A scientometrics analysis of physical activity and transcranial stimulation research

Abstract

Background: The search for alternatives to improve physical performance is rising, and in recent years has been focused on the brain. No bibliometric study analyzing research on physical activity (PA) and transcranial stimulation has been found in the scientific literature. Aims: To provide an overview of the existing scientific research on PA and transcranial brain stimulation in healthy and sports participants, using a bibliometric analysis and graphic mapping of the references in the field. To do this, we analyze annual publication trends in this area, identifying the most productive and cited authors, journals and countries with the highest number of publications, and the most cited documents and keywords. Methods: Those publications related to this area, published in journals indexed in the web of science main collection were retrieved and analyzed using the traditional laws of bibliometrics. Results: A total of 305 documents were found. Annual publications followed an exponential growth trend (R2 = 94.2%); with A. J. Pearce (9 documents) is the most productive coauthor and M.C. Ridding, H. Theoret and M. Lassonde as the most prominent (with 5 most cited papers). The USA (67 papers) and the journal Frontiers in Human Neuroscience (12 papers) were the most productive country and journal respectively. The paper “Action anticipation and motor resonance in elite basketball players” was the most cited paper and “transcranial magnetic stimulation” was the most used keyword. Conclusion: There are extensive research networks throughout the world, with the USA leading the production. Publications on the issue are of high interest in the scientific community as an exponential increase in publications over the last few years was found. The contribution of these findings is to offer a complete picture of the relationship between PA and transcranial brain stimulation in healthy individuals and athletes. Therefore, this comprehensive analysis provides fruitful information for sports researchers and policymakers to make future correct decisions about how to better design and implement training interventions in these groups of individuals.