SEARCH · Search bioRxiv

Results for “Neuroscience”

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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 649 records · Page 36Linked to original sources

bioRxiv2016

Dendritic trafficking faces physiologically critical speed-precision tradeoffs

Nervous system function requires intracellular transport of channels, receptors, mRNAs, and other cargo throughout complex neuronal morphologies. Local signals such as synaptic input can regulate cargo trafficking, motivating the leading conceptual model of neuron-wide transport, sometimes called the \"sushi-belt model\" (Doyle and Kiebler, 2011). Current theories and experiments are based on this model, yet its predictions are not rigorously understood. We formalized the sushi belt model mathematically, showing how it can achieve arbitrarily complex spatial distributions of cargo in reconstructed morphologies. However, the model also predicts an unavoidable, morphology dependent tradeoff between speed, precision and metabolic efficiency of cargo transport. With experimental estimates of trafficking kinetics, the model predicts delays of many hours or days for modestly accurate and efficient cargo delivery throughout a dendritic tree. These findings challenge current understanding of the efficacy of nucleus-to-synapse trafficking and may explain the prevalence of local biosynthesis in neurons.

Neuroscience↗

bioRxiv2016

The basis of sharp spike onset in standard biophysical models

In most vertebrate neurons, spikes initiate in the axonal initial segment. When recorded in the soma, they have a surprisingly sharp onset, as if sodium (Na) channels opened abruptly. On the basis of multicompartmental models, this phenomenon has been previously attributed to the progressive sharpening of spikes as they backpropagate from the initiation site to the soma. Here we show in the same models that the biophysical basis of the phenomenon is not backpropagation but critical resistive coupling between the soma and the initial segment. Accordingly, spike initiation results from the interplay between Na current and axial resistive current flowing from axonal initiation site to soma, rather than between local Na and potassium transmembrane currents at the initiation site. The sharp onset of somatic spikes is therefore not an artifact of recording spikes at the incorrect location, but rather the signature that spike initiation does not follow the standard account.

Neuroscience↗

bioRxiv2016

The wiring diagram of a glomerular olfactory system

The sense of smell enables animals to react to long-distance cues according to learned and innate valences. Here, we have mapped with electron microscopy the complete wiring diagram of the Drosophila larval antennal lobe, an olfactory neuropil similar to the vertebrate olfactory bulb. We found a canonical circuit with uniglomerular projection neurons (uPNs) relaying gain-controlled ORN activity to the mushroom body and the lateral horn. A second, parallel circuit with multiglomerular projection neurons (mPNs) and hierarchically connected local neurons (LNs) selectively integrates multiple ORN signals already at the first synapse. LN-LN synaptic connections putatively implement a bistable gain control mechanism that either computes odor saliency through panglomerular inhibition, or allows some glomeruli to respond to faint aversive odors in the presence of strong appetitive odors. This complete wiring diagram will support experimental and theoretical studies towards bridging the gap between circuits and behavior.

Neuroscience↗

bioRxiv2016

Incorporating and compensating cerebrospinal fluid in surface-based forward models of magneto- and electroencephalography

MEG/EEG source imaging is usually done using a three-shell (3-S) or a simpler head model. Such models omit cerebrospinal fluid (CSF) that strongly affects the volume currents. We present a four-compartment (4-C) boundary-element (BEM) model that incorporates the CSF and is computationally efficient and straightforward to build using freely available software. We propose a way for compensating the omission of CSF by decreasing the skull conductivity of the 3-S model, and study the robustness of the 4-C and 3-S models to errors in skull conductivity.\n\nWe generated dense boundary meshes using MRI datasets and automated SimNIBS pipeline. Then, we built a dense 4-C reference model using Galerkin BEM, and 4-C and 3-S test models using coarser meshes and both Galerkin and collocation BEMs. We compared field topographies of cortical sources, applying various skull conductivities and fitting conductivities that minimized the relative error in 4-C and 3-S models. When the CSF was left out from the EEG model, our compensated, unbiased approach improved the accuracy of the 3-S model considerably compared to the conventional approach, where CSF is neglected without any compensation (mean relative error < 20% vs. > 40%). The error due to the omission of CSF was of the same order in MEG and compensated EEG. EEG has, however, large overall error due to uncertain skull conductivity.\n\nOur results show that a realistic 4-C MEG/EEG model can be implemented using standard tools and basic BEM, without excessive workload or computational burden. If the CSF is omitted, compensated skull conductivity should be used in EEG.

