG 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.02.19.431945v1?rss=1"
</link>
<description><![CDATA[
During comprehension, the meaning extracted from serial language input can be described by hierarchical phrase structure. Whether our brains explicitly encode hierarchical structure during processing is, however, debated. In this study we recorded Magnetoencephalography (MEG) during reading of structurally ambiguous sentences to probe neural activity for representations of underlying phrase structure. 10 human subjects were presented with simple sentences, each containing a prepositional phrase that was ambiguous with respect to its attachment site. Disambiguation was possible based on semantic information. We applied multivariate pattern analyses (MVPA) to the MEG data using linear classifiers as well as representational similarity analysis to probe various effects of phrase structure building on the neural signal. Using MVPA techniques we successfully decoded both syntactic (part-of-speech) as well as semantic information from the brain signal. Importantly, however, we did not find any patterns in the neural signal that differentiate between different hierarchical structures. Nor did we find neural traces of syntactic or semantic reactivation following disambiguating sentence material. These null findings suggest that subjects may not have processed the sentences with respect to their underlying phrase structure. We discuss methodological limits of our analysis as well as cognitive theories of "shallow processing", i.e. in how far rich semantic information can prevent thorough syntactic analysis during processing.
]]></description>
<dc:creator>Arana, S. L.</dc:creator>
<dc:creator>Schoffelen, J.-M.</dc:creator>
<dc:creator>Mitchell, T.</dc:creator>
<dc:creator>Hagoort, P.</dc:creator>
<dc:date>2021-02-19</dc:date>
<dc:identifier>doi:10.1101/2021.02.19.431945</dc:identifier>
<dc:title><![CDATA[MVPA does not reveal neural representations of hierarchical linguistic structure in MEG]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-02-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.02.15.431309v1?rss=1">
<title>
<![CDATA[
Audiovisual adaptation is expressed in spatial and decisional codes 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.02.15.431309v1?rss=1"
</link>
<description><![CDATA[
The brain adapts dynamically to the changing sensory statistics of its environment. The neural circuitries and representations that support this cross-sensory plasticity remain unknown. We combined psychophysics and model-based representational fMRI and EEG to characterize how the adult human brain adapts to misaligned audiovisual signals. We show that audiovisual adaptation moulds regional BOLD-responses and fine-scale activity patterns in a widespread network from Heschls gyrus to dorsolateral prefrontal cortices. Crucially, audiovisual recalibration relies on distinct spatial and decisional codes that are expressed with opposite gradients and timecourses across the auditory processing hierarchy. Early activity patterns in auditory cortices encode sounds in a continuous space that flexibly adapts to misaligned visual inputs. Later activity patterns in frontoparietal cortices code decisional uncertainty consistent with these spatial transformations. Our findings demonstrate that regions throughout the auditory processing hierarchy multiplex spatial and decisional codes to adapt flexibly to the changing sensory statistics in the environment.
]]></description>
<dc:creator>Aller, M.</dc:creator>
<dc:creator>Mihalik, A.</dc:creator>
<dc:creator>Noppeney, U.</dc:creator>
<dc:date>2021-02-17</dc:date>
<dc:identifier>doi:10.1101/2021.02.15.431309</dc:identifier>
<dc:title><![CDATA[Audiovisual adaptation is expressed in spatial and decisional codes]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-02-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.02.15.431283v1?rss=1">
<title>
<![CDATA[
Optimal Reinforcement Learning with Asymmetric Updating in Volatile Environments: a Simulation Study 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.02.15.431283v1?rss=1"
</link>
<description><![CDATA[
AO_SCPLOWBSTRACTC_SCPLOWThe ability to predict the future is essential for decision-making and interaction with the environment to avoid punishment and gain reward. Reinforcement learning algorithms provide a normative way for interactive learning, especially in volatile environments. The optimal strategy for the classic reinforcement learning model is to increase the learning rate as volatility increases. Inspired by optimistic bias in humans, an alternative reinforcement learning model has been developed by adding a punishment learning rate to the classic reinforcement learning model. In this study, we aim to 1) compare the performance of these two models in interaction with different environments, and 2) find optimal parameters for the models. Our simulations indicate that having two different learning rates for rewards and punishments increases performance in a volatile environment. Investigation of the optimal parameters shows that in almost all environments, having a higher reward learning rate compared to the punishment learning rate is beneficial for achieving higher performance which in this case is the accumulation of more rewards. Our results suggest that to achieve high performance, we need a shorter memory window for recent rewards and a longer memory window for punishments. This is consistent with optimistic bias in human behavior.
]]></description>
<dc:creator>Rostami Kandroodi, M.</dc:creator>
<dc:creator>Vahabie, A.-h.</dc:creator>
<dc:creator>Ahmadi, S.</dc:creator>
<dc:creator>Nadjar Araabi, B.</dc:creator>
<dc:creator>Nili Ahmadabadi, M.</dc:creator>
<dc:date>2021-02-16</dc:date>
<dc:identifier>doi:10.1101/2021.02.15.431283</dc:identifier>
<dc:title><![CDATA[Optimal Reinforcement Learning with Asymmetric Updating in Volatile Environments: a Simulation Study]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-02-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.02.16.430904v1?rss=1">
<title>
<![CDATA[
Predictive coding is a consequence of energy efficiency in recurrent neural networks 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.02.16.430904v1?rss=1"
</link>
<description><![CDATA[
Predictive coding represents a promising framework for understanding brain function. It postulates that the brain continuously inhibits predictable sensory input, ensuring a preferential processing of surprising elements. A central aspect of this view is its hierarchical connectivity, involving recurrent message passing between excitatory bottom-up signals and inhibitory top-down feedback. Here we use computational modelling to demonstrate that such architectural hard-wiring is not necessary. Rather, predictive coding is shown to emerge as a consequence of energy efficiency. When training recurrent neural networks to minimise their energy consumption while operating in predictive environments, the networks self-organise into prediction and error units with appropriate inhibitory and excitatory interconnections, and learn to inhibit predictable sensory input. Moving beyond the view of purely top-down driven predictions, we furthermore demonstrate, via virtual lesioning experiments, that networks perform predictions on two timescales: fast lateral predictions among sensory units, and slower prediction cycles that integrate evidence over time.
]]></description>
<dc:creator>Ali, A.</dc:creator>
<dc:creator>Ahmad, N.</dc:creator>
<dc:creator>de Groot, E.</dc:creator>
<dc:creator>van Gerven, M. A. J.</dc:creator>
<dc:creator>Kietzmann, T. C.</dc:creator>
<dc:date>2021-02-16</dc:date>
<dc:identifier>doi:10.1101/2021.02.16.430904</dc:identifier>
<dc:title><![CDATA[Predictive coding is a consequence of energy efficiency in recurrent neural networks]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-02-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.02.15.431231v1?rss=1">
<title>
<![CDATA[
Shared genetic influences on resting-state functional networks of the brain 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.02.15.431231v1?rss=1"
</link>
<description><![CDATA[
The amplitude of activation in brain resting state networks (RSNs), measured with resting-state functional MRI, is heritable and genetically correlated across RSNs, indicating pleiotropy. Recent univariate genome-wide association studies (GWAS) explored the genetic underpinnings of individual variation in RSN activity. Yet univariate genomic analyses do not describe the pleiotropic nature of RSNs. In this study we used a novel multivariate method called genomic SEM to model latent factors that capture the shared genomic influence on RSNs and to identify SNPs and genes driving this pleiotropy. Using summary statistics from GWAS of 21 RSNs reported in UK Biobank (N = 31,688), the genomic latent factor analysis was first conducted in a discovery sample (N = 21,081), and then tested in an independent sample from the same cohort (N = 10,607). In the discovery sample, we show that the genetic organization of RSNs can be best explained by two distinct but correlated genetic factors that divide multimodal association networks and sensory networks. Eleven of the 17 factor loadings were replicated in the independent sample. With the multivariate GWAS, we found and replicated nine independent SNPs associated with the joint architecture of RSNs. Further, by combining the discovery and replication samples, we discovered additional SNP and gene associations with the two factors of RSN amplitude. We conclude that modelling the genetic effects on brain function in a multivariate way is a powerful approach to learn more about the biological mechanisms involved in brain function.
]]></description>
<dc:creator>Guimaraes, J. P. O. F. T.</dc:creator>
<dc:creator>Sprooten, E.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Bralten, J.</dc:creator>
<dc:date>2021-02-15</dc:date>
<dc:identifier>doi:10.1101/2021.02.15.431231</dc:identifier>
<dc:title><![CDATA[Shared genetic influences on resting-state functional networks of the brain]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-02-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.11.17.384586v1?rss=1">
<title>
<![CDATA[
Multisensory integration-attention trade-off in cochlear-implanted deaf individuals 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.11.17.384586v1?rss=1"
</link>
<description><![CDATA[
AO_SCPLOWBSTRACTC_SCPLOWThe cochlear implant (CI) allows profoundly deaf individuals to partially recover hearing. Still, due to the coarse acoustic information provided by the implant, CI users have considerable difficulties in recognizing speech, especially in noisy environments. CI users therefore rely heavily on visual cues to augment speech comprehension, more so than normal-hearing individuals. However, it is unknown how attention to one (focused) or both (divided) modalities plays a role in multisensory speech recognition. Here we show that unisensory speech listening and reading were negatively impacted in divided-attention tasks for CI users - but not for normal-hearing individuals. Our psychophysical experiments revealed that, as expected, listening thresholds were consistently better for the normal-hearing, while lipreading thresholds were largely similar for the two groups. Moreover, audiovisual speech recognition for normal-hearing individuals could be described well by probabilistic summation of auditory and visual speech recognition, while CI users were better integrators than expected from statistical facilitation alone. Our results suggest that this benefit in integration comes at a cost. Unisensory speech recognition is degraded for CI users when attention needs to be divided across modalities. We conjecture that CI users exhibit an integration-attention trade-off. They focus solely on a single modality during focused-attention tasks, but need to divide their limited attentional resources in situations with uncertainty about the upcoming stimulus modality. We argue that in order to determine the benefit of a CI for speech comprehension, situational factors need to be discounted by presenting speech in realistic or complex audiovisual environments.

