The Dynamics of a Neural Network of Coupled Phase Oscillators with Synaptic Plasticity Controlling a Minimally Cognitive Agent

Abstract

This work explores the neuronal synchronisation and phase information dynamics of an enhanced version of the widely used Kuramoto model of phase interacting oscillators. The framework is applied to a simulated robotic agent engaged in a minimally cognitive benchmark task. The outcomes of this research contribute not only to uncover the role of neuronal synchronisation and phase information in the generation of cognitive behaviours but also to the understanding of oscillatory properties in neural networks.