High accuracy decoding of dynamical motion from a large retinal population

TL;DR

This study demonstrates that a large retinal ganglion cell population can decode motion with hyperacuity precision using a linear decoder, revealing a redundant neural organization that encodes high-accuracy motion information beyond classical receptive field predictions.

Contribution

It shows that retinal ganglion cells encode motion with high precision through a redundant, sparse firing pattern, challenging traditional receptive field models.

Findings

Motion can be decoded with hyperacuity precision from retinal activity.

Ganglion cells fire sparsely over large areas, not just within receptive fields.

Redundant neural organization enables high-accuracy motion representation.

Abstract

Motion tracking is a challenge the visual system has to solve by reading out the retinal population. 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 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. Instead, we found that ganglion cells fired sparsely over an area much larger than predicted by their receptive fields, so that the neural image did not track the bar. This highly redundant organization allows for diverse collections of ganglion cells to represent high-accuracy motion information in a form easily read out by downstream neural circuits.