Medication‐invariant resting aperiodic and periodic neural activity in Parkinson's disease

Parkinson's disease (PD) has been associated with greater total power in canonical frequency bands (i.e., alpha, beta) of the resting electroencephalogram (EEG). However, PD has also been associated with a reduction in the proportion of total power across all frequency bands. This discrepancy may be explained by aperiodic activity (exponent and offset) present across all frequency bands. Here, we examined differences in the eyes‐open (EO) and eyes‐closed (EC) resting EEG of PD participants (N = 26) on and off medication, and age‐matched healthy controls (CTL; N = 26). We extracted power from canonical frequency bands using traditional methods (total alpha and beta power) and extracted separate parameters for periodic (parameterized alpha and beta power) and aperiodic activity (exponent and offset). Cluster‐based permutation tests over spatial and frequency dimensions indicated that total alpha and beta power, and aperiodic exponent and offset were greater in PD participants, independent of medication status. After removing the exponent and offset, greater alpha power in PD (vs. CTL) was only present in EO recordings and no reliable differences in beta power were observed. Differences between PD and CTL in the resting EEG are likely driven by aperiodic activity, suggestive of greater relative inhibitory neural activity and greater neuronal spiking. Our findings suggest that resting EEG activity in PD is characterized by medication‐invariant differences in aperiodic activity which is independent of the increase in alpha power with EO. This highlights the importance of considering aperiodic activity contributions to the neural correlates of brain disorders. Parkinson's disease (PD) is marked not only by greater total power in alpha and beta frequency bands of EEG but also with a reduction in total power potentially due to changes in aperiodic activity. We provide evidence that a greater exponent and offset (greater inhibition) in aperiodic activity drive frequency band changes in PD. Furthermore, we demonstrate the efficacy of EEG as a non‐invasive technique to assess changes in excitation and inhibition (E:I) balance and PD biomarkers.