Competitive oscillatory dynamics in excitable neuron networks.

IF 3
Frontiers in network physiology Pub Date : 2025-09-05 eCollection Date: 2025-01-01 DOI:10.3389/fnetp.2025.1613288
Zhigang Zheng, Lin Yan, Tao Li, Jiajing Liu, Lei Wang, Yu Qian
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引用次数: 0

Abstract

Collective dynamics of networks of excitable neurons can be considered as the emergence of ordering from microscopic self-organization at the macroscopic scale. Sustained oscillation can emerge on networks of neurons even if a single neuron is dynamical excitable and non-oscillatory. Fundamental ingredients of networks such as loops, trees, and hubs, play distinct roles in supporting, propagating and impeding sustained oscillations. In this paper, we explore the mechanism of collective self-sustained oscillations on neuron networks by analyzing the functions of different topologies in shaping the oscillatory patterns on excitable neuron networks. The Winfree loops are revealed to be responsible for generating collective oscillations as the oscillation core, and other neurons act as the propagating paths. The existence of large numbers of loops in a network indicates potential competitions of the formation of collective oscillatory dynamics. The roles of loop-loop competition in homogeneous networks and loop-hub competition in heterogeneous networks are extensively discussed.

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可兴奋神经元网络的竞争振荡动力学。
可兴奋神经元网络的集体动力学可以被认为是宏观尺度上微观自组织有序的出现。即使单个神经元具有动态可兴奋性和非振荡性,神经元网络也会出现持续振荡。网络的基本成分,如环路、树和枢纽,在支持、传播和阻碍持续振荡方面发挥着不同的作用。本文通过分析不同拓扑结构在可兴奋神经元网络振荡模式形成中的作用,探讨了神经元网络集体自持续振荡的机制。Winfree回路作为振荡核心负责产生集体振荡,其他神经元作为传播路径。网络中大量环路的存在表明了集体振荡动力学形成的潜在竞争。广泛讨论了同质网络中的环环竞争和异质网络中的环-枢纽竞争的作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
2.70
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0.00%
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