Stability of Localized Patterns in Neural Fields

TL;DR

This paper analyzes the stability of localized patterns in two-dimensional neural fields, deriving conditions for stability, exploring their behavior beyond destabilization, and demonstrating the emergence of non-circular solutions and tessellations.

Contribution

It extends the understanding of neural field stability from one-dimensional to two-dimensional cases, introducing a modified model that guarantees stationary states and reveals new solution types.

Findings

Derived stability conditions for localized solutions

Modified the neural field model to ensure stationary states

Found that destabilization leads to periodic tessellations

Abstract

We investigate two-dimensional neural fields as a model of the dynamics of macroscopic activations in a cortex-like neural system. While the one-dimensional case has been treated comprehensively by Amari 30 years ago, two-dimensional neural fields are much less understood. We derive conditions for the stability for the main classes of localized solutions of the neural field equation and study their behavior beyond parameter-controlled destabilization. We show that a slight modification of original model yields an equation whose stationary states are guaranteed to satisfy the original problem and numerically demonstrate that it admits localized non-circular solutions. Generically, however, only periodic spatial tessellations emerge upon destabilization of rotationally-invariant solutions.