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[非线性数学(混沌理论)对脑电图分析的贡献]

[Contribution of non-linear mathematics (chaos theory) to EEG analysis].

作者信息

Rey M, Guillemant P

机构信息

Service d'EFSN, CHU Timone, Marseille.

出版信息

Neurophysiol Clin. 1997 Nov;27(5):406-28. doi: 10.1016/s0987-7053(97)88807-7.

Abstract

Since 1963, nonlinear dynamics or "chaos theory" were widely used in various area of physics. The first application to the analysis of the human electroencephalogram (EEG) was performed in 1985. A tutorial revue of some concepts of nonlinear dynamics is presented with the various results obtained since 1985. The dimensional complexity of the EEG (DC) seems a good descriptor of the "desynchronisation" or decorrelation of the EEG: DC is high with eyes open, during a mental task and also during a tonic epileptic discharge. DC is low with eyes closed, during slow wave sleep, and during a clonic epileptic discharge. The measure of DC could allow a more objective comparison between various states of electrical cerebral activity.

摘要

自1963年以来,非线性动力学或“混沌理论”在物理学的各个领域得到了广泛应用。1985年首次将其应用于人类脑电图(EEG)分析。本文介绍了非线性动力学的一些概念,并回顾了自1985年以来获得的各种结果。脑电图的维度复杂性(DC)似乎是脑电图“去同步化”或去相关性的一个很好的描述指标:睁眼时、进行心理任务时以及强直性癫痫放电期间,DC值较高。闭眼时、慢波睡眠期间以及阵挛性癫痫放电期间,DC值较低。DC的测量可以使大脑电活动的各种状态之间进行更客观的比较。

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