SO_SCPLOWIGNIFICANCEC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWSTATEMENTC_SCPLOWDeaf individuals using a cochlear implant require significant amounts of effort to listen in noisy environments due to their impoverished hearing. Lipreading can benefit them and reduce the burden of listening by providing an additional source of information. Here we show that the improved speech recognition for audiovisual stimulation comes at a cost, however, as the cochlear-implant users now need to listen and speech-read simultaneously, paying attention to both modalities. The data suggests that cochlear-implant users run into the limits of their attentional resources, and we argue that they, unlike normal-hearing individuals, always need to consider whether a multisensory benefit outweighs the unisensory cost in everyday environments.
]]></description>
<dc:creator>van de Rijt, L. P. H.</dc:creator>
<dc:creator>van Opstal, J. A.</dc:creator>
<dc:creator>van Wanrooij, M. M.</dc:creator>
<dc:date>2020-11-19</dc:date>
<dc:identifier>doi:10.1101/2020.11.17.384586</dc:identifier>
<dc:title><![CDATA[Multisensory integration-attention trade-off in cochlear-implanted deaf individuals]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-11-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.03.04.433946v1?rss=1">
<title>
<![CDATA[
TAFKAP: An improved method for probabilistic decoding of cortical activity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.03.04.433946v1?rss=1"
</link>
<description><![CDATA[
Cortical activity can be difficult to interpret. Neural responses to the same stimulus vary between presentations, due to random noise and other sources of variability. This unreliable relationship to external stimuli renders any pattern of activity open to a multitude of plausible interpretations. We have previously shown that this uncertainty in cortical stimulus representations can be characterized using a probabilistic decoding algorithm, which inverts a generative model of stimulus-evoked cortical responses. Here, we improve upon this method in two important ways, which both target the precision with which the generative model can be estimated from limited, noisy training data. We show that these improvements lead to considerably better estimation of the presented stimulus and its associated uncertainty. Estimates of the presented stimulus are recovered with an accuracy that exceeds that of standard decoding methods (SVMs), and in some cases even approaches the behavioral accuracy of human observers. Moreover, the uncertainty in the decoded probability distributions better characterizes the precision of cortical stimulus information from trial to trial.
]]></description>
<dc:creator>van Bergen, R. S.</dc:creator>
<dc:creator>Jehee, J. F. M.</dc:creator>
<dc:date>2021-03-05</dc:date>
<dc:identifier>doi:10.1101/2021.03.04.433946</dc:identifier>
<dc:title><![CDATA[TAFKAP: An improved method for probabilistic decoding of cortical activity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-03-05</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.12.10.418947v1?rss=1">
<title>
<![CDATA[
No behavioral evidence for rhythmic facilitation of perceptual discrimination 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.12.10.418947v1?rss=1"
</link>
<description><![CDATA[
It has been hypothesized that internal oscillations can synchronize (i.e., entrain) to external environmental rhythms, thereby facilitating perception and behavior. To date, evidence for the link between the phase of neural oscillations and behavior has been scarce and contradictory; moreover, it remains an open question whether the brain can use this tentative mechanism for active temporal prediction. In our present study, we conducted a series of auditory pitch discrimination tasks with 181 healthy participants in an effort to shed light on the proposed behavioral benefits of rhythmic cueing and entrainment. In the three versions of our task, we observed no perceptual benefit of purported entrainment: targets occurring in-phase with a rhythmic cue provided no perceptual benefits in terms of discrimination accuracy or reaction time when compared with targets occurring out-of-phase or targets occurring randomly, nor did we find performance differences for targets preceded by rhythmic vs. random cues. However, we found a surprising effect of cueing frequency on reaction time, in which participants showed faster responses to cue rhythms presented at higher frequencies. We therefore provide no evidence of entrainment, but instead a tentative effect of covert active sensing in which a faster external rhythm leads to a faster communication rate between motor and sensory cortices, allowing for sensory inputs to be sampled earlier in time.
]]></description>
<dc:creator>Lin, W. M.</dc:creator>
<dc:creator>Oetringer, D.</dc:creator>
<dc:creator>Bakker-Marshall, I.</dc:creator>
<dc:creator>Emmerzaal, J.</dc:creator>
<dc:creator>Wilsch, A.</dc:creator>
<dc:creator>ElShafei, H. A.</dc:creator>
<dc:creator>El Rassi, E.</dc:creator>
<dc:creator>Haegens, S.</dc:creator>
<dc:date>2020-12-11</dc:date>
<dc:identifier>doi:10.1101/2020.12.10.418947</dc:identifier>
<dc:title><![CDATA[No behavioral evidence for rhythmic facilitation of perceptual discrimination]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-12-11</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.12.07.414425v1?rss=1">
<title>
<![CDATA[
Linguistic constraints modulate speech timing in an oscillating neural network 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.12.07.414425v1?rss=1"
</link>
<description><![CDATA[
Neuronal oscillations putatively track speech in order to optimize sensory processing. However, it is unclear how isochronous brain oscillations can track pseudo-rhythmic speech input. Here we propose that oscillations can track pseudo-rhythmic speech when considering that speech time is dependent on predictions flowing from internal language models. We show that the temporal dynamics of speech are dependent on the predictability of words in a sentence. A computational model including oscillations, feedback, and inhibition is able to track the natural pseudo-rhythmic speech input. As the model processes, it generates temporal phase codes, which are a candidate mechanism for carrying information forward in time. The model is optimally sensitive to the natural temporal speech dynamics and can explain empirical data on temporal speech illusions. Our results reveal that speech tracking does not only rely on the input acoustics but instead entails an interaction between oscillations and constraints flowing from internal language models.
]]></description>
<dc:creator>Ten Oever, S.</dc:creator>
<dc:creator>Martin, A. E.</dc:creator>
<dc:date>2020-12-07</dc:date>
<dc:identifier>doi:10.1101/2020.12.07.414425</dc:identifier>
<dc:title><![CDATA[Linguistic constraints modulate speech timing in an oscillating neural network]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-12-07</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.03.01.433450v1?rss=1">
<title>
<![CDATA[
Spontaneous neural oscillations influence behavior and sensory representations by suppressing neuronal excitability 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.03.01.433450v1?rss=1"
</link>
<description><![CDATA[
The ability to process and respond to external input is critical for adaptive behavior. Why, then, do neural and behavioral responses vary across repeated presentations of the same sensory input? Spontaneous fluctuations of neuronal excitability are currently hypothesized to underlie the trial-by-trial variability in sensory processing. To test this, we capitalized on invasive electrophysiology in neurosurgical patients performing an auditory discrimination task with visual cues: specifically, we examined the interaction between prestimulus alpha oscillations, excitability, task performance, and decoded neural stimulus representations. We found that strong prestimulus oscillations in the alpha+ band (i.e., alpha and neighboring frequencies), rather than the aperiodic signal, correlated with a low excitability state, indexed by reduced broadband high-frequency activity. This state was related to slower reaction times and reduced neural stimulus encoding strength. We propose that the alpha+ rhythm modulates excitability, thereby resulting in variability in behavior and sensory representations despite identical input.
]]></description>
<dc:creator>Iemi, L.</dc:creator>
<dc:creator>Gwilliams, L.</dc:creator>
<dc:creator>Samaha, J.</dc:creator>
<dc:creator>Auksztulewicz, R.</dc:creator>
<dc:creator>Cycowicz, Y. M.</dc:creator>
<dc:creator>King, J.-R.</dc:creator>
<dc:creator>Nikulin, V. V.</dc:creator>
<dc:creator>Thesen, T.</dc:creator>
<dc:creator>Doyle, W.</dc:creator>
<dc:creator>Devinsky, O.</dc:creator>
<dc:creator>Schroeder, C. E.</dc:creator>
<dc:creator>Melloni, L.</dc:creator>
<dc:creator>Haegens, S.</dc:creator>
<dc:date>2021-03-02</dc:date>
<dc:identifier>doi:10.1101/2021.03.01.433450</dc:identifier>
<dc:title><![CDATA[Spontaneous neural oscillations influence behavior and sensory representations by suppressing neuronal excitability]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-03-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.02.27.433155v1?rss=1">
<title>
<![CDATA[
A de novo paradigm for male infertility 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.02.27.433155v1?rss=1"
</link>
<description><![CDATA[
IntroductionDe novo mutations (DNMs) are known to play a prominent role in sporadic disorders with reduced fitness1. We hypothesize that DNMs play an important role in male infertility and explain a significant fraction of the genetic causes of this understudied disorder. To test this hypothesis, we performed trio-based exome-sequencing in a unique cohort of 185 infertile males and their unaffected parents. Following a systematic analysis, 29 of 145 rare protein altering DNMs were classified as possibly causative of the male infertility phenotype. We observed a significant enrichment of Loss-of-Function (LoF) DNMs in LoF-intolerant genes (p-value=1.00x10-5) as well as predicted pathogenic missense DNMs in missense-intolerant genes (p-value=5.01x10-4). One DNM gene identified, RBM5, is an essential regulator of male germ cell pre-mRNA splicing2. In a follow-up study, 5 rare pathogenic missense mutations affecting this gene were observed in a cohort of 2,279 infertile patients, with no such mutations found in a cohort of 5,784 fertile men (p-value=0.009). Our results provide the first evidence for the role of DNMs in severe male infertility and point to many new candidate genes affecting fertility.
]]></description>
<dc:creator>Oud, M. S.</dc:creator>
<dc:creator>Smits, R. M.</dc:creator>
<dc:creator>Smith, H. E.</dc:creator>
<dc:creator>Mastrorosa, F. K.</dc:creator>
<dc:creator>Holt, G. S.</dc:creator>
<dc:creator>Houston, B. J.</dc:creator>
<dc:creator>de Vries, P. F.</dc:creator>
<dc:creator>Alobaidi, B. K.</dc:creator>
<dc:creator>Batty, L. E.</dc:creator>
<dc:creator>Ismail, H.</dc:creator>
<dc:creator>Greenwood, J.</dc:creator>
<dc:creator>Sheth, H.</dc:creator>
<dc:creator>Mikulasova, A.</dc:creator>
<dc:creator>Astuti, G.</dc:creator>
<dc:creator>Gilissen, C. S.</dc:creator>
<dc:creator>McEleny, K.</dc:creator>
<dc:creator>Turner, H.</dc:creator>
<dc:creator>Coxhead, J.</dc:creator>
<dc:creator>Cockell, S. J.</dc:creator>
<dc:creator>Braat, D.</dc:creator>
<dc:creator>Fleischer, K.</dc:creator>
<dc:creator>D'Hauwers, K.</dc:creator>
<dc:creator>Schaafsma, E.</dc:creator>
<dc:creator>GEMINI Consortium,</dc:creator>
<dc:creator>Nagirnaja, L.</dc:creator>
<dc:creator>Conrad, D.</dc:creator>
<dc:creator>Friedrich, C.</dc:creator>
<dc:creator>Kliesch, S.</dc:creator>
<dc:creator>Aston, K. I.</dc:creator>
<dc:creator>Riera-Escamilla, A.</dc:creator>
<dc:creator>Krausz, C. G.</dc:creator>
<dc:creator>Gonzaga-Jauregui, C.</dc:creator>
<dc:creator>Santibanez-Koref, M.</dc:creator>
<dc:creator>Elliott, D.</dc:creator>
<dc:creator>Vissers, L.</dc:creator>
<dc:creator>Tüttelmann, F.</dc:creator>
<dc:creator>O'Bryan, M.</dc:creator>
<dc:creator>Ramos, L.</dc:creator>
<dc:creator>Xavier, M. J.</dc:creator>
<dc:creator>van der Heijden, G</dc:creator>
<dc:date>2021-02-27</dc:date>
<dc:identifier>doi:10.1101/2021.02.27.433155</dc:identifier>
<dc:title><![CDATA[A de novo paradigm for male infertility]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-02-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.03.10.434856v1?rss=1">
<title>
<![CDATA[
Non-linearity matters: a deep learning solution to the generalization of hidden brain patterns across population cohorts 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.03.10.434856v1?rss=1"
</link>
<description><![CDATA[
Finding an interpretable and compact representation of complex neuroimage data can be extremely useful for understanding brain behavioral mapping and hence for explaining the biological underpinnings of mental disorders. Hand-crafted representations, as well as linear transformations, may not accurately reflect the significant variability across individuals. Here, we applied a data-driven approach to learn interpretable and generalizable latent representations that link cognition with underlying brain systems; we applied a three-dimensional autoencoder to two large-scale datasets to find an interpretable latent representation of high dimensional task fMRI image data. This representation also accounts for demographic characteristics, achieved by solving a joint optimization problem that simultaneously reconstructs the data and predicts clinical or demographic variables. We then applied normative modeling to the latent variables to define summary statistics ( latent indices) to find a multivariate mapping to non-imaging measures. We trained our model with multi-task fMRI data derived from the Human Connectome Project (HCP) that provides whole-brain coverage across a range of cognitive tasks. Next, in a transfer learning setting, we tested the generalization of our latent space on UK Biobank data as an independent dataset. Our model showed high performance in terms of age and predictions and was capable of capturing complex behavioral characteristics and preserving the individualized variabilities using a highly interpretable latent representation.
]]></description>
<dc:creator>Zabihi, M.</dc:creator>
<dc:creator>Kia, S. M.</dc:creator>
<dc:creator>Wolfers, T.</dc:creator>
<dc:creator>Dinga, R.</dc:creator>
<dc:creator>Llera, A.</dc:creator>
<dc:creator>Bzdok, D.</dc:creator>
<dc:creator>Beckmann, C.</dc:creator>
<dc:creator>marquand, A.</dc:creator>
<dc:date>2021-03-14</dc:date>
<dc:identifier>doi:10.1101/2021.03.10.434856</dc:identifier>
<dc:title><![CDATA[Non-linearity matters: a deep learning solution to the generalization of hidden brain patterns across population cohorts]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-03-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.03.13.432212v1?rss=1">
<title>
<![CDATA[
Structural Covariance Networks in Post-Traumatic Stress Disorder: A Multisite ENIGMA-PGC Study 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.03.13.432212v1?rss=1"
</link>
<description><![CDATA[
IntroductionCortical thickness (CT) and surface area (SA) are established biomarkers of brain pathology in posttraumatic stress disorder (PTSD). Structural covariance networks (SCN) constructed from CT and SA may represent developmental associations, or unique interactions between brain regions, possibly influenced by a common causal antecedent. The ENIGMA-PGC PTSD Working Group aggregated PTSD and control subjects data from 29 cohorts in five countries (n=3439).

MethodsUsing Destrieux Atlas, we built SCNs and compared centrality measures between PTSD subjects and controls. Centrality is a graph theory measure derived using SCN.

ResultsNotable nodes with higher CT-based centrality in PTSD compared to controls were left fusiform gyrus, left superior temporal gyrus, and right inferior temporal gyrus. We found sex-based centrality differences in bilateral frontal lobe regions, left anterior cingulate, left superior occipital cortex and right ventromedial prefrontal cortex (vmPFC). Comorbid PTSD and MDD showed higher CT-based centrality in the right anterior cingulate gyrus, right parahippocampal gyrus and lower SA-based centrality in left insular gyrus.

ConclusionUnlike previous studies with smaller sample sizes ([&le;]318), our study found differences in centrality measures using a sample size of 3439 subjects. This is the first cross-sectional study to examine SCN interactions with age, sex, and comorbid MDD. Although limited to group level inferences, centrality measures offer insights into a nodes relationship to the entire functional connectome unlike approaches like seed-based connectivity or independent component analysis. Nodes having higher centrality have greater structural or functional connections, lending them invaluable for translational treatments like neuromodulation.
]]></description>
<dc:creator>Rakesh, G.</dc:creator>
<dc:creator>Sun, D.</dc:creator>
<dc:creator>Logue, M.</dc:creator>
<dc:creator>Clarke-Rubright, E.</dc:creator>
<dc:creator>O Leary, B. M.</dc:creator>
<dc:creator>Haswell, C.</dc:creator>
<dc:creator>Xie, H.</dc:creator>
<dc:creator>Thompson, P.</dc:creator>
<dc:creator>Dennis, E.</dc:creator>
<dc:creator>Jahanshad, N.</dc:creator>
<dc:creator>Koch, S.</dc:creator>
<dc:creator>Frijling, J.</dc:creator>
<dc:creator>Nawijn, L.</dc:creator>
<dc:creator>Olff, M.</dc:creator>
<dc:creator>van Zuiden, M.</dc:creator>
<dc:creator>Rashid, F.</dc:creator>
<dc:creator>Zhu, X.</dc:creator>
<dc:creator>De Bellis, M.</dc:creator>
<dc:creator>Daniels, J. K.</dc:creator>
<dc:creator>Sierk, A.</dc:creator>
<dc:creator>Manthey, A.</dc:creator>
<dc:creator>Stevens, J. S.</dc:creator>
<dc:creator>Jovanovic, T.</dc:creator>
<dc:creator>Stein, M. B.</dc:creator>
<dc:creator>Shenton, M.</dc:creator>
<dc:creator>van der Werff, S. J. A.</dc:creator>
<dc:creator>van der Wee, N. J. A.</dc:creator>
<dc:creator>Vermeiren, R. R. J. M.</dc:creator>
<dc:creator>Schmahl, C.</dc:creator>
<dc:creator>Herzog, J.</dc:creator>
<dc:creator>Kaufman, M. L.</dc:creator>
<dc:creator>O'Connor, L.</dc:creator>
<dc:creator>Lebois, L. A. M.</dc:creator>
<dc:creator>Baker, J. T.</dc:creator>
<dc:creator>Gruber, S. A.</dc:creator>
<dc:creator>Wolff, J. D.</dc:creator>
<dc:creator>Wolf, E. J.</dc:creator>
<dc:creator>Winternitz, S.</dc:creator>
<dc:creator>Gonenc, A.</dc:creator>
<dc:creator>Ressler, K. J.</dc:creator>
<dc:creator>Hofmann, D.</dc:creator>
<dc:creator>Bryant, R. A.</dc:creator>
<dc:creator></dc:creator>
<dc:date>2021-03-16</dc:date>
<dc:identifier>doi:10.1101/2021.03.13.432212</dc:identifier>
<dc:title><![CDATA[Structural Covariance Networks in Post-Traumatic Stress Disorder: A Multisite ENIGMA-PGC Study]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-03-16</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.04.12.439440v1?rss=1">
<title>
<![CDATA[
Self-regulation of stress-related large-scale brain network balance using real-time fMRI Neurofeedback 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.04.12.439440v1?rss=1"
</link>
<description><![CDATA[
It has recently been shown that acute stress affects the allocation of neural resources between large-scale brain networks, and the balance between the executive control network and the salience network in particular. Maladaptation of this dynamic resource reallocation process is thought to play a major role in stress-related psychopathology, suggesting that stress resilience may be determined by the retained ability to adaptively reallocate neural resources between these two networks. Actively training this ability could hence be a potentially promising way to increase resilience in individuals at risk for developing stress-related symptomatology. Using real-time functional Magnetic Resonance Imaging, the current study investigated whether individuals can learn to self-regulate stress-related large-scale network balance. Participants were engaged in a bidirectional and implicit real-time fMRI neurofeedback paradigm in which they were intermittently provided with a visual representation of the difference signal between the average activation of the salience and executive control networks, and tasked with attempting to self-regulate this signal. Our results show that, given feedback about their performance over three training sessions, participants were able to (1) learn strategies to differentially control the balance between SN and ECN activation on demand, as well as (2) successfully transfer this newly learned skill to a situation where they (a) did not receive any feedback anymore, and (b) were exposed to an acute stressor in form of the prospect of a mild electric stimulation. The current study hence constitutes an important first successful demonstration of neurofeedback training based on stress-related large-scale network balance - a novel approach that has the potential to train control over the central response to stressors in real-life and could build the foundation for future clinical interventions that aim at increasing resilience.

