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High Accuracy Decoding of Dynamical Motion from a Large Retinal Population.

Marre O, Botella-Soler V, Simmons KD, Mora T, Tkačik G, Berry MJ - PLoS Comput. Biol. (2015)

Bottom Line: We show that the bar's position can be reconstructed from retinal activity with a precision in the hyperacuity regime using a linear decoder acting on 100+ cells.The classical view would have suggested that the firing rates of the cells form a moving hill of activity tracking the bar's position.As a result, population redundancy was high, and we could find multiple, disjoint subsets of neurons that encoded the trajectory with high precision.

View Article: PubMed Central - PubMed

Affiliation: Department of Molecular Biology and Neuroscience Institute, Princeton University, Princeton, United States of America; Institut de la Vision, INSERM UMRS 968, UPMC UM 80, CNRS UMR 7210, Paris, France.

ABSTRACT
Motion tracking is a challenge the visual system has to solve by reading out the retinal population. It is still unclear how the information from different neurons can be combined together to estimate the position of an object. Here we recorded a large population of ganglion cells in a dense patch of salamander and guinea pig retinas while displaying a bar moving diffusively. We show that the bar's position can be reconstructed from retinal activity with a precision in the hyperacuity regime using a linear decoder acting on 100+ cells. We then took advantage of this unprecedented precision to explore the spatial structure of the retina's population code. The classical view would have suggested that the firing rates of the cells form a moving hill of activity tracking the bar's position. Instead, we found that most ganglion cells in the salamander fired sparsely and idiosyncratically, so that their neural image did not track the bar. Furthermore, ganglion cell activity spanned an area much larger than predicted by their receptive fields, with cells coding for motion far in their surround. As a result, population redundancy was high, and we could find multiple, disjoint subsets of neurons that encoded the trajectory with high precision. This organization allows for diverse collections of ganglion cells to represent high-accuracy motion information in a form easily read out by downstream neural circuits.

No MeSH data available.


Related in: MedlinePlus

Ganglion cell spike trains during random bar motion.A: Position of the bar as a function of time. B: Example of one stimulus frame; motion is perpendicular to the bar (red arrow). Ellipse fitted to the spatial receptive field profile of one representative ganglion cell (pink). C: Spiking activity of 180 cells in the guinea-pig retina in response to a bar moving randomly with the trajectory shown in A. Each line corresponds to one cell, and the points represent spikes. The order of the cells along the y-axis is arbitrary. D: Spiking activity of 123 cells in the salamander retina responding to a bar moving randomly. Same convention as C.
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pcbi.1004304.g001: Ganglion cell spike trains during random bar motion.A: Position of the bar as a function of time. B: Example of one stimulus frame; motion is perpendicular to the bar (red arrow). Ellipse fitted to the spatial receptive field profile of one representative ganglion cell (pink). C: Spiking activity of 180 cells in the guinea-pig retina in response to a bar moving randomly with the trajectory shown in A. Each line corresponds to one cell, and the points represent spikes. The order of the cells along the y-axis is arbitrary. D: Spiking activity of 123 cells in the salamander retina responding to a bar moving randomly. Same convention as C.

Mentions: We used a large multi-electrode array with 252 electrodes to record the responses of ganglion cells in the salamander and guinea pig retinas (see Methods), while presenting a randomly moving bar (Fig 1A, 1B). The density of the electrodes allowed us to record a large fraction (at least 50%) of the ganglion cells in the retina patch covered by the array [14]. The neurons were recorded over a compact region and had highly overlapping receptive fields. Up to 189 cells were recorded simultaneously (see example spike rasters in Fig 1C) over several hours. The stimulus was a dark bar (width = 100 μm) on a grey background moving diffusively over the photoreceptor layer (with a diffusion constant D = 62.5mm2s−1). The trajectory was a random walk with a restoring force to keep the bar close to the array (Fig 1A, and Methods), spanning a region corresponding to roughly 10 degrees of visual angle.