Neuroscience↗

bioRxiv2016

Validating silicon polytrodes with paired juxtacellular recordings: method and dataset

Cross-validating new methods for recording neural activity is necessary to accurately interpret and compare the signals they measure. Here we describe a procedure for precisely aligning two probes for in vivo \"paired-recordings\" such that the spiking activity of a single neuron is monitored with both a dense extracellular silicon polytrode and a juxtacellular micro-pipette. Our new method allows for efficient, reliable, and automated guidance of both probes to the same neural structure with micron resolution. We also describe a new dataset of paired-recordings, which is available online. We propose that our novel targeting system, and ever expanding cross-validation dataset, will be vital to the development of new algorithms for automatically detecting/sorting single-units, characterizing new electrode materials/designs, and resolving nagging questions regarding the origin and nature of extracellular neural signals.

Neuroscience↗

bioRxiv2016

Sex-dependent and sex-independent brain resting-state functional connectivity in children with autism spectrum disorder

BackgroundMales are more likely to suffer from autism spectrum disorder (ASD) than females. As to whether females with ASD have similar brain alterations remain an open question. The current study aimed to examine sex-dependent as well as sex-independent alterations in resting-state functional connectivity in individuals with ASD compared with typically developing (TD) individuals.\n\nMethodResting-state functional MRI data were acquired from the Autism Brain Imaging Data Exchange (ABIDE). Subjects between 6 to 20 years of age were included for analysis. After matching the intelligence quotient between groups for each dataset, and removing subjects due to excessive head motion, the resulting effective sample contained 28 females with ASD, 49 TD females, 129 males with ASD, and 141 TD males, with a two (diagnosis) by two (sex) design. Functional connectivity among 153 regions of interest (ROIs) comprising the whole brain was computed. Two by two analysis of variance was used to identify connectivity that showed diagnosis by sex interaction or main effects of diagnosis.\n\nResultsThe main effects of diagnosis were found mainly between visual cortex and other brain regions, indicating sex-independent connectivity alterations. We also observed two connections whose connectivity showed diagnosis by sex interaction between the precuneus and medial cerebellum as well as the precunes and dorsal frontal cortex. While males with ASD showed higher connectivity in these connections compared with TD males, females with ASD had lower connectivity than their counterparts.\n\nConclusionsBoth sex-dependent and sex-independent functional connectivity alterations are present in ASD.

Neuroscience↗

bioRxiv2016

Gene Expression Signatures of Sporadic ALS Motor Neuron Populations

BackgroundAmyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease primarily affecting motor neurons (MNs) to cause progressive paralysis. Ninety percent of cases are sporadic (sALS) and ten percent are familial (fALS). The molecular mechanisms underlying neurodegeneration remain elusive and there is a lack of promising biomarkers that define ALS phenotypes and progression. To date, most expression studies have focused on either complex whole tissues that contain cells other than MNs or induced pluripotent derived MNs (iMNs). Furthermore, as human tissue samples have high variability, estimation of differential gene-expression is not a trivial task.\n\nResultsHere, we report a battery of orthogonal computational analyses to discover geneexpression defects in laser capture microdissected and enriched MN RNA pools from sALS patient spinal cords in regions destined for but not yet advanced in neurodegenerative stage. We used total RNA-sequencing (RNA-seq), applied multiple percentile rank (MPR) analysis to analyze MN-specific gene-expression signatures, and used high-throughput qPCR to validate RNA-seq results. Furthermore, we used a systems-level approach that identified molecular networks perturbed in sALS MNs. Weighted gene co-expression correlation network (WGCNA) analysis revealed defects in neurotransmitter biosynthesis and RNA-processing pathways while gene-gene interaction analysis showed abnormalities in networks that pertained to cell-adhesion, immune response and wound healing.\n\nConclusionsWe discover gene-expression signatures that distinguish sALS from control MNs and our findings illuminate possible mechanisms of cellular toxicity. Our systematic and comprehensive analysis serves as a framework to reveal expression signatures and disrupted pathways that will be useful for future mechanistic studies and biomarker based therapeutic research.

