Biology subjects

Zucker, S. W.

Publications and source records attributed to Zucker, S. W..

4 recordsLinked to original sources

bioRxiv2024

Encoding manifolds constructed from grating responses organize responses to natural scenes in cortical visual areas

A challenge in sensory neuroscience is understanding how populations of neurons operate in concert to represent diverse stimuli. To meet this challenge, we have created ``encoding manifolds'' that reveal the overall responses of brain areas to diverse stimuli and organize individual neurons in stimulus-response coordinates according to their selectivity and response dynamics. Here we use encoding manifolds to compare the population-level encoding of primary visual cortex (VISp) with that of five higher visual areas (VISam, VISal, VISpm, VISlm, and VISrl), using data from the Allen Institute Visual Coding-Neuropixels dataset from the mouse. We show that the topology of the encoding manifold for VISp and for higher visual areas is continuous, with smooth coordinates along which stimulus selectivity and response dynamics are organized with layer and cell-type specificity. Surprisingly, the manifolds revealed novel relationships between how natural scenes are encoded relative to static gratings--a relationship conserved across visual areas. Namely, neurons preferring natural scenes preferred either low or high spatial frequency gratings, but not intermediate ones. Analyzing responses by cortical layer reveals a preference for gratings concentrated in layer 6, whereas preferences for natural scenes tended to be higher in layers 2/3 and 4. The results demonstrate how machine learning approaches can be used to organize and visualize the structure of sensory coding, thereby revealing novel relationships within and across brain areas and sensory stimuli.

neuroscience↗

bioRxiv2023

Population encoding of stimulus features along the visual hierarchy

The retina and primary visual cortex (V1) both exhibit diverse neural populations sensitive to diverse visual features. Yet it remains unclear how neural populations in each area partition stimulus space to span these features. One possibility is that neural populations are organized into discrete groups of neurons, with each group signaling a particular constellation of features. Alternatively, neurons could be continuously distributed across feature-encoding space. To distinguish these possibilities, we presented a battery of visual stimuli to mouse retina and V1 while measuring neural responses with multi-electrode arrays. Using machine learning approaches, we developed a manifold embedding technique that captures how neural populations partition feature space and how visual responses correlate with physiological and anatomical properties of individual neurons. We show that retinal populations discretely encode features, while V1 populations provide a more continuous representation. Applying the same analysis approach to convolutional neural networks that model visual processing, we demonstrate that they partition features much more similarly to the retina, indicating they are more like big retinas than little brains.

neuroscience↗

bioRxiv2018

Flow stimuli reveal ecologically-appropriate responses in mouse visual cortex

Assessments of the mouse visual system based on spatial frequency analysis imply that its visual capacity is low, with few neurons responding to spatial frequencies greater than 0.5 cycles/degree. However, visually-mediated behaviors, such as prey capture, suggest that the mouse visual system is more precise. We introduce a new stimulus class--visual flow patterns--that is more like what the mouse would encounter in the natural world than are sine-wave gratings but is more tractable for analysis than are natural images. We used 128-site silicon microelectrodes to measure the simultaneous responses of single neurons in the primary visual cortex (V1) of alert mice. While holding temporal-frequency content fixed, we explored a class of drifting patterns of black or white dots that have energy only at higher spatial frequencies. These flow stimuli evoke strong visually-mediated responses well beyond those predicted by spatial frequency analysis. Flow responses predominate in higher spatial-frequency ranges (0.15-1.6 cycles/degree); many are orientation- or direction-selective; and flow responses of many neurons depend strongly on sign of contrast. Many cells exhibit distributed responses across our stimulus ensemble. Together, these results challenge conventional linear approaches to visual processing and expand our understanding of the mouses visual capacity to behaviorally-relevant ranges.\n\nSignificance StatementThe visual system of the mouse is now widely studied as a model for development and disease in humans. Studies of its primary visual cortex (V1) using conventional grating stimuli to construct linear-nonlinear receptive fields suggest that the mouse must have very poor vision. Using novel stimuli resembling the flow of images across the retina as the mouse moves through the grass, we find that most V1 neurons respond reliably to very much finer details of the visual scene than previously believed. Our findings suggest that the conventional notion of a unique receptive field does not capture the operation of the neural network in mouse V1.

neuroscience↗

bioRxiv2018

Spatial Self-Organization Resolves Conflicts Between Individuality and Collective Migration

Collective behavior can spontaneously emerge when individuals follow common rules of interaction. However, the behavior of each individual will differ due to existing genetic and non-genetic variation within the population. It remains unclear how this individuality is managed to achieve collective behavior. We quantified individuality in bands of clonal Escherichia coli cells that migrate collectively along a channel by following a self-generated gradient of attractant. We discovered that despite substantial differences in individual chemotactic abilities, the cells are able to migrate as a coherent group by spontaneously sorting themselves within the moving band. This sorting mechanism ensures that differences between individual chemotactic abilities are compensated by differences in the local steepness of the traveling gradient each individual must navigate, and determines the minimum performance required to travel with the band. By resolving conflicts between individuality and collective migration, this mechanism enables populations to maintain advantageous diversity while on the move.

biophysics↗