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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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At least 991 records · Page 55Linked to original sources

bioRxiv2016

Consistency of EEG source localization and connectivity estimates

As the EEG inverse problem does not have a unique solution, the sources reconstructed from EEG and their connectivity properties depend on forward and inverse modeling parameters such as the choice of an anatomical template and electrical model, prior assumptions on the sources, and further implementational details. In order to use source connectivity analysis as a reliable research tool, there is a need for stability across a wider range of standard estimation routines. Using resting state EEG recordings of N=65 participants acquired within two studies, we present the first comprehensive assessment of the consistency of EEG source localization and functional/effective connectivity metrics across two anatomical templates (ICBM152 and Colin27), three electrical models (BEM, FEM and spherical harmonics expansions), three inverse methods (WMNE, eLORETA and LCMV), and three software implementations (Brainstorm, Fieldtrip and our own toolbox). Source localizations were found to be more stable across reconstruction pipelines than subsequent estimations of functional connectivity, while effective connectivity estimates where the least consistent. All results were relatively unaffected by the choice of the electrical head model, while the choice of the inverse method and source imaging package induced a considerable variability. In particular, a relatively strong difference was found between LCMV beamformer solutions on one hand and eLORETA/WMNE distributed inverse solutions on the other hand. We also observed a gradual decrease of consistency when results are compared between studies, within individual participants, and between individual participants. In order to provide reliable findings in the face of the observed variability, additional simulations involving interacting brain sources are required. Meanwhile, we encourage verification of the obtained results using more than one source imaging procedure.

Neuroscience↗

bioRxiv2016

Astrocytes locally translate transcripts in their peripheral processes

Local translation in neuronal processes is key to the alteration of synaptic strength that contributes to long term potentiation and learning and memory. Here, we present evidence that astrocytes have ribosomes in their peripheral and perisynaptic processes, and that de novo protein synthesis occurs in the astrocyte periphery. We also developed a new biochemical approach to profile and define a set of candidate transcripts that are locally translated in astrocyte processes, several of which were validated in vivo using in situ hybridization of sparsely labeled cells. Computational analyses indicate that localized translation is both sequence dependent and enriched for particular biological functions. This includes novel pathways such as fatty acid synthesis as well as pathways consistent with known roles for astrocyte processes, such as GABA and glutamate metabolism. Finally, enriched transcripts also include key glial regulators of synaptic refinement, suggesting that local production of astrocyte proteins may support microscale alterations of adjacent synapses.\n\nSignificance StatementCellular compartments are specialized for particular functions. In astrocytes, the peripheral processes, particularly near synapses, contain proteins specialized for reuptake of neurotransmitters and ions, and have been shown to alter their morphology in response to activity. Regulated transport of a specific subset of nuclear-derived mRNAs to particular compartments is thought to support the specialization of these compartments and allow for local regulation of translation. In neurons, local translation near activated synapses is thought to generate the proteins needed for the synaptic alterations that constitute memory. We demonstrate that astrocytes also have sequence-dependent local translation in their peripheral processes, including transcripts with roles in regulating synapses. This suggests local translation in astrocyte processes may also play a role in modulating synapses.

Neuroscience↗

bioRxiv2016

ENTROPY IN PRIMARY SENSORY AREAS LOWER THAN IN ASSOCIATIVE ONES: THE BRAIN LIES IN HIGHER DIMENSIONS THAN THE ENVIRONMENT

The brain, rather than integrate sensory inputs and concentrate them into concepts as currently believed, appears to increase the complexity from the perceived object to the idea of it. Topological models predict indeed an increase in dimensions and symmetries from the environment to the higher activities of the brain. Models predict that informational entropy in the primary sensory areas must be lower than in the higher associative ones. In order to demonstrate the novel hypothesis, we introduce a method for the measurement of information in fMRI neuroimages, i.e., nucleus clusterings Renyi entropy derived from strong proximities in feature-based Voronoi tessellations, e.g., maximal nucleus clustering. The technique facilitates the objective detection of entropy/information in zones of fMRI images generally not taken into account. We found that the Renyi entropy is higher in associative cortices than in the visual primary ones. It suggests that the brain lies in higher dimensions than the environment and that it does not concentrate, but rather dilutes the message coming from external inputs.

