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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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.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 1,153 records · Page 64Linked to original sources

bioRxiv2016

Microsaccadic information sampling provides Drosophila hyperacute vision

Small fly eyes should not see fine image details. Because flies exhibit saccadic visual behaviors and their compound eyes have relatively few ommatidia (sampling points), their photoreceptors would be expected to generate blurry and coarse retinal images of the world. Here we demonstrate that Drosophila see the world far better than predicted from the classic theories. By using electrophysiological, optical and behavioral assays, we found that R1-R6 photoreceptors encoding capacity in time is maximized to fast high-contrast bursts, which resemble their light input during saccadic behaviors. Whilst over space, R1-R6s resolve moving objects at saccadic speeds beyond the predicted motion-blur-limit. Our results show how refractory phototransduction and rapid photomechanical photoreceptor contractions jointly sharpen retinal images of moving objects in space-time, enabling hyperacute vision, and explain how such microsaccadic information sampling exceeds the compound eyes optical limits. These discoveries elucidate how acuity depends upon photoreceptor function and eye movements.

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bioRxiv2016

THETA-Rhythm makes the world go round: Dissociative effects of TMS theta vs alpha entrainment of right pTPJ on embodied perspective transformations

Introduction Introduction Materials and Methods Results and Discussion References Being able to imagine another persons experience and perspective of the world is a crucial human social ability (Call & Tomasello, 1999) and recent reports suggest that humans \"embody\" anothers viewpoint by mentally rotating their own body representation into the others orientation (Kessler, Cao, OShea, & Wang, 2014; Kessler & Rutherford, 2010; Kessler & Thomson, 2010; Surtees, Apperly, & Samson, 2013). Using Magnetoencephalography (MEG) our group recently reported in Cortex that brain oscillations at theta frequency (3-7 Hz), originating from the right posterior temporo-parietal-junction (pTPJ) reflected cognitive as well as embod ...

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bioRxiv2016

Adaptive, arousal-related adjustments of perceptual biases optimize perception in a dynamic environment

Prior expectations can be used to improve perceptual judgments about ambiguous stimuli. However, little is known about if and how these improvements are maintained in dynamic environments in which the quality of appropriate priors changes from one stimulus to the next. Using a novel sound-localization task, we show that changes in stimulus predictability lead to arousal-mediated adjustments in the magnitude of prior-driven biases that optimize perceptual judgments about each stimulus. These adjustments depend on task-dependent changes in the relevance and reliability of prior expectations, which subjects update using both normative and idiosyncratic principles. The resulting variations in biases across task conditions and individuals are reflected in modulations of pupil diameter, such that larger stimulus-evoked pupil responses correspond to smaller biases. These results suggest a critical role for the arousal system in adjusting the strength of perceptual biases with respect to inferred environmental dynamics to optimize perceptual judgements.

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bioRxiv2016

Neuronal synchrony and the relation between the BOLD response and the local field potential.

The most widespread measures of human brain activity are the blood oxygen level dependent (BOLD) signal and surface field potential. Prior studies report a variety of relationships between these signals. To develop an understanding of how to interpret these signals and the relationship between them, we developed a model of (a) neuronal population responses, and (b) transformations from neuronal responses into the fMRI BOLD signal and electrocorticographic (ECoG) field potential. Rather than seeking a transformation between the two measures directly, this approach interprets each measure with respect to the underlying neuronal population responses. This model accounts for the relationship between BOLD and ECoG data from human visual cortex in V1-V3, with the model predictions and data matching in three ways: Across stimuli, the BOLD amplitude and ECoG broadband power were positively correlated, the BOLD amplitude and alpha power (8-13 Hz) were negatively correlated, and the BOLD amplitude and narrowband gamma power (30-80 Hz) were uncorrelated. The two measures provide complementary information about human brain activity and we infer that features of the field potential that are uncorrelated with BOLD arise largely from changes in synchrony, rather than level, of neuronal activity.

