节点文献
抑郁症脑电特异性研究进展
Research Progress in Electroencephalography of Depression
【摘要】 抑郁症是以显著而持久的心境低落为主要症状的一组情感性精神障碍疾病,发病率高并遍布各年龄组。随着世界经济的飞速发展、社会生活竞争的日益加剧,全球抑郁症的发病率也快速提升,且患病与自杀事件已呈低龄化趋势,对抑郁症的预防诊治工作亟待重视与研究。以往抑郁诊治多依赖于主观量表评估和医生经验判定,一致性差且误诊率、漏诊率高,缺乏客观有效、方便快捷的定量诊断指标与方法。脑电(EEG)作为一种非侵入式探测大脑皮层神经电活动变化的研究手段,时间分辨率高,含有丰富的中枢神经认知生理活动信息,是获取抑郁症大脑病理变化的客观有效方法,且近年来抑郁症EEG特异性研究已取得部分成果。全面综述抑郁症EEG特征节律、非线性动力学参数、事件相关电位(ERP)响应,以及脑神经网络特异性研究现状、存在问题及解决方案等进展情况,并对未来愿景进行展望,以期推进抑郁诊治方法研究,助力开发更为有效的抑郁防治技术。
【Abstract】 Depression is an affective disease with significant and prolonged mood depression as the main symptoms,having a high incidence and spreading across all age groups. With the rapid development of the world economy and the ever-increasing competition in social life,the incidence of global depression has also rapidly risen. At the same time,diseased and suicide has showed a trend of younger age. Therefore,attention must be paid to the prevention and treatment of depression. Currently,diagnosis and treatment of depression mainly depend on subjective scale evaluation and doctor ’ s experience,with poor consistency,while high misdiagnosis rate and missed diagnosis rate,not objective and effective enough,and lacking of convenient and rapid quantitative diagnostic indicators and methods. Electroencephalography( EEG) is a non-invasive measure to detect changes in cerebral cortical neural activity,which has high time resolution and rich information on central neurocognitive and physiological activities. And it is an objective and effective method to obtain brain pathological changes in depression. In recent years,the specificity of EEG for depression has achieved progress.This paper comprehensively reviewed the progress of EEG rhythm,nonlinear dynamic parameters,event-related potentials( ERPs) response and specificity of brain neural network research,existing problems,solutions for these problems,and discussed future visions,in order to promote the diagnosis and treatment of depression and to develop more effective anti-depression techniques.
【Key words】 depression; electroencephalography; non-linear dynamics; event-related potentials; brain network;
- 【文献出处】 中国生物医学工程学报 ,Chinese Journal of Biomedical Engineering , 编辑部邮箱 ,2020年03期
- 【分类号】R749.4
- 【被引频次】20
- 【下载频次】1445