Liu Mingrui, Liu Baohu, Ye Zelin, Wu Dongyu
Department of Rehabilitation, Wangjing Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Department of Cardiovascular, Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Front Neurosci. 2023 Mar 20;17:1128851. doi: 10.3389/fnins.2023.1128851. eCollection 2023.
Electroencephalogram (EEG), one of the most commonly used non-invasive neurophysiological examination techniques, advanced rapidly between 2005 and 2022, particularly when it was used for the diagnosis and prognosis of mild cognitive impairment (MCI). This study used a bibliometric approach to synthesize the knowledge structure and cutting-edge hotspots of EEG application in the MCI.
Related publications in the Web of Science Core Collection (WosCC) were retrieved from inception to 30 September 2022. CiteSpace, VOSviewer, and HistCite software were employed to perform bibliographic and visualization analyses.
Between 2005 and 2022, 2,905 studies related to the application of EEG in MCI were investigated. The United States had the highest number of publications and was at the top of the list of international collaborations. In terms of total number of articles, IRCCS San Raffaele Pisana ranked first among institutions. The Clinical Neurophysiology published the greatest number of articles. The author with the highest citations was Babiloni C. In descending order of frequency, keywords with the highest frequency were "EEG," "mild cognitive impairment," and "Alzheimer's disease".
The application of EEG in MCI was investigated using bibliographic analysis. The research emphasis has shifted from examining local brain lesions with EEG to neural network mechanisms. The paradigm of big data and intelligent analysis is becoming more relevant in EEG analytical methods. The use of EEG to link MCI to other related neurological disorders, and to evaluate new targets for diagnosis and treatment, has become a new research trend. The above-mentioned findings have implications in the future research on the application of EEG in MCI.
脑电图（EEG）作为最常用的非侵入性神经生理学检查技术之一，在2005年至2022年间发展迅速，尤其在用于轻度认知障碍（MCI）的诊断和预后方面。本研究采用文献计量学方法，综合分析脑电图在MCI中的知识结构和前沿热点。
检索Web of Science核心合集（WosCC）中从创刊至2022年9月30日的相关出版物。使用CiteSpace、VOSviewer和HistCite软件进行文献计量和可视化分析。
2005年至2022年间，共调查了2905项与脑电图在MCI中的应用相关的研究。美国的出版物数量最多，在国际合作排名中位居榜首。在文章总数方面，IRCCS San Raffaele Pisana在机构中排名第一。《临床神经生理学》发表的文章数量最多。被引次数最高的作者是Babiloni C。按频率降序排列，出现频率最高的关键词是“脑电图”、“轻度认知障碍”和“阿尔茨海默病”。
通过文献计量分析研究了脑电图在MCI中的应用。研究重点已从利用脑电图检查局部脑损伤转向神经网络机制。大数据和智能分析范式在脑电图分析方法中变得越来越重要。利用脑电图将MCI与其他相关神经系统疾病联系起来，并评估新的诊断和治疗靶点，已成为新的研究趋势。上述发现对未来脑电图在MCI中的应用研究具有启示意义。
