Population coding by globally coupled phase oscillators

TL;DR

This paper models neural coding using globally coupled phase oscillators, analyzing how coupling and noise influence information efficiency and revealing transient improvements during relaxation.

Contribution

It introduces a simple oscillator model for neural coding, quantifies information efficiency with Fisher information, and studies transient dynamics post-stimulus.

Findings

Transient increase in coding efficiency after stimulus presentation

Coupling and noise significantly affect information coding

System relaxes to a stationary state with altered efficiency

Abstract

A system of globally coupled phase oscillators subject to an external input is considered as a simple model of neural circuits coding external stimulus. The information coding efficiency of the system in its asynchronous state is quantified using Fisher information. The effect of coupling and noise on the information coding efficiency in the stationary state is analyzed. The relaxation process of the system after the presentation of an external input is also studied. It is found that the information coding efficiency exhibits a large transient increase before the system relaxes to the final stationary state.