Chimera-like state in ensemble of bistable neurons

A. Andreev, N. Frolov, Natalija A. Alexandrova, Marija A. Chaban
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Abstract

We investigate the nonlinear dynamics of a neural network. As a model of a neuron, we use Hodgkin-Huxley mathematical model. We choose the neuron’s parameters corresponding to a bistable region in which both fixed point and limit cycle are coexisting. We discover that depending on external current and coupling strength we can achieve a chimera-like state when one part of the neurons is in the resting state, while the other one is in the oscillatory regime in a certain area of coupling strength and external current amplitude.
双稳态神经元集合中的嵌合体状态
我们研究了神经网络的非线性动力学。作为神经元的模型,我们使用霍奇金-赫胥黎数学模型。选取不动点和极限环共存的双稳区域对应的神经元参数。我们发现,依靠外部电流和耦合强度,我们可以使一部分神经元处于静息状态,而另一部分神经元在一定的耦合强度和外部电流幅值区域内处于振荡状态。
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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