Resting state electroencephalography alpha activity predicts cognitive scores in rapid eye movement sleep behavior disorder
Bibliographic record
Abstract
Idiopathic rapid eye movement (REM) sleep behavior disorder (iRBD) is characterized by the loss of atonia during REM sleep, causing dream-enacting behavior. Although iRBD occurs without any clear signs of neurodegenerative disorders, most patients with iRBD eventually develop Parkinson's disease or dementia with Lewy bodies, typically accompanied by cognitive decline. Hence, identifying a biomarker that reflects a neurophysiological state of iRBD has therapeutic potential. Here, we show that spatially clustered alpha (8-12 Hz) oscillatory activities in the scalp can predict cognitive performance in patients with iRBD. A cohort of 62 Korean patients with iRBD underwent resting-state electroencephalography (rsEEG) recordings and participated in the Montreal Cognitive Assessment tests, a common measure for cognitive function. Spectral analysis of the rsEEG data revealed that overall power and transient bursting parameters of alpha activity negatively correlated with Montreal Cognitive Assessment test scores. These results accounted for potential confounding factors such as the spatial distribution of the electrodes, age, sex, emotional states, and medication use. This finding was specific to the alpha activity because theta (4-8 Hz) and beta (12-30 Hz) oscillatory activities were not correlated with the cognitive test scores. Thus, these results suggest that clustered resting-state alpha activity is associated with cognitive impairments in iRBD. Our findings emphasize the importance of rsEEG dynamics in cognitive assessment and highlight the potential utility of rsEEG as an early biomarker for cognitive decline in iRBD patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".