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bioRxiv2016

Predictive representations can link model-based reinforcement learning to model-free mechanisms

Humans and animals are capable of evaluating actions by considering their long-run future rewards through a process described using model-based reinforcement learning (RL) algorithms. The mechanisms by which neural circuits perform the computations prescribed by model-based RL remain largely unknown; however, multiple lines of evidence suggest that neural circuits supporting model-based behavior are structurally homologous to and overlapping with those thought to carry out model-free temporal difference (TD) learning. Here, we lay out a family of approaches by which model-based computation may be built upon a core of TD learning. The foundation of this framework is the successor representation, a predictive state representation that, when combined with TD learning of value predictions, can produce a subset of the behaviors associated with model-based learning, while requiring less decision-time computation than dynamic programming. Using simulations, we delineate the precise behavioral capabilities enabled by evaluating actions using this approach, and compare them to those demonstrated by biological organisms. We then introduce two new algorithms that build upon the successor representation while progressively mitigating its limitations. Because this framework can account for the full range of observed putatively model-based behaviors while still utilizing a core TD framework, we suggest that it represents a neurally plausible family of mechanisms for model-based evaluation.\n\nAuthor SummaryAccording to standard models, when confronted with a choice, animals and humans rely on two separate, distinct processes to come to a decision. One process deliberatively evaluates the consequences of each candidate action and is thought to underlie the ability to flexibly come up with novel plans. The other process gradually increases the propensity to perform behaviors that were previously successful and is thought to underlie automatically executed, habitual reflexes. Although computational principles and animal behavior support this dichotomy, at the neural level, there is little evidence supporting a clean segregation. For instance, although dopamine -- famously implicated in drug addiction and Parkinsons disease -- currently only has a well-defined role in the automatic process, evidence suggests that it also plays a role in the deliberative process. In this work, we present a computational framework for resolving this mismatch. We show that the types of behaviors associated with either process could result from a common learning mechanism applied to different strategies for how populations of neurons could represent candidate actions. In addition to demonstrating that this account can produce the full range of flexible behavior observed in the empirical literature, we suggest experiments that could detect the various approaches within this framework.

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bioRxiv2016

Single or Multi-Frequency Generators in On-going Brain Activity: a Mechanistic Whole-Brain Model following empirical MEG evidences

During rest, envelopes of band-limited on-going MEG signals co-vary across the brain in consistent patterns, which have been related to resting-state networks measured with fMRI. To investigate the genesis of such envelope correlations, we consider a whole-brain network model assuming two distinct fundamental scenarios: one where each brain area generates oscillations in a single frequency, and a novel one where each brain area can generate oscillations in multiple frequency bands. The models share, as a common generator of damped oscillations, the normal form of a supercritical Hopf bifurcation operating at the critical border between the steady state and the oscillatory regime. The envelopes of the simulated signals are compared with empirical MEG data using new methods to analyse the envelope dynamics in terms of their phase coherence and stability across the spectrum of carrier frequencies.\n\nConsidering the whole-brain model with a single frequency generator in each brain area, we obtain the best fit with the empirical MEG data when the fundamental frequency is tuned at 12Hz. However, when multiple frequency generators are placed at each local brain area, we obtain an improved fit of the spatio-temporal structure of on-going MEG data across all frequency bands. Our results indicate that the brain is likely to operate on multiple frequency channels during rest, introducing a novel dimension for future models of large-scale brain activity.

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bioRxiv2016

Tractography-based connectomes are dominated by false-positive connections

Fiber tractography based on non-invasive diffusion imaging is at the heart of connectivity studies of the human brain. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain dataset with ground truth white matter tracts, we organized an open international tractography challenge, which resulted in 96 distinct submissions from 20 research groups. While most state-of-the-art algorithms reconstructed 90% of ground truth bundles to at least some extent, on average they produced four times more invalid than valid bundles. About half of the invalid bundles occurred systematically in the majority of submissions. Our results demonstrate fundamental ambiguities inherent to tract reconstruction methods based on diffusion orientation information, with critical consequences for the approach of diffusion tractography in particular and human connectivity studies in general.

