Biology subjects

Jun, N. Y.

Publications and source records attributed to Jun, N. Y..

6 recordsLinked to original sources

bioRxiv2023

Multiple objects evoke fluctuating responses in several regions of the visual pathway

How neural representations preserve information about multiple stimuli is mysterious. Because tuning of individual neurons is coarse (for example, visual receptive field diameters can exceed perceptual resolution), the populations of neurons potentially responsive to each individual stimulus can overlap, raising the question of how information about each item might be segregated and preserved in the population. We recently reported evidence for a potential solution to this problem: when two stimuli were present, some neurons in the macaque visual cortical areas V1 and V4 exhibited fluctuating firing patterns, as if they responded to only one individual stimulus at a time (Jun et al., 2022). However, whether such an information encoding strategy is ubiquitous in the visual pathway and thus could constitute a general phenomenon remains unknown. Here we provide new evidence that such fluctuating activity is also evoked by multiple stimuli in visual areas responsible for processing visual motion (middle temporal visual area, MT), and faces (middle fundus and anterolateral face patches in inferotemporal cortex - areas MF and AL), thus extending the scope of circumstances in which fluctuating activity is observed. Furthermore, consistent with our previous results in the early visual area V1, MT exhibits fluctuations between the representations of two stimuli when these form distinguishable objects but not when they fuse into one perceived object, suggesting that fluctuating activity patterns may underlie visual object formation. Taken together, these findings point toward an updated model of how the brain preserves sensory information about multiple stimuli for subsequent processing and behavioral action. Impact StatementNeural fluctuations in multiple areas along the visual cortical hierarchy could allow the brain to represent distinct co-occurring visual stimuli.

neuroscience↗

bioRxiv2022

Efficient coding, channel capacity and the emergence of retinal mosaics

Among the most striking features of retinal organization is the grouping of its output neurons, the retinal ganglion cells (RGCs), into a diversity of functional types. Each of these types exhibits a mosaic-like organization of receptive fields (RFs) that tiles the retina and visual space. Previous work has shown that many features of RGC organization, including the existence of ON and OFF cell types, the structure of spatial RFs, and their relative arrangement, can be predicted on the basis of efficient coding theory. This theory posits that the nervous system is organized to maximize information in its encoding of stimuli while minimizing metabolic costs. Here, we use efficient coding theory to present a comprehensive account of mosaic organization in the case of natural videos as the retinal channel capacity--the number of simulated RGCs available for encoding--is varied. We show that mosaic density increases with channel capacity up to a series of critical points at which, surprisingly, new cell types emerge. Each successive cell type focuses on increasingly high temporal frequencies and integrates signals over large spatial areas. In addition, we show theoretically and in simulation that a transition from mosaic alignment to anti-alignment across pairs of cell types is observed with increasing output noise and decreasing input noise. Together, these results offer a unified perspective on the relationship between retinal mosaics, efficient coding, and channel capacity that can help to explain the stunning functional diversity of retinal cell types.

neuroscience↗

bioRxiv2021

The optimal spatial arrangement of ON and OFF receptive fields

Many sensory systems utilize parallel ON and OFF pathways that signal stimulus increments and decrements, respectively. These pathways consist of ensembles or grids of ON and OFF detectors spanning sensory space. Yet encoding by opponent pathways raises a question: How should grids of ON and OFF detectors be arranged to optimally encode natural stimuli? We investigated this question using a model of the retina guided by efficient coding theory. Specifically, we optimized spatial receptive fields and contrast response functions to encode natural images given noise and constrained firing rates. We find that the optimal arrangement of ON and OFF receptive fields exhibits a transition between aligned and anti-aligned grids. The preferred phase depends on detector noise and the statistical structure of the natural stimuli. These results reveal that noise and stimulus statistics produce qualitative shifts in neural coding strategies and provide novel theoretical predictions for the configuration of opponent pathways in the nervous system. Significance StatementAcross a wide variety of species, cells in the retina specialized for signaling either increases (ON) or decreases (OFF) in light represent one of the most basic building blocks of visual computation. These cells coordinate to form mosaics, with each cell responsible for a small, minimally-overlapping portion of visual space, but the ways in which these mosaics could be spatially coordinated with each other are relatively unknown. Here, we show how efficient coding theory, which hypothesizes that the nervous system minimizes the amount of redundant information it encodes, can predict the relative spatial arrangement of ON and OFF mosaics. The most information-efficient arrangements are determined both by levels of noise in the system and the statistics of natural images.

