时间变化的信息测量:对信息存储的适应性估计,适用于大脑-心脏相互作用
Yuri Antonacci1, Chiara Barà1, Andrea Zaccaro2
1Department of Engineering, University of Palermo, Palermo, Italy.
Frontiers in network physiology
|November 3, 2023
概括
这项研究引入了一种新的时间变化方法,用于测量生理系统中的信息存储 (IS),即使动态发生变化. 这种方法揭示了对整个心脏周期中大脑与心脏相互作用的新见解.
科学领域:
- 网络生理学 网络生理学
- 信息理论 信息理论
- 动态系统分析 动态系统分析
背景情况:
- 网络生理学研究了维护健康的生理系统相互作用.
- 信息存储 (IS) 测量过程规律性,但假定静止性.
- 静止性假设限制了追踪生理系统中的短暂动态.
研究的目的:
- 开发一种时间变化的方法,用于在非静止条件下估计信息存储 (IS).
- 随着时间的推移,追踪生理系统动态中的短暂途径.
- 通过一种新的IS估计方法来研究大脑与心脏的相互作用.
主要方法:
- 提出了一种使用递归最小平方 (RLS) 算法来估计IS的时间变化方法.
- 在模拟的时间变动动态上测试了该方法.
- 分析了健康志愿者的脑电图 (EEG) 信号,与心跳同步.
主要成果:
- 基于RLS的方法成功地追踪了模拟信息存储中的突然和缓慢变化.
- 在心脏周期阶段之间观察到时间变化的IS变异性的显著差异.
- 平均的IS值显示,头皮周围头部区域的调制较弱.
结论:
- 考虑生理非静止性的先进方法对于准确的IS测量至关重要.
- 建议的时间变化的RLS方法对于识别神经心脏系统中的时空动态非常有价值.
- 这种方法增强了对复杂的大脑与心脏相互作用的理解.
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