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首页> 外文期刊>Neuropsychopharmacology >Individual |[lsquo]|Fingerprints|[rsquo]| in Human Sleep EEG Topography
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Individual |[lsquo]|Fingerprints|[rsquo]| in Human Sleep EEG Topography

机译:个体| [lsquo] |指纹| [rsquo] |在人类睡眠脑电图地形中

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The sleep EEG of eight healthy young men was recorded from 27 derivations during a baseline night and a recovery night after 40 h of waking. Individual power maps of the nonREM sleep EEG were calculated for the delta, theta, alpha, sigma and beta range. The comparison of the normalized individual maps for baseline and recovery sleep revealed very similar individual patterns within each frequency band. This high correspondence was quantified and statistically confirmed by calculating the Manhattan distance between all pairs of maps within and between individuals. Although prolonged waking enhanced power in the low-frequency range (0.75–10.5 Hz) and reduced power in the high-frequency range (13.25–25 Hz), only minor effects on the individual topography were observed. Nevertheless, statistical analysis revealed frequency-specific regional effects of sleep deprivation. The results demonstrate that the pattern of the EEG power distribution in nonREM sleep is characteristic for an individual and may reflect individual traits of functional anatomy.
机译:在基线夜晚和醒来40小时后的恢复夜晚,从27个派生中记录了8位健康年轻人的睡眠EEG。计算了非快速眼动睡眠脑电图的各个功率图,包括δ,θ,α,sigma和β范围。基线和恢复睡眠的归一化个体图的比较显示了每个频带内非常相似的个体模式。通过计算个体内部和个体之间所有成对地图之间的曼哈顿距离,可以量化并通过统计学方式确认这种高度对应。尽管长时间唤醒会增强低频范围(0.75–10.5 Hz)中的功率,并降低高频范围(13.25–25 Hz)中的功率,但仅观察到对单个地形的微小影响。然而,统计分析显示睡眠剥夺的特定频率区域效应。结果表明,非快速眼动睡眠中脑电功率分布的模式是个体的特征,并且可能反映了功能解剖的个体特征。

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