HighlightsO_LIAcute stress affects the allocation of neural resources between large-scale brain networks
C_LIO_LIWe provide a first successful demonstration of neurofeedback training based on stress-related large-scale brain networks
C_LIO_LINovel approach has the potential to train control over central response to stressors in real-life
C_LIO_LICould build foundation for future clinical interventions to increase resilience
C_LI
]]></description>
<dc:creator>Krause, F.</dc:creator>
<dc:creator>Kogias, N.</dc:creator>
<dc:creator>Krentz, M.</dc:creator>
<dc:creator>Luehrs, M.</dc:creator>
<dc:creator>Goebel, R.</dc:creator>
<dc:creator>Hermans, E.</dc:creator>
<dc:date>2021-04-13</dc:date>
<dc:identifier>doi:10.1101/2021.04.12.439440</dc:identifier>
<dc:title><![CDATA[Self-regulation of stress-related large-scale brain network balance using real-time fMRI Neurofeedback]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-04-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.02.08.428915v1?rss=1">
<title>
<![CDATA[
Brain age relates to early life factors but not to accelerated brain aging 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.02.08.428915v1?rss=1"
</link>
<description><![CDATA[
Brain age is a widely used index for quantifying individuals brain health as deviation from a normative brain aging trajectory. Higher than expected brain age is thought partially to reflect above-average rate of brain aging. We explicitly tested this assumption in two large datasets and found no association between cross-sectional brain age and steeper brain decline measured longitudinally. Rather, brain age in adulthood was associated with early-life influences indexed by birth weight and polygenic scores. The results call for nuanced interpretations of cross-sectional indices of the aging brain and question their validity as markers of ongoing within-person changes of the aging brain. Longitudinal imaging data should be preferred whenever the goal is to understand individual change trajectories of brain and cognition in aging.
]]></description>
<dc:creator>Vidal-Pineiro, D.</dc:creator>
<dc:creator>Wang, Y.</dc:creator>
<dc:creator>Krogsrud, S. K.</dc:creator>
<dc:creator>Amlien, I. K.</dc:creator>
<dc:creator>Baare, W. F.</dc:creator>
<dc:creator>Bartres-Faz, D.</dc:creator>
<dc:creator>Bertram, L.</dc:creator>
<dc:creator>Brandmaier, A. M.</dc:creator>
<dc:creator>Drevon, C. A.</dc:creator>
<dc:creator>Duzel, S.</dc:creator>
<dc:creator>Ebmeier, K. P.</dc:creator>
<dc:creator>Henson, R. N.</dc:creator>
<dc:creator>Junque, C.</dc:creator>
<dc:creator>Kievit, R.</dc:creator>
<dc:creator>Kuhn, S.</dc:creator>
<dc:creator>Leonardsen, E.</dc:creator>
<dc:creator>Lindenberger, U.</dc:creator>
<dc:creator>Madsen, K. S.</dc:creator>
<dc:creator>Magnussen, F.</dc:creator>
<dc:creator>Mowinckel, A. M.</dc:creator>
<dc:creator>Nyberg, L.</dc:creator>
<dc:creator>Roe, J. M.</dc:creator>
<dc:creator>Segura, B.</dc:creator>
<dc:creator>Sorensen, O.</dc:creator>
<dc:creator>Suri, S.</dc:creator>
<dc:creator>Zsoldos, E.</dc:creator>
<dc:creator>AIBL,</dc:creator>
<dc:creator>Walhovd, K. B.</dc:creator>
<dc:creator>Fjell, A. M.</dc:creator>
<dc:date>2021-02-08</dc:date>
<dc:identifier>doi:10.1101/2021.02.08.428915</dc:identifier>
<dc:title><![CDATA[Brain age relates to early life factors but not to accelerated brain aging]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-02-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.10.28.359711v1?rss=1">
<title>
<![CDATA[
Leveraging big data for classification of children who stutter from fluent peers 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.10.28.359711v1?rss=1"
</link>
<description><![CDATA[
IntroductionLarge datasets, consisting of hundreds or thousands of subjects, are becoming the new data standard within the neuroimaging community. While big data creates numerous benefits, such as detecting smaller effects, many of these big datasets have focused on non-clinical populations. The heterogeneity of clinical populations makes creating datasets of equal size and quality more challenging. There is a need for methods to connect these robust large datasets with the carefully curated clinical datasets collected over the past decades.

MethodsIn this study, resting-state fMRI data from the Adolescent Brain Cognitive Development study (N=1509) and the Human Connectome Project (N=910) is used to discover generalizable brain features for use in an out-of-sample (N=121) multivariate predictive model to classify young (3-10yrs) children who stutter from fluent peers.

ResultsAccuracy up to 72% classification is achieved using 10-fold cross validation. This study suggests that big data has the potential to yield generalizable biomarkers that are clinically meaningful. Specifically, this is the first study to demonstrate that big data-derived brain features can differentiate children who stutter from their fluent peers and provide novel information on brain networks relevant to stuttering pathophysiology.

DiscussionThe results provide a significant expansion to previous understanding of the neural bases of stuttering. In addition to auditory, somatomotor, and subcortical networks, the big data-based models highlight the importance of considering large scale brain networks supporting error sensitivity, attention, cognitive control, and emotion regulation/self-inspection in the neural bases of stuttering.
]]></description>
<dc:creator>Rutherford, S.</dc:creator>
<dc:creator>Angstadt, M.</dc:creator>
<dc:creator>Sripada, C.</dc:creator>
<dc:creator>Chang, S.-E.</dc:creator>
<dc:date>2020-10-29</dc:date>
<dc:identifier>doi:10.1101/2020.10.28.359711</dc:identifier>
<dc:title><![CDATA[Leveraging big data for classification of children who stutter from fluent peers]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-10-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.03.26.437133v1?rss=1">
<title>
<![CDATA[
Coordinating With a Robot Partner Affects Action Monitoring Related Neural Processing 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.03.26.437133v1?rss=1"
</link>
<description><![CDATA[
Robots start to play a role in our social landscape, and they are progressively becoming responsive, both physically and socially. It begs the question of how humans react to and interact with robots in a coordinated manner and what the neural underpinnings of such behavior are. This exploratory study aims to understand the differences in human-human and human-robot interactions at a behavioral level and from a neurophysiological perspective. For this purpose, we adapted a collaborative dynamical paradigm from Hwang et al. (1). All 16 participants held two corners of a tablet while collaboratively guiding a ball around a circular track either with another participant or a robot. In irregular intervals, the ball was perturbed outward creating an artificial error in the behavior, which required corrective measures to return to the circular track again. Concurrently, we recorded electroencephalography (EEG). In the behavioral data, we found an increased velocity and positional error of the ball from the track in the human-human condition vs. human-robot condition. For the EEG data, we computed event-related potentials. To explore the temporal and spatial differences in the two conditions, we used time-regression with overlap-control and corrected for multiple-comparisons using Threshold-Free-Cluster Enhancement. We found a significant difference between human and robot partners driven by significant clusters at fronto-central electrodes. The amplitudes were stronger with a robot partner, suggesting a different neural processing. All in all, our exploratory study suggests that coordinating with robots affects action monitoring related processing. In the investigated paradigm, human participants treat errors during human-robot interaction differently from those made during interactions with other humans.
]]></description>
<dc:creator>Czeszumski, A.</dc:creator>
<dc:creator>Gert, A. L.</dc:creator>
<dc:creator>Keshava, A.</dc:creator>
<dc:creator>Ghadirzadeh, A.</dc:creator>
<dc:creator>Kalthoff, T.</dc:creator>
<dc:creator>Ehinger, B. V.</dc:creator>
<dc:creator>Tiessen, M.</dc:creator>
<dc:creator>Björkman, M.</dc:creator>
<dc:creator>Kragic, D.</dc:creator>
<dc:creator>König, P.</dc:creator>
<dc:date>2021-03-29</dc:date>
<dc:identifier>doi:10.1101/2021.03.26.437133</dc:identifier>
<dc:title><![CDATA[Coordinating With a Robot Partner Affects Action Monitoring Related Neural Processing]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-03-29</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.04.05.438429v1?rss=1">
<title>
<![CDATA[
Warped Bayesian Linear Regression for Normative Modelling of Big Data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.04.05.438429v1?rss=1"
</link>
<description><![CDATA[
Normative modelling is becoming more popular in neuroimaging due to its ability to make predictions of deviation from a normal trajectory at the level of individual participants. It allows the user to model the distribution of several neuroimaging modalities, giving an estimation for the mean and centiles of variation. With the increase in the availability of big data in neuroimaging, there is a need to scale normative modelling to big data sets. However, the scaling of normative models has come with several challenges.

So far, most normative modelling approaches used Gaussian process regression, and although suitable for smaller datasets (up to a few thousand participants) it does not scale well to the large cohorts currently available and being acquired. Furthermore, most neuroimaging modelling methods that are available assume the predictive distribution to be Gaussian in shape. However, deviations from Gaussianity can be frequently found, which may lead to incorrect inferences, particularly in the outer centiles of the distribution. In normative modelling, we use the centiles to give an estimation of the deviation of a particular participant from the  normal trend. Therefore, especially in normative modelling, the correct estimation of the outer centiles is of utmost importance, which is also where data are sparsest.

Here, we present a novel framework based on Bayesian Linear Regression with likelihood warping that allows us to address these problems, that is, to scale normative modelling elegantly to big data cohorts and to correctly model non-Gaussian predictive distributions. In addition, this method provides also likelihood-based statistics, which are useful for model selection.

To evaluate this framework, we use a range of neuroimaging-derived measures from the UK Biobank study, including image-derived phenotypes (IDPs) and whole-brain voxel-wise measures derived from diffusion tensor imaging. We show good computational scaling and improved accuracy of the warped BLR for certain IDPs and voxels if there was a deviation from normality of these parameters in their residuals.

The present results indicate the advantage of a warped BLR in terms of; computational scalability and the flexibility to incorporate non-linearity and non-Gaussianity of the data, giving a wider range of neuroimaging datasets that can be correctly modelled.
]]></description>
<dc:creator>Fraza, C.</dc:creator>
<dc:creator>Dinga, R.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>Marquand, A. F.</dc:creator>
<dc:date>2021-04-06</dc:date>
<dc:identifier>doi:10.1101/2021.04.05.438429</dc:identifier>
<dc:title><![CDATA[Warped Bayesian Linear Regression for Normative Modelling of Big Data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-04-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.04.05.438482v1?rss=1">
<title>
<![CDATA[
Ripple Band Phase Precession of Place Cell Firing during Replay 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.04.05.438482v1?rss=1"
</link>
<description><![CDATA[
Phase coding offers several theoretical advantages for information transmission compared to an equivalent rate code. Phase coding is shown by place cells in the rodent hippocampal formation, which fire at progressively earlier phases of the movement related 6-12Hz theta rhythm as their spatial receptive fields are traversed. Importantly, however, phase coding is independent of carrier frequency, and so we asked whether it might also be exhibited by place cells during 150-250Hz ripple band activity, when they are thought to replay information to neocortex. We demonstrate that place cells which fire multiple spikes during candidate replay events do so at progressively earlier ripple phases, and that spikes fired across all replay events exhibit a negative relationship between decoded location within the firing field and ripple phase. These results provide insights into the mechanisms underlying phase coding and place cell replay, as well as the neural code propagated to downstream neurons.
]]></description>
<dc:creator>Bush, D.</dc:creator>
<dc:creator>Olafsdottir, F.</dc:creator>
<dc:creator>Barry, C.</dc:creator>
<dc:creator>Burgess, N.</dc:creator>
<dc:date>2021-04-06</dc:date>
<dc:identifier>doi:10.1101/2021.04.05.438482</dc:identifier>
<dc:title><![CDATA[Ripple Band Phase Precession of Place Cell Firing during Replay]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-04-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.04.01.438029v1?rss=1">
<title>
<![CDATA[
The monitoring system is attuned to others' actions during dyadic motor interactions 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.04.01.438029v1?rss=1"
</link>
<description><![CDATA[
Successful interpersonal motor interactions necessitate the simultaneous monitoring of our own and our partners actions. To characterize the dynamics of the action monitoring system for tracking self and other behaviors during dyadic synchronous interactions, we combined EEG recordings and immersive Virtual Reality in two tasks where participants were asked to coordinate their actions with those of a Virtual Partner (VP). The two tasks differed in the features to be monitored: the Goal task required participants to predict and monitor the VPs reaching goal; the Spatial task required participants to predict and monitor the VPs reaching trajectory. In both tasks, the VP performed unexpected movement corrections to which the participant needed to adapt. By comparing the neural activity locked to the detection of unexpected changes in the VP action (other-monitoring) or to the participants action-replanning (self-monitoring), we show that during interpersonal interactions the monitoring system is more attuned to others than to ones own actions. Additionally, distinctive neural responses to VPs unexpected goals and trajectory corrections were found: goal corrections were reflected both in early fronto-central and later posterior neural responses while trajectory deviations from the expected movement were reflected only in later and posterior responses. Since these responses were locked to the partners behavior and not to ones own, our results indicate that during interpersonal interactions the action monitoring system is dedicated to evaluating the partners movements. Hence, our results reveal an eminently social role of the monitoring system during motor interactions.

Significance StatementNon-verbal synchronous interpersonal interactions require the monitoring of both our actions and those of our partners. Understanding the neural underpinnings of this ability with a focus on the dynamics between self- and other-monitoring is fundamental to the comprehension of social coordination. By combining EEG and immersive Virtual Reality we demonstrate that the monitoring system is more attuned to others actions than to our own. In two tasks, we show that the neural activity associated with unexpected corrections in the goal or the trajectory of an action are locked to the partners actions rather than to the participants subsequent adaptation. This pattern of results highlights a social mode adopted by the monitoring system to handle motor interactions.
]]></description>
<dc:creator>Moreau, Q.</dc:creator>
<dc:creator>Tieri, G.</dc:creator>
<dc:creator>Era, V.</dc:creator>
<dc:creator>Aglioti, S. M.</dc:creator>
<dc:creator>Candidi, M.</dc:creator>
<dc:date>2021-04-02</dc:date>
<dc:identifier>doi:10.1101/2021.04.01.438029</dc:identifier>
<dc:title><![CDATA[The monitoring system is attuned to others' actions during dyadic motor interactions]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-04-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.04.23.441147v1?rss=1">
<title>
<![CDATA[
Beta-band desynchronization reflects uncertainty in effector selection during motor planning 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.04.23.441147v1?rss=1"
</link>
<description><![CDATA[
While beta-band activity during motor planning is known to be modulated by uncertainty about where to act, less is known about its modulations to uncertainty about how to act. To investigate this issue, we recorded oscillatory brain activity with EEG while human participants (n = 17) performed a hand choice reaching task. The reaching hand was either predetermined or of participants choice, and the target was close to one of the two hands or at about equal distance from both. To measure neural activity in a motion-artifact-free time window, the location of the upcoming target was cued 1000-1500 ms before the presentation of the target, whereby the cue was valid in 50% of trials. As evidence for motor planning during the cueing phase, behavioral observations showed that the cue affected later hand choice. Furthermore, reaction times were longer in the choice than in the predetermined trials, supporting the notion of a competitive process for hand selection. Modulations of beta-band power over central cortical regions, but not alpha-band or theta-band power, were in line with these observations. During the cueing period, reaches in predetermined trials were preceded by larger decreases in beta-band power than reaches in choice trials. Cue direction did not affect reaction times or beta-band power, which may be due to the cue being invalid in 50% of trials, retaining effector uncertainty during motor planning. Our findings suggest that effector uncertainty, similar to target uncertainty, selectively modulates beta-band power during motor planning.

