No abstract

Background: Sleep disturbance is a prevalent and highly disabling comorbidity in individuals with Parkinson's disease (PD) that leads to worsening of daytime symptoms, accelerated disease progression and reduced quality of life. Objectives: We aimed to investigate changes in sleep neurophysiology in PD particularly during non-rapid eye movement (NREM) sleep, both in the presence and absence of deep brain stimulation (DBS). Methods: Multi-night (n=58) intracranial recordings were performed at-home, from chronic electrocorticography and subcortical electrodes, with sensing-enabled DBS pulse generators, paired with portable polysomnography. Four people with PD and one person with cervical dystonia were evaluated to determine the neural structures, signals and connections modulated during NREM sleep and prior to spontaneous awakenings. Recordings were performed both ON and OFF DBS in the presence of conventional dopaminergic replacement medications. Results: We demonstrate an increase in cortico-basal slow wave activity in delta (1-4 Hz) and a decrease in beta (13-31 Hz) during NREM (N2 and N3) versus wakefulness in PD. Cortical-subcortical coherence was also found to be higher in the delta range and lower in the beta range during NREM versus wakefulness. DBS stimulation resulted in a further elevation in cortical delta and a decrease in alpha (8-13 Hz) and low beta (13-15 Hz) power compared to the OFF stimulation state. During NREM sleep, we observed a strong inverse interaction between subcortical beta and cortical slow wave activity and found that subcortical beta increases prior to spontaneous awakenings. Conclusions: Chronic, multi-night recordings in PD reveal opposing sleep stage specific modulations of cortico-basal slow wave activity in delta and subcortical beta power and connectivity in NREM, effects that are enhanced in the presence of DBS. Within NREM specifically, subcortical beta and cortical delta are strongly inversely correlated and subcortical beta power is found to increase prior to and predict spontaneous awakenings. We find that DBS therapy appears to improve sleep in PD partially through direct modulation of cortico-basal beta and delta oscillations. Our findings help elucidate a contributory mechanism responsible for sleep disturbances in PD and highlight potential biomarkers for future precision neuromodulation therapies targeting sleep and spontaneous awakenings.

Background: Cognitive dysfunction is common in Parkinson’s disease (PD) and is diagnosed by complex, time-consuming psychometric tests which are affected by language and education, subject to learning effects, and not suitable for continuous monitoring of cognition. Objectives: We developed and evaluated an EEG-based biomarker to index cognitive functions in PD from a few minutes of resting-state EEG. Methods: We hypothesized that synchronous changes in EEG across the power spectrum can measure cognition. We optimized a data-driven algorithm to efficiently capture these changes and index cognitive function in 100 PD and 49 control participants. We compared our EEG-based cognitive index with the Montreal cognitive assessment (MoCA) and cognitive tests across different domains from the National Institutes of Health (NIH) Toolbox using cross-validation schemes, regression models, and randomization tests. Results: We observed cognition-related changes in EEG activities over multiple spectral rhythms. Utilizing only 8 best-performing EEG electrodes, our proposed index strongly correlated with cognition (rho = 0.68, p value < 0.001 with MoCA; rho ≥ 0.56, p value < 0.001 with cognitive tests from the NIH Toolbox) outperforming traditional spectral markers (rho = -0.30 – 0.37). The index showed a strong fit in regression models (R2 = 0.46) with MoCA, yielded 80% accuracy in detecting cognitive impairment, and was effective in both PD and control participants. Conclusions: Our approach is computationally efficient for real-time indexing of cognition across domains, implementable even in hardware with limited computing capabilities, making it potentially compatible with dynamic therapies such as closed-loop neurostimulation, and will inform next-generation neurophysiological biomarkers for monitoring cognition in PD and other neurological diseases.