REM sleep EEG slowing reflects brain cholinergic denervation in aging and Mild Cognitive Impairment
Bibliographic record
Abstract
Abstract Brain cholinergic denervation is among the earliest manifestations of Alzheimer’s disease, and rapid eye movement (REM) sleep alterations have also been described early in the course of the disease. While cholinergic activity supports cortical activation during REM sleep, direct evidence for a link between cholinergic degeneration and early REM sleep alterations in humans is still lacking. Here, we tested the long-standing hypothesis that early cholinergic denervation may be associated with REM sleep EEG slowing in older adults with and without Mild Cognitive Impairment. Twenty-four older participants (mean age: 71.29 ± 4.85 years; 58.33% women; 25% participants with amnestic Mild Cognitive Impairment) without dementia or moderate-to-severe obstructive sleep apnea underwent a night of in-laboratory polysomnography, comprehensive neuropsychological evaluation, structural MRI and molecular PET imaging with [ 18 F]-Fluoroethoxybenzovesamicol (FEOBV), known for its sensitivity to quantify brain cholinergic innervation. Voxel-wise multiple regressions assessed the associations between REM sleep characteristics (i.e., REM sleep percentage, relative theta power and EEG slowing ratios, defined as [delta + theta]/[alpha + beta] power) and FEOBV-PET standard uptake value ratio maps corrected for partial volume effects, controlling for sex. Given that FEOBV uptake was higher in women compared to men, we also performed exploratory sex-stratified analyses adjusted for age. Higher REM sleep EEG slowing over frontal and parietal derivations was significantly associated with cortical cholinergic denervation, notably in fronto-parietal areas and the medial temporal lobe ( P<0.005 level, combined with a cluster-level family-wise error correction). Exploratory sex-stratified analyses revealed that REM sleep EEG slowing was associated with cholinergic denervation in medial temporal regions in women, and neocortical regions in men. These findings provide the first direct in vivo evidence that REM sleep EEG slowing could represent a sensitive marker of cortical cholinergic denervation in older adults, prior to dementia onset. Thus, quantitative REM sleep EEG may constitute a promising marker for early diagnosis and disease-modifying interventions in Alzheimer’s disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".