动力学,同步和流动的移动波浪模式的流量合网络的查伊神经元
Dianavinnarasi Joseph1, Rakshanaa Kumar2, Anitha Karthikeyan3
1Centre for Nonlinear Systems, Chennai Institute of Technology, Chennai 600069, India.
Bio Systems
|December 30, 2023
概括
这项研究探讨了磁流查伊神经元模型中的神经元同步. 我们发现网络拓显著影响同步模式,揭示了对复杂大脑动态的洞察力.
科学领域:
- 计算神经科学是一种神经科学.
- 复杂系统动力学 复杂系统动力学
- 非线性动力学是一种非线性动力学.
背景情况:
- 神经元电活动同步对于大脑的信息处理至关重要.
- 查伊神经元模型提供了一个计算效率高,但又全面的神经元行为表现.
- 电磁感应效应可以纳入神经元模型,导致诸如磁流神经元之类的现象.
研究的目的:
- 为了研究磁流查伊神经元模型的同步动态.
- 分析网络拓对结合的神经元中的同步模式的影响.
- 探索查伊神经元网络的稳定性和新出现的行为.
主要方法:
- 使用了理论分析和数值模拟.
- 两叉图和利亚普诺夫指数被用来描述单个神经元的动态.
- 主稳定性函数分析和利亚普诺夫理论评估了合网络中的同步稳定性.
主要成果:
- 单一磁流查伊神经元模型表现出复杂的动态和分叉.
- 结合的神经元显示模式锁定和阿诺德的舌头结构.
- 网络拓学对新出现的动态产生了关键的影响,包括连贯性,不连贯性和虚构图案,在常规,小世界和随机网络中观察到不同的行为.
结论:
- 磁流查伊神经元模型为研究复杂的同步现象提供了一个有价值的平台.
- 网络拓在塑造神经网络的集体动态方面发挥着重要作用.
- 这些发现有助于我们更好地理解合的神经元如何实现和保持同步的电活动.
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