New & NoteworthyWhile reach-related beta-band power in central cortical areas is known to modulate with the number of potential targets, here we show, using a cueing paradigm, that the power in this frequency band, but not in the alpha or theta-band, is also modulated by the uncertainty of which hand to use. This finding supports the notion that multiple possible effector-specific actions can be specified in parallel up to the level of motor preparation.
]]></description>
<dc:creator>van Helvert, M. J. L.</dc:creator>
<dc:creator>Oostwoud Wijdenes, L.</dc:creator>
<dc:creator>Geerligs, L.</dc:creator>
<dc:creator>Medendorp, W. P.</dc:creator>
<dc:date>2021-04-23</dc:date>
<dc:identifier>doi:10.1101/2021.04.23.441147</dc:identifier>
<dc:title><![CDATA[Beta-band desynchronization reflects uncertainty in effector selection during motor planning]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-04-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.04.23.440002v1?rss=1">
<title>
<![CDATA[
Structuring time: The hippocampus constructs sequence memories that generalize temporal relations across experiences 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.04.23.440002v1?rss=1"
</link>
<description><![CDATA[
The hippocampal-entorhinal region supports memory for episodic details, such as temporal relations of sequential events, and mnemonic constructions combining experiences for inferential reasoning. However, it is unclear whether hippocampal event memories reflect temporal relations derived from mnemonic constructions, event order, or elapsing time, and whether these sequence representations generalize temporal relations across similar sequences. Here, participants mnemonically constructed times of events from multiple sequences using infrequent cues and their experience of passing time. After learning, event representations in the anterior hippocampus reflected temporal relations based on constructed times. Temporal relations were generalized across sequences, revealing distinct representational formats for events from the same or different sequences. Structural knowledge about time patterns, abstracted from different sequences, biased the construction of specific event times. These findings demonstrate that mnemonic construction and the generalization of relational knowledge combine in the hippocampus, consistent with the simulation of scenarios from episodic details and structural knowledge.
]]></description>
<dc:creator>Bellmund, J. L. S.</dc:creator>
<dc:creator>Deuker, L.</dc:creator>
<dc:creator>Montijn, N. D.</dc:creator>
<dc:creator>Doeller, C. F.</dc:creator>
<dc:date>2021-04-23</dc:date>
<dc:identifier>doi:10.1101/2021.04.23.440002</dc:identifier>
<dc:title><![CDATA[Structuring time: The hippocampus constructs sequence memories that generalize temporal relations across experiences]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-04-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.04.22.440945v1?rss=1">
<title>
<![CDATA[
KMT2D haploinsufficiency in Kabuki Syndrome disrupts neuronal function through transcriptional and chromatin rewiring independent of H3K4-monomethylation 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.04.22.440945v1?rss=1"
</link>
<description><![CDATA[
Kabuki syndrome (KS) is a rare multisystem disorder, characterized by intellectual disability, growth delay, and distinctive craniofacial features. It is mostly caused by de novo mutations of KMT2D, which is responsible for histone H3lysine 4 mono-methylation (H3K4me1) that marks active and poised enhancers. We assessed the impact of KMT2D mutations on chromatin and transcriptional regulation in a cohort of multiple KS1 tissues, including primary patient samples and disease-relevant lineages, namely cortical neurons (iN), neural crest stem cells (NCSC), and mesenchymal cells (MC). In parallel, we generated an isogenic line derived from human embryonic stem cells (hESC) for the stepwise characterization of neural precursors and mature neurons. We found that transcriptional dysregulation was particularly pronounced in cortical neurons and widely affected synapse activity pathways. This was consistent with highly specific alterations of spontaneous network-bursts patterns evidenced by Micro-electrode-array (MEA)-based neural network. Profiling of H3K4me1 unveiled the almost complete uncoupling between this chromatin mark and the effects on transcription, which is instead reflected by defects in H3K27ac. Finally, we identified the direct targets of KMT2D in mature cortical neurons, uncovering TEAD2 as the main mediator of KMT2D haploinsufficiency. Our results uncover the multi-tissue architecture of KS1 dysregulation and define a unique electrical phenotype and its molecular underpinnings for the cortical neuronal lineage.
]]></description>
<dc:creator>Gabriele, M.</dc:creator>
<dc:creator>Vitriolo, A.</dc:creator>
<dc:creator>Cuvertino, S.</dc:creator>
<dc:creator>Pereira, M. F.</dc:creator>
<dc:creator>Franconi, C.</dc:creator>
<dc:creator>Germain, P.-L.</dc:creator>
<dc:creator>Capocefalo, D.</dc:creator>
<dc:creator>Castaldi, D.</dc:creator>
<dc:creator>Tenderini, E.</dc:creator>
<dc:creator>Bechet, N. B.</dc:creator>
<dc:creator>Millar, C.</dc:creator>
<dc:creator>Koemans, T. S.</dc:creator>
<dc:creator>Sabherwal, N.</dc:creator>
<dc:creator>Stumpel, C.</dc:creator>
<dc:creator>Frega, M.</dc:creator>
<dc:creator>Palumbo, O.</dc:creator>
<dc:creator>Carella, M.</dc:creator>
<dc:creator>Malerba, N.</dc:creator>
<dc:creator>Squeo, G. M.</dc:creator>
<dc:creator>Kleefstra, T.</dc:creator>
<dc:creator>Van Bokhoven, H.</dc:creator>
<dc:creator>Kimber, S. J.</dc:creator>
<dc:creator>Banka, S.</dc:creator>
<dc:creator>Merla, G.</dc:creator>
<dc:creator>Nadif Kasri, N.</dc:creator>
<dc:creator>Testa, G.</dc:creator>
<dc:date>2021-04-23</dc:date>
<dc:identifier>doi:10.1101/2021.04.22.440945</dc:identifier>
<dc:title><![CDATA[KMT2D haploinsufficiency in Kabuki Syndrome disrupts neuronal function through transcriptional and chromatin rewiring independent of H3K4-monomethylation]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-04-23</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.04.16.440223v1?rss=1">
<title>
<![CDATA[
Post mortem mapping of connectional anatomy for the validation of diffusion MRI 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.04.16.440223v1?rss=1"
</link>
<description><![CDATA[
Despite the impressive advances in diffusion MRI (dMRI) acquisition and analysis that have taken place during the Human Connectome era, dMRI tractography is still an imperfect source of information on the circuitry of the brain. In this review, we discuss methods for post mortem validation of dMRI tractography, fiber orientations, and other microstructural properties of axon bundles that are typically extracted from dMRI data. These methods include anatomic tracer studies, Klinglers dissection, myelin stains, label-free optical imaging techniques, and others. We provide an overview of the basic principles of each technique, its limitations, and what it has taught us so far about the accuracy of different dMRI acquisition and analysis approaches.
]]></description>
<dc:creator>Yendiki, A.</dc:creator>
<dc:creator>Aggarwal, M.</dc:creator>
<dc:creator>Axer, M.</dc:creator>
<dc:creator>Howard, A. F.</dc:creator>
<dc:creator>van Cappellen van Walsum, A.-M.</dc:creator>
<dc:creator>Haber, S. N.</dc:creator>
<dc:date>2021-04-19</dc:date>
<dc:identifier>doi:10.1101/2021.04.16.440223</dc:identifier>
<dc:title><![CDATA[Post mortem mapping of connectional anatomy for the validation of diffusion MRI]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-04-19</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.04.23.441170v1?rss=1">
<title>
<![CDATA[
Causal neural mechanisms of context-based object recognition 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.04.23.441170v1?rss=1"
</link>
<description><![CDATA[
Objects can be recognized based on their intrinsic features, including shape, color, and texture. In daily life, however, such features are often not clearly visible, for example when objects appear in the periphery, in clutter, or at a distance. Interestingly, object recognition can still be highly accurate under these conditions when objects are seen within their typical scene context. What are the neural mechanisms of context-based object recognition? According to parallel processing accounts, context-based object recognition is supported by the parallel processing of object and scene information in separate pathways. Output of these pathways is then combined in downstream regions, leading to contextual benefits in object recognition. Alternatively, according to feedback accounts, context-based object recognition is supported by (direct or indirect) feedback from scene-selective to object-selective regions. Here, in three pre-registered transcranial magnetic stimulation (TMS) experiments, we tested a key prediction of the feedback hypothesis: that scene-selective cortex causally and selectively supports context-based object recognition before object-selective cortex does. Early visual cortex (EVC), object-selective lateral occipital cortex (LOC), and scene-selective occipital place area (OPA) were stimulated at three time points relative to stimulus onset while participants categorized degraded objects in scenes and intact objects in isolation, in different trials. Results confirmed our predictions: relative to isolated object recognition, context-based object recognition was selectively and causally supported by OPA at 160-200 ms after onset, followed by LOC at 260-300 ms after onset. These results indicate that context-based expectations facilitate object recognition by disambiguating object representations in visual cortex.
]]></description>
<dc:creator>Wischnewski, M.</dc:creator>
<dc:creator>Peelen, M. V.</dc:creator>
<dc:date>2021-04-26</dc:date>
<dc:identifier>doi:10.1101/2021.04.23.441170</dc:identifier>
<dc:title><![CDATA[Causal neural mechanisms of context-based object recognition]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-04-26</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.04.27.441620v1?rss=1">
<title>
<![CDATA[
Shaping information processing: the role of oscillatory dynamics in a working-memory task 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.04.27.441620v1?rss=1"
</link>
<description><![CDATA[
Neural oscillations are thought to reflect low-level operations that can be employed for higher-level cognitive functions. Here, we investigated the role of brain rhythms in the 1-30 Hz range by recording MEG in human participants performing a visual delayed match-to-sample paradigm in which orientation or spatial frequency of sample and probe gratings had to be matched. A cue occurring before or after sample presentation indicated the to-be-matched feature. We demonstrate that alpha/beta power decrease tracks the presentation of the informative cue and indexes faster responses. Moreover, these faster responses coincided with an augmented phase alignment of slow oscillations, as well as phase-amplitude coupling between slow and fast oscillations. Importantly, stimulus decodability was boosted by both low alpha power and high beta power. In summary, we provide support for a comprehensive framework in which different rhythms play specific roles: slow rhythms control input sampling, while alpha (and beta) gates the information flow, beta recruits task-relevant circuits, and the timing of faster oscillations is controlled by slower ones.

Significance statementBrain oscillations reflect low-level operations, building blocks, that control the flow of information through the brain. We propose and test a novel comprehensive framework in which slow oscillations control input sampling, alpha gates information flow, beta recruits task-relevant circuits, and the timing of faster oscillations is controlled by slower ones. We collected MEG data while participants performed a visual delayed match-to-sample task with pre- & retro-cues. Phase alignment of slow oscillations, governing input sampling, indexed faster responses. Alpha/beta power, gating information flow, boosted behavior & tracked informative cues. Low alpha (gating) & high beta (circuit-setup) power boosted signal information content. This is an essential step towards a more unified framework regarding the role of oscillatory dynamics in shaping information processing.
]]></description>
<dc:creator>ElShafei, H.</dc:creator>
<dc:creator>Zhou, J. A.</dc:creator>
<dc:creator>Haegens, S.</dc:creator>
<dc:date>2021-04-27</dc:date>
<dc:identifier>doi:10.1101/2021.04.27.441620</dc:identifier>
<dc:title><![CDATA[Shaping information processing: the role of oscillatory dynamics in a working-memory task]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-04-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.04.29.441753v1?rss=1">
<title>
<![CDATA[
Movement-Preceding Neural Activity under Parametrically Varying Levels of Time Pressure 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.04.29.441753v1?rss=1"
</link>
<description><![CDATA[
Self-initiated movements are known to be preceded by the readiness potential or RP, a gradual increase in surface-negativity of cortical potentials that can begin up to 1 second or more before movement onset. The RP has been extensively studied for decades, and yet we still lack a clear understanding of its functional role. Attempts to model the RP as an accumulation-to-bound process suggest that this signal is a by-product of time-locking to crests in neural noise rather than the outcome of a pre-conscious decision to initiate a movement. One parameter of the model accounts for the imperative to move now, with cued movements having a strong imperative and purely spontaneous movements having no imperative. Two different variants of the model have been proposed, and both predict a decrease in the (negative) amplitude of the early RP as the imperative grows stronger. In order to test this empirically, we conducted an experiment where subjects produced self-initiated movements under varying levels of time pressure, and we investigated the amplitude, shape, and latency of the RP as a function of the imperative to move, operationalised as a time limit. We identified distinct changes in the amplitude of the early RP that grew non-linearly as the time limit grew shorter. Thus these data did not support the prediction made by the model. In addition, our results confirm that the shape of the RP is not stereotypically negative, being either positive or absent in about half of the subjects.
]]></description>
<dc:creator>Trovo', B.</dc:creator>
<dc:creator>Visser, Y.</dc:creator>
<dc:creator>Iscan, Z.</dc:creator>
<dc:creator>Schurger, A.</dc:creator>
<dc:date>2021-04-30</dc:date>
<dc:identifier>doi:10.1101/2021.04.29.441753</dc:identifier>
<dc:title><![CDATA[Movement-Preceding Neural Activity under Parametrically Varying Levels of Time Pressure]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-04-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.04.30.442171v1?rss=1">
<title>
<![CDATA[
Minimal phrase composition revealed by intracranial recordings 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.04.30.442171v1?rss=1"
</link>
<description><![CDATA[
The ability to comprehend phrases is an essential integrative property of the brain. Here we evaluate the neural processes that enable the transition from single word processing to a minimal compositional scheme. Previous research has reported conflicting timing effects of composition, and disagreement persists with respect to inferior frontal and posterior temporal contributions. To address these issues, 19 patients (10 male, 19 female) implanted with penetrating depth or surface subdural intracranial electrodes heard auditory recordings of adjective-noun, pseudoword-noun and adjective-pseudoword phrases and judged whether the phrase matched a picture. Stimulus-dependent alterations in broadband gamma activity, low frequency power and phase-locking values across the language-dominant left hemisphere were derived. This revealed a mosaic located in the posterior superior temporal sulcus (pSTS), in which closely neighboring cortical sites displayed exclusive sensitivity to either lexicality or phrase structure, but not both. Distinct timings were found for effects of phrase composition (210-300 ms) and pseudoword processing (approximately 300-700 ms), and these were localized to neighboring electrodes in pSTS. The pars triangularis and temporal pole encode anticipation of composition in broadband low frequencies, and both regions exhibit greater functional connectivity with pSTS during phrase composition. Our results suggest that the pSTS is a highly specialized region comprised of sparsely interwoven heterogeneous constituents that encodes both lower and higher level linguistic features. This hub in pSTS for minimal phrase processing may form the neural basis for the human-specific computational capacity for forming hierarchically organized linguistic structures.

