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人类睡眠脑电图的关联维数:夜间过程中的周期性变化。

Correlation dimension of the human sleep electroencephalogram: cyclic changes in the course of the night.

作者信息

Achermann P, Hartmann R, Gunzinger A, Guggenbühl W, Borbély A A

机构信息

Institute of Pharmacology, University of Zürich, Switzerland.

出版信息

Eur J Neurosci. 1994 Mar 1;6(3):497-500. doi: 10.1111/j.1460-9568.1994.tb00292.x.

Abstract

The complexity of the electroencephalogram (EEG) during human sleep can be estimated by calculating the correlation dimension. Due to the large number of calculations required by this approach, only selected short (4-164 s) segments of the sleep EEG have been analysed previously. By using a new type of personal supercomputer, we were able to calculate the correlation dimension of overlapping 1 min EEG segments for the entire sleep episode (480 min) of 11 subjects and thereby delineate the time course of the changes. The correlation dimension was high in episodes of rapid eye movement (REM) sleep, declined progressively within each non-REM sleep episode, and reached a low level at times when EEG slow waves (0.75-4.5 Hz) were dominant. However, whereas slow-wave activity showed its typical progressive decline from non-REM/REM sleep cycle 1 to 4, no such trend was present for the correlation dimension. By providing an estimate of the complexity of a signal and being independent of amplitude and frequency measures, the correlation dimension represents a novel approach to exploring the dynamics of sleep and the processes underlying its regulation.

摘要

通过计算关联维数,可以估计人类睡眠期间脑电图(EEG)的复杂性。由于这种方法需要大量计算,此前仅对睡眠EEG中选定的短片段(4 - 164秒)进行了分析。通过使用新型个人超级计算机,我们能够计算11名受试者整个睡眠阶段(480分钟)重叠1分钟EEG片段的关联维数,从而描绘出变化的时间进程。快速眼动(REM)睡眠阶段的关联维数较高,在每个非快速眼动睡眠阶段内逐渐下降,并在EEG慢波(0.75 - 4.5赫兹)占主导时达到较低水平。然而,虽然慢波活动显示出从非快速眼动/快速眼动睡眠周期1到4典型的逐渐下降趋势,但关联维数不存在这种趋势。关联维数通过提供对信号复杂性的估计且独立于幅度和频率测量,代表了一种探索睡眠动态及其调节基础过程的新方法。

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