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

TitleHigh Accuracy Decoding of Dynamical Motion from a Large Retinal Population.
Publication TypeJournal Article
Year of Publication2015
AuthorsMarre, O, Botella-Soler, V, Simmons, KD, Mora, T, Tkačik, G, Berry, MJ
JournalPLoS Comput Biol
Volume11
Issue7
Paginatione1004304
Date Published2015 Jul
ISSN1553-7358
KeywordsAction Potentials, Animals, Computer Simulation, Guinea Pigs, Light, Models, Neurological, Motion Perception, Nerve Net, Photic Stimulation, Retinal Ganglion Cells, Synaptic Transmission, Urodela, Vision, Ocular
Abstract

<p>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.</p>

DOI10.1371/journal.pcbi.1004304
Alternate JournalPLoS Comput. Biol.
PubMed ID26132103
PubMed Central IDPMC4489022
Grant ListEY 014196 / EY / NEI NIH HHS / United States
EY 017934 / EY / NEI NIH HHS / United States