Fractal dimensions of short EEG time series in humans

被引：39

作者：

Preissl, H ^{[1
]}

Lutzenberger, W ^{[1
]}

Pulvermuller, F ^{[1
]}

Birbaumer, N ^{[1
]}

机构：

[1] UNIV STUDI,PADUA,ITALY

来源：

NEUROSCIENCE LETTERS | 1997年 / 225卷 / 02期

关键词：

chaos; electroencephalogram; dimension; non-linearity; surrogate data;

D O I：

10.1016/S0304-3940(97)00192-4

中图分类号：

Q189 [神经科学];

学科分类号：

071006 ;

摘要：

Fractal dimension has been proposed as a useful measure for the characterisation of electrophysiological time series. But one of the problems of this approach, is the difficulty to record time series long enough to determine the 'real' fractal dimension. Nevertheless it is possible to calculate fractal dimensions for very short data-segments. Using time series of different length it is possible to show, that there is a monotoneous relation between fractal dimension and the number of data-points. This relation could be further interpreted with the help of an extrapolation scheme. In addition this effect is also seen with surrogate data, generated from that signal. We conclude that it is feasible to use fractal dimension as a tool to characterise the complexity for shea electroencephalographic (EEG) time series, but it is not possible to decide whether the brain is a chaotic system or not. (C) 1997 Elsevier Science Ireland Ltd.

引用

页码：77 / 80

页数：4

共 21 条

[1] ALL-NIGHT SLEEP EEG AND ARTIFICIAL STOCHASTIC-CONTROL SIGNALS HAVE SIMILAR CORRELATION DIMENSIONS [J].