复杂性同步:衡量大脑,心脏和肺部之间的相互作用
Korosh Mahmoodi1,2, Scott E Kerick3, Paolo Grigolini4
1US Combat Capabilities Command, Army Research Laboratory, Aberdeen Proving Ground, MD, 21005, USA. koroshmahmoodi@gmail.com.
Scientific reports
|July 15, 2023
概括
网络效应 (NE) 通过像大脑和心脏这样的生理器官网络 (ONs) 同步复杂性. 这种复杂性同步 (CS) 是一个跨学科的现象,提供了一种分析复杂网络动态的一般方法.
科学领域:
- 复杂系统科学 复杂系统科学
- 物理网络动态 物理网络动态
- 网络效应分析 网络效应分析
背景情况:
- 大脑,心脏和肺部的器官网络 (ONs) 产生时间序列,反映网络内部和内部的相互作用.
- 这些生理时间序列展示了关键事件 (CE) 和复杂的动态.
- 之前的研究已经探索了连贯性质,但对复杂性同步缺乏普遍的理解.
研究的目的:
- 调查网络效应 (NE) 对生理器官网络 (ON) 的时间序列的可测量后果.
- 分析大脑,心脏和肺部网络之间的复杂性和同步模式.
- 引入复杂性同步 (CS) 作为一种跨学科的概念,用于描述复杂的网络动态.
主要方法:
- 利用修改的扩散分析 (MDEA) 来评估时间序列的复杂性.
- 分析了从EEG (大脑),ECG (心脏) 和呼吸时间序列中得出的缩放指数.
- 检查了在生理ONs中的多分体行为的定量相互依赖.
主要成果:
- 经过时间的推移,在生理ONs中,通过缩放指数测量复杂性的准周期性变化得到证明.
- 观察到一个普遍的复杂性同步,独立于潜在的连贯性质.
- 确定了大脑,心脏和呼吸系统时间序列的缩放指数之间的高阶同步.
结论:
- 网络效应 (NE) 在生理器官网络 (ON) 中导致复杂性同步 (CS).
- CS是由这些网络中的多元结构动态的定量相互依赖性来管理的.
- 复杂性同步 (CS) 提供了一个一般的框架,用于在各种科学和技术领域描述复杂的网络动态.
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