Solitary states in multiplex neural networks: Onset and vulnerability

Leonhard Schülen, David A. Janzen, Everton S. Medeiros and Anna Zakharova

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

Abstract: We investigate solitary states in a two-layer multiplex network of FitzHugh-Nagumo neurons in the oscillatory regime. We demonstrate how solitary states can be induced in a multiplex network consisting of two non-identical layers. More specifically, we show that these patterns can be introduced via weak multiplexing into a network that is fully synchronized in isolation. We show that this result is robust under variations of the inter-layer coupling strength and largely independent of the choice of initial conditions. Moreover, we study the vulnerability of solitary states with respect to changes in the inter-layer topology. In more detail, we remove links that connect two solitary nodes of each layer and evaluate the resulting pattern. We find a highly non-trivial dependence of the survivability of the solitary states on topological (position in the network) and dynamical (phase of the oscillation) characteristics.

Keywords: Solitary states; Multiplex networks; FitzHugh-Nagumo model; Synchronization; Phase sensitivity (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:145:y:2021:i:c:s0960077921000230

DOI: 10.1016/j.chaos.2021.110670

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