Neuroscience↗

bioRxiv2016

Optimistic reinforcement learning: computational and neural bases

While forming and updating beliefs about future life outcomes, people tend to consider good news and to disregard bad news. This tendency is supposed to support the optimism bias. Whether this learning bias is specific to \"high-level\" abstract belief update or a particular expression of a more general \"low-level\" reinforcement learning process is unknown. Here we report evidence in favor of the second hypothesis. In a simple instrumental learning task, participants incorporated better-than-expected outcomes at a higher rate compared to worse-than-expected ones. In addition, functional imaging indicated that inter-individual difference in the expression of optimistic update corresponds to enhanced prediction error signaling in the reward circuitry. Our results constitute a new step in the understanding of the genesis of optimism bias at the neurocomputational level.

Neuroscience↗

bioRxiv2016

Does crossed aphasia originate from developmental disorders? A Mini-review and case study

Cognitive impairments associated with crossed aphasia were investigated in a single case study and a review of the literature. A review of literature identifies 4 main cognitive co-morbidities that are significantly associated with crossed aphasia. We present a case of confirmed crossed aphasia with dyslexia and dysgraphia, in which the latter two cannot be fully explained by the current lesion and are probable developmental disorders (dyslexia/dysgraphia). Extensive longitudinal cognitive investigations and a series of advanced imaging techniques (structural and functional) were used to investigate the cognitive and neuroanatomical basis of crossed aphasia and associated impairments in this patient. Using the results from the literature review and the single case study, we suggest that developmental disorders can be an underlying cause of partial right lateralisation shift of language processes, thereby supporting the theory that developmental disorders can be an underlying cause of crossed aphasia.\n\nHighlightsO_LICentral apraxia, dysgraphia, hemi-neglect & acalculia associated with CA\nC_LIO_LIDevelopmental disorders can underlie partial right lateralisation shift\nC_LIO_LIDysfunction of left hemisphere can cause crossed aphasia\nC_LIO_LIClinically, pre-morbid impairments must be investigated in CA cases\nC_LI

Neuroscience↗

bioRxiv2016

Contents of Consciousness Investigated as Integrated Information in Direct Human Brain Recordings

Integrated information theory postulates that the particular way stimuli appear when we consciously experience them arises from integrated information relationships across neural populations. We investigated if such equivalence holds by testing if similar/different percepts map onto similar/different information structures. We computed integrated information structure from intracranial EEGs recorded in 6 neurosurgical patients who had electrodes implanted over posterior cortices. During recording, we dissociated subjective percepts from physical inputs in three distinct stimulus paradigms (passive viewing, continuous flash suppression, and backward masking). Unsupervised classification showed that integrated information within stimulus-selective cortical regions classified visual experiences with significant accuracy (peaking on average around 64% classification accuracy). Classification by other relevant information theoretic measures such as mutual information and entropy was consistently poorer (56% and 54% accuracy). The findings argue that concepts from integrated information theory are empirically testable, promising a potential link between conscious experience and informational structures.

