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Research Article | Open Access

The pattern dynamics of interneuronal networks with inhibitory synaptic coupling

Ying XuXiaodi Li( )
School of Mathematics and Statistics, Shandong Normal University, Ji'nan, 250014, China
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Abstract

Interneurons modulate the excitability of neural networks and maintain neural activity balance via inhibitory or excitatory synaptic connections. Here, we studied the formation of patterns of interneuronal networks with inhibitory synaptic coupling. We found that both electrical synaptic coupling and inhibitory synaptic coupling play a crucial role in the formation of neural network patterns. In addition, delayed inhibitory synapses can also affect the transition of target waves to chaotic states. As the strength of electrical synaptic coupling increases, the firing behavior of neurons gradually becomes highly ordered. When the inhibitory synaptic delay reaches a critical value, we observe a transition in oscillatory patterns from an ordered state to a synchronized state. We further investigated how inhibitory synaptic conductance influences the formation of oscillatory patterns in the network. The study reveals that increasing synaptic conductance disrupts the structure of target waves, inducing chaotic states such as spiral wave fragmentation, while simultaneously elevating neuronal firing rates.

CLC number: 62M10, 92C15

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AIMS Mathematics
Pages 10976-10993

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Cite this article:
Xu Y, Li X. The pattern dynamics of interneuronal networks with inhibitory synaptic coupling. AIMS Mathematics, 2025, 10(5): 10976-10993. https://doi.org/10.3934/math.2025498

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Received: 27 March 2025
Revised: 26 April 2025
Accepted: 30 April 2025
Published: 15 May 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)