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

• Type of Material: Article
• Authors: Adeel A Memon, University of Alabama Birmingham; Corina Catiul, University of Alabama Birmingham; Zachary Irwin, University of Alabama Birmingham; Jennifer Pilkington, University of Alabama Birmingham; Raima A Memon, University of Alabama Birmingham; Allen Joop, University of Alabama Birmingham; Kimberly H Wood, University of Alabama Birmingham; Gary Cutter, University of Alabama Birmingham; Svjetlana Miocinovic, Emory University; Amy W Amara, University of Alabama Birmingham
• Language: English
• Date: 2023-01-01
• Publisher: IOS PRESS
• Publication Version: Final Published Version
• Copyright Statement: © 2023 – The authors. Published by IOS Press
• License: Creative Commons Attribution-NonCommercial 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.3233/JPD-223565
• Title of Journal or Parent Work: JOURNAL OF PARKINSONS DISEASE
• Volume: 13
• Issue: 3
• Start Page: 351
• End Page: 365
• Keywords: Science & Technology; Life Sciences & Biomedicine; sleep spindles; OSCILLATION; rapid eye movement sleep; slow waves; Neurosciences & Neurology; HIPPOCAMPAL; coupling; EYE-MOVEMENT SLEEP; SPINDLES; quantitative sleep EEG; ATROPHY; EEG; phase-amplitude; REM-SLEEP; Parkinson's disease; non-rapid eye movement sleep; Neurosciences; ALPHA; SLOW WAVES
• Research Categories: Health Sciences, Pathology

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.