SignificanceLinguists have claimed that the integration of multiple words into a phrase demands a computational procedure distinct from single word processing. Here, we provide intracranial recordings from a large patient cohort, with high spatiotemporal resolution, to track the cortical dynamics of phrase composition. Epileptic patients volunteered to participate in a task in which they listened to phrases ("red boat"), word-pseudoword or pseudoword-word pairs (e.g., "red fulg"). At the onset of the second word in phrases, greater broadband high gamma activity was found in posterior superior temporal sulcus in electrodes that exclusively indexed phrasal meaning, and not lexical meaning. These results provide direct, high-resolution signatures of minimal phrase composition in humans, a potentially species-specific computational capacity.
]]></description>
<dc:creator>Murphy, E.</dc:creator>
<dc:creator>Woolnough, O.</dc:creator>
<dc:creator>Rollo, P. S.</dc:creator>
<dc:creator>Roccaforte, Z. J.</dc:creator>
<dc:creator>Segaert, K.</dc:creator>
<dc:creator>Hagoort, P.</dc:creator>
<dc:creator>Tandon, N.</dc:creator>
<dc:date>2021-05-01</dc:date>
<dc:identifier>doi:10.1101/2021.04.30.442171</dc:identifier>
<dc:title><![CDATA[Minimal phrase composition revealed by intracranial recordings]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-05-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.04.30.442198v1?rss=1">
<title>
<![CDATA[
Multimodal brain features at preschool age and the relationship with pre-reading measures one year later: an exploratory study 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.04.30.442198v1?rss=1"
</link>
<description><![CDATA[
Pre-reading language skills develop rapidly in early childhood and are related to brain structure and function in young children prior to formal education. However, the early neurobiological development that support these skills is not well understood and has not been assessed longitudinally using multiple imaging approaches. Here we acquired anatomical, diffusion tensor imaging (DTI) and resting state functional MRI (rs-fMRI) from 35 children at 3.5 years of age. Children were assessed for pre-reading abilities using the NEPSY-II subtests one year later (4.5 years). We applied a data-driven linked independent component analysis to explore the shared co-variation of grey and white matter measures. Two sources of structural variation at 3.5 years of age demonstrated a weak relationship with Speeded Naming scores at 4.5 years of age. The first imaging component involved volumetric variability in reading-related cortical regions alongside microstructural features of the superior longitudinal fasciculus. The second component was dominated by cortical volumetric variations within the cerebellum and visual association area. In a subset of children with rs-fMRI data, we evaluated the inter-network functional connectivity of the left-lateralized fronto-parietal language (FPL) network and its relationship with pre-reading measures. Higher functional connectivity between the FPL functional network and the default mode and visual networks at 3.5 years predicted better Phonological Processing scores at 4.5 years. Together, these results suggest that the integration of functional networks, as well as the co-development of white and grey matter brain structures in early childhood, may support the emergence of pre-reading measures in preschool children.
]]></description>
<dc:creator>Manning, K. Y.</dc:creator>
<dc:creator>Reynolds, J. E.</dc:creator>
<dc:creator>Long, X.</dc:creator>
<dc:creator>Llera, A.</dc:creator>
<dc:creator>Dewey, D.</dc:creator>
<dc:creator>Lebel, C.</dc:creator>
<dc:date>2021-05-01</dc:date>
<dc:identifier>doi:10.1101/2021.04.30.442198</dc:identifier>
<dc:title><![CDATA[Multimodal brain features at preschool age and the relationship with pre-reading measures one year later: an exploratory study]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-05-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.05.05.442735v1?rss=1">
<title>
<![CDATA[
Subtly altered topological asymmetry of brain structural covariance networks in autism spectrum disorder across 43 datasets from the ENIGMA consortium 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.05.05.442735v1?rss=1"
</link>
<description><![CDATA[
Small average differences in the left-right asymmetry of cerebral cortical thickness have been reported in individuals with autism spectrum disorder (ASD) compared to typically developing controls. Although these alterations affect multiple and widespread cortical regional asymmetries, the extent to which specific structural networks might be affected remains unknown. Inter-regional morphological covariance analysis can capture network connectivity relations between different cortical areas at the macroscale level. Here, we used cortical thickness data from 1,455 individuals with ASD and 1,560 controls, across 43 independent datasets of the ENIGMA consortiums ASD Working Group, to assess hemispheric asymmetries of intra-individual structural covariance networks, using graph theory-based topological metrics. Compared with typical features of small-world architecture in controls, the ASD sample showed significantly altered asymmetry of hemispheric networks involving the fusiform, rostral middle frontal, and medial orbitofrontal cortex, driven by shifts toward higher randomization of the corresponding right-hemispheric networks in ASD. A network involving the superior frontal cortex showed decreased right-hemisphere randomization. Based on comparisons with meta-analyzed functional neuroimaging data, the altered connectivity asymmetry particularly affected networks that subserve working memory, executive functions, language, reading, and sensorimotor processes. Taken together, these findings provide new insights into how altered brain left-right asymmetry in ASD affects specific structural and functional brain networks. Altered asymmetrical brain development in ASD may be partly propagated among spatially distant regions through structural connectivity.
]]></description>
<dc:creator>Sha, Z.</dc:creator>
<dc:creator>Rooij, D. v.</dc:creator>
<dc:creator>Anagnostou, E.</dc:creator>
<dc:creator>Arango, C.</dc:creator>
<dc:creator>Auzias, G.</dc:creator>
<dc:creator>Behrmann, M.</dc:creator>
<dc:creator>Bernhardt, B.</dc:creator>
<dc:creator>Bolte, S.</dc:creator>
<dc:creator>Busatto, G. F.</dc:creator>
<dc:creator>Calderoni, S.</dc:creator>
<dc:creator>Calvo, R.</dc:creator>
<dc:creator>Daly, E.</dc:creator>
<dc:creator>Deruelle, C.</dc:creator>
<dc:creator>Duan, M.</dc:creator>
<dc:creator>Duran, F. L. S.</dc:creator>
<dc:creator>Durston, S.</dc:creator>
<dc:creator>Ecker, C.</dc:creator>
<dc:creator>Ehrlich, S.</dc:creator>
<dc:creator>Fair, D.</dc:creator>
<dc:creator>Fedor, J.</dc:creator>
<dc:creator>Fitzgerald, J.</dc:creator>
<dc:creator>Floris, D. L.</dc:creator>
<dc:creator>Franke, B.</dc:creator>
<dc:creator>Freitag, C. M.</dc:creator>
<dc:creator>Gallagher, L.</dc:creator>
<dc:creator>Glahn, D. C.</dc:creator>
<dc:creator>Haar, S.</dc:creator>
<dc:creator>Hoekstra, L.</dc:creator>
<dc:creator>Jahanshad, N.</dc:creator>
<dc:creator>Jalbrzikowski, M.</dc:creator>
<dc:creator>Janssen, J.</dc:creator>
<dc:creator>King, J. A.</dc:creator>
<dc:creator>Lazaro, L.</dc:creator>
<dc:creator>Luna, B.</dc:creator>
<dc:creator>McGrath, J.</dc:creator>
<dc:creator>Medland, S. E.</dc:creator>
<dc:creator>Molloy, C.</dc:creator>
<dc:creator>Muratori, F.</dc:creator>
<dc:creator>Murphy, D. G. M.</dc:creator>
<dc:creator>Neufeld, J.</dc:creator>
<dc:creator>O'Hearn, K.</dc:creator>
<dc:creator>Oranje, B.</dc:creator>
<dc:creator>Parellada, M.</dc:creator>
<dc:creator>Pariente, J.</dc:creator>
<dc:creator>Postema, M.</dc:creator>
<dc:date>2021-05-06</dc:date>
<dc:identifier>doi:10.1101/2021.05.05.442735</dc:identifier>
<dc:title><![CDATA[Subtly altered topological asymmetry of brain structural covariance networks in autism spectrum disorder across 43 datasets from the ENIGMA consortium]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-05-06</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.05.07.443084v1?rss=1">
<title>
<![CDATA[
Short Association Fibre Tractography 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.05.07.443084v1?rss=1"
</link>
<description><![CDATA[
It is estimated that in the human brain, short association fibres (SAF) represent more than half of the total white matter volume and their involvement has been implicated in a range of neurological and psychiatric conditions. This population of fibres, however, remains relatively understudied in the neuroimaging literature. Some of the challenges pertinent to the mapping of SAF include their variable anatomical course and proximity to the cortical mantle, leading to partial volume effects and potentially affecting streamline trajectory estimation. This work considers the impact of seeding and filtering strategies and choice of scanner, acquisition, data resampling to propose a whole-brain, surface-based short ([&le;]30-40 mm) SAF tractography approach. The framework is shown to produce longer streamlines with a predilection for connecting gyri as well as high cortical coverage. We further demonstrate that certain areas of subcortical white matter become disproportionally underrepresented in diffusion-weighted MRI data with lower angular and spatial resolution and weaker diffusion weighting; however, collecting data with stronger gradients than are usually available clinically has minimal impact, making our framework translatable to data collected on commonly available hardware. Finally, the tractograms are examined using voxel- and surfacebased measures of consistency, demonstrating moderate reliability, low repeatability and high between-subject variability, urging caution when streamline count-based analyses of SAF are performed.
]]></description>
<dc:creator>Shastin, D.</dc:creator>
<dc:creator>Genc, S.</dc:creator>
<dc:creator>Parker, G. D.</dc:creator>
<dc:creator>Koller, K.</dc:creator>
<dc:creator>Tax, C. M. W.</dc:creator>
<dc:creator>Evans, J.</dc:creator>
<dc:creator>Hamandi, K.</dc:creator>
<dc:creator>Gray, W. P.</dc:creator>
<dc:creator>Jones, D. K.</dc:creator>
<dc:creator>Chamberland, M.</dc:creator>
<dc:date>2021-05-09</dc:date>
<dc:identifier>doi:10.1101/2021.05.07.443084</dc:identifier>
<dc:title><![CDATA[Short Association Fibre Tractography]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-05-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.05.07.442790v1?rss=1">
<title>
<![CDATA[
ENIGMA HALFpipe: Interactive, reproducible, and efficient analysis for resting-state and task-based fMRI data 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.05.07.442790v1?rss=1"
</link>
<description><![CDATA[
The reproducibility crisis in neuroimaging has led to an increased demand for standardized data processing workflows. Within the ENIGMA consortium, we developed HALFpipe (Harmonized AnaLysis of Functional MRI pipeline), an open-source, containerized, user-friendly tool that facilitates reproducible analysis of task-based and resting-state fMRI data through uniform application of preprocessing, quality assessment, single-subject feature extraction, and group-level statistics. It provides state-of-the-art preprocessing using fMRIPrep without the requirement for input data in Brain Imaging Data Structure (BIDS) format. HALFpipe extends the functionality of fMRIPrep with additional preprocessing steps, which include spatial smoothing, grand mean scaling, temporal filtering, and confound regression. HALFpipe generates an interactive quality assessment (QA) webpage to assess the quality of key preprocessing outputs and raw data in general. HALFpipe features myriad post-processing functions at the individual subject level, including calculation of task-based activation, seed-based connectivity, network-template (or dual) regression, atlas-based functional connectivity matrices, regional homogeneity (ReHo), and fractional amplitude of low frequency fluctuations (fALFF), offering support to evaluate a combinatorial number of features or preprocessing settings in one run. Finally, flexible factorial models can be defined for mixed-effects regression analysis at the group level, including multiple comparison correction. Here, we introduce the theoretical framework in which HALFpipe was developed, and present an overview of the main functions of the pipeline. HALFpipe offers the scientific community a major advance toward addressing the reproducibility crisis in neuroimaging, providing a workflow that encompasses preprocessing, post-processing, and QA of fMRI data, while broadening core principles of data analysis for producing reproducible results. Instructions and code can be found at https://github.com/HALFpipe/HALFpipe.
]]></description>
<dc:creator>Waller, L.</dc:creator>
<dc:creator>Erk, S.</dc:creator>
<dc:creator>Pozzi, E.</dc:creator>
<dc:creator>Toenders, Y. J.</dc:creator>
<dc:creator>Haswell, C. C.</dc:creator>
<dc:creator>Büttner, M.</dc:creator>
<dc:creator>Thompson, P. M.</dc:creator>
<dc:creator>Schmaal, L.</dc:creator>
<dc:creator>Morey, R. A.</dc:creator>
<dc:creator>Walter, H.</dc:creator>
<dc:creator>Veer, I. M.</dc:creator>
<dc:date>2021-05-09</dc:date>
<dc:identifier>doi:10.1101/2021.05.07.442790</dc:identifier>
<dc:title><![CDATA[ENIGMA HALFpipe: Interactive, reproducible, and efficient analysis for resting-state and task-based fMRI data]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-05-09</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.05.12.443095v1?rss=1">
<title>
<![CDATA[
Clone expansion of mutation-driven clonal hematopoiesis is associated with aging and metabolic dysfunction in individuals with obesity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.05.12.443095v1?rss=1"
</link>
<description><![CDATA[
AimsHaematopoietic clones caused by somatic mutations with [&ge;]2% variant allele frequency (VAF), known as clonal haematopoiesis of indeterminate potential (CHIP), increase with age and have been linked to risk of haematological malignancies and cardiovascular disease. Recent observations suggest that smaller clones are also associated with adverse clinical outcomes. Our aims were to determine the prevalence of clonal haematopoiesis driven by clones of variable sizes, and to examine the development of clones over time in relation to age and metabolic dysregulation over up to 20 years in individuals with obesity.

Methods and ResultsWe used an ultrasensitive single-molecule molecular inversion probe sequencing assay to identify clonal haematopoiesis driver mutations (CHDMs) in blood samples from individuals with obesity from the Swedish Obese Subjects study. In a single-timepoint dataset with samples from 1050 individuals, we identified 273 candidate CHDMs in 216 individuals, with VAF ranging from 0.01% to 31.15% and CHDM prevalence and clone sizes increasing with age. Longitudinal analysis over 20 years in CHDM-positive samples from 40 individuals showed that small clones can grow over time and become CHIP. VAF increased on average by 7% (range -4% to 27%) per year. Rate of clone growth was positively associated with insulin resistance (R=0.40, P=0.025) and low circulating levels of high-density lipoprotein-cholesterol (HDL-C) (R=-0.68, P=1.74E-05).

ConclusionOur results show that haematopoietic clones can be detected and monitored before they become CHIP and indicate that insulin resistance and low HDL-C, well-established cardiovascular risk factors, are associated with clonal expansion in individuals with obesity.

Translational perspectivesClonal haematopoiesis-driver mutations are somatic mutations in haematopoietic stem cells that lead to clones detectable in peripheral blood. Haematopoietic clones with a variant allele frequency (VAF) [&ge;]2%, known as clonal haematopoiesis of indeterminate potential (CHIP), are recognized as an independent cardiovascular risk factor. Here, we show that smaller clones are prevalent, and also correlate with age. Our longitudinal observations in individuals with obesity over 20 years showed that more than half of all clone-positive individuals show growing clones and clones with VAF <2% can grow and become CHIP. Importantly, clone growth was accelerated in individuals with insulin resistance and low high-density lipoprotein-cholesterol (HDL-C).

