相关实验视频
Updated: Sep 11, 2025

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Author Spotlight: Modular Neuronal Networks for Analyzing Brain Functions
Published on: June 7, 2024
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极端事件在多重神经网络中的传播
R Shashangan1, S Sudharsan2,3, Dibakar Ghosh2
1Bharathidasan University, Department of Nonlinear Dynamics, Tiruchirappalli 620024, Tamil Nadu, India.
Physical review. E
|August 19, 2025
概括
极端事件可以在网络层之间传播. 单向合可以在未合层中诱导事件,而双向合可以在合层中减轻事件.
科学领域:
- 复杂的网络是一个复杂的网络.
- 非线性动力学是一种非线性动力学.
- 网络神经科学 网络神经科学
背景情况:
- 之前的研究集中在单层网络中的极端事件传播上.
- 多重网络,具有相互连接的层,为研究事件动态提供了一个更复杂的系统.
研究的目的:
- 调查极端事件在多重网络中的两个不同的层之间传播的情况.
- 分析单向和双向层间合对极端事件动态的影响.
主要方法:
- 采用了两层网络模型,其中有一个全球合层和一个未合层.
- 使用非相同的FitzHugh-Nagumo神经元来模拟节点动态.
- 用概率图来定义极端和非极端状态的参数空间.
- 在未合层中检查了各种网络拓,以评估稳定性.
主要成果:
- 单向合引发了未合层中的极端事件.
- 双向合减轻了全球合层中的极端事件.
- 脱层中的极端事件从无序状态中出现,并同步爆发.
结论:
- 层间合在多重网络中显著影响极端事件的传播.
- 研究结果提供了对驱动极端事件及其同步的机制的见解.
- 这项研究作为了解现实世界互联系统中的极端事件动态的基础.
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