High Accuracy Decoding of Dynamical Motion from a Large Retinal Population. Author Olivier Marre, Vicente Botella-Soler, Kristina Simmons, Thierry Mora, Gašper Tkačik, Michael Berry Publication Year 2015 Type Journal Article 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. Keywords Animals, Action Potentials, Models, Neurological, Synaptic Transmission, Photic Stimulation, Nerve Net, Computer Simulation, Urodela, Vision, Ocular, Guinea Pigs, Light, Motion Perception, Retinal Ganglion Cells Journal PLoS Comput Biol Volume 11 Issue 7 Pages e1004304 Date Published 2015 Jul ISSN Number 1553-7358 DOI 10.1371/journal.pcbi.1004304 Alternate Journal PLoS Comput Biol PMCID PMC4489022 PMID 26132103 PubMedPubMed CentralGoogle ScholarBibTeXEndNote X3 XML