Zhou Peng, Wu Qian, Zhan Liying, Guo Zhihan, Wang Chaolun, Wang Shanze, Yang Qing, Lin Jiating, Zhang Fangyuan, Liu Lu, Lin Dehui, Fu Wenbin, Wu Xiang
Bao'an Traditional Chinese Medicine Hospital, Shenzhen, China.
Sanming Project of Medicine in Shenzhen, Fuwenbin's Acupuncture and Moxibustion Team of Guangdong Provincial Hospital of Chinese Medicine, Shenzhen, China.
Front Neurosci. 2023 Mar 7;17:1057908. doi: 10.3389/fnins.2023.1057908. eCollection 2023.
Depression is a serious psychiatric disorder characterized by prolonged sadness, loss of interest or pleasure. The dominant alpha peak activity in resting-state EEG is suggested to be an intrinsic neural marker for diagnosis of mental disorders.
To investigate an association between alpha peak activity and depression severity, the present study recorded resting-state EEG (EGI 128 channels, off-line average reference, source reconstruction by a distributed inverse method with the sLORETA normalization, parcellation of 68 Desikan-Killiany regions) from 155 patients with depression (42 males, mean age 35 years) and acquired patients' scores of Self-Rating Depression Scales. We measured both the alpha peak amplitude that is more related to synchronous neural discharging and the alpha peak frequency that is more associated with brain metabolism.
The results showed that over widely distributed brain regions, individual patients' alpha peak amplitudes were negatively correlated with their depressive scores, and individual patients' alpha peak frequencies were positively correlated with their depressive scores.
These results reveal that alpha peak amplitude and frequency are associated with self-rating depressive score in different manners, and the finding suggests the potential of alpha peak activity in resting-state EEG acting as an important neural factor in evaluation of depression severity in supplement to diagnosis.
抑郁症是一种严重的精神障碍，其特征为长期悲伤、兴趣或愉悦感丧失。静息态脑电图中的主导阿尔法峰值活动被认为是精神障碍诊断的一种内在神经标志物。
为了研究阿尔法峰值活动与抑郁严重程度之间的关联，本研究记录了155名抑郁症患者（42名男性，平均年龄35岁）的静息态脑电图（EGI 128通道，离线平均参考，采用分布式逆方法并经sLORETA归一化进行源重建，68个Desikan-Killiany区域的脑区划分），并获取了患者的自评抑郁量表得分。我们测量了与同步神经放电更相关的阿尔法峰值幅度以及与脑代谢更相关的阿尔法峰值频率。
结果显示，在广泛分布的脑区中，个体患者的阿尔法峰值幅度与其抑郁得分呈负相关，个体患者的阿尔法峰值频率与其抑郁得分呈正相关。
这些结果表明，阿尔法峰值幅度和频率以不同方式与自评抑郁得分相关，这一发现提示静息态脑电图中的阿尔法峰值活动有可能作为评估抑郁严重程度的一个重要神经因素，以补充诊断。
