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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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.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 1,441 records · Page 80Linked to original sources

bioRxiv2016

Quantitative Analysis of Dopamine Neuron Subtypes Generated from Mouse Embryonic Stem Cells

Dopamine (DA) neuron subtypes modulate specific physiological functions and are involved in distinct neurological disorders. Embryonic stem cell (ESC) derived DA neurons have the potential to aid in the study of disease mechanisms, drug discovery, and possibly cell replacement therapies. DA neurons can be generated from ESCs in vitro, but the subtypes of ESC-derived DA neurons have not been investigated in detail despite the diversity of DA neurons observed in vivo. Due to cell culture heterogeneity, sampling methods applied to ESC-derived cultures can be ambiguous and potentially biased. Therefore, we developed a quantification method to capture the depth of DA neuron production in vitro by estimating the error associated with systematic random sampling. Using this method, we quantified calbindin+ and calretinin+ subtypes of DA neurons generated from mouse ESCs. We found a higher production of the calbindin+ subtype (11-27%) compared to the calretinin+ subtype (2-13%) of DA neuron; in addition, DA neurons expressing neither subtype marker were also generated. We then examined whether exogenous sonic hedgehog (SHH) and fibroblast growth factor 8 (FGF8) affected subtype generation. Our results demonstrate that exogenous SHH and FGF8 did not alter DA neuron subtype generation in vitro. These findings suggest that a deeper understanding DA neuron derivation inclusive of mechanisms that govern the in vitro subtype specification of ESC-derived DA neurons is required.\n\nNoteAll research was planned and conducted while members were at Brown University\n\nResearch fundingNIH/NCRR/NIGMS RI Hospital COBRE Center for Stem Cell Biology (8P20GM103468-04) (MZ) Brown Institute for Brain Science Pilot Grant (4-63662) (MZ/DHK)

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bioRxiv2016

The triple-flash illusion reveals a driving role of alpha-band reverberations in visual perception

The modulatory role of spontaneous brain oscillations on perception of threshold-level stimuli is well established. Here, we provide evidence that alpha-band (7-14 Hz) oscillations not only modulate but also can drive perception. We used the \"triple-flash\" illusion: Occasional perception of three flashes when only two spatially-coincident veridical ones are presented, separated by ~100 ms. The illusion was proposed to result from superposition of two hypothetical oscillatory impulse response functions (IRF) generated in response to each flash (Bowen, 1989). In Experiment 1, we varied stimulus onset asynchrony (SOA) and validated Bowen's theory: the optimal SOA for illusion to occur was correlated, across subjects, with the subject-specific IRF period. Experiment 2 revealed that pre-stimulus parietal alpha EEG phase and power, as well as post-stimulus alpha phase-locking, together determine the occurrence of the illusion on a trial-by-trial basis. Thus, oscillatory reverberations create something out of nothing - a third flash where there are only two.

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bioRxiv2016

Openspritzer: an open hardware pressure ejection system for reliably delivering picolitre volumes.

The ability to reliably and precisely deliver picolitre volumes is an important component of biological research. Here we describe a high-performance, low-cost, open hardware pressure ejection system (Openspritzer), which can be constructed from off the shelf components. When connected to a standard micro-pipette via suitable pneumatic tubing, the device is capable of delivering minute doses of reagents to a wide range of biological and chemical systems. In this work, we characterise the performance of the device and compare it to a popular commercial system using two-photon fluorescence microscopy. We found that Openspritzer provides the same level of control over delivered reagent dose as the commercial system. Next, we demonstrate the utility of Openspritzer in a series of standard neurobiological applications. First, we used Openspritzer to deliver precise amounts of the neurotransmitters glutamate and GABA to hippocampal neurons to elicit time- and dose-precise excitatory and inhibitory responses, respectively. Second, we used Openspritzer to deliver infectious viral and bacterial agents to living tissue. Viral transfection of hippocampal interneurons with channelrhodopsin allowed for the optogenetic manipulation of hippocampal circuitry with light. Finally, we successfully used Openspritzer to infect organotypic hippocampal slice cultures with fluorescent Mycobacterium bovis bacilli. We anticipate that due to its high performance and low cost Openspritzer will be of interest to a broad range of researchers working in the life and physical sciences.

