PhD Program in Neuroscience, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy.
Sleep Centre, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy.
J Sleep Res. 2021 Oct;30(5):e13339. doi: 10.1111/jsr.13339. Epub 2021 Mar 26.
Over the last two decades, our understanding of clinical and pathophysiological aspects of sleep-related epileptic and non-epileptic paroxysmal behaviours has improved considerably, although it is far from complete. Indeed, even if many core characteristics of sleep-related hypermotor epilepsy and non-rapid eye movement parasomnias have been clarified, some crucial points remain controversial, and the overlap of the behavioural patterns between these disorders represents a diagnostic challenge. In this work, we focused on segments of multichannel sleep electroencephalogram free from clinical episodes, from two groups of subjects affected by sleep-related hypermotor epilepsy (N = 15) and non-rapid eye movement parasomnias (N = 16), respectively. We examined sleep stages N2 and N3 of the first part of the night (cycles 1 and 2), and assessed the existence of differences in the periodic and aperiodic components of the electroencephalogram power spectra between the two groups, using the Fitting Oscillations & One Over f (FOOOF) toolbox. A significant difference in the gamma frequency band was found, with an increased relative power in sleep-related hypermotor epilepsy subjects, during both N2 (p < .001) and N3 (p < .001), and a significant higher slope of the aperiodic component in non-rapid eye movement parasomnias, compared with sleep-related hypermotor epilepsy, during N3 (p = .012). We suggest that the relative power of the gamma band and the slope extracted from the aperiodic component of the electroencephalogram signal may be helpful to characterize differences between subjects affected by non-rapid eye movement parasomnias and those affected by sleep-related hypermotor epilepsy.
在过去的二十年中，尽管我们对睡眠相关癫痫和非癫痫阵发性行为的临床和病理生理学方面的理解有了很大的提高，但还远未完善。事实上，即使睡眠相关运动性癫痫和非快速眼动性睡眠障碍的许多核心特征已经得到阐明，但仍有一些关键问题存在争议，而且这些疾病之间的行为模式存在重叠，这给诊断带来了挑战。在这项工作中，我们专注于不受临床发作影响的多通道睡眠脑电图片段，分别来自两组受睡眠相关运动性癫痫（N=15）和非快速眼动性睡眠障碍（N=16）影响的受试者。我们检查了夜间第一部分的 N2 和 N3 睡眠阶段，并使用 Fitting Oscillations & One Over f (FOOOF) 工具箱评估了两组之间脑电图功率谱的周期性和非周期性成分的差异。我们发现伽马频带存在显著差异，在 N2（p<0.001）和 N3（p<0.001）期间，睡眠相关运动性癫痫患者的相对功率增加，而在 N3 期间，非快速眼动性睡眠障碍患者的非周期性成分斜率显著高于睡眠相关运动性癫痫患者（p=0.012）。我们认为，γ 频带的相对功率和从脑电图信号的非周期性成分中提取的斜率可能有助于表征受非快速眼动性睡眠障碍和睡眠相关运动性癫痫影响的受试者之间的差异。
