Pijn J P, Van Neerven J, Noest A, Lopes da Silva F H
Instituut voor Epilepsiebestrijding Meer en Bosch, Heemstede, The Netherlands.
Electroencephalogr Clin Neurophysiol. 1991 Nov;79(5):371-81. doi: 10.1016/0013-4694(91)90202-f.
EEG signals have been considered to result either from random processes or to be generated by non-linear dynamic systems exhibiting chaotic behaviour. In the latter case, the system may behave as a deterministic chaotic attractor. The complexity of the attractor can be characterized by the correlation dimension that can be computed from one signal generated by the system. A new procedure was developed and applied in order to test whether the correlation dimension, calculated from an EEG epoch, may correspond to a chaotic attractor or to a random process. This procedure was applied to EEG signals recorded from different sites of the limbic cortex of the rat during different states: wakeful rest, locomotion and in the course of an epileptic seizure induced by kindling. The signals recorded during the first two states had high dimensions and could not be distinguished from random noise. However, during an epileptic seizure the correlation dimension became low (between 2 and 4) indicating that in this state the networks behave as chaotic systems. A low correlation dimension appeared at different times and brain sites during an epileptic seizure. These results show that the computation of the correlation dimension may be useful in order to obtain insight into the dynamics of the propagation of an epileptic seizure in the brain.
脑电图(EEG)信号被认为要么源于随机过程,要么由表现出混沌行为的非线性动态系统产生。在后一种情况下,系统可能表现为确定性混沌吸引子。吸引子的复杂性可以通过相关维数来表征,相关维数可以从系统产生的一个信号中计算得出。为了测试从一段脑电图记录中计算出的相关维数是否对应于混沌吸引子或随机过程,开发并应用了一种新程序。该程序应用于大鼠边缘皮质不同部位在不同状态下记录的脑电图信号,这些状态包括清醒休息、运动以及在点燃诱导的癫痫发作过程中。在前两种状态下记录的信号具有高维数,无法与随机噪声区分开来。然而,在癫痫发作期间,相关维数变低(在2到4之间),表明在这种状态下神经网络表现为混沌系统。在癫痫发作期间,不同时间和脑区会出现低相关维数。这些结果表明,相关维数的计算可能有助于深入了解癫痫发作在大脑中传播的动力学。