Retinal processing: insights from mathematical modelling

TL;DR

This paper uses mathematical models to explore how retinal neurons process visual information, focusing on the influence of amacrine cell connectivity and stimulus correlations on ganglion cell responses and their implications for cortical processing.

Contribution

It introduces a mathematically tractable layered retina model incorporating amacrine cell connectivity and linear response theory to analyze retinal spike responses and correlations.

Findings

Retinal ganglion cell receptive fields can be computed from the model.

Amacrine cell networks influence spike train correlations.

Spatio-temporal stimulus correlations affect retinal output responses.

Abstract

The retina is the entrance of the visual system. Although based on common biophysical principles the dynamics of retinal neurons is quite different from their cortical counterparts, raising interesting problems for modellers. In this paper I address some mathematically stated questions in this spirit, discussing, in particular: (1) How could lateral amacrine cell connectivity shape the spatio-temporal spike response of retinal ganglion cells ? (2) How could spatio-temporal stimuli correlations and retinal network dynamics shape the spike train correlations at the output of the retina ? These questions are addressed, first, introducing a mathematically tractable model of the layered retina, integrating amacrine cells lateral connectivity and piecewise linear rectification, allowing to compute the retinal ganglion cells receptive field together with the voltage and spike correlations of retinal ganglion cells resulting from the amacrine cells networks. Then, I review some recent results showing how the concept of spatio-temporal Gibbs distributions and linear response theory can be used to characterize the collective spike response to a spatio-temporal stimulus of a set of retinal ganglion cells, coupled via effective interactions corresponding to the amacrine cells network. On these bases, I briefly discuss several potential consequences of these results at the cortical level.