With the acceleration of the aging society, the incidence of cognitive impairment in the elderly population continues to rise. Identifying the underlying neurobiological mechanisms and demographic factors is of great significance in delaying cognitive decline. In recent years, electroencephalography (EEG), as an objective indicator reflecting brain functional states, has become an important tool for studying cognitive function. Meanwhile, the potential benefits of physical activity on cognitive health have also gained widespread attention. This study aims to explore the relationship between cognitive function and brain electrical activity in elderly individuals, analyze the direct and indirect effects of physical activity on cognitive function, and identify the potential mediating role of demographic variables on cognitive status. Cognitive function screening was conducted on 209 community-dwelling elderly individuals. The Montreal Cognitive Assessment (MoCA) scale was used to evaluate cognitive levels, while resting-state EEG was used to measure multi-region and multi-frequency neural activity. Data on physical activity levels and sociodemographic variables were also collected. Differences were tested, and Pearson correlation analysis and mediation models were employed to assess the horizontal relationships and pathways between variables. Significant differences were observed between elderly individuals with varying levels of cognitive impairment in age, marital status, educational attainment, previous occupation, dietary habits, and place of residence (p < 0.05). MoCA scores were negatively associated with theta power, particularly in the frontal (Fp1, Fp2, F4) and central (C4) regions, and were also negatively correlated with increased beta and alpha power in selected regions (p < 0.05). Physical activity were positively associated with MoCA scores and negatively correlated with theta power at Fp1 and Fp2, as well as beta1 and beta2 power at F4, C4, and O2 (p < 0.05). EEG indices jointly associated with both physical activity and cognitive function included theta power at Fp1, Fp2, F4, C4, and O2, and beta1/beta2 power at F4, C4, and O2 (p < 0.05). Mediation analyses further indicated that specific EEG markers-namely beta2 power at Fp2 and theta power at F4-may partially mediate the relationship between physical activity and cognitive function (p < 0.05). Cognitive function in elderly individuals is influenced by multiple factors, including demographic characteristics, neural activation patterns, and physical activity. Resting-state EEG markers-particularly frontal theta power (e.g., Fp1, Fp2) and alterations in beta power across frontal, central, and occipital regions-may serve as potential biomarkers for cognitive status. Physical activity may enhance cognitive performance in older adults with cognitive impairment partly by modulating these specific neural markers, such as beta2 power at Fp2 and theta power at F4.
Xie et al. (Thu,) studied this question.