Translational outlook 1: Haematopoietic clones can be detected and monitored before they become CHIP.

Translational outlook 2: The association between insulin resistance and low HDL-C with growth of haematopoietic clones opens the possibility that treatments improving metabolism, such as weight loss, may reduce growth of clones and thereby cardiovascular risk.

One Sentence SummaryIn obesity, the growth rate of mutation-driven haematopoietic clones increased with insulin resistance and low HDL-C, both known risk factors for cardiovascular disease.
]]></description>
<dc:creator>van Deuren, R. C.</dc:creator>
<dc:creator>Andersson-Assarsson, J. C.</dc:creator>
<dc:creator>Kristensson, F. M.</dc:creator>
<dc:creator>Steehouwer, M.</dc:creator>
<dc:creator>Sjöholm, K.</dc:creator>
<dc:creator>Svensson, P.-A.</dc:creator>
<dc:creator>Peterse, M.</dc:creator>
<dc:creator>Gilissen, C.</dc:creator>
<dc:creator>Taube, M.</dc:creator>
<dc:creator>Jacobson, P.</dc:creator>
<dc:creator>Perkins, R.</dc:creator>
<dc:creator>Brunner, H. G.</dc:creator>
<dc:creator>Netea, M. G.</dc:creator>
<dc:creator>Peltonen, M.</dc:creator>
<dc:creator>Carlsson, B.</dc:creator>
<dc:creator>Hoischen, A.</dc:creator>
<dc:creator>Carlsson, L. M.</dc:creator>
<dc:date>2021-05-13</dc:date>
<dc:identifier>doi:10.1101/2021.05.12.443095</dc:identifier>
<dc:title><![CDATA[Clone expansion of mutation-driven clonal hematopoiesis is associated with aging and metabolic dysfunction in individuals with obesity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-05-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.05.11.443600v1?rss=1">
<title>
<![CDATA[
Generalizable predictive modeling of semantic processing ability from functional brain connectivity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.05.11.443600v1?rss=1"
</link>
<description><![CDATA[
Semantic processing (SP) is one of the critical abilities of humans for representing and manipulating meaningful and conceptual information. Neuroimaging studies of SP typically collapse data from many subjects, but both its neural organization and behavioral performance vary between individuals. It is not yet understood whether and how the individual variabilities in neural organizations contribute to the individual differences in SP behaviors. Here we aim to identify the neural signatures underlying SP variabilities by analyzing individual functional connectivity (FC) patterns based on a large-sample Human Connectome Project (HCP) dataset and rigorous predictive modeling. We used a two-stage predictive modeling approach to build an internally cross-validated model and to test the models generalizability with unseen data from different HCP sub-populations and task states as well as other out-of-sample datasets that are independent of the HCP. FC patterns within a putative semantic brain network were significantly predictive of individual SP scores summarized from five semantic tasks. This cross-validated predictive model can be used to predict unseen HCP data. The model generalizability was enhanced with FCs in language tasks than resting state and other task states and was better for females than males. The model constructed from the HCP dataset can be generalized to two independent cohorts that participated in different semantic tasks. FCs connecting to the Perisylvian language network show the most reliable contributions to predictive modeling and the out-of-sample generalization. These findings contribute to our understanding of the neural sources of individual differences in SP, which potentially lay the foundation for personalized education and improve intervention practice for patients with SP and language deficits.
]]></description>
<dc:creator>Meng, D.</dc:creator>
<dc:creator>Wang, S.</dc:creator>
<dc:creator>Wong, P.</dc:creator>
<dc:creator>Feng, G.</dc:creator>
<dc:date>2021-05-13</dc:date>
<dc:identifier>doi:10.1101/2021.05.11.443600</dc:identifier>
<dc:title><![CDATA[Generalizable predictive modeling of semantic processing ability from functional brain connectivity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-05-13</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.05.21.444993v1?rss=1">
<title>
<![CDATA[
Geodesic-based distance reveals non-linear topological features in neural activity from mouse visual cortex 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.05.21.444993v1?rss=1"
</link>
<description><![CDATA[
An increasingly popular approach to the analysis of neural data is to treat activity patterns as being constrained to and sampled from a manifold, which can be characterized by its topology. The persistent homology method identifies the type and number of holes in the manifold thereby yielding functional information about the coding and dynamic properties of the underlying neural network. In this work we give examples of highly non-linear manifolds in which the persistent homology algorithm fails when it uses the Euclidean distance which does not always yield a good approximation of the true distance distribution of a point cloud sampled from a manifold. To deal with this issue we propose a simple strategy for the estimation of the geodesic distance which is a better approximation of the true distance distribution and can be used to successfully identify highly non-linear features with persistent homology. To document the utility of our method we model a circular manifold, based on orthogonal sinusoidal basis functions and compare how the chosen metric determines the performance of the persistent homology algorithm. Furthermore we discuss the robustness of our method across different manifold properties and point out strategies for interpreting its results as well as some possible pitfalls of its application. Finally we apply this analysis to neural data coming from the Visual Coding - Neuropixels dataset recorded in mouse visual cortex after stimulation with drifting gratings at the Allen Institute. We find that different manifolds with a non-trivial topology can be seen across regions and stimulus properties. Finally, we discuss what these manifolds say about visual computation and how they depend on stimulus parameters.
]]></description>
<dc:creator>Beshkov, K.</dc:creator>
<dc:creator>Tiesinga, P.</dc:creator>
<dc:date>2021-05-21</dc:date>
<dc:identifier>doi:10.1101/2021.05.21.444993</dc:identifier>
<dc:title><![CDATA[Geodesic-based distance reveals non-linear topological features in neural activity from mouse visual cortex]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-05-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.05.18.444672v1?rss=1">
<title>
<![CDATA[
Contactless recordings of retinal activity using optically pumped magnetometers 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.05.18.444672v1?rss=1"
</link>
<description><![CDATA[
Optically pumped magnetometers (OPMs) have been adopted for the recording of brain activity. Without the need to be cooled to cryogenic temperatures, an array of these sensors can be placed more flexibly, which allows for the recording of neuronal structures other than neocortex. Here we use eight OPM sensors to record human retinal activity following flash stimulation. We compare this magnetoretinographic (MRG) activity to the simultaneously recorded electroretinogram of the eight participants. The MRG shows the familiar flash-evoked potentials (a-wave and b-wave) and shares a highly significant amount of information with the electroretinogram recording (both in a simultaneous and separate recording). We conclude that OPM sensors have the potential to become a contactless alternative to fiber electrodes for the recording of retinal activity. Such a contactless solution can benefit both clinical and neuroscientific settings.
]]></description>
<dc:creator>Westner, B. U.</dc:creator>
<dc:creator>Lubell, J. I.</dc:creator>
<dc:creator>Jensen, M.</dc:creator>
<dc:creator>Hokland, S.</dc:creator>
<dc:creator>Dalal, S. S.</dc:creator>
<dc:date>2021-05-18</dc:date>
<dc:identifier>doi:10.1101/2021.05.18.444672</dc:identifier>
<dc:title><![CDATA[Contactless recordings of retinal activity using optically pumped magnetometers]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-05-18</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.05.31.445808v1?rss=1">
<title>
<![CDATA[
Scaling principles of white matter brain connectivity 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.05.31.445808v1?rss=1"
</link>
<description><![CDATA[
Brains come in many shapes and sizes. Nature has endowed big-brained primate species like humans with a proportionally large cerebral cortex. White matter connectivity - the brains infrastructure for long-range communication - might not always scale at the same pace as the cortex. We investigated the consequences of this allometric scaling for white matter brain network connectivity. Structural T1 and diffusion MRI data were collated across fourteen primate species, describing a comprehensive 350-fold range in brain volume. We report volumetric scaling relationships that point towards a restriction in macroscale connectivity in larger brains. Building on previous findings, we show cortical surface to outpace white matter volume and the corpus callosum, suggesting the emergence of a white matter  bottleneck of lower levels of connectedness through the corpus callosum in larger brains. At the network level, we find a potential consequence of this bottleneck in shaping connectivity patterns, with homologous regions in the left and right hemisphere showing more divergent connectivity in larger brains. Our findings show conserved scaling relationships of major brain components and their consequence for macroscale brain circuitry, providing a comparative framework for expected connectivity architecture in larger brains such as the human brain.
]]></description>
<dc:creator>Ardesch, D. J.</dc:creator>
<dc:creator>Scholtens, L. H.</dc:creator>
<dc:creator>de Lange, S. C.</dc:creator>
<dc:creator>Roumazeilles, L.</dc:creator>
<dc:creator>Khrapitchev, A. A.</dc:creator>
<dc:creator>Preuss, T. M.</dc:creator>
<dc:creator>Rilling, J. K.</dc:creator>
<dc:creator>Mars, R. B.</dc:creator>
<dc:creator>van den Heuvel, M. P.</dc:creator>
<dc:date>2021-05-31</dc:date>
<dc:identifier>doi:10.1101/2021.05.31.445808</dc:identifier>
<dc:title><![CDATA[Scaling principles of white matter brain connectivity]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-05-31</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.05.31.446450v1?rss=1">
<title>
<![CDATA[
TORC1 and PKA activity towards ribosome biogenesis oscillates in synchrony with the budding yeast cell cycle 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.05.31.446450v1?rss=1"
</link>
<description><![CDATA[
Recent studies have revealed that the growth rate of budding yeast and mammalian cells varies during the cell cycle. By linking a multitude of signals to cell growth, the highly conserved Target of Rapamycin Complex 1 (TORC1) and Protein Kinase A (PKA) pathways are prime candidates for mediating the dynamic coupling between growth and division. However, measurements of TORC1 and PKA activity during the cell cycle are still lacking. Following the localization dynamics of two TORC1 and PKA targets via time-lapse microscopy in hundreds of yeast cells, we found that the activity of these pathways towards ribosome biogenesis fluctuates in synchrony with the cell cycle even under constant external conditions. Mutations of upstream TORC1 and PKA regulators suggested that internal metabolic signals partially mediate these activity changes. Our study reveals a new aspect of TORC1 and PKA signaling, which will be important for understanding growth regulation during the cell cycle.
]]></description>
<dc:creator>Guerra, P.</dc:creator>
<dc:creator>Vuillemenot, L.-A.</dc:creator>
<dc:creator>Been, M.</dc:creator>
<dc:creator>Milias-Argeits, A.</dc:creator>
<dc:date>2021-06-01</dc:date>
<dc:identifier>doi:10.1101/2021.05.31.446450</dc:identifier>
<dc:title><![CDATA[TORC1 and PKA activity towards ribosome biogenesis oscillates in synchrony with the budding yeast cell cycle]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-06-01</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.07.02.450779v1?rss=1">
<title>
<![CDATA[
Wild lab: A naturalistic free viewing experiment reveals previously unknown EEG signatures of face processing. 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.07.02.450779v1?rss=1"
</link>
<description><![CDATA[
Neural mechanisms of face perception are predominantly studied in well-controlled experimental settings that involve random stimulus sequences and fixed eye positions. While powerful, the employed paradigms are far from what constitutes natural vision. Here, we demonstrate the feasibility of ecologically more valid experimental paradigms using natural viewing behavior, by combining a free viewing paradigm on natural scenes, free of photographer bias, with advanced data processing techniques that correct for overlap effects and co-varying nonlinear dependencies of multiple eye movement parameters. We validate this approach by replicating classic N170 effects in neural responses, triggered by fixation onsets (fERPs). Importantly, our more natural stimulus paradigm yielded smaller variability between subjects than the classic setup. Moving beyond classic temporal and spatial effect locations, our experiment furthermore revealed previously unknown signatures of face processing. This includes modulation of early fERP components, as well as category-specific adaptation effects across subsequent fixations that emerge even before fixation onset.
]]></description>
<dc:creator>Gert, A. L.</dc:creator>
<dc:creator>Ehinger, B. V.</dc:creator>
<dc:creator>Timm, S.</dc:creator>
<dc:creator>Kietzmann, T. C.</dc:creator>
<dc:creator>Koenig, P.</dc:creator>
<dc:date>2021-07-02</dc:date>
<dc:identifier>doi:10.1101/2021.07.02.450779</dc:identifier>
<dc:title><![CDATA[Wild lab: A naturalistic free viewing experiment reveals previously unknown EEG signatures of face processing.]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-07-02</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.06.29.450360v1?rss=1">
<title>
<![CDATA[
Using wearable biosensors and ecological momentary assessments for the detection of prolonged stress in real life 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.06.29.450360v1?rss=1"
</link>
<description><![CDATA[
BackgroundIncreasing efforts toward prevention of stress-related mental disorders have created a need for unobtrusive real-life monitoring of stress-related symptoms. Wearable devices have emerged as a possible solution to aid in this process, but their use in real-life stress detection has not been systematically investigated.

MethodsUsing ecological momentary assessments (EMA) combined with wearable biosensors for ecological physiological assessments (EPA), we investigated the impact of an ecological stressor (i.e., an exam week) on physiological arousal and affect. With this paradigm we investigated whether we could use wearable devices to detect stress states using machine learning models.

ResultsDuring stressful high-stake exam (versus control) weeks, participants reported increased negative affect and decreased positive affect. Intriguingly, physiological arousal was decreased on average during the exam week. Time-resolved analyses revealed peaks in physiological arousal associated with both self-reported stress and self-reported positive affect, while the overall decrease in physiological arousal was mediated by lower positive affect during the stress period. We then used machine learning to show that a combination of EMA and physiology yields optimal identification of stress states.

