In healthy subjects, sleep has a typical structure of three to five cyclic transitions between different sleep states. In major depression, this regular pattern is often destroyed but can be reestablished during successful treatment. The differences between healthy and abnormal sleep are generally assessed in a time-consuming process, which consists of determining the nightly variations of the sleep states (the hypnogram) based on visual inspection of the electroencephalogram (EEG), electrooculogram, and electromyogram. In this study, three different methods of sleep EEG analysis (spectrum, outlier, and recurrence analysis) have been examined with regard to their ability to extract information about treatment effects in patients with major depression. Our data suggest that improved sleep patterns during treatment with antidepressant medication can be identified with an appropriate analysis of the EEG. By comparing different methods, we have found that many treatment effects identified by spectrum analysis can be reproduced by the much simpler technique of outlier analysis. Finally, the cyclic structure of sleep and its modification by antidepressant treatment is best illustrated by a non-linear approach, the so-called recurrence method.

中文翻译：

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重度抑郁症患者睡眠脑电图疗效评价不同方法的比较

在健康受试者中，睡眠具有在不同睡眠状态之间三到五个循环转换的典型结构。在重度抑郁症中，这种规律性模式通常会被破坏，但可以在成功治疗期间重新建立。健康和异常睡眠之间的差异通常在一个耗时的过程中进行评估，该过程包括基于对脑电图 (EEG)、眼电图和肌电图的目视检查来确定睡眠状态（睡眠图）的夜间变化。在这项研究中，研究了三种不同的睡眠 EEG 分析方法（频谱、异常值和复发分析），以了解它们提取重性抑郁症患者治疗效果信息的能力。我们的数据表明，可以通过对 EEG 的适当分析来确定抗抑郁药物治疗期间睡眠模式的改善。通过比较不同的方法，我们发现通过频谱分析确定的许多治疗效果可以通过更简单的异常值分析技术重现。最后，通过非线性方法，即所谓的复发方法，可以最好地说明睡眠的循环结构及其通过抗抑郁药治疗的改变。