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bioRxiv2016

Cortical excitability controls the strength of mental imagery

Mental imagery provides an essential simulation tool for remembering the past and planning the future, with its strength affecting both cognition and mental health. Research suggests that neural activity spanning prefrontal, parietal, temporal, and visual areas supports the generation of mental images. Exactly how this network controls the strength of visual imagery remains unknown. Here, brain imaging and transcranial magnetic phosphene data show that lower resting activity and excitability levels in early visual cortex (V1-V3) predict stronger sensory imagery. Electrically decreasing visual cortex excitability using tDCS increases imagery strength, demonstrating a causative role of visual cortex excitability in controlling visual imagery. These data suggest a neurophysiological mechanism of cortical excitability involved in controlling the strength of mental images.

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bioRxiv2016

Slice-sampled Bayesian PRF mapping

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.

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bioRxiv2016

A theory of working memory without consciousness or sustained activity

Working memory and conscious perception are thought to share similar brain mechanisms, yet recent reports of non-conscious working memory challenge this view. Combining visual masking with magnetoencephalography, we demonstrate the reality of non-conscious working memory and dissect its neural mechanisms. In a spatial delayed-response task, participants reported the location of a subjectively unseen target above chance-level after a long delay. Conscious perception and conscious working memory were characterized by similar signatures: a sustained desynchronization in the alpha/beta band over frontal cortex, and a decodable representation of target location in posterior sensors. During non-conscious working memory, such activity vanished. Our findings contradict models that identify working memory with sustained neural firing, but are compatible with recent proposals of activity-silent working memory. We present a theoretical framework and simulations showing how slowly decaying synaptic changes allow cell assemblies to go dormant during the delay, yet be retrieved above chance-level after several seconds.

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bioRxiv2016

Impact of gray matter signal regression in resting state and language task functional networks

A network analysis of the resting state (RS) and language task (LT) of fRMI data sets is presented. Specifically, the analysis compares the impact of the global signal regression of gray matter signal on the graph parameters and community structure derived of functional data. It was found that, without gray matter signal regression (GSR), the group comparison showed no significant changes of the global metrics between the two conditions studied. With gray matter signal regression, significant differences between the global (local) metrics for the conditions were obtained. The mean degree, the clustering coefficient of the network and the mean value of the local efficiency were metrics with significant changes. The community structure of group connectivity matrices was explored for both conditions (RS and LT) and for different preprocessing steps. When gray matter signal regression was performed, small changes of the community structure were observed. Approximately, the same regions were classified in the same communities before and after GSR. This means, that the community structure of the data is weakly affected by this preprocessing step. The modularity index presented significant changes between conditions (RS and LT) and between different preprocessing pipeline.

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bioRxiv2016

The contribution of area MT to visual motion perception depends on training

SummaryPerceptual decisions require the transformation of raw sensory inputs into cortical representations suitable for stimulus discrimination. One of the best-known examples of this transformation involves the middle temporal area (MT) of the primate visual cortex. Area MT provides a robust representation of stimulus motion, and previous work has shown that it contributes causally to performance on motion discrimination tasks. Here we report that the strength of this contribution can be highly plastic: Depending on the recent training history, pharmacological inactivation of MT can severely impair motion discrimination, or it can have little detectable influence. Similarly, depending on training, microstimulation can bias motion perception or simply introduce noise. Further analysis of neural and behavioral data suggests that training shifts the readout of motion information between MT and lower-level cortical areas. These results show that the contribution of individual brain regions to conscious perception can shift flexibly depending on sensory experience.

