老化中的规律性和随机性:静止状态EEG复杂性的差异,用最大的利亚普诺夫指数测量
Matthew King-Hang Ma1, Manson Cheuk-Man Fong2, Chenwei Xie2
1Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong.
Neuroimage. Reports
|June 26, 2025
概括
衰老的大脑表现出复杂性降低,支持衰老假说中的复杂性丧失. 这项研究使用了最大的Lyapunov指数 (LLE) 来显示老年人的规律性增加,以及信号域随机性.
科学领域:
- 神经科学是一个神经科学.
- 动态系统理论 动态系统理论
- 老年学是指老年学的学科.
背景情况:
- 衰老中的复杂性丧失假设 (LOCH) 得到了用信号域复杂性测量的脑电图 (EEG) 研究的支持.
- 之前的研究主要集中在信号域指标上,使动态系统的观点在老化大脑复杂性方面得到了较少的探索.
研究的目的:
- 从非线性动态系统的角度使用最大的莱普诺夫指数 (LLE) 来研究与年龄相关的大脑复杂性的变化.
- 检查与年龄相关的复杂性差异的区域特异性及其与其他复杂性指标的关系.
主要方法:
- 采用最大的Lyapunov指数 (LLE) 来量化年轻,年轻和老年年龄组的144名参与者的大脑复杂性.
- 利用了EEG数据的传感器空间和源空间分析.
- 与伦佩尔-齐夫复杂性 (LZC) 相关联的LLE以及对大脑区域的分析年龄组差异.
主要成果:
- 与年轻人相比,老年人观察到明显较低的LLE,这表明动态规律性增加.
- 与年龄相关的LLE差异在额头和部区域最为明显,在部区域的非显著发现.
- 源空间分析揭示了后带带膜中LLE的减少,并且发现了LLE和LZC之间的负相关性,这表明规律性和信号域随机性同时增加.
结论:
- 这些发现支持衰老假设 (LOCH) 的复杂性丧失,通过证明与年龄相关的大脑信号规律性 (较低的LLE) 和随机性 (较高的LZC) 的增加.
- 这项研究强调了像LLE这样的非线性动态系统测量在理解大脑衰老方面的有用性.
- 特定区域的与年龄相关的复杂性变化,特别是在前部区域,需要进一步调查.
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