ArticleJournal of Alzheimer's disease : JAD2023
EEG Entropy in REM Sleep as a Physiologic Biomarker in Early Clinical Stages of Alzheimer's Disease.
Article in Journal of Alzheimer's disease : JAD, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 27 citations in OpenAlex.
- Capturing silent oxidative stress in early Alzheimer's disease: prediction of CSF biomarkers from sleep qEEG data.GeroScience · 2026Article
- Technical system of electroencephalography-based brain-computer interface: Advances, applications, and challenges.Neural regeneration research · 2026Article
- Article
- Multiscale dispersion entropy of resting-state EEG in older adults with Alzheimer's disease, mild cognitive impairment, and remitted major depressive disorder.Journal of Alzheimer's disease : JAD · 2026Article
- Association of Sleep Spindle Activity With Cognitive Decline in Early Clinical Stages of Alzheimer Disease.Neurology · 2026Article
- Wavelet Entropy Analysis of EEG Signals During Wake and Sleep in Patients with Alzheimer's Disease: A Pilot Study.Neuropsychiatric disease and treatment · 2026Article
- Caffeine induces age-dependent increases in brain complexity and criticality during sleep.Communications biology · 2025Article
- Is EEG Entropy a Useful Measure for Alzheimer's Disease?Actas espanolas de psiquiatria · 2024Review
- Sleep functional connectivity, hyperexcitability, and cognition in Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Association of Disrupted Delta Wave Activity During Sleep With Long-Term Cardiovascular Disease and Mortality.Journal of the American College of Cardiology · 2024Article
- Predicting Alzheimer's disease CSF core biomarkers: a multimodal Machine Learning approach.Frontiers in aging neuroscience · 2024Article
- Associations Between Repetitive Negative Thinking and Objective and Subjective Sleep Health in Cognitively Healthy Older Adults.Nature and science of sleep · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundAlzheimer's disease (AD) is associated with EEG changes across the sleep-wake cycle. As the brain is a non-linear system, non-linear EEG features across behavioral states may provide an informative physiologic biomarker of AD. Multiscale fluctuation dispersion entropy (MFDE) provides a sensitive non-linear measure of EEG information content across a range of biologically relevant time-scales.
objectiveTo evaluate MFDE in awake and sleep EEGs as a potential biomarker for AD.
methodsWe analyzed overnight scalp EEGs from 35 cognitively normal healthy controls, 23 participants with mild cognitive impairment (MCI), and 19 participants with mild dementia due to AD. We examined measures of entropy in wake and sleep states, including a slow-to-fast-activity ratio of entropy (SFAR-entropy). We compared SFAR-entropy to linear EEG measures including a slow-to-fast-activity ratio of power spectral density (SFAR-PSD) and relative alpha power, as well as to cognitive function.
resultsSFAR-entropy differentiated dementia from MCI and controls. This effect was greatest in REM sleep, a state associated with high cholinergic activity. Differentiation was evident in the whole brain EEG and was most prominent in temporal and occipital regions. Five minutes of REM sleep was sufficient to distinguish dementia from MCI and controls. Higher SFAR-entropy during REM sleep was associated with worse performance on the Montreal Cognitive Assessment. Classifiers based on REM sleep SFAR-entropy distinguished dementia from MCI and controls with high accuracy, and outperformed classifiers based on SFAR-PSD and relative alpha power.
conclusionSFAR-entropy measured in REM sleep robustly discriminates dementia in AD from MCI and healthy controls.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.