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bioRxiv2017

Conditioning by Subthreshold Synaptic Input Changes the Characteristic Firing Pattern of CA3 Hippocampal Neurons

Unlike synaptic strength, intrinsic excitability is assumed to be a stable property of neurons. For example, learning of somatic conductances is generally not incorporated into computational models, and the discharge pattern of neurons in response to test stimuli is frequently used as a basis for phenotypic classification. However, it is increasingly evident that signal processing properties of neurons are more generally plastic on the timescale of minutes. Here we demonstrate that the intrinsic firing patterns of CA3 neurons of the rat hippocampus in vitro undergo rapid long-term plasticity in response to a few minutes of only subthreshold synaptic conditioning. This plasticity on the spike-timing could also be induced by intrasomatic injection of subthreshold depolarizing pulses and was blocked by kinase inhibitors, indicating that discharge dynamics are modulated locally. Cluster analysis of firing patterns before and after conditioning revealed systematic transitions towards adapting and intrinsic burst behaviours, irrespective of the patterns initially exhibited by the cells. We used a conductance-based model to decide appropriate pharmacological blockade, and found that the observed transitions are likely due to recruitment of calcium and M-type potassium conductances. We conclude that CA3 neurons adapt their conductance profile to the subthreshold activity of their input, so that their intrinsic firing pattern is not a static signature, but rather a reflection of their history of subthreshold activity. In this way, recurrent output from CA3 neurons may collectively shape the temporal dynamics of their embedding circuits.\n\nNew & NoteworthyDespite being widely conserved across the animal phyla, it is still a mystery why nerve cells present diverse discharge dynamics upon somatic step currents. Adding a new timing dimension to the intrinsic plasticity literature, here we show that CA3 neurons rapidly adapt through the space of known firing patterns in response to the subthreshold signals that they receive from their embedding circuit. This result implies that CA3 neurons collectively adjust their network processing to the temporal statistics of their circuit.

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bioRxiv2016

Distinctive BOLD Connectivity Patterns in the Schizophrenia Brain: Machine-learning based comparison between various connectivity measures

Recent functional magnetic resonance imaging (fMRI) studies have found distinctive functional connectivity in the schizophrenic brain. However, most of the studies focused on the correlation analysis to define the functional connectivity for BOLD fluctuations between brain regions, which resulted in the limited understanding to the network properties of altered wirings in the schizophrenic brain. Here I characterized the distinctiveness of BOLD connectivity pattern in the schizophrenic brain relative to healthy brain with various similarity measures in the time-frequency domain, while participants are performing the working memory task in the MRI scanner. To assess the distinctiveness of the connectivity pattern, discrimination performances of the pattern classifier machines trained by each similarity measurement were compared. As a result, the classifier machine trained by cross-spectral coherence pattern in low frequency fluctuation (LFF, 0.01-0.08 Hz band) made better performance than the machine trained by correlation-based connectivity pattern. Interestingly, the classifier machine trained by time-lagging patterns in cross-correlation function of LFF produced higher classifying sensitivity than the machines trained by other measures. These results indicate that there are unobserved but considerable features in the functional connectivity pattern of schizophrenic brain which traditional emphasis on correlation analysis does not capture.

