JOURNAL ARTICLE

Energy-induced chimera-like states in bilayer memristive FitzHugh–Nagumo neural networks

Ying XieXuening LiXueqin WangZhiqiu YeLijian YangYa Jia

Year: 2025 Journal:   Chaos An Interdisciplinary Journal of Nonlinear Science Vol: 35 (9)   Publisher: American Institute of Physics

Abstract

Despite extensive efforts to analyze synchronization and chimera states, it is limited to understand their emergence from an energy-based perspective in multilayer network synchronization. In this study, the bilayer FitzHugh–Nagumo neural network is constructed and the heterogeneity is realized by distinct dynamics of periodic and chaotic firing patterns. By analyzing the energy patterns of neurons, it is discovered that the intralayer synchronization is independent of the interlayer coupling in networks. Under specific conditions of intralayer coupling strength and nearest-neighbor connectivity, periodic neurons with a small energy difference give rise to chimera-like states. Meanwhile, chaotic neurons with a large energy difference induce a traveling phase-wave pattern. Furthermore, nonlocal coupling with proper synaptic strength leads to the emergence of a strong chimera-like state, which maintains energy between the energies of synchronized and desynchronized cases. The results uncover an energy-driven mechanism underlying the emergence of complex collective behaviors in multilayer neuronal systems, and it offers potential guidance for designing energy-efficient neuromorphic circuits.

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Topics

Nonlinear Dynamics and Pattern Formation
Physical Sciences →  Computer Science →  Computer Networks and Communications
stochastic dynamics and bifurcation
Physical Sciences →  Physics and Astronomy →  Statistical and Nonlinear Physics
Neural dynamics and brain function
Life Sciences →  Neuroscience →  Cognitive Neuroscience

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