Quantitative Sleep Electroencephalogram in Parkinson’s Disease: A Case-Control Study

Author:

Memon Adeel A.123,Catiul Corina1,Irwin Zachary34,Pilkington Jennifer1,Memon Raima A.56,Joop Allen1,Wood Kimberly H.17,Cutter Gary8,Miocinovic Svjetlana9,Amara Amy W.110

Affiliation:

1. Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA

2. Rockefeller Neuroscience Institute, Department of Neurology, West Virginia University, Morgantown, WV, USA

3. Neuroengineering Ph.D. program, University of Alabama at Birmingham, Birmingham, AL, USA

4. Department of Neurosurgery, University of Alabama at Birmingham, Birmingham, AL, USA

5. Department of Pathology, University of Alabama at Birmingham, Birmingham, AL, USA

6. Department of Pathology, Mayo Clinic, Rochester, MN, USA

7. Department of Psychology, Samford University, Birmingham, AL, USA

8. Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA

9. Department of Neurology, Emory University, Atlanta, GA, USA

10. Department of Neurology, University of Colorado, Anschutz Medical Center, Aurora, CO, USA

Abstract

Background: Sleep disorders are common in Parkinson’s disease (PD) and include alterations in sleep-related EEG oscillations. Objective: This case-control study tested the hypothesis that patients with PD would have a lower density of Scalp-Slow Wave (SW) oscillations and higher slow-to-fast frequencies ratio in rapid eye movement (REM) sleep than non-PD controls. Other sleep-related quantitative EEG (qEEG) features were also examined, including SW morphology, sleep spindles, and Scalp-SW spindle phase-amplitude coupling. Methods: Polysomnography (PSG)-derived sleep EEG was compared between PD participants (n = 56) and non-PD controls (n = 30). Following artifact rejection, sleep qEEG analysis was performed in frontal and central leads. Measures included SW density and morphological features of SW and sleep spindles, SW-spindle phase-amplitude coupling, and spectral power analysis in Non-REM (NREM) and REM. Differences in qEEG features between PD and non-PD controls were compared using two-tailed Welch’s t-tests, and correction for multiple comparisons was performed per the Benjamini-Hochberg method. Results: SW density was lower in PD than in non-PD controls (F = 13.5, p’ = 0.003). The PD group also exhibited higher ratio of slow REM EEG frequencies (F = 4.23, p’ = 0.013), higher slow spindle peak frequency (F = 24.7, p’ < 0.002), and greater SW-spindle coupling angle distribution non-uniformity (strength) (F = 7.30, p’ = 0.034). Conclusion: This study comprehensively evaluates sleep qEEG including SW-spindle phase amplitude coupling in PD compared to non-PD controls. These findings provide novel insights into how neurodegenerative disease disrupts electrophysiological sleep rhythms. Considering the role of sleep oscillatory activity on neural plasticity, future studies should investigate the influence of these qEEG markers on cognition in PD.

Publisher

IOS Press

Subject

Cellular and Molecular Neuroscience,Neurology (clinical)

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