Neuroscience↗

bioRxiv2016

Estimation of Voxelwise Effective Connectivities: Applications to High Connectivity Sub-Regions within Hippocampal and within Corticostriatal Networks

Standard BOLD connectivity analyses depend on aggregating the signals of individual voxel within regions of interest (ROIs). In certain cases, this aggregation implies a loss of valuable functional and anatomical information about sub-regions of voxels that drive the ROI level connectivity. We describe a data-driven statistical search method that identifies the voxels that are chiefly responsible for exchanging signals between regions of interest that are known to be effectively connected. We apply the method to high-resolution resting state functional magnetic resonance imaging (rs-fMRI) data from medial temporal lobe regions of interest of a single healthy individual measured repeated times over a year and a half. The method successfully recovered densely connected voxels within larger ROIs of entorhinal cortex and hippocampus subfields consistent with the well-known medial temporal lobe structural connectivity. To assess the performance of our method in more common scanning protocols we apply it to resting state fMRI data of corticostriatal regions of interest for 50 healthy individuals. The method recovered densely connected voxels within the caudate nucleus and the putamen in good qualitative agreement with structural connectivity measurements. We describe related methods for estimation of effective connections at the voxel level that merit investigation.

Neuroscience↗

bioRxiv2016

Are reading and face processing related? An investigation of reading in developmental prosopagnosia

Recent hypotheses suggest that learning to read influences the cognitive and cerebral organization of other perceptual skills, including face processing. Developmental prosopagnosia (DP) is a disorder of face recognition in the absence of acquired brain injury, and in the context of normal intelligence and general cognitive development. To shed light on the potential relationship between reading and face processing in this group (and in general), we investigated reading performance in 10 participants with DP and 20 matched controls. We find that the group of DPs perform strikingly similar to the control group on four sensitive reading tests measuring visual recognition and naming of single letters and words, word length effects, and text reading speed and comprehension. Thus, there is a clear dissociation between impaired face processing and preserved reading in this group, a finding that challenges the recently proposed hypothesis that reading acquisition and face processing abilities are intrinsically linked. Developmental prosopagnosics can learn to read as fluently as normal subjects, while they are seemingly unable to learn efficient strategies for recognizing faces.

Neuroscience↗

bioRxiv2016

Predicting symptom severity in autism spectrum disorder based on cortical thickness measures in agglomerative data

Machine learning approaches have been widely used for the identification of neuropathology from neuroimaging data. However, these approaches require large samples and suffer from the challenges associated with multi-site, multi-protocol data. We propose a novel approach to address these challenges, and demonstrate its usefulness with the Autism Brain Imaging Data Exchange (ABIDE) database. We predict symptom severity based on cortical thickness measurements from 156 individuals with autism spectrum disorder (ASD) from four different sites. The proposed approach consists of two main stages: a domain adaptation stage using partial least squares regression to maximize the consistency of imaging data across sites; and a learning stage combining support vector regression for regional prediction of severity with elastic-net penalized linear regression for integrating regional predictions into a whole-brain severity prediction. The proposed method performed markedly better than simpler alternatives, better with multi-site than single-site data, and resulted in a considerably higher cross-validated correlation score than has previously been reported in the literature for multi-site data. This demonstration of the utility of the proposed approach for detecting structural brain abnormalities in ASD from the multi-site, multi-protocol ABIDE dataset indicates the potential of designing machine learning methods to meet the challenges of agglomerative data.

Neuroscience↗

bioRxiv2016

Light adaptation explains different linearity of ON and OFF responses

The visual system separates the responses to dark and light stimuli into OFF and ON channels. Recordings in visual thalamus indicate that these channels exhibit marked asymmetries in linearity: OFF responses grow roughly linearly with intensity decrements, but ON responses can saturate with small intensity increments. Here I show that this asymmetry is likely to originate in photoreceptors, as it follows from the classical description of their light responses and of their properties of light adaptation. Under this interpretation, the surprising aspect of the recordings is that the visual system does so little to change this asymmetry in subsequent stages.

Neuroscience↗

bioRxiv2016

Inter- and intra-individual differences in fluid reasoning show distinct cortical responses

Fluid intelligence is a general cognitive ability associated with problem solving in the absence of task-specific knowledge. Neuroscientific studies of fluid intelligence have studied both fluid intelligence tasks of varying difficulty and individual differences in fluid intelligence ability, but have failed to appropriately distinguish the two dimensions. Here we use task-based fMRI (N=34) to show that within and between subject dimensions show both partial overlap and widespread differences. Individuals with higher ability showed widespread increased activity including bilateral frontoparietal systems, whereas more difficult items were associated with more focal activity increases in middle frontal gyri, frontal poles and superior frontal poles. Finally, we show that when difficulty is equated across individuals, those with higher ability tend to show more fronto-parietal activity, whereas low fluid intelligence individuals tend to show greater activity in higher visual areas. The fMRI and behavioural data for our paper are freely available in online repositories.

