Weak multiplexing in neural networks: Switching between chimera and solitary states

TL;DR

This paper explores how weak multiplexing in neural networks influences complex spatio-temporal patterns, enabling control of neural states and inducing or suppressing chimera and solitary states through inter-layer coupling adjustments.

Contribution

It demonstrates that weak inter-layer coupling can control neural network states and induce or suppress chimera and solitary states without changing individual layer parameters.

Findings

Weak multiplexing induces chimera states with different velocity profiles.

Coupling mismatch can suppress one-headed chimeras and promote synchronization.

Small intra-layer mismatch leads to solitary states across the network.

Abstract

We investigate spatio-temporal patterns occurring in a two-layer multiplex network of oscillatory FitzHugh-Nagumo neurons, where each layer is represented by a nonlocally coupled ring. We show that weak multiplexing, i.e., when the coupling between the layers is smaller than that within the layers, can have a significant impact on the dynamics of the neural network. We develop control strategies based on weak multiplexing and demonstrate how the desired state in one layer can be achieved without manipulating its parameters, but only by adjusting the other layer. We find that for coupling range mismatch weak multiplexing leads to the appearance of chimera states with different shapes of the mean velocity profile for parameter ranges where they do not exist in isolation. Moreover, we show that introducing a coupling strength mismatch between the layers can suppress chimera states with one incoherent domain (one-headed chimeras) and induce various other regimes such as in-phase synchronization or two-headed chimeras. Interestingly, small intra-layer coupling strength mismatch allows to achieve solitary states throughout the whole network.