Fluctuation-response Relation Unifies Dynamical Behaviors in Neural Fields

TL;DR

This paper introduces a unified fluctuation-response relation that connects neural fields' intrinsic dynamics with their ability to track external stimuli, explaining anticipation mechanisms in neural systems.

Contribution

It derives a general fluctuation-response relation based on symmetry principles, unifying diverse neural tracking behaviors under a common theoretical framework.

Findings

Unified prediction of neural tracking behavior

Link between intrinsic dynamics and stimulus response

Theoretical foundation for anticipation in neural fields

Abstract

Anticipation is a strategy used by neural fields to compensate for transmission and processing delays during the tracking of dynamical information, and can be achieved by slow, localized, inhibitory feedback mechanisms such as short-term synaptic depression, spike-frequency adaptation, or inhibitory feedback from other layers. Based on the translational symmetry of the mobile network states, we derive generic fluctuation-response relations, providing unified predictions that link their tracking behaviors in the presence of external stimuli to the intrinsic dynamics of the neural fields in their absence.