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bioRxiv2016

Dual origins of measured phase-amplitude coupling reveal distinct neural mechanisms underlying episodic memory in the human cortex

Phase-amplitude coupling (PAC) is hypothesized to coordinate neural activity, but its role in successful memory formation in the human cortex is unknown. Measures of PAC are difficult to interpret, however. Both increases and decreases in PAC have been linked to memory encoding, and PAC may arise due to different neural mechanisms. Here, we use a waveform analysis to examine PAC in the human cortex as participants with intracranial electrodes performed a paired associates memory task. We found that successful memory formation exhibited significant decreases in left temporal lobe and prefrontal cortical PAC, and these two regions exhibited changes in PAC within different frequency bands. Two underlying neural mechanisms, nested oscillations and sharp waveforms, were responsible for the changes in these regions. Our data therefore suggest that decreases in measured cortical PAC during episodic memory reflect two distinct underlying mechanisms that are anatomically segregated in the human brain.

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bioRxiv2016

Bayesian mapping reveals that attention boosts neural responses to predicted and unpredicted stimuli

Predictive coding posits that the human brain continually monitors the environment for regularities and detects inconsistencies. It is unclear, however, what effect attention has on expectation processes, as there have been relatively few studies and the results of these have yielded contradictory findings. Here, we employed Bayesian model comparison to adjudicate between two alternative computational models. The Opposition model states that attention boosts neural responses equally to predicted and unpredicted stimuli, whereas the Interaction model assumes that attentional boosting of neural signals depends on the level of predictability. We designed a novel, audiospatial attention task that orthogonally manipulated attention and prediction by playing oddball sequences in either the attended or unattended ear. We observed sensory prediction error responses, with electroencephalography, across all attentional manipulations. Crucially, posterior probability maps revealed that, overall, the Opposition model better explained scalp and source data, suggesting that attention boosts responses to predicted and unpredicted stimuli equally. Furthermore, Dynamic Causal Modelling (DCM) showed that these Opposition effects were expressed in plastic changes within the mismatch negativity network. Our findings provide empirical evidence for a computational model of the opposing interplay of attention and expectation in the brain.

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bioRxiv2016

TrkB signaling underlies the rapid antidepressant effects of isoflurane

A brief burst-suppressing isoflurane anesthesia has been shown to rapidly alleviate symptoms of depression in a subset of patients, but the neurobiological basis of these observations remains obscure. We show that a single isoflurane anesthesia produces antidepressant-like behavioural effects in the learned helplessness paradigm and regulates molecular events implicated in the mechanism of action of rapid-acting antidepressant ketamine: activation of brain-derived neurotrophic factor (BDNF) receptor TrkB, facilitation of mammalian target of rapamycin (mTOR) signaling pathway and inhibition of glycogen synthase kinase 3{beta} (GSK3{beta}). Moreover, isoflurane affected neuronal plasticity by facilitating long-term potentiation in the hippocampus. We also found that isoflurane increased activity of the parvalbumin interneurons, and facilitated GABAergic transmission in wild type mice but not in transgenic mice with reduced TrkB expression in parvalbumin interneurons. Our findings strengthen the role of TrkB signaling in the antidepressant responses and encourage further evaluation of isoflurane as a rapid-acting antidepressant devoid of the psychotomimetic effects and abuse potential of ketamine.

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bioRxiv2016

The effect of subthreshold transcranial magnetic stimulation on the excitation of corticospinal volleys with different conduction times

Previous studies in humans interested in inhibitory synaptic activity at the level of the primary motor cortex (M1) have frequently used an electrophysiological technique call short intracortical inhibition (SICI). This technique consists of two subsequent pulses with transcranial magnetic stimulation (TMS), of which the first pulse (S1) has been argued to target local inhibitory connections, reducing corticospinal output generated by the second pulse (S2). However, the reduction of corticospinal output is not seen in every tested subject, sometimes S1 even increased corticospinal output. Thus there seems to be more occurring than just the targeting of local inhibitory connections by S1, indicating that the mechanisms of SICI are not fully understood. In the present study, in 18 healthy young subjects we applied a method allowing to segregate corticospinal volleys with different conduction times and investigated the effect of S1 on the excitation of these volleys. Our results revealed three major findings, which can be summarized as follows: i) S1 acted not only locally at the level of M1, but produced corticospinal activity which may influence corticospinal output by S2 at the spinal level; ii) there was not only reduced excitation of corticospinal volleys by S1, but also an increased excitation of corticospinal volleys with longer conduction times; iii) at the level of M1, S1 indeed targeted preferentially inhibitory synaptic connections, and these reduced corticospinal excitation of the fastest conduction corticospinal volleys.\n\nOur results indicate that underlying mechanisms in studies applying SICI should be interpreted with caution.

