自发脑电(EEG)信号反映了大脑皮层神经元细胞群自发性、节律性的电生理活动,含有丰富的生理与病理信息,是临床脑神经与精神疾病诊断的重要依据.文中从频域分析、非线性动力学分析和因果性、同步性、独立成分分析等方面,综述了抑郁患者症自发EEG信号特异性研究进展并探讨了可能发展动向.抑郁症患者EEG信号频域分析方法,受性别、年龄及方法本身的限制,结论差异较大.非线性动力学及其他分析方法,得到了相对可靠的特异性分析结果,且部分参数变化与抑郁症状的临床变化有显著的相关性,有望为客观评价抗抑郁药物治疗效果提供新的检测手段,值得进行深入研究.
Resting EEG reflects spontaneous and rhythmic electrical activity of the cortical neurons and contains rich physiological and pathological information, which is an important tool for the clinical diagnosis of brain disorders and mental illness. This article reviewed the research progress and development of the resting EEG of depression in three aspects: the frequency domain analysis, the nonlinear dynamic analysis and other methods such as causality, synchronization and independent component analysis. Influenced by gender, age and the restriction of the method itself, the conclusions achieved by frequency domain analysis were different in some aspects. In contrast, nonlinear dynamic and other analysis methods got relatively reliable results. Moreover, some parameters changed with clinical depressive symptoms were expected to be the marker of depression diagnosis and treatment effect evaluation of antidepressant drugs, which was worthy of further study.