PREDICTABILITY OF HUMAN EEG - A DYNAMIC APPROACH
PREDICTABILITY OF HUMAN EEG - A DYNAMIC APPROACH
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DOI：
10.1007/bf00224705
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发表时间：
1991-01-01
影响因子：
1.9
通讯作者：
BABLOYANTZ, A
中科院分区：
文献类型：
--
作者：
GALLEZ, D;BABLOYANTZ, A
在非线性动力学的新方法框架下分析了人类头皮的脑电图记录。大脑活动分为三个阶段：α波（闭上眼睛）、深度睡眠（第四阶段）和克雅氏昏迷。计算了吸引子的两个动力学参数。它们是李雅普诺夫指数，用来衡量相空间中轨迹的发散或收敛；还有Kolmogorov或度量熵，其逆给出给定脑电图信号的平均预测时间。在所有考虑的阶段中，结果揭示了至少两个正李雅普诺夫指数的存在，这是混沌的足迹。在阿尔法波的情况下，这个数字增加到3个正指数，这表明尽管在很短的时间内，阿尔法波似乎非常连贯，但大脑的可变性在较长时间的活动中显著增加。从昏迷到深度睡眠，再到α波，熵/混沌的程度会增加。深度睡眠中观察到的较长的预测时间表明，这些波与信息处理速度较慢有关。阿尔法波的预测时间要短得多，这表明信息丢失得很快。最后，在Lyapunov指数的帮助下，使用两种不同的猜想来评估吸引子的维度，并将其与先前由Grassberger-Procaccia算法获得的值进行比较。
The electroencephalogram recordings from human scalp are analysed in the framework of recent methods of nonlinear dynamics. Three stages of brain activity are considered: the alpha waves (eyes closed), the deep sleep (stage four) and the Creutzfeld-Jakob coma. Two dynamical parameters of the attractors are evaluated. These are the Lyapunov exponents, which measure the divergence or convergence of trajectories in phase space and the Kolmogorov or metric entropy, whose inverse gives the mean predicting time of a given EEG signal. In all the stages considered, the results reveal the presence of at least two positive Lyapunov exponents, which are the footprints of chaos. This number increases to three positive exponents in the case of alpha waves, indicating that although for very short episodes the alpha waves seem extremely coherent, the variability of the brain increases markedly over larger periods of activity. The degree of entropy/chaos increases from coma to deep sleep and then to alpha waves. The large predicting time observed for deep sleep suggests that these waves are related to a slow rate of information processing. The predicting time of the alpha waves is much smaller, indicating a rapid loss of information. Finally, with the help of the Lyapunov exponents, the attractor's dimensions are evaluated using two different conjectures and compared to values obtained previously by the Grassberger-Procaccia algorithm.