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bioRxiv2016

Visual processing mode switching regulated by VIP cells

The responses of neurons in mouse primary visual cortex (V1) to visual stimuli depend on behavioral states. Specifically, surround suppression is reduced during locomotion. Although locomotion-induced vasoactive intestinal polypeptide positive (VIP) interneuron depolarization can account for the reduction of surround suppression, the functions of VIP cell depolarization are not fully understood. Here we utilize a firing rate model and a computational model to elucidate the potential functions of VIP cell depolarization during locomotion. Our analyses suggest 1) that surround suppression sharpens the visual responses in V1 to a stationary scene, 2) that depolarized VIP cells enhance V1 responses to moving objects by reducing self-induced surround suppression and 3) that during locomotion V1 neuron responses to some features of the moving objects can be selectively enhanced. Thus, VIP cells regulate surround suppression to allow pyramidal neurons to optimally encode visual information independent of behavioral state.

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bioRxiv2016

Individual differences in functional connectivity during naturalistic viewing conditions

Naturalistic viewing paradigms such as movies have been shown to reduce participant head motion and improve arousal during fMRI scanning relative to task-free rest, and have been used to study both functional connectivity and task-evoked BOLD-signal changes. These task-evoked changes result in cortical activity that is synchronized across subjects and involves large areas of the cortex, and it is unclear whether individual differences in functional connectivity are enhanced or diminished under such naturalistic conditions. This work first aims to characterize variability in functional connectivity (FC) across two distinct movie conditions and eyes-open rest (n=34 healthy adults, 2 scan sessions each). At the whole-brain level, we found that movies have higher intra- and inter-subject correlations in cluster-wise FC relative to rest. The anatomical distribution of inter-subject variability was similar across conditions, with higher variability occurring at the lateral prefrontal lobes and temporoparietal junctions. Second, we used an unsupervised test-retest matching (or \"finger-printin\") algorithm that identifies individual subjects from within a group based on functional connectivity patterns, quantifying the accuracy of the algorithm across the three conditions. We also evaluated the impact of parcellation resolution, scan duration, and number of edges on observed inter-individual differences. The movies and resting state all enabled identification of individual subjects based on FC matrices, with accuracies between 62 and 100%. Overall, pairings involving movies outperformed rest, and the more social and faster-paced movie attained 100% accuracy. When the parcellation resolution, scan duration and number of edges used were increased, accuracies improved across conditions, and the pattern of movies>rest was preserved. These results suggest that using dynamic stimuli such as movies enhances the detection of FC patterns that are distinct at the individual level.\n\nHighlightsO_LIIntra- and inter-subject FC correlations are compared across rest and movies.\nC_LIO_LIMovies outperformed rest in an unsupervised identification algorithm based on FC.\nC_LIO_LIMovies outperform rest regardless of parcellation, scan length, or number of edges.\nC_LIO_LIWatching movies enhances the detection of individual differences in FC.\nC_LI

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bioRxiv2016

Sleep regulation of the distribution of cortical firing rates

Sleep is thought to mediate mnemonic and homeostatic functions. However, the mechanism by which this brain state can implement both the \"selective\" plasticity needed to consolidate novel memory traces as well as the \"general\" plasticity necessary to maintain a well-functioning neuronal system is unclear. Recent findings show that both of these functions differentially affect neurons based on their intrinsic firing rate, a ubiquitous neuronal heterogeneity. Furthermore, they are both implemented by the NREM slow oscillation, which also distinguishes neurons based on firing rate during sequential activity at the DOWN->UP transition. These findings suggest a mechanism by which spiking activity during the slow oscillation acts to maintain network statistics that promote a skewed distribution of neuronal firing rates, and \"perturbation\" of that activity by hippocampal replay acts to integrate new memory traces into the existing cortical network.