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bioRxiv2016

Stabilized supralinear network dynamics account for stimulus-induced changes of noise variability in the cortex

Variability and correlations in cortical activity are ubiquitously modulated by stimuli. Correlated variability is quenched following stimulus onset across multiple cortical areas, suppressing low-frequency components of the LFP and of Vm-LFP coherence. Modulation of Fano factors and correlations in area MT is tuned for stimulus direction. What circuit mechanisms underly these behaviors? We show that a simple model circuit, the stochastic Stabilized Supralinear Network (SSN), robustly explains these results. Stimuli modulate variability by modifying two forms of effective connectivity between activity patterns that characterize excitatory-inhibitory (E/I) circuits. Increases in the strength with which activity patterns inhibit themselves reduce correlated variability, while increases in feedforward connections between patterns (transforming E/I imbalance into balanced fluctuations) increase variability. These results suggest an operating regime of cortical dynamics that involves fast fluctuations and fast responses to stimulus changes, unlike previous models of variability suppression through suppression of chaos or networks with multiple attractors.

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bioRxiv2017

Rapid cerebrovascular reactivity mapping: Enabling vascular reactivity information to be routinely acquired

Cerebrovascular reactivity mapping (CVR), using magnetic resonance imaging (MRI) and carbon dioxide as a stimulus, provides useful information on how cerebral blood vessels react under stress. This information has proven to be useful in the study of vascular disorders, dementia and healthy ageing. However, clinical adoption of this form of CVR mapping has been hindered by relatively long scan durations of 7 to 12 minutes. By replacing the conventional block presentation of carbon dioxide enriched air with a sinusoidally modulated stimulus, the aim of this study was to investigate whether more clinically acceptable scan durations are possible. Firstly, the conventional block protocol was compared with a sinusoidal protocol of the same duration of 7 minutes. Estimates of the magnitude of the CVR signal (CVR magnitude) and the relative timing of the CVR response (CVR phase) were found to be in good agreement between the stimulus protocols. Secondly, data from the sinusoidal protocol was reanalysed using decreasing amounts of data in the range 1 to 6 minutes. The CVR magnitude was found to tolerate this reduction in scan duration better than CVR phase. However, these analyses indicate that scan durations in the range of 3 to 5 minutes produce robust data.

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bioRxiv2016

The Bayesian-Laplacian Brain

We outline what we believe could be an improvement in future discussions of the brain acting as a Bayesian-Laplacian system. We do so by distinguishing between two broad classes of priors on which the brains inferential systems operate: in one category are biological priors ({beta} priors) and in the other artifactual ones ( priors). We argue that {beta} priors, of which colour categories and faces are good examples, are inherited or acquired very rapidly after birth, are highly or relatively resistant to change through experience, and are common to all humans. The consequence is that the probability of posteriors generated from {beta} priors having universal assent and agreement is high. By contrast, priors, of which man-made objects are examples, are acquired post-natally and modified at various stages throughout post-natal life; they are much more accommodating of, and hospitable to, new experiences. Consequently, posteriors generated from them are less likely to find universal assent. Taken together, in addition to the more limited capacity of experiment and experience to alter the {beta} priors compared to priors, another cardinal distinction between the two is that the probability of posteriors generated from {beta} priors having universal agreement is greater than that for priors. The two categories are not, however, always totally distinct and can merge into one another to varying extents, resulting in posteriors that draw upon both categories.

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bioRxiv2016

Dynamically controlled light delivery over large brain volumes through tapered optical fibers

Optogenetics promises spatiotemporal precise control of neural processes using light. However, the spatial extent of illumination within the brain is difficult to control and cannot be adjusted using standard fiber optics. We demonstrate that optical fibers with tapered tips can be used to illuminate either large brain volumes or dynamically selectable subregions. Remotely adjusting the light input angle to the fiber varies the light-emitting portion of the taper over several millimeters without movement of the implant. We use this mode to activate dorsal versus ventral striatum of individual mice and reveal different effects of each manipulation on motor behavior. Conversely injecting light over the full numerical aperture of the fiber results in light emission from the entire taper surface, achieving broader and more efficient optogenetic activation of neurons when compared to the standard flat-faced fiber stimulation. Thus, tapered fibers permit focal or broad illumination that can be precisely and dynamically matched to experimental needs.

