NONLINEAR FORECASTING MEASUREMENTS OF MULTICHANNEL EEG DYNAMICS

被引：41

作者：

PEZARD, L ^{[1
]}

MARTINERIE, J ^{[1
]}

BRETON, F ^{[1
]}

BOURZEIX, JC ^{[1
]}

RENAULT, B ^{[1
]}

机构：

[1] UNIV PARIS 06,HOP LA PITIE SALPETRIERE,LENA,CNRS,URA 654,UNITE PSYCHOPHYSIOL COGNIT,F-75651 PARIS 13,FRANCE

来源：

ELECTROENCEPHALOGRAPHY AND CLINICAL NEUROPHYSIOLOGY | 1994年 / 91卷 / 05期

关键词：

HUMAN MULTICHANNEL EEG; DYNAMICAL SYSTEMS; NONLINEAR FORECASTING; KOLMOGOROV ENTROPY; CHAOS; ATTENTIONAL CONDITIONS;

D O I：

10.1016/0013-4694(94)90123-6

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

This work presents a new method for studying the underlying dynamics of multichannel EEG on the basis of the mathematical theory of dynamical systems. It computes the local loss of predictability and Kolmogorov entropy of the dynamics reconstructed from brain electrical activity. This reconstruction uses multichannel recordings in order to quantify an equivalent of spatio-temporal mapping. Five experimental conditions have been studied: closed eyes at rest, closed eyes and counting even numbers, staring at a spotlight, passive and active auditive odd-ball tasks. The entropy is positive for all the experimental conditions which proves that the underlying EEG dynamics are chaotic. Moreover, on the basis of the dynamical signature it is possible to differentiate 3 types of EEG activity: the rest closed eyes activity, the task closed eyes activity (counting and odd-ball tasks) and the open eyes activity (staring at a spotlight). It is inferred that this index could characterize task-related changes in brain activity.

引用

页码：383 / 391

页数：9

共 52 条

[1] SINGULAR-VALUE DECOMPOSITION AND THE GRASSBERGER-PROCACCIA ALGORITHM [J].