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Research Article | Open Access

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

Canhong Long1Zuozhi Liu1,2( )Can Ma1
School of Mathematics and Statistics, Guizhou University of Finance and Economics, Guiyang, 550025, China
School of Mathematics, Northwest University, Xi'an, 710069, China
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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.

CLC number: 26A33, 34K37

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AIMS Mathematics
Pages 8673-8687

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Cite this article:
Long C, Liu Z, Ma C. Synchronization dynamics in fractional-order FitzHugh–Nagumo neural networks with time-delayed coupling. AIMS Mathematics, 2025, 10(4): 8673-8687. https://doi.org/10.3934/math.2025397

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Received: 22 January 2025
Revised: 02 April 2025
Accepted: 03 April 2025
Published: 15 April 2025
©2025 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)