Biology subjects

Berry, M. J.

Publications and source records attributed to Berry, M. J..

12 recordsLinked to original sources

bioRxiv2025

A Theory of Thalamocortical Loops in Evidence Accumulation and Decision-Making

A prominent property of the neocortex is that it forms reciprocal excitatory loops with the thalamus. Here, we propose a function for the loops between layer 5 pyramidal tract neurons in the cortex and matrix-type relay cells in the thalamus, which is based on known anatomy and biophysics. This pathway forms an amplifier circuit with a gain less than unity in the resting condition. However, descending cortical input to apical tufts of L5 neurons can raise the gain of these neurons, boosting the thalamocortical loop into either an integrating or an amplifying regime. Multiple thalamocortical loops compete via lateral inhibition in the thalamus, resulting in a winner-take-all global dynamic among the motor commands encoded by each loop. When L5 neurons are driven by sensory inputs, the integration regime closely resembles the drift-diffusion model of decision-making. We explore basic relationships among parameters of this model and compare broadly against neurophysiological data.

neuroscience↗

bioRxiv2023

Stimulus invariant aspects of the retinal code drive discriminability of natural scenes

Everything that the brain sees must first be encoded by the retina, which maintains a reliable representation of the visual world in many different, complex natural scenes while also adapting to stimulus changes. This study quantifies whether and how the brain selectively encodes stimulus features about scene identity in complex naturalistic environments. While a wealth of previous work has dug into the static and dynamic features of the population code in retinal ganglion cells, less is known about how populations form both flexible and reliable encoding in natural moving scenes. We record from the larval salamander retina responding to five different natural movies, over many repeats, and use these data to characterize the population code in terms of single-cell fluctuations in rate and pairwise couplings between cells. Decomposing the population code into independent and cell-cell interactions reveals how broad scene structure is encoded in the retinal output. while the single-cell activity adapts to different stimuli, the population structure captured in the sparse, strong couplings is consistent across natural movies as well as synthetic stimuli. We show that these interactions contribute to encoding scene identity. We also demonstrate that this structure likely arises in part from shared bipolar cell input as well as from gap junctions between retinal ganglion cells and amacrine cells.

neuroscience↗

bioRxiv2022

Learning low-dimensional generalizable naturalfeatures from retina using a U-net

Much of sensory neuroscience focuses on presenting stimuli that are chosen by the experimenter because they are parametric and easy to sample and are thought to be behaviorally relevant to the organism. However, it is not generally known what these relevant features are in complex, natural scenes. This work focuses on using the retinal encoding of natural movies to determine the presumably behaviorally-relevant features that the brain represents. It is prohibitive to parameterize a natural movie and its respective retinal encoding fully. We use time within a natural movie as a proxy for the whole suite of features evolving across the scene. We then use a task-agnostic deep architecture, an encoder-decoder, to model the retinal encoding process and characterize its representation of "time in the natural scene" in a compressed latent space. In our end-to-end training, an encoder learns a compressed latent representation from a large population of salamander retinal ganglion cells responding to natural movies, while a decoder samples from this compressed latent space to generate the appropriate future movie frame. By comparing latent representations of retinal activity from three movies, we find that the retina has a generalizable encoding for time in the natural scene: the precise, low-dimensional representation of time learned from one movie can be used to represent time in a different movie, with up to 17 ms resolution. We then show that static textures and velocity features of a natural movie are synergistic. The retina simultaneously encodes both to establishes a generalizable, low-dimensional representation of time in the natural scene.

neuroscience↗

bioRxiv2021

Passive Exposure Sparsifies Neural Activity in the Primary Visual Cortex

A notable feature of neural activity is sparseness - namely, that only a small fraction of neurons in a local circuit have high activity at any moment. Not only is sparse neural activity observed experimentally in most areas of the brain, but sparseness has been proposed as an optimization or design principle for neural circuits. Sparseness can increase the energy efficiency of the neural code as well as allow for beneficial computations to be carried out. But how does the brain achieve sparse-ness? Here, we found that when neurons in the primary visual cortex were passively exposed to a set of images over several days, neural responses became more sparse. Sparsification was driven by a decrease in the response of neurons with low or moderate activity, while highly active neurons retained similar responses. We also observed a net decorrelation of neural activity. These changes sculpt neural activity for greater coding efficiency.

