Control of coherence resonance in multiplex neural networks

Maria Masoliver, Cristina Masoller and Anna Zakharova

Chaos, Solitons & Fractals, 2021, vol. 145, issue C

Abstract: We study the dynamics of two neuronal populations weakly and mutually coupled in a multiplexed ring configuration. We simulate the neuronal activity with the stochastic FitzHugh–Nagumo (FHN) model. The two neuronal populations perceive different levels of noise: one population exhibits spiking activity induced by supra-threshold noise (layer 1), while the other population is silent in the absence of inter-layer coupling because its own level of noise is sub-threshold (layer 2). We find that, for appropriate levels of noise in layer 1, weak inter-layer coupling can induce coherence resonance (CR), anti-coherence resonance (ACR) and inverse stochastic resonance (ISR) in layer 2. We also find that a small number of randomly distributed inter-layer links is sufficient to induce these phenomena in layer 2. Our results hold for small and large neuronal populations.

Keywords: Synchronization; Multiplex network; Coherence resonance; FitzHugh–Nagumo neuron (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:145:y:2021:i:c:s0960077921000199

DOI: 10.1016/j.chaos.2021.110666

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