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Random versus maximum entropy models of neural population activity

The principle of maximum entropy provides a useful method for inferring statistical mechanics models from observations in correlated systems, and is widely used in a variety of fields where accurate data are available. While the assumptions underlying maximum entropy are intuitive and appealing, its adequacy for describing complex empirical data has been little studied in comparison to alternative approaches. Here data from the collective spiking activity of retinal neurons is reanalysed. The accuracy of the maximum entropy distribution constrained by mean firing rates and pairwise correlations is compared to a random ensemble of distributions constrained by the same observables. In general, maximum entropy approximates the true distribution better than the typical or mean distribution from that ensemble. This advantage improves with population size, with groups as small as 8 being almost always better described by maximum entropy. Failure of maximum entropy to outperform random models is found to be associated with strong correlations in the population.

neuroscience

Neurons in the mouse deep superior colliculus encode orientation/direction through suppression and extract selective visual features

The superior colliculus (SC) is an integrative sensorimotor structure that contributes to multiple visiondependent behaviors. It is a laminated structure; the superficial SC layers (sSC) contain cells that respond to visual stimuli, while the deep SC layers (dSC) contain cells that also respond to auditory and somatosensory stimuli. Despite the increasing interest in mice for visual system study, the differences in the visual response properties between the sSC and the dSC are largely unknown. Here we used a large-scale silicon probe recording system to examine the visual response properties of neurons within the SC of head-fixed, awake and behaving mice. We find that both the sSC and dSC cells respond to visual stimuli, but dSC cells have three key differences. (1) The majority of the dSC orientation/direction selective (OS/DS) cells have their firing rate suppressed by drifting sinusoidal gratings (negative OS/DS cells) rather than being stimulated like the sSC cells (positive OS/DS cells). (2) Almost all the dSC cells have complex-cell-like spatial summation nonlinearity, and a significantly smaller fraction of the positive OS/DS cells in the dSC respond to flashing spots than those in the sSC. (3) The dSC cells lack Y-like spatial summation nonlinearity unlike the sSC cells. These results provide the first description of cells that are suppressed by a visual stimulus with a specific orientation or direction, show that neurons in the dSC have properties analogous to cortical complex cells, and show the presence of Y-like nonlinearity in the sSC but their absence in the dSC.\n\nSignificance statementThe superior colliculus receives visual input from the retina in its superficial layers (sSC) and induces eye/head orientating movements and innate defensive responses in its deeper layers (dSC). Despite their importance, very little is known about the visual response properties of dSC neurons. Using highdensity electrode recordings and novel model-based analysis, we find that the dSC contains cells with a novel property; they are suppressed by the orientation or direction of specific stimuli. We also show that dSC cells have properties similar to cortical \"complex\" cells. Conversely, cells with Y-like nonlinear spatial summation properties are located only in the sSC. These findings contribute to our understanding of how the SC processes visual inputs, a critical step in comprehending visually-guided behaviors.\n\nAcknowledgementsThis work was supported by the Brain Research Seed Funding provided by UCSC and from the National Institutes of Health Grant NEI R21EYO26758 to D. A. F. and A. M. L. We thank Michael Stryker for training on the electrophysiology experiments and his very helpful comments on the manuscript, Sotiris Masmanidis for providing us with the silicon probes, Forest Martinez-McKinney and Serguei Kachiguin for their technical contributions to the silicon probe system, Jeremiah Tsyporin for taking an image of neural tissues and the training of mice, Jena Yamada, Anahit Hovhannisyan, Corinne Beier, and Sydney Weiser, for their helpful comments on the manuscript.

neuroscience

Variability and stability of large-scale cortical oscillation patterns

Individual differences in brain organization exist at many spatial and temporal scales, contributing to the substantial heterogeneity underlying human thought and behavior. Oscillatory neural activity is crucial for these behaviors, but how such rhythms are expressed across the cortex within and across individuals has not been thoroughly characterized. Combining electroencephalography (EEG) with representational similarity and multivariate classification techniques, we provide a systematic characterization of brain-wide activity across frequency bands and oscillatory features during rest and task performance. Results indicate that oscillatory profiles exhibit sizable group-level correspondences, indicating the presence of common templates of oscillatory organization. At the same time, we observed well-defined subject-specific network profiles that were discernible above and beyond the structure shared across individuals. These individualized patterns were sufficiently stable over time to allow successful classification of individuals several months later. Finally, our findings indicate that the network structure of rhythmic activity varies considerably across distinct oscillatory frequencies and features, suggesting the existence of multiple, parallel information processing streams embedded in distributed electrophysiological activity. Together, these findings affirm the richness of spatiotemporal EEG signals and emphasize the utility of multivariate network analyses for understanding the role of brain oscillations in physiology and behavior.