Neuroscience↗

bioRxiv2016

The Effects of Pitch Shifts on Delay-induced Changes in Vocal Sequencing in a Songbird

Like human speech, vocal behavior in songbirds depends critically on auditory feedback. In both humans and songbirds, vocal skills are acquired by a process of imitation whereby current vocal production is compared to an acoustic target. Similarly, performance in adulthood relies strongly on auditory feedback, and online manipulations of auditory signals can dramatically alter acoustic production even after vocalizations have been well learned. Artificially delaying auditory feedback can disrupt both speech and birdsong, and internal delays in auditory feedback have been hypothesized as a cause of vocal dysfluency in persons who stutter. Furthermore, in both song and speech online shifts of the pitch (fundamental frequency) of auditory feedback lead to compensatory changes in vocal pitch for small perturbations, but larger pitch shifts produce smaller changes in vocal output. Intriguingly, large pitch shifts can partially restore normal speech in some dysfluent speakers, suggesting that the effects of auditory feedback delays might be ameliorated by online pitch manipulations. While birdsong provides a promising model system for understanding speech production, the interaction between sensory feedback delays and pitch shifts have not yet been assessed in songbirds. To investigate this, we asked whether the addition of a pitch shift modulates delay-induced changes in Bengalese finch song, hypothesizing that pitch shifts would reduce the effects of feedback delays. Compared the effects of delays alone, combined delays and pitch shifts resulted in a significant reduction in behavioral changes in one type of sequencing (branch points) but not another (distribution of repeated syllables).\n\nSignificance StatementVocal behavior depends critically on an organisms ability to monitor the sound of its own voice (\"auditory feedback\"). Studies of both humans and songbirds have demonstrated that successful vocal performance depends critically on the quality and timing of such feedback, however the interaction between vocal acoustics and the timing of auditory feedback is unclear. Here we used songbirds to examine this interaction by measuring vocal performance during delays and distortions (pitch shifts) of auditory feedback.

Neuroscience↗

bioRxiv2016

Calcium Dependent Gap Junction Plasticity: Modulation of Electrotonic Coupling in the Inferior Olive Glomerulus

Dendritic spines in glomeruli of the inferior olive are coupled by gap junctions and receive both inhibitory and excitatory inputs, yet the function of this configuration remains to be elucidated. In this issue of Neuron, Lefler et al. (2014) show that the GABAergic input from the cerebellar nuclei to neurons of the inferior olive dynamically affects both their coupling and subthreshold oscillations for short periods, while Mathy et al. (2014) and Turecek et al. (2014) show that the glutamatergic input to the olivary neurons can instruct plasticity of coupled dendrites in the long-term. The data sets from all three papers can be reconciled when put together in a model of the neuropil comprising the characteristic olivary glomeruli.

Neuroscience↗

bioRxiv2016

Revealing unobserved factors underlying cortical activity using a rectified latent variable model applied to neural population recordings

The activity of sensory cortical neurons is not only driven by external stimuli, but is also shaped by other sources of input to the cortex. Unlike external stimuli these other sources of input are challenging to experimentally control or even observe, and as a result contribute to variability of neuronal responses to sensory stimuli. However, such sources of input are likely not \"noise\", and likely play an integral role in sensory cortex function. Here, we introduce the rectified latent variable model (RLVM) in order to identify these sources of input using simultaneously recorded cortical neuron populations. The RLVM is novel in that it employs non-negative (rectified) latent variables, and is able to be much less restrictive in the mathematical constraints on solutions due to the use an autoencoder neural network to initialize model parameters. We show the RLVM outperforms principal component analysis, factor analysis and independent component analysis across a variety of measures using simulated data. We then apply this model to the 2-photon imaging of hundreds of simultaneously recorded neurons in mouse primary somatosensory cortex during a tactile discrimination task. Across many experiments, the RLVM identifies latent variables related to both the tactile stimulation as well as non-stimulus aspects of the behavioral task, with a majority of activity explained by the latter. These results suggest that properly identifying such latent variables is necessary for a full understanding of sensory cortical function, and demonstrates novel methods for leveraging large population recordings to this end.

