目的 分析脑电图应用于孤独症谱系障碍(ASD)领域的研究现状、研究热点和发展趋势.方法 检索2014年1月至2024年1月Web of Science核心合集相关文献,采用CiteSpace 6.2.R4进行可视化分析.结果 最终纳入文献1 509篇,发文量呈逐年上升趋势.发文量和节点中心性最高的国家为美国.该领域发文期刊主要集中于临床医学、免疫学、心理学等学科.关键词共现和聚类结果表明,研究主要聚焦于ASD核心症状与脑电图指标的相关性研究、ASD及其共患病的鉴别诊断、脑功能连接以及康复疗效的评估.近3年突现的关键词主要为人工智能和机器学习.结论 脑电图应用于ASD领域的研究热度呈上升趋势,未来可以重点关注利用脑电图联合多模态神经成像及机器学习技术探索ASD脑网络机制.
Electroencephalography applied in autism spectrum disorder research in decade:a bibliometrics analysis
Objective To analyze the current state,research hotspots,and development trends of electroencephalography(EEG)applied in the field of autism spectrum disorder(ASD).Methods Relevant literature from the Web of Science core collection database from January,2014 to January,2024 were retrieved and analyzed using CiteSpace 6.2.R4.Results A total of 1 509 articles were included,with an increasing trend in publication volume over the years.The United States ranked highest in both publication volume and node centrality.The primary journals in this field were concentrated in clinical medicine,immunology and psychology.Keyword co-occurrence and clustering indicated that research primarily focused on the correlation between core symptoms of ASD and EEG indicators,differential diagnosis of ASD and its comorbidities,brain functional connectivity,and assessment of rehabilitation efficacy.Keywords bursted in the past three years mainly included artificial intelligence and machine learning.Conclusion The researches in EEG technology in the field of ASD is generally increasing.Future researches may focus on exploring the brain network mechanisms of ASD using EEG combined with multimodal neuroimaging,and machine learning technologies.
国家科技期刊平台
NSTL
万方数据