neuroscience

RL mechanisms of short-term plasticity of auditory cortex

The decision-making process is exposed to modulatory factors, and, according to the expected value (EV) concept the two most influential factors are magnitude of prospective behavioural outcome and probability of receiving this outcome. The discrepancy between received and predicted outcomes is reflected by the reward prediction error (RPE), which is believed to play a crucial role in learning in dynamic environment. Feedback related negativity (FRN), a frontocentral negative component registered in EEG during feedback presentation, has been suggested as a neural signature of RPE. In modern neurobiological models of decision-making the primary sensory input is assumed to be constant over the time and independent of the evaluation of the option associated to it. In this study we investigated whether the electrophysiological changes in auditory cues perception is modulated by the strengths of reinforcement signal, represented in the EEG as FRN.\n\nWe quantified the changes in sensory processing through a classical passive oddball paradigm before and after performance a neuroeconomic monetary incentive delay (MID) task. Outcome magnitude and probability were encoded in the physical characteristics of auditory incentive cues. We evaluated the association between individual biomarkers of reinforcement signal (FRN) and the degree of perceptual learning, reflected by changes in auditory ERP components (mismatch negativity and P3a). We observed a significant correlation of MMN and valence - dFRN, reflecting differential processing of gains and omission of gains. Changes in P3a were correlated to probability - dFRN, including information on salience of the outcome, in addition to its valence.\n\nMID task performance evokes plastic changes associated with more fine-grained discrimination of auditory anticipatory cues and enhanced involuntary attention switch towards these cues. Observed signatures of neuro-plasticity of the auditory cortex may play an important role in learning and decision-making processes through facilitation of perceptual discrimination of valuable external stimuli. Thus, the sensory processing of options and the evaluation of options are not independent as implicitly assumed by the modern neuroeconomics models of decision-making.

neuroscience

The computations underlying human confidence reports are probabilistic, but not Bayesian

Humans can meaningfully report their confidence in a perceptual or cognitive decision. It is widely believed that these reports reflect the Bayesian probability that the decision is correct, but this hypothesis has not been rigorously tested against non-Bayesian alternatives. We use two perceptual categorization tasks in which Bayesian confidence reporting requires subjects to take sensory uncertainty into account in a specific way. We find that subjects do take sensory uncertainty into account when reporting confidence, suggesting that brain areas involved in reporting confidence can access low-level representations of sensory uncertainty. However, behavior is not fully consistent with the Bayesian hypothesis and is better described by simple heuristic models. Both conclusions are robust to changes in the uncertainty manipulation, task, response modality, model comparison metric, and additional flexibility in the Bayesian model. Our results suggest that adhering to a rational account of confidence behavior may require incorporating implementational constraints.

neuroscience

MicroRNA exocytosis by large dense-core vesicle fusion

Neurotransmitters and peptide hormones are secreted into outside the cell by a vesicle fusion process. Although non-coding RNA (ncRNA) that include microRNA (miRNA) regulates gene expression inside the cell where they are transcribed, extracellular miRNA has been recently discovered outside the cells, proposing that miRNA might be released to participate in cell-to-cell communication. Despite its importance of extracellular miRNA, the molecular mechanisms by which miRNA can be stored in vesicles and released by vesicle fusion remain enigmatic. Using next-generation sequencing, vesicle purification techniques, and synthetic neurotransmission, we observe that large dense-core vesicles (LDCVs) contain a variety of miRNAs including miR-375. Furthermore, miRNA exocytosis is mediated by the SNARE complex and accelerated by Ca2+. Our results suggest that miRNA can be a novel neuromodulator that can be stored in vesicles and released by vesicle fusion together with classical neurotransmitters.\n\nOne Sentence SummaryUsing next-generation sequencing (NGS) for microRNA (miRNA) and synthetic neurotransmission, we observed that large dense-core vesicles (LDCVs) contain a variety of miRNA together with classical neurotransmitters, and that miRNA can be released by vesicle fusion mediated by SNARE.

neuroscience

Fractone bulbs derive from ependymal cells and their laminin composition affects cell proliferation in the subventricular zone

Fractones are extracellular matrix structures in the neural stem cell niche of the subventricular zone (SVZ), where they appear as round deposits named bulbs or thin branching lines called stems. Their cellular origin and what determines their localization at this site is poorly studied and it remains unclear whether they influence neural stem and progenitor cells formation, proliferation and/or maintenance. To address these questions, we analyzed whole mount preparations of the lateral ventricle by confocal microscopy using different extracellular matrix and cell markers. We found that bulbs are rarely connected to stems and that they contain laminin 5 and 2 chains, respectively. Fractone bulbs were profusely distributed throughout the SVZ and appeared associated with the center of pinwheels, a critical site for adult neurogenesis. We demonstrate that bulbs appear at the apical membrane of ependymal cells at the end of the first week after birth. The use of transgenic mice lacking laminin 5 gene expression (Lama5) in endothelium and in FoxJ1-expressing ependymal cells, revealed ependymal cells as the source of laminin 5-containing fractone bulbs. Loss of laminin 5 from bulbs correlated with a 60% increase in cell proliferation, as determined by PH3 staining, and with a selective reduction in the number of quiescent neural stem cells in the SVZ. These results indicate that fractones are a key component of the SVZ and suggest that laminin 5 modulates the physiology of the neural stem cell niche.\n\nSignificance StatementOur work unveils key aspects of fractones, extracellular matrix structures present in the SVZ that still lack a comprehensive characterization. We show that fractones extensively interact with neural stem cells, whereas some of them are located precisely at pinwheel centers, which are hotspots for adult neurogenesis. Our results also demonstrate that fractones increase in size during aging and that their interactions with NSPCs become more complex in old mice. Lastly, we show that fractone bulbs are produced by ependymal cells and that their laminin content regulates neural stem cells.

neuroscience

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)

neuroscience

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.

neuroscience

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.

neuroscience

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.

neuroscience

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.

neuroscience

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.

neuroscience

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.

neuroscience

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.

neuroscience

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.

neuroscience

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.

neuroscience

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.

neuroscience