Neuroscience↗

bioRxiv2016

A Neural Oscillatory Signature of Reference

The ability to use words to refer to the world is vital to the communicative power of human language. In particular, the anaphoric use of words to refer to previously mentioned concepts (antecedents) allows dialogue to be coherent and meaningful. Psycholinguistic theory posits that anaphor comprehension involves reactivating a memory representation of the antecedent. Whereas this implies the involvement of recognition memory, the neural processes for reference resolution are largely unknown. Here, we report time-frequency analysis of four EEG experiments to reveal the increased coupling of functional neural systems associated with referentially coherent expressions compared to referentially ambiguous expressions. Despite varying in modality, language, and type of referential expression, all experiments showed larger gamma-band power for coherence compared to ambiguity. Beamformer analysis in high-density Experiment 4 localised this increase to posterior parietal cortex around 400-600 ms after anaphor-onset and to frontal-temporal cortex around 500-1000 ms. We argue that the observed gamma-band power increases reflect successful referential binding and resolution, which links incoming information to antecedents through an interaction between the brains recognition memory networks and frontal-temporal language network. We integrate these findings with previous results from patient and neuroimaging studies, and outline a nascent cortico-hippocampal theory of reference.

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bioRxiv2016

A new foreperiod effect on single-trial phase coherence.\\ Part I: existence and relevance

Expecting events in time leads to more efficient behavior. A remarkable early finding in the study of temporal expectancy is the foreperiod effect on reaction times; i.e., the fact that the time period between a warning signal and an impendent stimuli, to which subjects are instructed to respond as quickly as possible, influences reaction times. Recently it has been shown that the phase of oscillatory activity preceding stimulus presentation is related to behavior. Here we connect both of these findings by reporting a novel foreperiod effect on the inter-trial phase coherence triggered by a stimulus to which subjects do not respond. Until now, inter-trial phase coherence has been used to describe a regularity in the phases of groups of trials. We propose a single-trial measure of inter-trial phase coherence and prove its soundness. Equipped with this measure, and using a multivariate decoding method, we demonstrate that the foreperiod duration modulates single-trial phase coherence. In principle, this modulation could be an artifact due to the decoding method used to detect it. We show that this is not the case, since the modulation can also be observed with a very simple averaging method. Although real, the single-trial modulation of inter-trial phase coherence by the foreperiod duration could just reflect a nuisance in our data. We argue against this possibility by showing that the strength of the modulation correlates with subjects behavioral measures, both error rates and mean-reaction times. We anticipate that the new foreperiod effect on inter-trial phase coherence, and the decoding method used here to detect it, will be important tools to understand cognition at the single-trial level. In Part II of this manuscript, we support this claim, by showing that attention modulates the strength of the new foreperiod effect in a trial-by-trial basis.

Neuroscience↗

bioRxiv2016

PRIMARY EVIDENCE OF A DONUT-LIKE, FOURTH SPATIAL DIMENSION IN THE BRAIN

We introduce a novel method for the measurement of information in fMRI neuroimages, i.e., nucleus clusterings Renyi entropy derived from strong proximities in feature-based Voronoi tessellations, e.g., maximal nucleus clustering (MNC). We show how MNC is a novel, fast and inexpensive image-analysis technique, independent from the standard blood-oxygen-level dependent signals, which facilitates the objective detection of hidden temporal patterns of entropy/information in zones of fMRI images generally not taken into account by the subjective standpoint of the observer. In order to evaluate the potential applications of MNC, we looked for the presence of a fourth dimensions distinctive hallmarks in a temporal sequence of 2D images taken during spontaneous brain activity. Indeed, recent findings suggest that several brain activities, such as mind-wandering and memory retrieval, might take place in the functional space of a four dimensional hypersphere, which is a double donut-like structure undetectable in the usual three dimensions. We found that the Renyi entropy is higher in MNC areas than in the surrounding ones, and that these temporal patterns closely resemble the trajectories predicted by the possible presence of a hypersphere in the brain.

