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脑电图模型中的鲁棒混沌:对脑动力学的启示。

Robust chaos in a model of the electroencephalogram: Implications for brain dynamics.

作者信息

Dafilis Mathew P., Liley David T. J., Cadusch Peter J.

机构信息

Centre for Intelligent Systems and Complex Processes, School of Biophysical Sciences and Electrical Engineering, Swinburne University of Technology, Hawthorn Vic 3122, Australia.

出版信息

Chaos. 2001 Sep;11(3):474-478. doi: 10.1063/1.1394193.

Abstract

Various techniques designed to extract nonlinear characteristics from experimental time series have provided no clear evidence as to whether the electroencephalogram (EEG) is chaotic. Compounding the lack of firm experimental evidence is the paucity of physiologically plausible theories of EEG that are capable of supporting nonlinear and chaotic dynamics. Here we provide evidence for the existence of chaotic dynamics in a neurophysiologically plausible continuum theory of electrocortical activity and show that the set of parameter values supporting chaos within parameter space has positive measure and exhibits fat fractal scaling. (c) 2001 American Institute of Physics.

摘要

为从实验时间序列中提取非线性特征而设计的各种技术,并未就脑电图(EEG)是否具有混沌性提供明确证据。缺乏确凿的实验证据的同时,能够支持非线性和混沌动力学的脑电图生理学上合理的理论也很匮乏。在此,我们为电皮质活动的一种神经生理学上合理的连续统理论中混沌动力学的存在提供了证据,并表明在参数空间内支持混沌的参数值集具有正测度且呈现胖分形标度。(c)2001美国物理研究所。

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