Predictive information in a sensory population

TL;DR

This paper demonstrates that the earliest visual processing stages, specifically retinal ganglion cells, efficiently encode predictive information about future sensory inputs and their own activity, approaching physical limits and enabling downstream prediction.

Contribution

It reveals that retinal ganglion cells encode near-optimal predictive information, extending the principle of efficient neural representation to early visual processing stages.

Findings

Retinal ganglion cells carry near-maximum predictive information about future inputs.

Groups of cells encode predictive information close to the physical limit set by input statistics.

Downstream neurons can further compress and encode predictive information, showing feature selectivity.

Abstract

Guiding behavior requires the brain to make predictions about future sensory inputs. Here we show that efficient predictive computation starts at the earliest stages of the visual system. We estimate how much information groups of retinal ganglion cells carry about the future state of their visual inputs, and show that every cell we can observe participates in a group of cells for which this predictive information is close to the physical limit set by the statistical structure of the inputs themselves. Groups of cells in the retina also carry information about the future state of their own activity, and we show that this information can be compressed further and encoded by downstream predictor neurons, which then exhibit interesting feature selectivity. Efficient representation of predictive information is a candidate principle that can be applied at each stage of neural computation.