Neuroscience↗

bioRxiv2016

Specific excitatory connectivity for feature integration in mouse primary visual cortex

Local excitatory connections in mouse primary visual cortex (V1) are stronger and more prevalent between neurons that share similar functional response features. However, the details of how functional rules for local connectivity shape neuronal responses in V1 remain unknown. We hypothesised that complex responses to visual stimuli may arise as a consequence of rules for selective excitatory connectivity within the local network in the superficial layers of mouse V1. In mouse V1 many neurons respond to overlapping grating stimuli (plaid stimuli) with highly selective and facilitatory responses, which are not simply predicted by responses to single gratings presented alone. This complexity is surprising, since excitatory neurons in V1 are considered to be mainly tuned to single preferred orientations. Here we examined the consequences for visual processing of two alternative connectivity schemes: in the first case, local connections are aligned with visual properties inherited from feedforward input (a like-to-like scheme specifically connecting neurons that share similar preferred orientations); in the second case, local connections group neurons into excitatory subnetworks that combine and amplify multiple feedforward visual properties (a feature binding scheme). By comparing predictions from large scale computational models with in vivo recordings of visual representations in mouse V1, we found that responses to plaid stimuli were best explained by a assuming feature binding connectivity. Unlike under the like-to-like scheme, selective amplification within feature-binding excitatory subnetworks replicated experimentally observed facilitatory responses to plaid stimuli; explained selective plaid responses not predicted by grating selectivity; and was consistent with broad anatomical selectivity observed in mouse V1. Our results show that visual feature binding can occur through local recurrent mechanisms without requiring feedforward convergence, and that such a mechanism is consistent with visual responses and cortical anatomy in mouse V1.\n\nAuthor summaryThe brain is a highly complex structure, with abundant connectivity between nearby neurons in the neocortex, the outermost and evolutionarily most recent part of the brain. Although the network architecture of the neocortex can appear disordered, connections between neurons seem to follow certain rules. These rules most likely determine how information flows through the neural circuits of the brain, but the relationship between particular connectivity rules and the function of the cortical network is not known. We built models of visual cortex in the mouse, assuming distinct rules for connectivity, and examined how the various rules changed the way the models responded to visual stimuli. We also recorded responses to visual stimuli of populations of neurons in anaesthetised mice, and compared these responses with our model predictions. We found that connections in neocortex probably follow a connectivity rule that groups together neurons that differ in simple visual properties, to build more complex representations of visual stimuli. This finding is surprising because primary visual cortex is assumed to support mainly simple visual representations. We show that including specific rules for non-random connectivity in cortical models, and precisely measuring those rules in cortical tissue, is essential to understanding how information is processed by the brain.

Neuroscience↗

bioRxiv2016

Schizophrenia and human self-domestication: a linguistic approach

Schizophrenia (SZ) is a pervasive neurodevelopmental disorder entailing social and cognitive deficits, including marked problems with language. Its complex multifactorial etiopathogenesis, including genetic and environmental factors, is still widely uncertain. SZ incidence has always been high and quite stable in human populations, across time and regardless of cultural implications, due to unclear reasons. It has been hypothesised that SZ pathophysiology may involve the biological components that changed during the recent human evolutionary history and led to our distinctive mode of cognition, which includes language skills. In this paper we explore this possibility, focusing on the self-domestication of the human species. This has been claimed to account for many human-specific distinctive traits, including aspects of our behaviour and cognition, and to favour the emergence of complex languages through cultural evolution. The \"domestication syndrome\" in mammals comprises the constellation of traits exhibited by domesticated strains, seemingly resulting from the hypofunction of the neural crest. It is our intention to show that people with SZ exhibit more marked domesticated traits at the morphological, physiological, and behavioural levels. We also show that genes involved in domestication and neural crest development and function comprise nearly 20% SZ candidates, most of which exhibit altered expression profiles in the brain of SZ patients, specifically in areas involved in language processing. Based on these observations, we conclude that SZ may represent an abnormal ontogenetic itinerary for the human faculty of language, resulting, at least in part, from changes in genes important for the \"domestication syndrome\" and, primarily involving the neural crest.

