Research hotspots and trends of neuroimaging in social anxiety: a CiteSpace bibliometric analysis based on Web of Science and Scopus database

斯科普斯 神经影像学 科学网 社交焦虑 认知 心理学 文献计量学 焦虑 梅德林 图书馆学 计算机科学 政治学 神经科学 精神科 法学
作者
Peng Zhang,Jianing Zhang,Mingliang Wang,Shuyuan Feng,Yuqing Yuan,Ding Lin
出处
期刊:Frontiers in Behavioral Neuroscience [Frontiers Media]
卷期号:18: 1448412-1448412 被引量:5
标识
DOI:10.3389/fnbeh.2024.1448412
摘要

Background This study focused on the research hotspots and development trends of the neuroimaging of social anxiety (SA) in the past 25 years. Methods We selected 1,305 studies on SA neuroimaging from the Web of Science and Scopus from January 1998 to December 2023. CiteSpace was used to analyze the number of published articles visually, cited references, cooperation among authors and institutions, co-occurrence of keywords, clustering of keywords, burst of keywords, and time zone of co-occurring keywords. Results A total of 1,305 articles were included, and the annual number of articles published over nearly 25 years showed the overall trend is on the rise. The analysis of author and institutional collaboration reveals that most authors collaborate closely. Among them, the team led by Pine, Daniel S published 59 articles, making it the most central team. Harvard University is identified as the most central institution in this network. The research hotspots can be categorized into four areas: research techniques, cognitive processing research areas, core brain regions and brain networks, and the neural predictors of treatment outcomes in SA. The most recent burst keywords are “cognitive behavioral therapy,” “systematic review,” “machine learning,” “major clinical study,” “transcranial direct current stimulation,” “depression,” and “outcome assessment,” which provided clues on research frontiers. Based on the burst map and keyword time zone map, it appears that exploring the activity of brain regions involved in cognitive processing, such as face processing and attentional bias, as well as the comorbidity of SA and depression, through brain imaging technology, using brain signals as predictors of treatment outcomes in SA. Conclusion This study conducted a comprehensive, objective, and visual analysis of publications, and revealed hot topics and trends concerning the study of the brain mechanism of SA from 1998 to 2023. This work might assist researchers in identifying new insights on potential collaborators and institutions, hot topics, and research directions.
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