25-year neuroimaging research on spoken language processing: a bibliometric analysis.

Area of Science:

• Cognitive Neuroscience
• Neuroimaging
• Spoken Language Processing

Background:

• Spoken language processing is crucial for daily communication and a key area for cognitive and neural scientists.
• Understanding the dynamics of research in this field provides insights into scientific progress and collaboration patterns.

Purpose of the Study:

• To analyze the publication trends and characteristics of neuroimaging research on spoken language processing from 2000 to 2024.
• To identify key research areas, collaborations, and future directions within this scientific domain.

Main Methods:

• A bibliometric analysis was performed using data from the Web of Science database.
• A total of 8,085 articles were analyzed, examining authors, journals, citations, and countries of origin.
• Keyword mapping and institutional collaboration network analysis were employed, along with burst detection for trend prediction.

Main Results:

• The study reveals a consistent increase in publication volume and high academic impact (citations) over the analyzed period.
• Collaboration networks indicate strong ties between institutions in the United States, United Kingdom, and Germany.
• Future research trends suggest a growing interest in classification, Alzheimer's disease, and neural oscillations related to spoken language.

Conclusions:

• The field of neuroimaging for spoken language processing is expanding, with significant international collaboration.
• Emerging topics like AI and age-related cognitive decline (Alzheimer's disease) are likely to shape future research.
• The findings offer valuable insights for researchers and institutions planning future studies in this domain.