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bioRxiv2016

CORTICO-CORTICAL FEEDBACK CONTROLS SPATIAL SUMMATION IN PRIMATE VISUAL CORTEX

In the cerebral cortex, sensory information travels along feedforward connections through a hierarchy of areas, which, in turn, send a denser network of feedback connections to lower-order areas. Feedback has been implicated in attention, expectation, and sensory context, but the cellular mechanisms underlying these diverse feedback functions are unknown. Using specific optogenetic inactivation of feedback connections in the primate visual cortex, we have identified the cellular mechanisms of feedback-mediated modulations of early sensory processing. Specifically, we found that feedback modulates receptive field size, surround suppression and response gain, similar to the modulatory effects of visual spatial attention. A recurrent network model captured these effects. These feedback-mediated modulations allow higher-order cortical areas to dynamically regulate spatial resolution, sensitivity to image features, and efficiency of coding natural images in lower-order cortical areas.

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bioRxiv2016

Dissecting the role of non-coding RNAs in the accumulation of amyloid and tau neuropathologies in Alzheimer’s disease

BackgroundGiven multiple studies of brain microRNA (miRNA) in relation to Alzheimers disease (AD) with few consistent results and the heterogeneity of this disease, the objective of this study was to explore their mechanism by evaluating their relation to different elements of Alzheimers disease pathology, confounding factors and mRNA expression data from the same subjects in the same brain region.\n\nResultsWe report analyses of expression profiling of miRNA (n=700 subjects) and lincRNA (n=540 subjects) from the dorsolateral prefrontal cortex of individuals participating in two longitudinal cohort studies of aging. Evaluating well-established (miR-132, miR-129), we confirm their association with pathologic AD in our dataset, and then characterize their in disease role in terms of neuritic {beta}-amyloid plaques and neurofibrillary tangle pathology. Additionally, we identify one new miRNA (miR-99) and four lincRNA that are associated with these traits. Many other previously reported associations of microRNA with AD are associated with the confounders quantified in our longitudinal cohort. Finally, by performing analyses integrating both miRNA and RNA sequence data from the same individuals (525 samples), we characterize the impact of AD associated miRNA on human brain expression: we show that the effects of miR-132 and miR-129-5b converge on certain genes such as EP300 and find a role for miR200 and its target genes in AD using an integrated miRNA/mRNA analysis.\n\nConclusionsOverall, miRNAs play a modest role in human AD, but we observe robust evidence that a small number of miRNAs are responsible for specific alterations in the cortical transcriptome that are associated with AD.

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bioRxiv2016

Large-scale network dynamics of beta-band oscillations underlie auditory perceptual decision making

Perceptual decisions vary in the speed at which we make them. Evidence suggests that translating sensory information into behavioral decisions relies on distributed interacting neural populations, with decision speed hinging on power modulations of neural oscillations. Yet, the dependence of perceptual decisions on the large-scale network organization of coupled neural oscillations has remained elusive. We measured magnetoencephalography signals in human listeners who judged acoustic stimuli made of carefully titrated clouds of tone sweeps. These stimuli were used under two task contexts where the participants judged the overall pitch or direction of the tone sweeps. We traced the large-scale network dynamics of source-projected neural oscillations on a trial-by-trial basis using power envelope correlations and graph-theoretical network discovery. Under both tasks, faster decisions were predicted by higher segregation and lower integration of coupled beta-band (~16-28 Hz) oscillations. We also uncovered brain network states that promoted faster decisions and emerged from lower-order auditory and higher-order control brain areas. Specifically, decision speed in judging tone-sweep direction critically relied on nodal network configurations of anterior temporal, cingulate and middle frontal cortices. Our findings suggest that global network communication during perceptual decision-making is implemented in the human brain by large-scale couplings between beta-band neural oscillations.\n\nAuthor SummaryThe speed at which we make perceptual decisions varies. This translation of sensory information into behavioral decisions hinges on dynamic changes in neural oscillatory activity. However, the large-scale neural network embodiment supporting perceptual decision-making is unclear. Alavash et al. address this question by experimenting two auditory perceptual decision-making situations. Using graph-theoretical network discovery, they trace the large-scale network dynamics of coupled neural oscillations to uncover brain network states supporting the speed of auditory perceptual decisions. They find that higher network segregation of coupled beta-band oscillations supports faster auditory perceptual decisions over trials. Moreover, when auditory perceptual decisions are relatively difficult, the decision speed benefits from higher segregation of frontal cortical areas, but lower segregation and integration of auditory cortical areas.

