Bifurcation delay in a network of nonlocally coupled slow-fast FitzHugh–Nagumo neurons

Premraj Durairaj (), Saravanan Shanmugam, Prasanth Durairaj and Mohamed Rhaima ()
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Premraj Durairaj: Huaqiao University
Saravanan Shanmugam: Chennai Institute of Technology
Prasanth Durairaj: Chennai Institute of Technology
Mohamed Rhaima: King Saud University

The European Physical Journal B: Condensed Matter and Complex Systems, 2024, vol. 97, issue 5, 1-8

Abstract: Abstract Many slow-fast systems can exhibit delayed bifurcation, which means that the crucial transition occurs after some delay during the transition between the oscillatory and steady states due to the presence of a slowly varying parameter. We specifically analyze the dynamical behavior of bifurcation delay in a network of nonlocally coupled FitzHugh–Nagumo neurons by adjusting the frequency of slowly varying currents. Interestingly, we observe an appearance of chimera-like states despite a tiny parameter mismatch in the frequency of any single node. The observed chimera-like state is evidenced through the mean-phase velocity profile. The robustness of the obtained results is then tested by perturbing multiple neurons in three different ways: constant, linearly increasing, and decreasing frequency of certain nodes. Importantly, we discover that the observed chimera state is resilient to all perturbations. Graphical abstract

Date: 2024
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DOI: 10.1140/epjb/s10051-024-00707-2

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