Explores how Lévy noise induces neuron excitation and chaos transitions, suggesting critical underlying dynamics.
The focus of this paper is the transition of a neuron from a quiescence to an excitable state caused by Lévy noise. In this study, the stochastic FitzHugh–Nagumo model is used. The key role of the deterministic transient attractor in noise-induced excitation is revealed. The mechanisms of excitation and the subsequent transition from order to chaos are studied as a function of the Lévy index [Formula: see text] in terms of stochastic [Formula: see text]- and [Formula: see text]-bifurcations.
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Bashkirtseva et al. (2026) studied this question.
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