Neuroscience↗

bioRxiv2016

Activity of the C. elegans egg-laying behavior circuit is controlled by competing activation and feedback inhibition

Like many behaviors, Caenorhabditis elegans egg laying alternates between inactive and active states. To understand how the underlying neural circuit turns the behavior on and off, we optically recorded circuit activity in behaving animals while manipulating circuit function using mutations, optogenetics, and drugs. In the active state, the circuit shows rhythmic activity phased with the body bends of locomotion. The serotonergic HSN command neurons initiate the active state, but accumulation of unlaid eggs also promotes the active state independent of the HSNs. The cholinergic VC motor neurons slow locomotion during egg-laying muscle contraction and egg release. The uv1 neuroendocrine cells mechanically sense passage of eggs through the vulva and release tyramine to inhibit egg laying, in part via the LGC-55 tyramine-gated Cl- channel on the HSNs. Our results identify discrete signals that entrain or detach the circuit from the locomotion central pattern generator to produce active and inactive states.

Neuroscience↗

bioRxiv2016

Learning improves conscious access at the bottom, but not the top: Reverse hierarchical effects in perceptual learning and metacognition

Experience with visual stimuli can improve their perceptual performance, a phenomenon termed visual perceptual learning (VPL), but how does VPL shape our conscious experience of learned stimuli? VPL has been found to improve measures of metacognition, suggesting increased conscious stimulus accessibility. Such studies however, have largely failed to control objective task accuracy, which typically correlates with metacognition. Here, using a staircase method to control this confound, we investigated whether VPL improves the metacognitive accuracy of perceptual judgements. Across three consecutive days, subjects learned to discriminate faces based on either their identity or contrast. Holding objective accuracy constant, perceptual thresholds improved in both tasks, while metacognitive accuracy diverged, with face contrast VPL improving metacognition, and face identity VPL failing to. Our findings can be interpreted in a reverse hierarchy theory-like model of VPL, which counterintuitively predicts that the VPL of low- but not high-level stimulus properties should improve conscious stimulus accessibility.

Neuroscience↗

bioRxiv2016

Ankyrin G membrane partners drive the establishment and maintenance of the axon initial segment

The axon initial segment (AIS) is a specialized neuronal compartment that plays a key role in neuronal development and excitability. It concentrates multiple ion channels and cell adhesion molecules. The anchoring of these AIS membrane components is known to be highly dependent of the scaffold protein ankyrin G (ankG) but whether ankG membrane partners play a reciprocal role in ankG targeting and stabilization has not been studied yet. In cultured hippocampal neurons and cortical organotypic slices, we found that shRNA-mediated knockdown of ankG membrane partners led to a decrease of ankG concentration and perturbed the AIS formation and maintenance. These perturbations were rescued by expressing an AIS-targeted sodium channel, or a minimal construct containing the ankyrin-binding domain of Nav1.2 and a membrane anchor. We thus demonstrate that a tight and precocious association of ankG to its membrane partners is crucial for the establishment and maintenance of the AIS.

Neuroscience↗

bioRxiv2016

Improving the temporal accuracy of functional Magnetic Resonance Imaging

A major drawback of functional Magnetic Resonance Imaging (fMRI) concerns the lack of temporal accuracy of the measured signal. Although this limitation stems in part from the neuro-vascular nature of the fMRI signal, it also reflects particular methodological decisions in the fMRI data analysis pathway. Here we show that the temporal accuracy of fMRI is affected by the specific way in which whole-brain volumes are created from individually acquired brain slices. Specifically, we show how the current volume creation method leads to whole-brain volumes that contain within-volume temporal distortions and that are available at a low temporal resolution. To address these limitations, we propose a new framework for fMRI data analysis. The new framework creates whole-brain volumes from individual brain slices that are all acquired at the same point in time relative to a presented stimulus. These whole-brain volumes contain no temporal distortions, and are available at a high temporal resolution. Statistical signal extraction occurs on the basis of a novel time point-by-time point approach. We evaluated the temporal characteristics of the extracted signal in the standard and new framework with simulated and real-world fMRI data. The new slice-based data-analytic framework yields greatly improved temporal accuracy of fMRI signals.

