Li Pengcheng, Yokoyama Mio, Okamoto Daiki, Nakatani Hironori, Yagi Tohru
School of Environment and Society, Tokyo Institute of Technology, Tokyo, Japan.
School of Information and Telecommunication Engineering, Tokai University, Tokyo, Japan.
Front Hum Neurosci. 2024 Aug 12;18:1384330. doi: 10.3389/fnhum.2024.1384330. eCollection 2024.
Depressive states in both healthy individuals and those with major depressive disorder exhibit differences primarily in symptom severity rather than symptom type, suggesting that there is a spectrum of depressive symptoms. The increasing prevalence of mild depression carries lifelong implications, emphasizing its clinical and social significance, which parallels that of moderate depression. Early intervention and psychotherapy have shown effective outcomes in subthreshold depression. Electroencephalography serves as a non-invasive, powerful tool in depression research, with many studies employing it to discover biomarkers and explore underlying mechanisms for the identification and diagnosis of depression. However, the efficacy of these biomarkers in distinguishing various depressive states in healthy individuals and in understanding the associated mechanisms remains uncertain. In our study, we examined the power spectrum density and the region-based phase-locking value in healthy individuals with various depressive states during their resting state. We found significant differences in neural activity, even among healthy individuals. Participants were categorized into high, middle, and low depressive state groups based on their response to a questionnaire, and eyes-open resting-state electroencephalography was conducted. We observed significant differences among the different depressive state groups in theta- and beta-band power, as well as correlations in the theta-beta ratio in the frontal lobe and phase-locking connections in the frontal, parietal, and temporal lobes. Standardized low-resolution electromagnetic tomography analysis for source localization comparing the differences in resting-state networks among the three depressive state groups showed significant differences in the frontal and temporal lobes. We anticipate that our study will contribute to the development of effective biomarkers for the early detection and prevention of depression.
健康个体和重度抑郁症患者的抑郁状态主要在症状严重程度而非症状类型上存在差异，这表明存在一系列抑郁症状。轻度抑郁症患病率的上升具有终身影响，凸显了其临床和社会意义，这与中度抑郁症相当。早期干预和心理治疗已在阈下抑郁症中显示出有效结果。脑电图是抑郁症研究中一种非侵入性的强大工具，许多研究利用它来发现生物标志物并探索抑郁症识别和诊断的潜在机制。然而，这些生物标志物在区分健康个体的各种抑郁状态以及理解相关机制方面的功效仍不确定。在我们的研究中，我们在静息状态下检查了处于各种抑郁状态的健康个体的功率谱密度和基于区域的锁相值。我们发现即使在健康个体中神经活动也存在显著差异。参与者根据对问卷的回答被分为高、中、低抑郁状态组，并进行了睁眼静息状态脑电图检查。我们观察到不同抑郁状态组在θ波和β波功率方面存在显著差异，以及额叶中θ-β比率和额叶、顶叶和颞叶中锁相连接的相关性。通过标准化低分辨率电磁断层扫描分析进行源定位，比较三个抑郁状态组静息状态网络的差异，结果显示额叶和颞叶存在显著差异。我们预计我们的研究将有助于开发用于早期检测和预防抑郁症的有效生物标志物。
