{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,6]],"date-time":"2026-06-06T15:13:57Z","timestamp":1780758837820,"version":"3.54.1"},"reference-count":64,"publisher":"SAGE Publications","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAD"],"published-print":{"date-parts":[[2023,2,14]]},"abstract":"<jats:p>Background: Alzheimer\u2019s 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. Objective: To evaluate MFDE in awake and sleep EEGs as a potential biomarker for AD. Methods: We 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. Results: SFAR-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. Conclusion: SFAR-entropy measured in REM sleep robustly discriminates dementia in AD from MCI and healthy controls.<\/jats:p>","DOI":"10.3233\/jad-221152","type":"journal-article","created":{"date-parts":[[2023,1,13]],"date-time":"2023-01-13T12:30:56Z","timestamp":1673613056000},"page":"1557-1572","source":"Crossref","is-referenced-by-count":28,"title":["EEG Entropy in REM Sleep as a Physiologic Biomarker in Early Clinical Stages of Alzheimer\u2019s Disease"],"prefix":"10.1177","volume":"91","author":[{"given":"Hamed","family":"Azami","sequence":"first","affiliation":[{"name":"Massachusetts Alzheimer\u2019s Disease Research Center, Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sebastian","family":"Moguilner","sequence":"additional","affiliation":[{"name":"Massachusetts Alzheimer\u2019s Disease Research Center, Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hector","family":"Penagos","sequence":"additional","affiliation":[{"name":"Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rani A.","family":"Sarkis","sequence":"additional","affiliation":[{"name":"Department of Neurology, Brigham and Women\u2019s Hospital, Boston, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Steven E.","family":"Arnold","sequence":"additional","affiliation":[{"name":"Massachusetts Alzheimer\u2019s Disease Research Center, Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen N.","family":"Gomperts","sequence":"additional","affiliation":[{"name":"Massachusetts Alzheimer\u2019s Disease Research Center, Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alice D.","family":"Lam","sequence":"additional","affiliation":[{"name":"Massachusetts Alzheimer\u2019s Disease Research Center, Department of Neurology, Massachusetts General Hospital, Charlestown, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","reference":[{"key":"10.3233\/JAD-221152_ref1","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1016\/j.jalz.2019.01.010","article-title":"2019 Alzheimer\u2019s disease facts and figures","volume":"15","author":"Alzheimer\u2019s Association","year":"2019","journal-title":"Alzheimers Dement"},{"key":"10.3233\/JAD-221152_ref2","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1016\/S0140-6736(15)01124-1","article-title":"Alzheimer\u2019s disease","volume":"388","author":"Scheltens","year":"2016","journal-title":"Lancet"},{"key":"10.3233\/JAD-221152_ref3","doi-asserted-by":"crossref","first-page":"15056","DOI":"10.1038\/nrdp.2015.56","article-title":"Alzheimer\u2019s disease","volume":"1","author":"Masters","year":"2015","journal-title":"Nat Rev Dis Primers"},{"key":"10.3233\/JAD-221152_ref4","doi-asserted-by":"crossref","first-page":"1051","DOI":"10.3233\/JAD-140843","article-title":"Biomarkers for preclinical Alzheimer\u2019s disease","volume":"42","author":"Tan","year":"2014","journal-title":"J Alzheimers Dis"},{"key":"10.3233\/JAD-221152_ref5","doi-asserted-by":"crossref","first-page":"954","DOI":"10.1038\/s41591-021-01382-x","article-title":"Biomarkers for neurodegenerative diseases","volume":"27","author":"Hansson","year":"2021","journal-title":"Nat Med"},{"key":"10.3233\/JAD-221152_ref6","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1186\/s13195-020-00588-4","article-title":"The clinical promise of biomarkers of synapse damage or loss in Alzheimer\u2019s disease","volume":"12","author":"Colom-Cadena","year":"2020","journal-title":"Alzheimers Res Ther"},{"key":"10.3233\/JAD-221152_ref7","doi-asserted-by":"crossref","first-page":"1287","DOI":"10.1016\/j.clinph.2020.03.003","article-title":"Early diagnosis of Alzheimer\u2019s disease: The role of biomarkers including advanced EEG signal analysis. 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