Neuroscience↗

bioRxiv2016

Intrinsic brain connectivity after partial sleep deprivation in young and older adults: results from the Stockholm Sleepy Brain study

Sleep deprivation has been reported to affect intrinsic brain connectivity, notably reducing connectivity in the default mode network. Studies to date have however shown inconsistent effects, in many cases lacked monitoring of wakefulness, and largely included young participants. We investigated effects of sleep deprivation on intrinsic brain connectivity in young and older participants. Participants aged 20-30 (n=30) and 65-75 (n=23) years underwent partial sleep deprivation (3h sleep) in a cross-over design, with two 8-minutes eyes-open resting state functional magnetic resonance imaging (fMRI) runs in each session, monitored by eye-tracking. We assessed intrinsic brain connectivity using independent components analysis (ICA) as well as seed-region analyses of functional connectivity, and also analysed global signal variability, regional homogeneity, and the amplitude of low-frequency fluctuations. Sleep deprivation caused increased global signal variability. In our study, changes in investigated resting state networks and in regional homogeneity were not statistically significant. Younger participants had higher connectivity in most examined networks, as well as higher regional homogeneity in areas including anterior and posterior cingulate cortex. In conclusion, we found that sleep deprivation caused increased global signal variability. We speculate that this may be caused by wake-state instability.

Neuroscience↗

bioRxiv2016

Investigating resting-state functional connectivity in the cervical spinal cord at 3T

The study of spontaneous fluctuations in the blood-oxygen-level-dependent (BOLD) signal has recently been extended from the brain to the spinal cord. Two ultra-high field functional magnetic resonance imaging (fMRI) studies in humans have provided evidence for reproducible resting-state connectivity between the dorsal horns as well as between the ventral horns, and a study in non-human primates has shown that these resting-state signals are impacted by spinal cord injury. As these studies were carried out at ultra-high field strengths using region-of-interest (ROI) based analyses, we investigated whether such resting-state signals could also be observed at the clinically more prevalent field strength of 3T. In a reanalysis of a sample of 20 healthy human participants who underwent a resting-state fMRI acquisition of the cervical spinal cord, we were able to observe significant dorsal horn connectivity as well as ventral horn connectivity, but no consistent effects for connectivity between dorsal and ventral horns, thus replicating the human 7T results. These effects were not only observable when averaging along the acquired length of the spinal cord, but also when we examined each of the acquired spinal segments separately, which showed similar patterns of connectivity. Finally, we investigated the robustness of these resting-state signals against variations in the analysis pipeline by varying the type of ROI creation, temporal filtering, nuisance regression and connectivity metric. We observed that - apart from the effects of band-pass filtering - ventral horn connectivity showed excellent robustness, whereas dorsal horn connectivity showed moderate robustness. Together, our results provide evidence that spinal cord resting-state connectivity is a robust and spatially consistent phenomenon that could be a valuable tool for investigating the effects of pathology, disease progression, and treatment response in neurological conditions with a spinal component, such as spinal cord injury.

Neuroscience↗

bioRxiv2016

Measuring MEG closer to the brain: Performance of on-scalp sensor arrays

Optically-pumped magnetometers (OPMs) have recently reached sensitivity levels required for magnetoencephalogra-phy (MEG). OPMs do not need cryogenics and can thus be placed within millimetres from the scalp into an array that adapts to the invidual head size and shape, thereby reducing the distance from cortical sources to the sensors. Here, we quantified the improvement in recording MEG with hypothetical on-scalp OPM arrays compared to a 306-channel state-of-the-art SQUID array (102 magnetometers and 204 planar gradiometers).\n\nWe simulated OPM arrays that measured either normal (nOPM; 102 sensors), tangential (tOPM; 204 sensors), or all components (aOPM; 306 sensors) of the magnetic field. We built forward models based on magnetic resonance images of 10 adult heads; we employed a three-compartment boundary element model and distributed current dipoles evenly across the cortical mantle.\n\nCompared to the SQUID magnetometers, nOPM and tOPM yielded 7.5 and 5.3 times higher signal power, while the correlations between the field patterns of source dipoles were reduced by factors of 2.8 and 3.6, respectively. Values of the field-pattern correlations were similar across nOPM, tOPM and SQUID gradiometers. Volume currents reduced the signals of primary currents on average by 10%, 72% and 15% in nOPM, tOPM and SQUID magnetometers, respectively. The information capacities of the OPM arrays were clearly higher than that of the SQUID array. The dipole-localization accuracies of the arrays were similar while the minimum-norm-based point-spread functions were on average 2.4 and 2.5 times more spread for the SQUID array compared to nOPM and tOPM arrays, respectively.

Neuroscience↗