Synchronization dynamics in fractional-order FitzHugh–Nagumo neural networks with time-delayed coupling

Studying the synchronization of neural networks is crucial for understanding brain function and diagnosing neurological disorders. However, most existing research focuses on integer-order systems and overlooks the effects of time-delay coupling. To address this, this paper was devoted to investigating the synchronization behaviors of time-delay coupled fractional-order FitzHugh–Nagumo networks. The sufficient conditions for the synchronization of two coupled neurons were derived using the Lyapunov stability criterion. Furthermore, the synchronization factor was utilized to elucidate the combined effects of coupling strength and time delay, as well as the influence of time delay on fractional-order dynamics. The analysis began with two coupled systems, and the results were then extended to networks with a larger number of nodes. Numerical examples were presented to illustrate the obtained results.

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Publication Details

Journal
AIMS Mathematics
Published
2025-01-01
DOI
https://doi.org/10.3934/math.2025397
Citations
2
Primary Topic
stochastic dynamics and bifurcation
Type
article
Field-Weighted Citation Impact
2.65
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article

Synchronization dynamics in fractional-order FitzHugh–Nagumo neural networks with time-delayed coupling

Zuozhi Liu, Christopher J. Long, Can Ma
2 citations
AIMS Mathematics
stochastic dynamics and bifurcation
2.65
article

Synchronization dynamics in fractional-order FitzHugh–Nagumo neural networks with time-delayed coupling

Zuozhi Liu, Christopher J. Long, Can Ma
article en
2 citations

Abstract

Studying the synchronization of neural networks is crucial for understanding brain function and diagnosing neurological disorders. However, most existing research focuses on integer-order systems and overlooks the effects of time-delay coupling. To address this, this paper was devoted to investigating the synchronization behaviors of time-delay coupled fractional-order FitzHugh–Nagumo networks. The sufficient conditions for the synchronization of two coupled neurons were derived using the Lyapunov stability criterion. Furthermore, the synchronization factor was utilized to elucidate the combined effects of coupling strength and time delay, as well as the influence of time delay on fractional-order dynamics. The analysis began with two coupled systems, and the results were then extended to networks with a larger number of nodes. Numerical examples were presented to illustrate the obtained results.

AIMS MathematicsVol. 10(4)
Guizhou University of Finance and Economics (CN), Northwest University (CN)
Openalex Percentile: Top 11%
stochastic dynamics and bifurcation
2.65
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Synchronization dynamics in fractional-order FitzHugh–Nagumo neural networks with time-delayed coupling — Zuozhi Liu, Christopher J. Long, et al. · AIMS Mathematics (2025) | TGRS Research Map | TGRS