Source-space EEG alpha activity reveals brain age gaps due to neurodegeneration and disparity

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dc.contributor.authorOtero, Monica
dc.contributor.authorCarriel-Rubilar, Felipe I.
dc.contributor.authorHernandez, Hernan
dc.contributor.authorCuadros, Jhosmary
dc.contributor.authorCondado, Jorge G.
dc.contributor.authorSainz-Ballesteros, Agustin
dc.contributor.authorSantamaria-Garcia, Hernando
dc.contributor.authorYıldırım, Ebru
dc.date.accessioned2026-06-18T06:07:53Z
dc.date.available2026-06-18T06:07:53Z
dc.date.issued2026
dc.departmentFakülteler, Sağlık Bilimleri Fakültesi, Fizyoterapi ve Rehabilitasyon Bölümü
dc.description.abstractBrain clocks are promising tools for evaluating brain health. However, most current methods rely on structural neuroimaging. Functionally based approaches remain scarce, especially for assessing age-related neurodegenerative diseases. This study examines whether the brain age gap (BAG), the difference between chronological and predicted brain age, reflects neurodegeneration when estimated from electroencephalographic resting-state (rsEEG) alpha-oscillations, a well-established marker of brain functional aging. It also explores whether alpha-based brain clocks reflect sociodemographic diversity and structural inequality. The BAG was computed using spectral descriptors of alpha-activity in the rsEEG source space of 1228 healthy participants, individuals with mild cognitive impairment (MCI), and patients with Alzheimer's disease or behavioral variant frontotemporal dementia, residing in 10 countries with varying levels of structural inequality. BAGs are increased in MCI and dementia groups, particularly in posterior cortical regions. Structural inequality emerges as the strongest predictor of BAG, surpassing cognition, education, and sex. The findings indicate that an alpha-oscillation-based brain clock provides a sensitive functional marker of brain aging, capable of capturing neurodegenerative processes as well as the impact of social disparities. This scalable, accessible approach to brain health shows promise for translational use and population-wide screening in underserved, resource-limited settings.
dc.identifier.doi10.1038/s42003-026-10205-z
dc.identifier.issn2399-3642
dc.identifier.issue1
dc.identifier.pmid4216-2258
dc.identifier.scopus2-s2.0-105040756265
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1038/s42003-026-10205-z
dc.identifier.urihttps://hdl.handle.net/11501/2747
dc.identifier.volume9
dc.identifier.wosWOS:001781324000001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.institutionauthorYıldırım, Ebru
dc.institutionauthorid0000-0002-7715-3035
dc.language.isoen
dc.publisherNature Research
dc.relation.ispartofCommunications Biology
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectAging
dc.subjectAlpha Rhythm
dc.subjectAlzheimer Disease
dc.subjectBrain
dc.subjectCognitive Dysfunction
dc.subjectElectroencephalography
dc.subjectFemale
dc.subjectHumans
dc.subjectMale
dc.subjectMiddle Aged
dc.subjectNeurodegenerative Diseases
dc.titleSource-space EEG alpha activity reveals brain age gaps due to neurodegeneration and disparity
dc.typeArticle

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