Topics and trends in artificial intelligence assisted human brain research

Abstract

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.

Fig 1. Proposed analytic framework.

Fig 2. Annual trends of the identified topics (2009–2018).

Fig 3. Graphing positive correlations between the 30 identified topics.

Fig 4. Topic proportion distributions of the influential countries/regions and institutes in AI-assisted human brain research ranked by h-index.

Fig 5. Topic proportion distributions by year.

Fig 6. Effects of funding and international collaboration on topic proportions.

Differences between papers with and without funding (a), as well as papers with and without international collaboration (b).