neuroscience↗

bioRxiv2020

Connectomic analysis reveals an interneuron with an integral role in the retinal circuit for night vision

The mammalian rod bipolar (RB) cell pathway is perhaps the best-studied circuit in the vertebrate retina. Its synaptic interactions with other retinal circuits, however, remain unresolved. Here, we combined anatomical and physiological analyses of the mouse retina to discover that the majority of synaptic inhibition to the AII amacrine cell (AC), the central neuron in the RB pathway, is provided by a single interneuron type: a multistratified, axon-bearing GABAergic AC, with dendrites in both ON and OFF synaptic layers, but with a pure ON (depolarizing) response to light. We used the nNOS-CreER mouse retina to confirm the identity of this interneuron as the wide-field NOS-1 AC. Our study demonstrates generally that novel neural circuits can be identified from targeted connectomic analyses and specifically that the NOS-1 AC mediates long-range inhibition during night vision and is a major element of the RB pathway.

neuroscience↗

bioRxiv2019

Patterns of neural correlations in V1 vary with the number of objects

Sensory receptive fields are large enough that they can contain more than one perceptible stimulus. How, then, can the brain encode information about each of the stimuli that may be present at a given moment? We recently showed that when more than one stimulus is present, single neurons can fluctuate between coding one vs. the other(s) across some time period, suggesting a form of neural multiplexing of different stimuli (Caruso et al., 2018). Here we investigate (a) whether such coding fluctuations occur in early visual cortical areas; (b) how coding fluctuations are coordinated across the neural population; and (c) how coordinated coding fluctuations depend on the parsing of stimuli into separate vs. fused objects. We found coding fluctuations do occur in macaque V1 but only when the two stimuli form separate objects. Such separate objects evoked a novel pattern of V1 spike count ("noise") correlations involving distinct distributions of positive and negative values. This bimodal correlation pattern was most pronounced among pairs of neurons showing the strongest evidence for coding fluctuations or multiplexing. Whether a given pair of neurons exhibited positive or negative correlations depended on whether the two neurons both responded better to the same object or had different object preferences. Distinct distributions of spike count correlations based on stimulus preferences were also seen in V4 for separate objects but not when two stimuli fused to form one object. These findings suggest multiple objects evoke different response dynamics than those evoked by single stimuli, lending support to the multiplexing hypothesis and suggesting a means by which information about multiple objects can be preserved despite the apparent coarseness of sensory coding. Significance StatementHow the brain separates information about multiple objects despite overlap in the neurons responsive to each item is not well understood. Here we show that some neurons in V1 exhibit coding fluctuations in response to two objects, and that these coding fluctuations are coordinated at the population level in ways that are not observed for single objects. Broadly similar results were obtained in V4. These response dynamics lend support to the hypothesis that information about individual objects may be multiplexed across the neural population, preserving information about each item despite the coarseness of sensory coding.

neuroscience↗

bioRxiv2018

Channelrhodopsin variants engage distinct patterns of network activity

Channelrhodopsins (ChRs) are light-gated ion channels that enable cell type-specific activation of neurons or neural circuits. Channelrhodopsin-2 has been widely used as a tool to probe circuit function in vitro and in vivo. Several recently developed ChR variants are characterized by faster kinetics and reduced desensitization. However, little is known about how their varying properties may regulate their interaction with local network dynamics. We compared ChR-evoked patterns of multi-unit activity and local field potentials in primary visual cortex of mice expressing three ChR variants with distinct temporal profiles: Chronos, Chrimson, and ChR2. We assessed overall activation of by measuring the amplitude and temporal progression of evoked spiking. Using gamma-range (30-80Hz) LFP power as an assay for local network engagement, we examined the recruitment of cortical network activity by each tool. All ChR variants caused light-evoked increases in firing in vivo, but each demonstrated different temporal patterning of evoked activity. In addition, the three ChRs had distinct effects on cortical gamma-band activity. Our findings suggest that variations in the kinetics of optogenetic tools can substantially affect their efficacy in neural networks in vivo, as well as the manner in which their activation engages circuit resonance.

neuroscience↗