Shared Spectral Parameters Between EEG and Basal Ganglia LFP Distinguish Sleep-Specific Oscillations in Parkinson's Disease.

BACKGROUND

In Parkinson's disease (PD), sleep-related oscillatory dynamics between basal ganglia and cortical nodes may inform sleep dysfunction. The subthalamic nucleus (STN) is highly interconnected with human sleep circuitry and is a current target of interest for sleep neuromodulation.

METHODS

To investigate correlated cortical-subcortical activity, we recorded simultaneous PSG and STN local field potentials (LFP) in 19 patients undergoing deep brain stimulation (DBS) for PD. We evaluated the correlation in spectral power between STN-LFP and EEG during polysomnogram (PSG)-defined stages of sleep. In addition, we analyzed aperiodic 1/f spectral parameters (exponent and offset), which have been identified as markers of arousal across sleep stages. Finally, we trained classifiers on aperiodic features to test whether 1/f structure alone could recover PSG-defined sleep stages from EEG and STN-LFP.

RESULTS

Results revealed a significant interaction between recording modality and sleep stage. During wakefulness and REM sleep, STN-LFP exhibited a significantly steeper spectral slope compared to scalp EEG. However, this dissociation diminished with sleep depth; slopes appeared more similar during N2 and reversed during N3, where EEG became steeper than LFP. Across subjects, the aperiodic component showed robust state dependence and modality differences with STN-LFP maintaining higher exponents overall. STN-LFP aperiodic features alone classified sleep stages above chance and outperformed scalp EEG, approaching the combined-modality ceiling.

CONCLUSION

These findings highlight distinct subcortical electrophysiological signatures in sleep-dependent regulation of neural arousal across brain networks in PD. These insights offer potential biomarkers for both invasive and non-invasive forms of closed-loop neuromodulation strategies targeting sleep dysfunction.

TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT04620551.