OBJECTIVE: Polysomnography studies in Parkinson's disease (PD) patients show altered sleep microstructure with decreased level of arousability, indicating impaired sleep-wake dynamics in PD. The aim of this study was to investigate dynamical aspects of sleep EEG in PD as compared to healthy controls.
METHODS: In this retrospective, controlled study, we applied a previously established mathematical model of sleep EEG analysis (state space model) to PD patients and age- and gender-matched healthy volunteers (N=64). Dynamical aspects of sleep were quantified by measuring the spectral variability of the sleep EEG (by means of state space velocity).
RESULTS: State space analysis revealed preserved global sleep-wake architecture in PD patients, but the velocity of sleep stage transitions was significantly reduced as compared to healthy controls. Correlation analysis revealed a strong association of state space velocity with arousal scores and daily dopamine agonist intake.
CONCLUSIONS: Quantitative analysis of spectral sleep EEG variability (state space velocity) revealed reduced sleep-wake dynamics in PD patients as compared to control subjects.
SIGNIFICANCE: We propose state space velocity as an objective and quantitative measure for altered sleep microstructure and as a potential biomarker of sleep alterations in PD, not accessible by conventional sleep analysis.