Visual analysis of high-definition transcranial direct current stimulation research / 中国组织工程研究

ABSTRACT

BACKGROUND:In recent years,High-definition transcranial direct current stimulation(HD-tDCS)has garnered significant attention due to its potential non-invasive modulation of brain function.However,there is still a lack of visual analysis in the literature regarding this technique. OBJECTIVE:To perform a visual analysis of HD-tDCS-related research so as to explore the current status and trends in this field. METHODS:English literature related to HD-tDCS was retrieved from the Web of Science Core Collection database covering the period from January 1,2010 to May 6,2023.The VOSviewer software was used to visualize and analyze the source journals,countries/regions,authors,institutions,cited references,and keywords of the included literature,creating a knowledge map to uncover the research landscape and hotspots. RESULTS AND CONCLUSION:A total of 336 articles were included,showing a consistent increase in the annual publication count of HD-tDCS research.Among these,the United States contributed the highest number of publications(141 articles)with 4 221 citations,followed by China with 70 articles and 401 citations.Brain Stimulation was the most prolific journal(28 articles),Marom Bikson was the most productive author(37 articles),and The City College of New York was the most active institution(35 articles).The most frequently mentioned keywords in the field included motor cortex,regulation,working memory,excitability,and dorsolateral prefrontal cortex.Notable recent keywords in the last 5 years include attention-deficit/hyperactivity disorder,brain networks,and stimulation intensity.Currently,the volume of HD-tDCS research is relatively limited,but is on an upward trajectory,indicating substantial research potential.It is expected that future studies in this domain will continue to focus on the application of HD-tDCS in cognitive and neuropsychiatric disorders,while also exploring its therapeutic mechanisms targeting the motor cortex and dorsolateral prefrontal cortex based on brain network analysis.