Characteristics of the top 100 cited electroencephalography articles on aging: a bibliometric analysis.

Electroencephalography (EEG) is a widely used tool in neuroscience. To explore the features of the top 100 cited articles related to EEG and aging over the past decade, we conducted a bibliometric analysis using Web of Science Core Collection (WoSCC) data as of January 21, 2024. The selected top 100 cited papers were analyzed using VOSviewer and Excel. We examined the distribution of publication years, authors, institutions, countries/regions, and journals. Hotspots were identified through keyword analysis. The analyzed articles were published between 2014 and 2021, with the majority being published before 2020 (n=91). Citation counts in WoSCC ranged from 24 to 250, with a median of 40 and a mean of 53. A total of 818 authors from 283 institutions in 35 countries/territories contributed to these top papers. The United States of America (USA) (n=37), Germany (n=14), and Canada (n=11) ranked in the top three in terms of total publications or citations. The predominant journals were in the fields of Neuroscience (n=58), Geriatrics & Gerontology (n=22), Clinical Neurology (n=13), and Anesthesiology (n=9), which published most of the high-quality articles. Key themes included EEG, aging, Alzheimer's disease, mild cognitive impairment, functional connectivity, and alpha oscillations. Emerging topics included sleep, machine learning, delirium, postoperative cognitive function, virtual reality, monitoring, resting state, coherence, and transcranial direct current stimulation. In conclusion, this study provides a comprehensive overview of the trends in scientific literature on EEG in aging over the past decade. Authors and institutions from North America, Europe, and East Asia led in contributions. Journals focusing on neuroscience, geriatrics, and anesthesiology published the majority of articles. Degenerative neurological diseases and cognitive impairment were prominent topics, suggesting future studies should explore EEG's diagnostic utility for these disorders.