睡眠剥夺下警觉度变化的非线性研究

Non-Linear Research of Alertness Levels under Sleep Deprivation

本文采用Lempel-Zin复杂度与脑电地形图(BEAM)相结合的方法研究睡眠剥夺(SD)下警觉度的变化过程。10名受试者进行了36h的SD,并且每6h进行了自发和Oddball听觉诱发实验,记录了自发脑电(EEG)和诱发EEG,构建了基于复杂度的脑电地形趋势图。结果表明,36hSD中,警觉度可以分为三个阶段:前12h为警觉度较高的阶段,中间12h为警觉度快速下降的阶段,最后12h为警觉度较低的阶段。在SD过程中,自发EEG的复杂度在全脑范围内有不同程度的下降,与主观量表的趋势相符;诱发EEG的额叶复杂度降低,其趋势与行为学结果相符。所以,EEG复杂度可以有效地反映大脑警觉度的变化,且复杂度计算简单、运算速度快,为以后应用于警觉度的实时监测提供了新的途径。

We applied Lempel-Ziv complexity （LZC） combined with brain electrical activity mapping （BEAM） to study the change of alertness under sleep deprivation in our research. Ten subjects were involved in 36 hours sleep deprivation （SD）, during which spontaneous electroencephalogram （EEG） experiments and auditory evoked EEG ex- periments-Oddball were recorded once every 6 hours. Spontaneous and evoked EEG data were calculated and BEAMs were structured. Results showed that during the 36 hours of SD, alertness could be divided into three stages, i.e. the first 12 hours as the high stage, the middle 12 hours as the rapid decline stage and the last 12 hours as the low stage. During the period SD, LZC of Spontaneous EEG decreased over the whole brain to some extent, but remained consistent with the subjective scales. By BEAMs of event related potential, LZC on frontal cortex decreased, but kept consistent with the behavioral responses. Therefore, LZC can be effective to reflect the change of brain alert- ness. At the same time LZC could be used as a practical index to monitor real-time alertness because of its simple computation and fast calculation.