This paper analyzed literatures on the specificity study of electroencephalogram (EEG) in the diagnosis of depression since 2010 to 2020, summarized the recent research directions in this field and prospected the future research hotspots at home and abroad. Based on databases of China National Knowledge Infrastructure (CNKI) and the core collection of Web of Science (WOS), CiteSpace software was used to analyze the relevant literatures in this research field. The number of relevant literatures, countries, authors, research institutions, key words, cited literatures and periodicals related to this research were analyzed, respectively, to explore research hotspots and development trends in this field. A total of 2 155 articles were included in the WOS database. The most published institution was the University of Toronto, the most published country was the United States, China occupied the third place, and the hot keywords were anxiety, disorder, brain and so on. A total of 529 literatures were included and analyzed in CNKI database. The institution with the most publications was the Mental Health Center of West China Hospital of Sichuan University, and the hot keywords were EEG signal, event-related potential, convolutional neural network, schizophrenia, etc . This study finds that EEG study of depression is developing rapidly at home and abroad. Research directions in the world mainly focus on exploring the characteristics of spontaneous EEG rhythm and nonlinear dynamic parameters during sleep in depressed patients. In addition, synchronous transcranial magnetic stimulation (TMS) and EEG technologies also attract much attention abroad, and the future research hotspot will be on the mechanism of EEG on patients with major depression. Domestic research directions mainly focus on the classification of resting EEG and the control study of resting EEG power spectrum entropy in patients with schizophrenia and depression, and future research hotspot is the basic and clinical EEG study of depressed patients complicated with anxiety.
本文分析了国内外 2010 年至 2020 年脑电图诊断抑郁症特异性研究的相关文献，总结了该领域研究方向及展望国内外未来研究热点。基于中国知网和 Web of Science 核心合集数据库，运用 CiteSpace 软件对这一研究领域的相关文献进行可视化分析。对发文数量、国家、作者、研究机构、关键词、被引文献及期刊进行分析，探索此领域研究热点及发展趋势。Web of Science 数据库共纳入 2 155 篇文献。发文最多的机构是多伦多大学，发文最多的国家是美国，中国的发文量占据第三位；热点关键词是焦虑、失调、大脑等。中国知网数据库共纳入 529 篇文献。其中发文量最多的机构是四川大学华西医院心理卫生中心；热点关键词是脑电信号、事件相关电位、卷积神经网络、精神分裂症等。本研究发现国内外在抑郁症脑电研究领域发展迅速。国际上的研究方向主要集中于探究抑郁患者睡眠时的自发脑电节律特征及非线性动力学参数上。此外，国外对于同步经颅磁刺激和脑电这项技术也很关注，预测未来的研究热点为重性抑郁症患者的脑电诊断机制等基础研究。国内在该领域的研究发展形式良好，研究方向主要集中于精神分裂症和抑郁症患者静息态脑电分类及静息态脑电功率谱熵的对照研究上，预测未来的研究热点为抑郁患者并发焦虑症的基础及临床脑电研究。.
Keywords: CiteSpace; depressive disorder; electroencephalogram; visual analysis.