Magnetoencephalography-based prediction of longitudinal symptom progression in Parkinson’s disease

The progressive motor dysfunction of Parkinson’s disease (PD) has been linked to widespread functional changes within the basal ganglia-thalamic-cortical network, particularly in the beta frequency range (13-30 Hz). However, the longitudinal evolution of cortical neurophysiological changes and their relationship to clinical progression remain poorly understood, particularly when accounting for the aperiodic component of the neuronal signal.

We aimed to close this gap by conducting a longitudinal resting-state magnetoencephalography (MEG) study in 27 persons with PD and 30 healthy individuals with a mean follow-up time of four years. Clinical symptom progression was assessed using the annual change in MDS-UPDRS-III motor scale, adjusted for changes in dopamine replacement therapy. Neurophysiological changes were assessed using source reconstructed MEG data parcellated into 68 cortical regions, from which power spectra were parameterized to separate oscillatory peaks in the beta, alpha (8-12 Hz), and theta (4-8 Hz) frequency bands from the aperiodic component described by its exponent and offset.

Neurophysiologically, we observed that a steepening of the aperiodic slope in the left sensorimotor region was associated with a progression of rigidity, and that an increase in the aperiodic offset with an increase in bradykinesia. Peak beta power in parieto-temporo-occipital regions was elevated at baseline compared with healthy controls, correlating with less severe bradykinesia. This negative relationship weakened over time in patients with progressive bradykinesia but remained stable in non-progressors, suggesting an association with compensatory mechanisms.

Using partial least squares regression to predict future motor disease progression from baseline neurophysiological features, the model was able to explain 19.5 % of the variability in motor progression in an independent validation cohort consisting of 18 persons with PD, with the aperiodic features contributing most to the predictions.

Our findings demonstrate a close relationship between cortical PD-related neurophysiological alterations and longitudinal changes in symptom severity. The results emphasize the importance of separating aperiodic neural activity from periodic oscillations since we show that a progressive steepening of the aperiodic exponent in the sensorimotor region represented the most prominent PD-related longitudinal cortical change, potentially reflecting a progressive shift of the excitatory-inhibitory balance towards inhibition. Furthermore, our results challenge traditional interpretations of cortical beta oscillations as purely antikinetic and highlight the potential predictive value of simple resting-state neurophysiological features for predicting future disease progression in PD.