neuroscience↗

bioRxiv2020

The generation of cortical novelty responses through inhibitory plasticity

Animals depend on fast and reliable detection of novel stimuli in their environment. Indeed, neurons in multiple sensory areas respond more strongly to novel in comparison to familiar stimuli. Yet, it remains unclear which circuit, cellular and synaptic mechanisms underlie those responses. Here, we show that inhibitory synaptic plasticity readily generates novelty responses in a recurrent spiking network model. Inhibitory plasticity increases the inhibition onto excitatory neurons tuned to familiar stimuli, while inhibition for novel stimuli remains low, leading to a network novelty response. Generated novelty responses do not depend on the exact temporal structure but rather on the distribution of presented stimuli. By including tuning of inhibitory neurons, the network further captures stimulus-specific adaptation. Finally, we suggest that disinhibition can control the amplification of novelty responses. Therefore, inhibitory plasticity provides a flexible, biologically-plausible mechanism to detect the novelty of bottom-up stimuli, enabling us to make numerous experimentally testable predictions.

neuroscience↗

bioRxiv2020

Salamander retinal ganglion cell responses to rich stimuli

The retinas phenomenological function is often considered to be well-understood: individual retinal ganglion cells are sensitive to a projection of the light stimulus movie onto a classical center-surround linear filter. Recent models elaborating on this basic framework by adding a second linear filter or spike histories, have been quite successful at predicting ganglion cell spikes for spatially uniform random stimuli, and for random stimuli varying spatially with low resolution. Fitting models for stimuli with more finely grained spatial variations becomes difficult because of the very high dimensionality of such stimuli. We present a method of reducing the dimensionality of a fine one dimensional random stimulus by using wavelets, allowing for several clean predictive linear filters to be found for each cell. For salamander retinal ganglion cells, we find in addition to the spike triggered average, 3 identifiable types of linear filters which modulate the firing of most cells. While some cells can be modeled fairly accurately, many cells are poorly captured, even with as many as 4 filters. The new linear filters we find shed some light on the nonlinearities in the retinas integration of temporal and fine spatial information.

neuroscience↗

bioRxiv2019

Alpha herpesvirus egress and spread from neurons uses constitutive secretory mechanisms independent of neuronal firing activity

Alpha herpesviruses naturally infect the peripheral nervous system, and can spread to the central nervous system causing severe deadly or debilitating disease. Because alpha herpesviruses spread along synaptic circuits, and infected neurons exhibit altered electrophysiology and increased spontaneous firing, we hypothesized that alpha herpesviruses use activity-dependent synaptic vesicle-like regulated secretory mechanisms for egress and spread from neurons. To address this hypothesis, we used a compartmentalized primary neuron culture system to measure egress and spread of pseudorabies virus (PRV), pharmacological and optogenetics approaches to modulate neuronal firing activity, and a live-cell fluorescence microscopy assay to directly visualize the exocytosis of individual virus particles from infected neurons. Using tetrodotoxin to silence neuronal activity, we observed no inhibition of virus spread, and using potassium chloride or optogenetics to elevate neuronal activity, we also show no increase in virus spread. Using a live-cell fluorescence microscopy method to directly measure virus egress from infected neurons, we observed no association between virus particle exocytosis and intracellular Ca2+ signaling. Finally, we observed virus particle exocytosis occurs in association with constitutive secretory Rab GTPases, Rab6a and Rab8a, not Rab proteins that are associated with the Ca2+-regulated secretory pathway in neurons, Rab3a and Rab11a. Therefore, we conclude that alpha herpesvirus egress and spread is independent of neuronal activity and Ca2+ signaling because virus particle exocytosis uses constitutive secretory mechanisms in neurons.\n\nAuthor SummaryAlpha herpesviruses, including important human pathogens Herpes Simplex Virus 1 and 2, and Varicella-Zoster Virus, are among the very few viruses that naturally infect the nervous system. These viruses cause recurrent herpetic and zosteriform lesions, peripheral neuropathies, and deadly or debilitating central nervous system diseases. Many of the molecular and cellular mechanisms of viral egress and spread remain unknown, particularly in the context of specialized neuronal cell biology. Our results indicate that elevated firing activity of infected neurons is not functionally or mechanistically linked to virus egress and spread; therefore, therapies targeting peripheral neuropathic symptoms, elevated neuronal activity, and synaptic vesicle secretory mechanisms are unlikely to affect virus spread in the nervous system.

microbiology↗

bioRxiv2019

Knowledge-guided analysis of ‘omics’ data using the KnowEnG cloud platform

We present KnowEnG, a free-to-use computational system for analysis of genomics data sets, designed to accelerate biomedical discovery. It includes tools for popular bioinformatics tasks such as gene prioritization, sample clustering, gene set analysis and expression signature analysis. The system offers knowledge-guided data-mining and machine learning algorithms, where user-provided data are analyzed in light of prior information about genes, aggregated from numerous knowledge-bases and encoded in a massive Knowledge Network. KnowEnG adheres to FAIR principles: its tools are easily portable to diverse computing environments, run on the cloud for scalable and cost-effective execution of compute-intensive and data-intensive algorithms, and are interoperable with other computing platforms. They are made available through multiple access modes including a web-portal, and include specialized visualization modules. We present use cases and re-analysis of published cancer data sets using KnowEnG tools and demonstrate its potential value in democratization of advanced tools for the modern genomics era.