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bioRxiv2016

A modification-specific peptide-based immunization approach using CRM197 carrier protein: Development of a selective vaccine against pyroglutamate Aβ peptides

Strategies aimed at reducing cerebral accumulation of the amyloid-{beta} (A{beta}) peptides have therapeutic potential in Alzheimers disease (AD). A{beta} immunization has proven to be effective at promoting A{beta} clearance in animal models but adverse effects have hampered its clinical evaluation. The first anti-A{beta} immunization clinical trial, which assessed a full-length A{beta}1-42 vaccine, increased the risk of encephalitis most likely because of autoimmune pro-inflammatory T helper 1 (Th1) response against all forms of A{beta}. Immunization against less abundant but potentially more pathologically relevant A{beta} products, such as N-terminally-truncated pyroglutamate-3 A{beta} (A{beta}pE3), could provide efficacy and improve tolerability in A{beta} immunotherapy. Here, we describe a selective vaccine against A{beta}pE3 using the diphtheria toxin mutant CRM197 as carrier protein for epitope presentation. CRM197 is currently used in licensed vaccines and has demonstrated excellent immunogenicity and safety in humans. In mice, our A{beta}pE3:CRM197 vaccine triggered the production of specific anti-A{beta}pE3 antibodies that did not cross-react with A{beta}1-42, non-cyclized A{beta}E3, or N-terminally-truncated pyroglutamate-11 A{beta} (A{beta}pE11). A{beta}pE3:CRM197 antiserum strongly labeled A{beta}pE3 in insoluble protein extracts and decorated cortical amyloid plaques in human AD brains. Anti-A{beta}pE3 antibodies were almost exclusively of the IgG1 isotype, suggesting an anti-inflammatory Th2 response bias to the A{beta}pE3:CRM197 vaccine. To the best of our knowledge, this study shows for the first time that CRM197 has potential as a safe and suitable vaccine carrier for active and selective immunization against specific protein sequence modifications or conformations, such as A{beta}pE3.

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bioRxiv2016

Ventral tegmental area neurons use an ensemble code for representing information about ongoing actions

Multiple and unpredictable numbers of actions are often required to achieve a goal. In order to organize behavior and allocate effort so that optimal behavioral policies can be selected, it is necessary to continually monitor ongoing actions. Real-time processing of information related to actions and outcomes is typically assigned to the prefrontal cortex and basal ganglia, but also depends on midbrain regions, especially the ventral tegmental area (VTA). We were interested in how individual VTA neurons, as well as networks within the VTA, encode salient events when an unpredictable number of serial actions are required to obtain a reward. We recorded from ensembles of putative dopamine and non-dopamine neurons in the VTA as animals performed multiple cued trials in a recording session where, in each trial, serial actions were randomly rewarded. While averaging population activity did not reveal a response pattern, we observed that different neurons selectively tuned to low, medium, or high numbered actions in a trial. This preferential tuning of putative dopamine and non-dopamine VTA neurons to different subsets of actions in a trial allowed information about binned action number to be decoded from the ensemble activity. At the network level, tuning curve similarity was positively associated with action-evoked noise correlations, suggesting that action number selectivity reflects functional connectivity within these networks. Analysis of phasic responses to cue and reward revealed that the requirement to execute multiple and uncertain numbers of actions weakens both cue-evoked responses and cue-reward response correlation. The functional connectivity and ensemble coding scheme that we observe here may allow VTA neurons to cooperatively provide a real-time account of ongoing behavior. These computations may be critical to cognitive and motivational functions that have long been associated with VTA dopamine neurons.

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