Neuroscience↗

bioRxiv2016

Overlap of movement planning and movement execution reduces reaction time by up to 100ms.

Motor planning is the process of preparing the appropriate motor commands in order to achieve a goal. This process has been largely considered as occurring before movement onset and has been traditionally associated with reaction time. However, in a virtual line bisection task, we observed an overlap between movement planning and execution.\n\nIn this task performed with a robotic manipulandum, we observed that the participants (N=30) made straight movements when the line was in front of them (near target) but made often curved movements towards a farther target that was located sideways in such a way that they crossed the line perpendicular to it. Unexpectedly, movements to the far targets had shorter reaction times than movements to the near target (mean difference: 32ms, SE: 5ms, max: 104ms). In addition, the curvature of the movement modulated reaction time. A larger increase in movement curvature from the near to the far target was associated with a larger reduction in reaction time. These highly curved movements started with a transport phase during which accuracy demands were not taken into account.\n\nWe concluded that accuracy demand imposes a reaction time penalty if it is processed before movement onset. This penalty is reduced if the start of the movement can consist of a transport phase and if the movement plan can be refined in function of accuracy demands later in the movement, hence demonstrating an overlap between movement planning and execution.\n\nNew and NoteworthyIn the planning of a movement, the brain has the opportunity to delay the incorporation of accuracy requirements on the motor plan in order to reduce the reaction time by up to 100ms. Such shortening of reaction time is observed here when the first phase of the movement consists in a transport phase. This forces us to reconsider the idea that motor plans are fully characterized before movement onset.

Neuroscience↗

bioRxiv2016

Selective maintenance mechanisms of seen and unseen sensory features in the human brain

Recent studies of 'unconscious working memory' have challenged the notion that only visible stimuli can be actively maintained over time. In the present study, we investigated the neural dynamics of subliminal maintenance using multivariate pattern analyses of magnetoencephalography recordings (MEG). Subjects were presented with a masked Gabor patch whose angle had to be briefly memorized. We show with an unprecedented level of precision, that irrelevant sensory features of contrast, frequency and phase are only encoded transiently. Conversely, the relevant feature of angle is encoded and maintained in a distributed and dynamically changing manner throughout the brief retention period. Furthermore, although the visibility of the stimulus correlates with an amplification of late neural codes, we show that unseen stimuli can be partially maintained in the corresponding neural assemblies. Together, these results invalidate several predictions of current neuronal theories of visual awareness and suggest that visual perception relies on a long sequence of neural assemblies that repeatedly recode and maintain task-relevant features at multiple levels of processing, even under unconscious conditions.

Neuroscience↗

bioRxiv2016

Balanced excitation and inhibition decorrelates visual feature representation in the mammalian inner retina

The retina extracts visual features for transmission to the brain. Different types of bipolar cell split the photoreceptor input into parallel channels and provide the excitatory drive for downstream visual circuits. Anatomically, mouse bipolar cell types have been described down to the ultrastructural level, but a similarly deep understanding of their functional diversity is lacking. By imaging light-driven glutamate release from more than 11,000 bipolar cell axon terminals in the intact retina, we here show that bipolar cell functional diversity is generated by the balanced interplay of dendritic excitatory inputs and axonal inhibitory inputs. The resultant centre and surround components of bipolar cell receptive fields interact to decorrelate bipolar cell output in the spatial and temporal domain. Our findings highlight the importance of inhibitory circuits in generating functionally diverse excitatory pathways and suggest that decorrelation of parallel visual pathways begins already at the second synapse of the mouse visual system.

Neuroscience↗