Chimera states in pulse coupled neural networks: the influence of dilution and noise

TL;DR

This paper investigates various dynamical states, including chimeras and chaos, in pulse-coupled neural networks, and examines how dilution and noise influence their stability and emergence.

Contribution

It introduces the analysis of broken symmetry chimera states in pulse-coupled neurons and explores their robustness under disorder and noise, revealing constructive effects.

Findings

Broken symmetry chimera states persist with high dilution and noise.

Disorder can induce chimera-like states in symmetric chaotic regimes.

Chimera states are robust up to 80% link removal and 8% noise.

Abstract

We analyse the possible dynamical states emerging for two symmetrically pulse coupled populations of leaky integrate-and-fire neurons. In particular, we observe broken symmetry states in this set-up: namely, breathing chimeras, where one population is fully synchronized and the other is in a state of partial synchronization (PS) as well as generalized chimera states, where both populations are in PS, but with different levels of synchronization. Symmetric macroscopic states are also present, ranging from quasi-periodic motions, to collective chaos, from splay states to population anti-phase partial synchronization. We then investigate the influence disorder, random link removal or noise, on the dynamics of collective solutions in this model. As a result, we observe that broken symmetry chimera-like states, with both populations partially synchronized, persist up to 80 \% of broken links and up to noise amplitudes 8 \% of threshold-reset distance. Furthermore, the introduction of disorder on symmetric chaotic state has a constructive effect, namely to induce the emergence of chimera-like states at intermediate dilution or noise level.