# Scaling of sensory information in large neural populations shows signatures of information-limiting correlations

## TL;DR

This study shows that sensory information in the mouse visual cortex is redundantly encoded by large neuron populations, with most information captured by smaller subpopulations.

## Contribution

The paper introduces a novel method to decompose noise correlations into information-limiting and nonlimiting components to predict information scaling in large neural populations.

## Key findings

- Sensory information scales sublinearly with the number of neurons due to correlated noise.
- Tens of thousands of neurons encode 95% of the information about visual stimulus direction.
- The neural code is widely distributed but redundant, allowing recovery of most information from smaller subpopulations.

## Abstract

How is information distributed across large neuronal populations within a given brain area? Information may be distributed roughly evenly across neuronal populations, so that total information scales linearly with the number of recorded neurons. Alternatively, the neural code might be highly redundant, meaning that total information saturates. Here we investigate how sensory information about the direction of a moving visual stimulus is distributed across hundreds of simultaneously recorded neurons in mouse primary visual cortex. We show that information scales sublinearly due to correlated noise in these populations. We compartmentalized noise correlations into information-limiting and nonlimiting components, then extrapolate to predict how information grows with even larger neural populations. We predict that tens of thousands of neurons encode 95% of the information about visual stimulus direction, much less than the number of neurons in primary visual cortex. These findings suggest that the brain uses a widely distributed, but nonetheless redundant code that supports recovering most sensory information from smaller subpopulations.

Information regarding a sensory stimulus is distributed in activity of neuronal populations. Here the authors show stimulus information scales sub-linearly with the number of neurons in mouse visual cortex due to correlated noise and may saturate in far fewer numbers of neurons than the total in V1.