cancer biology↗

bioRxiv2019

A Long Timescale Stimulus History Effect in the Primary Visual Cortex

Responses of neurons in the primary visual cortex (V1) are often understood as encoding the current visual stimulus. Yet, some studies indicate that temporal contingency effects exist in the responses of neurons in early sensory areas. We explored if the recent stimulus history would alter the response of V1 layer 2/3 pyramidal cells in head-fixed awake mice during presentation of sequences of complex images. The activity of individual neurons was sparse, such that either one or none of the images in the sequence typically yielded a strong response. We then substituted an image preceding this primary image in order to determine if responses to the primary image were affected. We found that the amplitude of the neurons response could be significantly altered by substitutions up to five images back from the primary image, even when the substituted image elicited virtually no response by itself. This stimulus history effect was heterogeneous across the population, with some cells showing facilitation and others suppression. For individual cells, the history effect was robust and reproducible across days. Our data show that responses of V1 neurons not only reflect the current stimulus but also encode, through their response amplitude, information about multiple images previously presented as far as 1000 msec in the past. This might enable V1 to retain information about the extended trajectory of past stimuli and perform complex temporal computations that are as of yet not appreciated.

neuroscience↗

bioRxiv2019

Nonlinear transfer and temporal gain control in ON bipolar cells

The separation of visual input into discrete channels begins at the photoreceptor to bipolar cell synapse. Current models of the ON pathway describe the time-varying membrane voltage of ON bipolar cells as a linear function of light fluctuations. While this linearity holds under some visual conditions, stimulating the retina with full-field, high contrast flashes reveals a number of nonlinearities already present in the input current of ON bipolar cells. First, we show that the synaptic input to ON bipolar cells is asymmetric in response to equal flashes of opposite polarity. Next, we show that this asymmetry emerges because the responses to dark flashes increase linearly with contrast, whereas responses to bright flashes are highly rectified. We also describe how the outward current saturates in response to dark flashes of increasing duration. Furthermore, varying the inter-flash interval between a pair of high contrast flashes reveals a rapid, transient form of gain control that modulates both the amplitude and time course of the flash response. We develop a phenomenological model that captures the primary features of the ON bipolar cell response at high contrast. Finally, we discuss the implications of these nonlinearities in our understanding of how retinal circuitry shapes the visual signal.

neuroscience↗

bioRxiv2018

A Biologically Plausible Mechanism to Learn Clusters of Neural Activity

When correlations within a neural population are strong enough, neural activity in early visual areas is organized into a discrete set of clusters. Here, we show that a simple, biologically plausible circuit can learn and then readout in real-time the identity of experimentally measured clusters of retinal ganglion cell population activity. After learning, individual readout neurons develop cluster tuning, meaning that they respond strongly to any neural activity pattern in one cluster and weakly to all other inputs. Different readout neurons specialize for different clusters, and all input clusters can be learned, as long as the number of readout units is mildly larger than the number of input clusters. We argue that this operation can be repeated as signals flow up the cortical hierarchy.

neuroscience↗

bioRxiv2017

Predictive Coding of Novel versus Familiar Stimuli in the Primary Visual Cortex

To explore theories of predictive coding, we presented mice with repeated sequences of images with novel images sparsely substituted. Under these conditions, mice could be rapidly trained to lick in response to a novel image, demonstrating a high level of performance on the first day of testing. Using 2-photon calcium imaging to record from layer 2/3 neurons in the primary visual cortex, we found that novel images evoked excess activity in the majority of neurons. When a new stimulus sequence was repeatedly presented, a majority of neurons had similarly elevated activity for the first few presentations, which then decayed to almost zero activity. The decay time of these transient responses was not fixed, but instead scaled with the length of the stimulus sequence. However, at the same time, we also found a small fraction of the neurons within the population ([~]2%) that continued to respond strongly and periodically to the repeated stimulus. Decoding analysis demonstrated that both the transient and sustained responses encoded information about stimulus identity. We conclude that the layer 2/3 population uses a two-channel predictive code: a dense transient code for novel stimuli and a sparse sustained code for familiar stimuli. These results extend and unify existing theories about the nature of predictive neural codes.

neuroscience↗