Electroencephalography applied in autism spectrum disorder research in decade: a bibliometrics analysis / 中国康复理论与实践

ABSTRACT

ObjectiveTo analyze the current state, research hotspots, and development trends of electroencephalography (EEG) applied in the field of autism spectrum disorder (ASD). MethodsRelevant literature from the Web of Science core collection database from January, 2014 to January, 2024 were retrieved and analyzed using CiteSpace 6.2.R4. ResultsA 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. ConclusionThe 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.