AUTHOR=Yao Shun , Zhu Jieying , Li Shuiyan , Zhang Ruibin , Zhao Jiubo , Yang Xueling , Wang You 

TITLE=Bibliometric Analysis of Quantitative Electroencephalogram Research in Neuropsychiatric Disorders From 2000 to 2021

JOURNAL=Frontiers in Psychiatry

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/psychiatry/articles/10.3389/fpsyt.2022.830819

DOI=10.3389/fpsyt.2022.830819

ISSN=1664-0640

ABSTRACT=Background: With the development of quantitative electroencephalography (QEEG), an increasing number of studies have been published on the clinical use of QEEG in the past two decades, especially in the diagnosis, treatment and prognosis of neuropsychiatric disorders. However, to date, the current status and developing trends of this research field have not been systematically analyzed from a macroscopic perspective. The present study aimed to identify the hot spots, knowledge base and frontiers of QEEG research in neuropsychiatric disorders from 2000 to 2021 through bibliometric analysis. 
Methods: QEEG related publications in neuropsychiatric field from 2000 to 2021 were retrieved from the Web of Science Core Collection(WOSCC). CiteSpace (5.8R3), VOSviewer (1.6.17) software and the online literature analysis platform (bibliometric.com) were employed to perform bibliographic and visualized analysis. 
Results: 1904 publications between 2000 and 2021 were retrieved. QEEG related publications in neuropsychiatric disorders increased steadily from 2000 to 2021, and research in psychiatric disorders requires more attention in comparison with research in neurological disorders. During the last two decades, QEEG has been mainly applied to neurodegenerative diseases, cerebrovascular diseases and mental disorders to reveal the pathological mechanisms, to assist clinical diagnosis, and to promote the selection of effective treatments. The recent hot topics focused on QEEG utilization in neurodegenerative disorders like Alzheimer’s and Parkinson's disease, TBI and related cerebrovascular diseases, epilepsy and seizure, attention deficit hyperactivity disorder, and other mental disorders like major depressive disorder and schizophrenia. In addition, studies to cross-validate QEEG biomarkers, to develop new biomarkers (e.g., functional connectivity and complexity), and to extract compound biomarkers by machine learning were the emerging trends. 
Conclusion: The present study integrated bibliometric information on the current status, the knowledge base and future directions of QEEG studies in neuropsychiatric disorders from a macroscopic perspective. It may provide valuable insights for researchers focusing on the utilization of QEEG in this field.