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bioRxiv2016

Second Generation Drosophila Chemical Tags: Sensitivity, Versatility and Speed

Labeling and visualizing cells and sub-cellular structures within thick tissues, whole organs and even intact animals is key to studying biological processes. This is particularly true for studies of neural circuits where neurons form sub-micron synapses but have arbors that may span millimeters in length. Traditionally labeling is achieved by immunofluorescence; however diffusion of antibody molecules (>100 kDa) is slow and often results in uneven labeling with very poor penetration into the centre of thick specimens; these limitations can be partially addressed by extending staining protocols to over a week (Drosophila brain) and months (mice). Recently we developed an alternative approach using genetically encoded chemical tags CLIP, SNAP, Halo and TMP for tissue labeling; this resulted in >100 fold increase in labeling speed in both mice and Drosophila, at the expense of a considerable drop in absolute sensitivity when compared to optimized immunofluorescence staining. We now present a second generation of UAS and LexA responsive CLIP, SNAPf and Halo chemical labeling reagents for flies. These multimerized tags with translational enhancers display up to 64 fold increase in sensitivity over first generation reagents. In addition we developed a suite of conditional reporters (4xSNAPf tag and CLIP-SNAP-Halo) that are activated by the DNA recombinase Bxb1. Our new reporters can be used with weak and strong GAL4 and LexA drivers and enable stochastic, intersectional and multicolor Brainbow labeling. These improvements in sensitivity and experimental versatility, while still retaining the substantial speed advantage that is a signature of chemical labeling, should significantly increase the scope of this technology.

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bioRxiv2016

Distributed alpha networks underlie individual differences in memory performance

Episodic memory, our ability to remember specific events, varies considerably across individuals. However, little is known about the neural basis of this variability. To address this issue, we investigated the role of distributed networks of oscillatory activity, as measured through electroencephalography (EEG). We observed that individual differences in alpha network structure reliably predict individual memory capacity. Specifically, individuals whose network profiles during encoding were most different from their resting state networks exhibited greatest subsequent memory performance, suggesting that optimal information processing requires substantial shifts in large-scale oscillatory organization. Furthermore, these results were not observed in circumscribed topographical regions or individual connections, indicating that distributed network approaches were more sensitive to functional processes than more conventional methods. These findings uncover a physiological correlate of individual differences in episodic memory and demonstrate the utility of multivariate EEG techniques to uncover brain-behavior correlates.

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bioRxiv2016

Transcranial stimulation enhances memory-relevant sleep oscillations and their functional coupling in mild cognitive impairment

Alzheimers disease (AD) not only involves loss of memory functions but also prominent deterioration of sleep physiology, already evident in the stage of mild cognitive impairment (MCI). Cortical slow oscillations (SO, 0.5-1 Hz) and thalamo-cortical spindle activity (12-15 Hz) during sleep, and their temporal coordination, are considered critical for memory formation. We investigated the potential of slow oscillatory transcranial direct current stimulation (so-tDCS), applied during a daytime nap in a sleep state-dependent manner, to modulate these activity patterns and sleep-related memory consolidation in 16 patients with MCI.\n\nStimulation significantly increased overall SO and spindle power, amplified spindle power during SO up-phases, and led to stronger synchronization between SO and spindle power fluctuations in electroencephalographic recordings. Moreover, visual declarative memory was improved by so-tDCS compared to sham stimulation, associated with stronger synchronization. These findings indicate a well-tolerated therapeutic approach for disordered sleep physiology and deficits in memory consolidation in MCI patients.

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