Frontiers in Aging Neuroscience
Resting-state cortical alpha frequency in Parkinson’s disease and multiple system atrophy: associations with diagnosis, age, and symptom burden
By Daichao Chen, Huada Tang, Yanfei Pan and 11 others.
Abstract
Background Parkinson’s disease (PD) and multiple system atrophy (MSA) are clinically overlapping neurodegenerative disorders that present with a complex, heterogeneous burden of motor and non-motor symptoms. Resting-state EEG reveals that cortical alpha slowing is a hallmark of pathological aging, yet its specific presence and clinical significance in these distinct synucleinopathies remain incompletely understood. Therefore, precisely quantifying the individual alpha frequency serves as a critical, non-invasive approach to characterize cortical network dysfunction across synucleinopathies and evaluate how aging moderates its association with clinical symptom burden. Methods We analyzed source-reconstructed resting-state EEG data from 104 participants, comprising patients with PD, patients with the parkinsonian (MSA-P) and cerebellar subtypes (MSA-C) of MSA, and healthy controls. To accurately capture oscillatory dynamics, a data-driven masking empirical mode decomposition approach was applied to extract the individual alpha frequency across canonical cortical networks. General linear models tested diagnostic group differences, age-related effects, and age-dependent associations between individual alpha frequency and clinical symptom scores. Results Relative to healthy controls, both PD and MSA-C exhibited significant lower cortical IAF, whereas MSA-P showed no significant global IAF difference. At the network level, significant reduction of IAF was detected in the visual and dorsal attention networks in both PD and MSA-C. Advancing age independently contributed to alpha slowing across all participants without accelerating the disease-related trajectories. Notably, chronological age significantly moderated the relationship between alpha slowing and non-motor symptoms. In older patients, reduced individual alpha frequency was strongly associated with a higher burden of overall non-motor, autonomic, and psychiatric/cognitive symptoms, a relationship not observed in younger patients or with motor symptom severity. Conclusion Cortical alpha slowing was detected in PD and MSA-C, but not in MSA-P. Age independently contributes to alpha slowing and strengthens its association with non-motor symptom burden, supporting age-aware interpretation of resting-state electroencephalography biomarkers in synucleinopathies.



