The aging rhythm: spatio-temporal dynamics of resting alpha oscillations in young and older brains

Aging is associated with substantial alterations in brain oscillatory activity, particularly within the alpha band (8-12 Hz). Yet, little is known about how aging affects the spatial propagation of alpha oscillations across cortical networks. In addition, although previous EEG studies have consistently reported age-related slowing of alpha peak frequency and changes in alpha power, the interpretation of these findings remains debated because oscillatory measures are influenced by age-related modifications in the aperiodic component of the power spectrum. Here, we investigated age-related changes in both the spectral and spatiotemporal properties of alpha activity using resting-state EEG data from a large cohort of younger (N = 326) and older adults (N = 108). To address the debate in the literature, analyses explicitly accounted for the aperiodic component of the EEG power spectrum. Consistent with previous literature, older adults exhibited a robust slowing of the individual alpha peak frequency, along with reductions in the aperiodic exponent and offset. Importantly, alpha-band power was also significantly reduced in older adults even after correcting for aperiodic activity, indicating that age-related alpha alterations cannot be fully explained by non-oscillatory spectral changes alone. Beyond conventional spectral measures, we characterized alpha-band traveling waves and identified age-related alterations in their propagation dynamics, particularly within frontal regions. Older adults showed enhanced medial-to-lateral and interhemispheric propagation patterns, suggesting reduced hemispheric segregation and increased bilateral coordination of rhythmic activity. These findings extend current models of cognitive aging by demonstrating that aging affects not only the spectral characteristics of alpha oscillations but also their large-scale spatiotemporal organization. Together, the results support the view that aging involves a functional reorganization of cortical communication dynamics, potentially reflecting compensatory mechanisms within distributed neural networks.