Longitudinal resting-state EEG-based modeling predicts phenoconversion and delineates heterogeneity in isolated REM
Soonhyun Yook1, Jung-Won Shin2, Tae-Gon Noh3
1University of Southern California.
Research Square
|April 3, 2026
Summary
Subtype and Stage Inference (SuStaIn) modeling of EEG identified two REM sleep behavior disorder subtypes. Specific longitudinal changes predict high risk for Lewy body diseases.
Area of Science:
- Neuroscience
- Neurology
- Sleep Medicine
Background:
- Isolated REM sleep behavior disorder is a prodromal syndrome for Lewy body diseases.
- High heterogeneity and limited neurophysiologic markers hinder phenoconversion prediction.
Purpose of the Study:
- To apply Subtype and Stage Inference (SuStaIn) modeling to longitudinal resting-state EEG data.
- To identify neurophysiologic markers for stratifying heterogeneity and predicting phenoconversion in REM sleep behavior disorder.
Main Methods:
- Longitudinal resting-state EEG data from 285 participants were analyzed using SuStaIn modeling.
- Two distinct subtypes were identified: posterior beta-dominant and frontal slow-wave-dominant.
- Longitudinal validation assessed subtype shifting and stage advancement.
Main Results:
- Subtype 1 (posterior beta-dominant) showed minimal progression and no phenoconversion.
- Subtype 2 (frontal slow-wave-dominant) exhibited progressive delta/theta increases and cognitive decline.
- Subtype shifting and accelerated stage advancement (ΔStage ≥ 2) identified individuals at exceptionally high risk for phenoconversion (0-15% survival by 7.5 years).
Conclusions:
- SuStaIn modeling effectively stratifies prodromal heterogeneity in REM sleep behavior disorder.
- Longitudinal subtype shifting and stage advancement are robust predictors of neurodegenerative progression.
- These findings enhance the predictive power of neurophysiologic markers for Lewy body diseases.
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