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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。
In this paper, Lempel-Zin complexity and the combination of EEG (BEAM) were used to study the changes of alertness during sleep deprivation (SD). Ten subjects underwent 36 h of SD, and spontaneous and Oddball auditory evoked experiments were performed every 6 h. Spontaneous EEG (EEG) and evoked EEG were recorded, and a complex EEG-based trend map was constructed. The results show that in 36hSD, the alertness can be divided into three phases: the first 12h is the stage with high alertness, the middle 12h is the stage with rapid decline of alertness, and the last 12h is the stage with low alertness. In the process of SD, the complexity of spontaneous EEG decreased to some extent in the whole brain, which was consistent with the subjective scale trend. The complexity of frontal lobe induced by EEG decreased and the trend was consistent with the behavioral results. Therefore, the complexity of EEG can effectively reflect the change of the alertness of the brain, and the complexity is simple and the computing speed is fast, which provides a new way for real-time monitoring of alertness.