Department of Psychology, University of Arizona, Tucson, Arizona, USA.
Psychophysiology. 2023 Aug;60(8):e14274. doi: 10.1111/psyp.14274. Epub 2023 Feb 22.
Nonlinear EEG analysis offers the potential for both increased diagnostic accuracy and deeper mechanistic understanding of psychopathology. EEG complexity measures have previously been shown to positively correlate with clinical depression. In this study, resting state EEG recordings were taken across multiple sessions and days with both eyes open and eyes closed conditions from a total of 306 subjects, 62 of which were in a current depressive episode, and 81 of which had a history of diagnosed depression but were not currently depressed. Three different EEG montages (mastoids, average, and Laplacian) were also computed. Higuchi fractal dimension (HFD) and sample entropy (SampEn) were calculated for each unique condition. The complexity metrics showed high internal consistency within session and high stability across days. Higher complexity was found in open-eye recordings compared to closed eyes. The predicted correlation between complexity and depression was not found. However, an unexpected sex effect was observed, in which males and females exhibited different topographic patterns of complexity.
非线性 EEG 分析有可能提高诊断准确性，并深入了解精神病理学的机制。EEG 复杂度测量此前已被证明与临床抑郁症呈正相关。在这项研究中，对总共 306 名受试者的多个阶段和多天的静息状态 EEG 记录进行了测量，其中 62 名受试者正处于当前的抑郁发作期，81 名受试者曾被诊断患有抑郁症但目前未处于抑郁状态。还计算了三种不同的 EEG 导联（乳突、平均和拉普拉斯）。为每个独特的条件计算了 Higuchi 分形维数（HFD）和样本熵（SampEn）。复杂度指标在会话内具有较高的内部一致性，在多天内具有较高的稳定性。睁眼记录的复杂度高于闭眼记录。复杂性与抑郁之间的预测相关性未被发现。然而，观察到了一个意想不到的性别效应，其中男性和女性表现出不同的复杂度拓扑模式。
