Multiple, not just Beta-Gamma, phase-amplitude couplings are associated with Parkinson's disease and related intervention effects.

OBJECTIVE

1) To evaluate the importance of various EEG Phase Amplitude Couplings (PACs) in predicting motor vigor (MV) in Parkinson's Disease (PD). 2) To determine the effects of dopaminergic medication and non-invasive galvanic vestibular stimulation (GVS) on MV-related PACs.

METHODS

EEG data from 18 PD patients in comparison to 20 HC controls, executing a simple overlearned handgrip task was used, to identify PD-specific alterations. A deep learning model, PACNET, based on the VGG-16 architecture, was used to predict MV from a visual representation of different PACs.

RESULTS

Delta-Beta, Theta-, Alpha-, and Beta-Gamma PACs were important for MV prediction. In PD subjects, GVS affected Delta-Beta, and Theta-, Beta- Gamma PAC's role in MV prediction in a stimulation-specific manner. Delta-Beta and Theta-Gamma PACs were more relevant for PD patients' MV prediction after L-dopa medication.

CONCLUSIONS

Multiple PACs are important for MV in Parkinson's disease. Therapeutic interventions affect PAC/MV associations.

SIGNIFICANCE: Multiple PACs, not just Beta-Gamma, are important for MV in PD and may serve as targets for neuromodulation strategies. A combined assessment of PACs could be a valuable biomarker for both disease evaluation and therapeutic effects in PD.