ConclusionsOur findings highlight the potential of wearable biosensors in stress-related mental-health monitoring, but critically show that psychological context is essential for interpreting physiological arousal detected using these devices.
]]></description>
<dc:creator>Tutunji, R.</dc:creator>
<dc:creator>Kogias, N.</dc:creator>
<dc:creator>Kapteijns, B.</dc:creator>
<dc:creator>Krentz, M.</dc:creator>
<dc:creator>Krause, F.</dc:creator>
<dc:creator>Vassena, E.</dc:creator>
<dc:creator>Hermans, E.</dc:creator>
<dc:date>2021-06-30</dc:date>
<dc:identifier>doi:10.1101/2021.06.29.450360</dc:identifier>
<dc:title><![CDATA[Using wearable biosensors and ecological momentary assessments for the detection of prolonged stress in real life]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-06-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.06.28.450248v1?rss=1">
<title>
<![CDATA[
Phenotypic and genetic associations of quantitative magnetic susceptibility in UK Biobank brain imaging 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.06.28.450248v1?rss=1"
</link>
<description><![CDATA[
A key aim in epidemiological neuroscience is identification of markers to assess brain health and monitor therapeutic interventions. Quantitative susceptibility mapping (QSM) is an emerging MRI technique that measures tissue magnetic susceptibility and has been shown to detect pathological changes in tissue iron, myelin and calcification. We developed a QSM processing pipeline to estimate magnetic susceptibility of multiple brain structures in 35,885 subjects from the UK Biobank prospective epidemiological study. We identified phenotypic associations of magnetic susceptibility that include body iron, disease, diet, and alcohol consumption. Genome-wide associations related magnetic susceptibility to genetic variants with biological functions involving iron, calcium, myelin, and extracellular matrix. These patterns of associations include relationships that are unique to QSM, in particular being complementary to T2* measures. These new imaging phenotypes are being integrated into the core UK Biobank measures provided to researchers world-wide, creating potential to discover novel, non-invasive markers of brain health.
]]></description>
<dc:creator>Wang, C.</dc:creator>
<dc:creator>Martins-Bach, A. B.</dc:creator>
<dc:creator>Alfaro-Almagro, F.</dc:creator>
<dc:creator>Douaud, G.</dc:creator>
<dc:creator>Klein, J. C.</dc:creator>
<dc:creator>Llera, A.</dc:creator>
<dc:creator>Fiscone, C.</dc:creator>
<dc:creator>Bowtell, R.</dc:creator>
<dc:creator>Elliott, L. T.</dc:creator>
<dc:creator>Smith, S. M.</dc:creator>
<dc:creator>Tendler, B. C.</dc:creator>
<dc:creator>Miller, K. L.</dc:creator>
<dc:date>2021-06-30</dc:date>
<dc:identifier>doi:10.1101/2021.06.28.450248</dc:identifier>
<dc:title><![CDATA[Phenotypic and genetic associations of quantitative magnetic susceptibility in UK Biobank brain imaging]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-06-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.06.29.449223v1?rss=1">
<title>
<![CDATA[
Information redundancy across spatial scales modulates early visual cortical processing 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.06.29.449223v1?rss=1"
</link>
<description><![CDATA[
Visual images contain redundant information across spatial scales where low spatial frequency contrast is informative towards the location and likely content of high spatial frequency detail. Previous research suggests that the visual system makes use of those redundancies to facilitate efficient processing. In this framework, a fast, initial analysis of low-spatial frequency (LSF) information guides the slower and later processing of high spatial frequency (HSF) detail. Here, we used multivariate classification as well as time-frequency analysis of MEG responses to the viewing of intact and phase scrambled images of human faces to demonstrate that the availability of redundant LSF information, as found in broadband intact images, correlates with a reduction in HSF representational dominance in both early and higher-level visual areas as well as a reduction of gamma-band power in early visual cortex. Our results indicate that the cross spatial frequency information redundancy that can be found in all natural images might be a driving factor in the efficient integration of fine image details.
]]></description>
<dc:creator>Petras, K.</dc:creator>
<dc:creator>Ten Oever, S.</dc:creator>
<dc:creator>Dalal, S. S.</dc:creator>
<dc:creator>Goffaux, V.</dc:creator>
<dc:date>2021-06-30</dc:date>
<dc:identifier>doi:10.1101/2021.06.29.449223</dc:identifier>
<dc:title><![CDATA[Information redundancy across spatial scales modulates early visual cortical processing]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-06-30</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2020.12.08.416016v1?rss=1">
<title>
<![CDATA[
Lexical frequency and sentence context influence the brain's response to single words 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2020.12.08.416016v1?rss=1"
</link>
<description><![CDATA[
Typical adults read remarkably quickly. Such fast reading is facilitated by brain processes that are sensitive to both word frequency and contextual constraints. It is debated as to whether these attributes have additive or interactive effects on language processing in the brain. We investigated this issue by analysing existing magnetoencephalography data from 99 participants reading intact and scrambled sentences. Using a cross-validated model comparison scheme, we found that lexical frequency predicted the word-by-word elicited MEG signal in a widespread cortical network, irrespective of sentential context. In contrast, index (ordinal word position) was more strongly encoded in sentence words, in left front-temporal areas. This confirms that frequency influences word processing independently of predictability, and that contextual constraints affect word-by-word brain responses. With a conservative multiple comparisons correction, only the interaction between lexical frequency and surprisal survived, in anterior temporal and frontal cortex, and not between lexical frequency and entropy, nor between lexical frequency and index. However, interestingly, the uncorrected index*frequency interaction revealed an effect in left frontal and temporal cortex that reversed in time and space for intact compared to scrambled sentences. Finally, we provide evidence to suggest that, in sentences, lexical frequency and predictability may independently influence early (<150ms) and late stages of word processing, but also interact during late stages of word processing (>150-250ms), thus helping to converge previous contradictory eye-tracking and electrophysiological literature. Current neuro-cognitive models of reading would benefit from accounting for these differing effects of lexical frequency and predictability on different stages of word processing.
]]></description>
<dc:creator>Huizeling, E.</dc:creator>
<dc:creator>Arana, S.</dc:creator>
<dc:creator>Hagoort, P.</dc:creator>
<dc:creator>Schoffelen, J.-M.</dc:creator>
<dc:date>2020-12-08</dc:date>
<dc:identifier>doi:10.1101/2020.12.08.416016</dc:identifier>
<dc:title><![CDATA[Lexical frequency and sentence context influence the brain's response to single words]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2020-12-08</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.06.28.450146v1?rss=1">
<title>
<![CDATA[
Circadian modulation of human sleep spindle frequency 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.06.28.450146v1?rss=1"
</link>
<description><![CDATA[
Homeostatic and circadian processes play a pivotal role in determining sleep structure, timing and quality. In sharp contrast with the wide accessibility of the EEG index of sleep homeostasis, an electrophysological measure of the circadian modulation of sleep is still non-available. Evidence suggests that sleep spindle frequencies decelerate during biological night. In order to test the feasibility of measuring this marker in common polysomnographic protocols, the Budapest-Munich database of sleep records (N = 251 healthy subjects, 122 females, age range: 4-69 years), as well as an afternoon nap sleep record database (N = 112 healthy subjects, 30 females, age range: 18-30 years) were analysed by the Individual Adjustment Method of sleep spindle analysis. Slow and fast sleep spindle frequencies were characterized by U-shaped overnight dynamics, with highest values in the first and the fourth-to-fifth sleep cycle and the lowest values in the middle of the sleeping period (cycles 2-3). Age-related attenuation of sleep spindle deceleration was evident. Estimated phases of the nadirs in sleep spindle frequencies were advanced in children as compared to other age groups. Additionally, nap sleep spindles were faster than night sleep spindles (0.57 and 0.39 Hz difference for slow and fast types, respectively). The fine frequency resolution analysis of sleep spindles is a feasible method of measuring the assumed circadian modulation of sleep. Moreover, age-related attenuation of circadian sleep modulation might be measurable by assessing the overnight dynamics in sleep spindle frequency. Phase of the minimal sleep spindle frequency is a putative biomarker of chronotype.
]]></description>
<dc:creator>Bodizs, R.</dc:creator>
<dc:creator>Horvath, C. G.</dc:creator>
<dc:creator>Szalardy, O.</dc:creator>
<dc:creator>Ujma, P. P.</dc:creator>
<dc:creator>Simor, P.</dc:creator>
<dc:creator>Gombos, F.</dc:creator>
<dc:creator>Kovacs, I.</dc:creator>
<dc:creator>Genzel, L.</dc:creator>
<dc:creator>Dresler, M.</dc:creator>
<dc:date>2021-06-28</dc:date>
<dc:identifier>doi:10.1101/2021.06.28.450146</dc:identifier>
<dc:title><![CDATA[Circadian modulation of human sleep spindle frequency]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-06-28</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.06.21.449154v1?rss=1">
<title>
<![CDATA[
The Digital Brain Bank: an open access platform for post-mortem datasets 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.06.21.449154v1?rss=1"
</link>
<description><![CDATA[
Post-mortem MRI provides the opportunity to acquire high-resolution datasets to investigate neuroanatomy, and validate the origins of image contrast through microscopy comparisons. We introduce the Digital Brain Bank (open.win.ox.ac.uk/DigitalBrainBank), a data release platform providing open access to curated, multimodal post-mortem neuroimaging datasets. Datasets span three themes - Digital Neuroanatomist: datasets for detailed neuroanatomical investigations; Digital Brain Zoo: datasets for comparative neuroanatomy; Digital Pathologist: datasets for neuropathology investigations. The first Digital Brain Bank release includes twenty one distinctive whole-brain diffusion MRI datasets for structural connectivity investigations, alongside microscopy and complementary MRI modalities. This includes one of the highest-resolution whole-brain human diffusion MRI datasets ever acquired, whole-brain diffusion MRI in fourteen non-human primate species, and one of the largest post-mortem whole-brain cohort imaging studies in neurodegeneration. The Digital Brain Bank is the culmination of our labs investment into post-mortem MRI methodology and MRI-microscopy analysis techniques. This manuscript provides a detailed overview of our work with post-mortem imaging to date, including the development of diffusion MRI methods to image large post-mortem samples, including whole, human brains. Taken together, the Digital Brain Bank provides crossscale, cross-species datasets facilitating the incorporation of post-mortem data into neuroimaging studies.
]]></description>
<dc:creator>Tendler, B. C.</dc:creator>
<dc:creator>Hanayik, T.</dc:creator>
<dc:creator>Ansorge, O.</dc:creator>
<dc:creator>Bangerter-Christensen, S.</dc:creator>
<dc:creator>Berns, G. S.</dc:creator>
<dc:creator>Bertelsen, M. F.</dc:creator>
<dc:creator>Bryant, K. L.</dc:creator>
<dc:creator>Foxley, S.</dc:creator>
<dc:creator>Howard, A. F. D.</dc:creator>
<dc:creator>Huszar, I.</dc:creator>
<dc:creator>Khrapitchev, A. A.</dc:creator>
<dc:creator>Leonte, A.</dc:creator>
<dc:creator>Manger, P. R.</dc:creator>
<dc:creator>Menke, R. A. L.</dc:creator>
<dc:creator>Mollink, J.</dc:creator>
<dc:creator>Mortimer, D.</dc:creator>
<dc:creator>Pallebage-Gamarallage, M.</dc:creator>
<dc:creator>Roumazeilles, L.</dc:creator>
<dc:creator>Sallet, J.</dc:creator>
<dc:creator>Scott, C.</dc:creator>
<dc:creator>Smart, A.</dc:creator>
<dc:creator>Turner, M. R.</dc:creator>
<dc:creator>Wang, C.</dc:creator>
<dc:creator>Jbabdi, S.</dc:creator>
<dc:creator>Mars, R. B.</dc:creator>
<dc:creator>Miller, K. L.</dc:creator>
<dc:date>2021-06-22</dc:date>
<dc:identifier>doi:10.1101/2021.06.21.449154</dc:identifier>
<dc:title><![CDATA[The Digital Brain Bank: an open access platform for post-mortem datasets]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-06-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.06.22.449393v1?rss=1">
<title>
<![CDATA[
Comparison of undirected frequency-domain connectivity measures for cerebro-peripheral analysis 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.06.22.449393v1?rss=1"
</link>
<description><![CDATA[
Analyses of cerebro-peripheral connectivity aim to quantify ongoing coupling between brain activity (measured by MEG/EEG) and peripheral signals such as muscle activity, continuous speech, or physiological rhythms (such as pupil dilation or respiration). Due to the distinct rhythmicity of these signals, undirected connectivity is typically assessed in the frequency domain. This leaves the investigator with two critical choices, namely a) the appropriate measure for spectral estimation (i.e., the transformation into the frequency domain) and b) the actual connectivity measure. As there is no consensus regarding best practice, a wide variety of methods has been applied. Here we systematically compare combinations of six standard spectral estimation methods (comprising fast Fourier and continuous wavelet transformation, bandpass filtering, and short-time Fourier transformation) and six connectivity measures (phase-locking value, Gaussian-Copula mutual information, Rayleigh test, weighted pairwise phase consistency, magnitude squared coherence, and entropy). We provide performance measures of each combination for simulated data (with precise control over true connectivity), a single-subject set of real MEG data, and a full group analysis of real MEG data. Our results show that, overall, wppc and gcmi tend to outperform other connectivity measures, while entropy was the only measure sensitive to bimodal deviations from a uniform phase distribution. For group analysis, choosing the appropriate spectral estimation method appeared to be more critical than the connectivity measure. We discuss practical implications (sampling rate, SNR, computation time, and data length) and aim to provide recommendations tailored to particular research questions.
]]></description>
<dc:creator>Gross, J.</dc:creator>
<dc:creator>Kluger, D. S.</dc:creator>
<dc:creator>Abbasi, O.</dc:creator>
<dc:creator>Chalas, N.</dc:creator>
<dc:creator>Steingraeber, N.</dc:creator>
<dc:creator>Daube, C.</dc:creator>
<dc:creator>Schoffelen, J.-M.</dc:creator>
<dc:date>2021-06-22</dc:date>
<dc:identifier>doi:10.1101/2021.06.22.449393</dc:identifier>
<dc:title><![CDATA[Comparison of undirected frequency-domain connectivity measures for cerebro-peripheral analysis]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-06-22</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.05.26.445829v1?rss=1">
<title>
<![CDATA[
The sensory and motor components of the cortical hierarchy are coupled to the rhythm of the stomach during rest 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.05.26.445829v1?rss=1"
</link>
<description><![CDATA[
Bodily rhythms appear as novel scaffolding mechanisms orchestrating the spatio-temporal organization of spontaneous brain activity. Here, we follow up on the discovery of the gastric resting-state network (Rebollo et al, 2018), composed of brain regions in which the fMRI signal is phase-synchronized to the slow (0.05 Hz) electrical rhythm of the stomach. Using a larger sample size (n=63 human participants), we further characterize the anatomy and effect sizes of gastric-brain coupling across resting-state networks, a fine grained cortical parcellation, as well as along the main gradients of cortical organization. Most (67%) of the gastric network is included in the somato-motor-auditory (38%) and visual (29%) resting state networks. Gastric brain coupling also occurs in the granular insula and, to a lesser extent, in the piriform cortex. Thus, all sensory and motor cortices corresponding to both exteroceptive and interoceptive modalities are coupled to the gastric rhythm during rest. Conversely, little gastric-brain coupling occurs in cognitive networks and transmodal regions. These results suggest not only that gastric rhythm and sensory-motor processes are likely to interact, but also that gastric-brain coupling might be a mechanism of sensory and motor integration that mostly bypasses cognition, complementing the classical hierarchical organization of the human brain.

