一种用于分析非静止生理网络中高阶相互作用的时间频率的方法
Yuri Antonacci1, Chiara Bará1, Laura Sparacino1
1Department of Engineering, University of Palermo, Palermo, Italy.
Journal of neural engineering
|October 21, 2025
概括
本研究引入了一种新的时间频率框架,用于分析动态网络中的高阶相互作用 (HOI). 该方法揭示了短暂的网络行为和功能变化,这些变化无法通过传统的时间域分析来检测.
科学领域:
- 网络科学 网络科学
- 信息理论 信息理论
- 时间频率分析
背景情况:
- 在网络中分析高阶相互作用 (HOI) 的现有方法往往无法捕捉时间相关性或频率特定的动态.
- 时间域分析假定静止,限制其检测生理网络中的短暂行为或频率特定相互作用的能力.
研究的目的:
- 开发一种新的框架,用于随机过程网络中的HOI的时间变化和时间频率分析.
- 为了能够检测频率特定的行为和动态网络中的短暂的功能链接.
主要方法:
- 利用矢量自回归模型的光谱表示来对HOI进行时间和频率解析的分析.
- 采用递归最小方程估计器,具有忘记因子,可对协同作用和冗余相互作用进行可靠的识别.
主要成果:
- 在模拟网络上进行了验证,证明了在特定频段中检测到短暂的协同行为.
- 应用于大鼠大脑唤起的潜能,识别冗余信息与胡须刺激同步.
- 观察到头向上倾斜后心血管振荡的冗余信息减少,表明功能断开.
结论:
- 拟议的框架提供了一种全面的方法来分析动态网络随时间和频率的层次组织.
- 这种方法适用于研究各种生理学和神经科学应用中的状态过渡期间的短暂高阶行为.
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