High Accuracy Decoding of Dynamical Motion from a Large Retinal Population.

Marre O, Botella-Soler V, Simmons KD, Mora T, Tkačik G, Berry MJ - PLoS Comput. Biol. (2015)

Ganglion cell spike trains during random bar motion.A: Position of the bar as a function of time. B: Example of one stimulus frame; motion is perpendicular to the bar (red arrow). Ellipse fitted to the spatial receptive field profile of one representative ganglion cell (pink). C: Spiking activity of 180 cells in the guinea-pig retina in response to a bar moving randomly with the trajectory shown in A. Each line corresponds to one cell, and the points represent spikes. The order of the cells along the y-axis is arbitrary. D: Spiking activity of 123 cells in the salamander retina responding to a bar moving randomly. Same convention as C.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4489022&req=5

pcbi.1004304.g001: Ganglion cell spike trains during random bar motion.A: Position of the bar as a function of time. B: Example of one stimulus frame; motion is perpendicular to the bar (red arrow). Ellipse fitted to the spatial receptive field profile of one representative ganglion cell (pink). C: Spiking activity of 180 cells in the guinea-pig retina in response to a bar moving randomly with the trajectory shown in A. Each line corresponds to one cell, and the points represent spikes. The order of the cells along the y-axis is arbitrary. D: Spiking activity of 123 cells in the salamander retina responding to a bar moving randomly. Same convention as C.
Mentions: We used a large multi-electrode array with 252 electrodes to record the responses of ganglion cells in the salamander and guinea pig retinas (see Methods), while presenting a randomly moving bar (Fig 1A, 1B). The density of the electrodes allowed us to record a large fraction (at least 50%) of the ganglion cells in the retina patch covered by the array [14]. The neurons were recorded over a compact region and had highly overlapping receptive fields. Up to 189 cells were recorded simultaneously (see example spike rasters in Fig 1C) over several hours. The stimulus was a dark bar (width = 100 μm) on a grey background moving diffusively over the photoreceptor layer (with a diffusion constant D = 62.5mm2s−1). The trajectory was a random walk with a restoring force to keep the bar close to the array (Fig 1A, and Methods), spanning a region corresponding to roughly 10 degrees of visual angle.

Bottom Line: We show that the bar's position can be reconstructed from retinal activity with a precision in the hyperacuity regime using a linear decoder acting on 100+ cells.The classical view would have suggested that the firing rates of the cells form a moving hill of activity tracking the bar's position.As a result, population redundancy was high, and we could find multiple, disjoint subsets of neurons that encoded the trajectory with high precision.

View Article: PubMed Central - PubMed

Affiliation: Department of Molecular Biology and Neuroscience Institute, Princeton University, Princeton, United States of America; Institut de la Vision, INSERM UMRS 968, UPMC UM 80, CNRS UMR 7210, Paris, France.

ABSTRACT
Motion tracking is a challenge the visual system has to solve by reading out the retinal population. It is still unclear how the information from different neurons can be combined together to estimate the position of an object. Here we recorded a large population of ganglion cells in a dense patch of salamander and guinea pig retinas while displaying a bar moving diffusively. We show that the bar's position can be reconstructed from retinal activity with a precision in the hyperacuity regime using a linear decoder acting on 100+ cells. We then took advantage of this unprecedented precision to explore the spatial structure of the retina's population code. The classical view would have suggested that the firing rates of the cells form a moving hill of activity tracking the bar's position. Instead, we found that most ganglion cells in the salamander fired sparsely and idiosyncratically, so that their neural image did not track the bar. Furthermore, ganglion cell activity spanned an area much larger than predicted by their receptive fields, with cells coding for motion far in their surround. As a result, population redundancy was high, and we could find multiple, disjoint subsets of neurons that encoded the trajectory with high precision. This organization allows for diverse collections of ganglion cells to represent high-accuracy motion information in a form easily read out by downstream neural circuits.

No MeSH data available.


Related in: MedlinePlus