Significance statementWhile there is growing interest for brain-body communication in general and brain-viscera communication in particular, little is known about how the brain interacts with the gastric rhythm, the slow electrical rhythm continuously produced in the stomach. Here, we show in human participants at rest that the gastric network, composed of brain regions synchronized with delays to the gastric rhythm, includes all motor and sensory (vision, audition, touch and interoception, olfaction) regions, but only few of the transmodal regions associated with higher-level cognition. Such results prompt for a reconsideration of the classical view of cortical organization, where the different sensory modalities are considered as relatively independent modules.
]]></description>
<dc:creator>Rebollo, I.</dc:creator>
<dc:creator>Tallon-Baudry, C.</dc:creator>
<dc:date>2021-05-27</dc:date>
<dc:identifier>doi:10.1101/2021.05.26.445829</dc:identifier>
<dc:title><![CDATA[The sensory and motor components of the cortical hierarchy are coupled to the rhythm of the stomach during rest]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-05-27</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.06.17.448869v1?rss=1">
<title>
<![CDATA[
Emergence of border-ownership by large-scale consistency and long-range interactions: Neuro-computational model to reflect global configurations 
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</title>
<link>
https://biorxiv.org/cgi/content/short/2021.06.17.448869v1?rss=1"
</link>
<description><![CDATA[
The visual system performs remarkably well to perceive depth order of surfaces without stereo disparity, indicating the importance of figure-ground organization based on pictorial cues. To understand how figure-ground organization emerges, it is essential to investigate how the global configuration of an image is reflected. In the past, many neuro- computational models developed to reproduce figure-ground organization implemented algorithms to give a bias to convex areas. However, in certain conditions, a convex area can be perceived as a hole and a non-convex area as figural. This occurs when the surface properties of the convex area are consistent with the background and, hence, are grouped together in our perception. We argue that large-scale consistency of surface properties is reflected in the border-ownership computation. We developed a model, called DISC2, that first analyzes relationships between two border-ownership signals of all possible combinations in the image. It then enhances signals if they satisfy the following conditions: 1. the two signals fit to a convex configuration, and 2. the surface properties at the locations of the two signals are consistent. The strength of the enhancement decays with distance between the signals. The model gives extremely robust responses to various images with complexities both in shape and depth order. Furthermore, we developed an advanced version of the model ("augmented model") where the global computation above interacts with local computation of curvilinearity, which further enhanced the robust nature of the model. The results suggest the involvement of similar computational processes in the brain for figure-ground organization.
]]></description>
<dc:creator>Kogo, N.</dc:creator>
<dc:creator>Froyen, V.</dc:creator>
<dc:date>2021-06-21</dc:date>
<dc:identifier>doi:10.1101/2021.06.17.448869</dc:identifier>
<dc:title><![CDATA[Emergence of border-ownership by large-scale consistency and long-range interactions: Neuro-computational model to reflect global configurations]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-06-21</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.06.16.448390v1?rss=1">
<title>
<![CDATA[
PET-BIDS, an extension to the brain imaging data structure for positron emission tomography 
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</title>
<link>
https://biorxiv.org/cgi/content/short/2021.06.16.448390v1?rss=1"
</link>
<description><![CDATA[
The Brain Imaging Data Structure (BIDS) is a standard for organizing and describing neuroimaging datasets. It serves not only to facilitate the process of data sharing and aggregation, but also to simplify the application and development of new methods and software for working with neuroimaging data. Here, we present an extension of BIDS to include positron emission tomography (PET) data (PET-BIDS). We describe the PET-BIDS standard in detail and share several open-access datasets curated following PET-BIDS. Additionally, we highlight several tools which are already available for converting, validating and analyzing PET-BIDS datasets.
]]></description>
<dc:creator>Norgaard, M.</dc:creator>
<dc:creator>Matheson, G. J.</dc:creator>
<dc:creator>Hansen, H. D.</dc:creator>
<dc:creator>Thomas, A. G.</dc:creator>
<dc:creator>Searle, G.</dc:creator>
<dc:creator>Rizzo, G.</dc:creator>
<dc:creator>Veronese, M.</dc:creator>
<dc:creator>Giacomel, A.</dc:creator>
<dc:creator>Yaqub, M.</dc:creator>
<dc:creator>Tonietto, M.</dc:creator>
<dc:creator>Funck, T.</dc:creator>
<dc:creator>Gillman, A.</dc:creator>
<dc:creator>Boniface, H.</dc:creator>
<dc:creator>Routier, A.</dc:creator>
<dc:creator>Dalenberg, J. R.</dc:creator>
<dc:creator>Betthauser, T.</dc:creator>
<dc:creator>Feingold, F.</dc:creator>
<dc:creator>Markiewicz, C. J.</dc:creator>
<dc:creator>Gorgolewski, K. J.</dc:creator>
<dc:creator>Blair, R. W.</dc:creator>
<dc:creator>Appelhoff, S.</dc:creator>
<dc:creator>Gau, R.</dc:creator>
<dc:creator>Salo, T.</dc:creator>
<dc:creator>Niso, G.</dc:creator>
<dc:creator>Pernet, C.</dc:creator>
<dc:creator>Phillips, C.</dc:creator>
<dc:creator>Oostenveld, R.</dc:creator>
<dc:creator>Carson, R. E.</dc:creator>
<dc:creator>Gallezot, J.-D.</dc:creator>
<dc:creator>Knudsen, G. M.</dc:creator>
<dc:creator>Innis, R. B.</dc:creator>
<dc:creator>Ganz, M.</dc:creator>
<dc:date>2021-06-17</dc:date>
<dc:identifier>doi:10.1101/2021.06.16.448390</dc:identifier>
<dc:title><![CDATA[PET-BIDS, an extension to the brain imaging data structure for positron emission tomography]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-06-17</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.06.14.448375v1?rss=1">
<title>
<![CDATA[
Sensitivity to Error During Visuomotor Adaptation is Similarly Modulated by Abrupt, Gradual and Random Perturbation Schedules 
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</title>
<link>
https://biorxiv.org/cgi/content/short/2021.06.14.448375v1?rss=1"
</link>
<description><![CDATA[
It has been suggested that sensorimotor adaptation involves at least two processes (i.e., fast and slow) that differ in retention and error sensitivity. Previous work has shown that repeated exposure to an abrupt force field perturbation results in greater error sensitivity for both the fast and slow processes. While this implies that the faster relearning is associated with increased error sensitivity, it remains unclear what aspects of prior experience modulate error sensitivity. In the present study, we manipulated the initial training using different perturbation schedules, thought to differentially affect fast and slow learning processes based on error magnitude, and then observed what effect prior learning had on subsequent adaptation. During initial training of a visuomotor rotation task, we exposed three groups of participants to either an abrupt, a gradual, or a random perturbation schedule. During a testing session, all three groups were subsequently exposed to an abrupt perturbation schedule. Comparing the two sessions of the control group who experienced repetition of the same perturbation, we found an increased error sensitivity for both processes. We found that the error sensitivity was increased for both the fast and slow processes, with no reliable changes in the retention, for both the gradual and structural learning groups when compared to the first session of the control group. We discuss the findings in the context of how fast and slow learning processes respond to a history of errors.

New & NoteworthyWe investigated what aspects of prior experience modulate error sensitivity, within the framework of a two-state model of short-term sensorimotor adaptation. We manipulated initial training on a visuomotor adaptation reaching task using specific perturbation schedules that are thought to differentially affect fast and slow learning processes, and we tested what effect these had on subsequent adaptation. We found that sensitivity to adaptation error was similarly modulated by abrupt, gradual, and random perturbation schedules.
]]></description>
<dc:creator>Coltman, S.</dc:creator>
<dc:creator>van Beers, R. J.</dc:creator>
<dc:creator>Medendorp, P. W.</dc:creator>
<dc:creator>Gribble, P.</dc:creator>
<dc:date>2021-06-15</dc:date>
<dc:identifier>doi:10.1101/2021.06.14.448375</dc:identifier>
<dc:title><![CDATA[Sensitivity to Error During Visuomotor Adaptation is Similarly Modulated by Abrupt, Gradual and Random Perturbation Schedules]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-06-15</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.06.03.446811v1?rss=1">
<title>
<![CDATA[
Computational Neuroimaging of Cognition-Emotion Interactions: Affective and Task-similar Interference Differentially Impact Working Memory 
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</title>
<link>
https://biorxiv.org/cgi/content/short/2021.06.03.446811v1?rss=1"
</link>
<description><![CDATA[
Cognition depends on resisting interference and responding to relevant stimuli. Distracting information, however, varies based on content, requiring distinct filtering mechanisms. For instance, affective information captures attention, disrupts performance and attenuates activation along frontal-parietal regions during cognitive engagement, while recruiting bottom-up regions. Conversely, distraction matching task features (i.e. task-similar) increases fronto-parietal activity. Neural mechanisms behind unique effects of different distraction on cognition remain unknown. Using fMRI in 45 adults, we tested whether affective versus task-similar interference show distinct signals during delayed working memory (WM). We found robust differences between distractor types along fronto-parietal versus affective-ventral neural systems. We studied a hypothesized mechanism of this effect via a biophysically-based computational WM model that implements a functional antagonism between affective/cognitive neural  modules. This architecture reproduced experimental effects: task-similar distractors increased, whereas affective distractors attenuated cognitive module activity while increasing affective module signals. The model architecture suggested that task-based connectivity may be altered in affective-ventral vs. fronto-parietal networks depending on distractor type. Empirically, affective interference significantly increased connectivity within the affective-ventral network, but reduced connectivity between affective-ventral and fronto-parietal networks, which predicted WM performance. These findings detail an antagonistic architecture between cognitive and affective systems, capable of flexibly engaging distinct distractions during cognition.
]]></description>
<dc:creator>Ji, J. L.</dc:creator>
<dc:creator>Repovs, G.</dc:creator>
<dc:creator>Yang, G. J.</dc:creator>
<dc:creator>Savic, A.</dc:creator>
<dc:creator>Murray, J. D.</dc:creator>
<dc:creator>Anticevic, A.</dc:creator>
<dc:date>2021-06-03</dc:date>
<dc:identifier>doi:10.1101/2021.06.03.446811</dc:identifier>
<dc:title><![CDATA[Computational Neuroimaging of Cognition-Emotion Interactions: Affective and Task-similar Interference Differentially Impact Working Memory]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-06-03</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.06.14.448106v1?rss=1">
<title>
<![CDATA[
Normative modeling of neuroimaging data using generalized additive models of location scale and shape 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.06.14.448106v1?rss=1"
</link>
<description><![CDATA[
Normative modeling aims to quantify the degree to which an individuals brain deviates from a reference sample with respect to one or more variables, which can be used as a potential biomarker of a healthy brain and as a tool to study heterogeneity of psychiatric disorders. The application of normative models is hindered by methodological challenges and lacks standards for the usage and evaluation of normative models. In this paper, we present generalized additive models for location scale and shape (GAMLSS) for normative modeling of neuroimaging data, a flexible modeling framework that can model heteroskedasticity, non-linear effects of variables, and hierarchical structure of the data. It can model non-Gaussian distributions, and it allows for an automatic model order selection, thus improving the accuracy of normative models while mitigating problems of overfitting. Furthermore, we describe measures and diagnostic tools suitable for evaluating normative models and step-by-step examples of normative modeling, including fitting several candidate models, selecting the best models, and transferring them to new scan sites.
]]></description>
<dc:creator>Dinga, R.</dc:creator>
<dc:creator>Fraza, C. J.</dc:creator>
<dc:creator>Bayer, J. M. M.</dc:creator>
<dc:creator>Kia, S. M.</dc:creator>
<dc:creator>Beckmann, C. F.</dc:creator>
<dc:creator>Marquand, A. F.</dc:creator>
<dc:date>2021-06-14</dc:date>
<dc:identifier>doi:10.1101/2021.06.14.448106</dc:identifier>
<dc:title><![CDATA[Normative modeling of neuroimaging data using generalized additive models of location scale and shape]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-06-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.06.14.448331v1?rss=1">
<title>
<![CDATA[
EEG-based visual deviance detection in freely behaving mice 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.06.14.448331v1?rss=1"
</link>
<description><![CDATA[
The mouse is widely used as an experimental model to study visual processing. To probe how the visual system detects changes in the environment, functional paradigms in freely behaving mice are strongly needed. We developed and validated the first EEG-based method to investigate visual deviance detection in freely behaving mice. Mice with EEG implants were exposed to a visual deviant detection paradigm that involved changes in light intensity as standard and deviant stimuli. By subtracting the standard from the deviant evoked waveform, deviant detection was evident as bi-phasic negativity (starting around 70 ms) in the difference waveform. Additionally, deviance-associated evoked (beta/gamma) and induced (gamma) oscillatory responses were found. We showed that the results were stimulus-independent by applying a "flip-flop" design and the results showed good repeatability in an independent measurement. Together, we put forward a validated, easy-to-use paradigm to measure visual deviance processing in freely behaving mice.
]]></description>
<dc:creator>Kat, R.</dc:creator>
<dc:creator>van den Berg, B.</dc:creator>
<dc:creator>Perenboom, M. J. L.</dc:creator>
<dc:creator>Schenke, M.</dc:creator>
<dc:creator>van den Maagdenberg, A. M. J. M.</dc:creator>
<dc:creator>Bruining, H.</dc:creator>
<dc:creator>Tolner, E. A.</dc:creator>
<dc:creator>Kas, M. J. H.</dc:creator>
<dc:date>2021-06-14</dc:date>
<dc:identifier>doi:10.1101/2021.06.14.448331</dc:identifier>
<dc:title><![CDATA[EEG-based visual deviance detection in freely behaving mice]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-06-14</prism:publicationDate>
<prism:section></prism:section>
</item>
<item rdf:about="https://biorxiv.org/cgi/content/short/2021.06.09.447733v1?rss=1">
<title>
<![CDATA[
Open multimodal iEEG-fMRI dataset from naturalistic stimulation with a short audiovisual film 
]]>
</title>
<link>
https://biorxiv.org/cgi/content/short/2021.06.09.447733v1?rss=1"
</link>
<description><![CDATA[
Intracranial human recordings are a valuable and rare resource that the whole neuroscience community can benefit from. Making such data available to the neuroscience community not only helps tackle the reproducibility issues in science, it also helps make more use of this valuable data. The latter is especially true for data collected using naturalistic tasks. Here, we describe a dataset collected from a large group of human subjects while they watched a short audiovisual film. The dataset is characterized by several unique features. First, it combines a large amount of intracranial data from 51 intracranial electroencephalography (iEEG) participants, who all did the same task. Second, the intracranial data are accompanied by fMRI recordings acquired for the same task in 30 functional magnetic resonance imaging (fMRI) participants. Third, the data were acquired using a rich audiovisual stimulus, for which we provide detailed speech and video annotations. This multimodal dataset can be used to address questions about neural mechanisms of multimodal perception and language comprehension as well as the nature of the neural signal acquired during the same task across brain recording modalities.
]]></description>
<dc:creator>Berezutskaya, J.</dc:creator>
<dc:creator>Vansteensel, M. J.</dc:creator>
<dc:creator>Aarnoutse, E. J.</dc:creator>
<dc:creator>Freudenburg, Z. V.</dc:creator>
<dc:creator>Piantoni, G.</dc:creator>
<dc:creator>Branco, M. P.</dc:creator>
<dc:creator>Ramsey, N. F.</dc:creator>
<dc:date>2021-06-10</dc:date>
<dc:identifier>doi:10.1101/2021.06.09.447733</dc:identifier>
<dc:title><![CDATA[Open multimodal iEEG-fMRI dataset from naturalistic stimulation with a short audiovisual film]]></dc:title>
<dc:publisher>Cold Spring Harbor Laboratory Press</dc:publisher>
<prism:publicationDate>2021-06-10</prism:publicationDate>
<prism:section></prism:section>
</item>
</rdf:RDF>
