Topics and trends in artificial intelligence assisted human brain research

• Published in: PloS one Vol. 15; no. 4; p. e0231192
• Main Authors: Chen, Xieling, Chen, Juan, Cheng, Gary, Gong, Tao
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 06.04.2020; Public Library of Science (PLoS)
• Subjects: Artificial intelligence; Bibliometrics; Biology and Life Sciences; Brain; Brain research; Citation indexes; Collaboration; Computer and Information Sciences; Correlation analysis; Datasets; Design; Information retrieval; Information technology; Interdisciplinary aspects; Keywords; Linguistics; Machine learning; Medicine and Health Sciences; Natural language processing; Neuroimaging; Neurosciences; Physical Sciences; Queries; Research and Analysis Methods; Research facilities; Research methodology; Resource allocation; Scientometrics; Social Sciences; Studies; Technology; Trends; Unstructured data; United Kingdom; China; Hong Kong
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0231192

Artificial intelligence (AI) assisted human brain research is a dynamic interdisciplinary field with great interest, rich literature, and huge diversity. The diversity in research topics and technologies keeps increasing along with the tremendous growth in application scope of AI-assisted human brain research. A comprehensive understanding of this field is necessary to assess research efficacy, (re)allocate research resources, and conduct collaborations. This paper combines the structural topic modeling (STM) with the bibliometric analysis to automatically identify prominent research topics from the large-scale, unstructured text of AI-assisted human brain research publications in the past decade. Analyses on topical trends, correlations, and clusters reveal distinct developmental trends of these topics, promising research orientations, and diverse topical distributions in influential countries/regions and research institutes. These findings help better understand scientific and technological AI-assisted human brain research, provide insightful guidance for resource (re)allocation, and promote effective international collaborations.