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

Brain 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) α-oscillations, a well-established marker of brain functional aging. It also explores whether α-based brain clocks reflect sociodemographic diversity and structural inequality. The BAG was computed using spectral descriptors of α-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 α-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.

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Publication Details

Journal
Communications Biology
Published
2026-05-21
DOI
https://doi.org/10.1038/s42003-026-10205-z
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Agustina Birba, İlayda Kıyı, Mónica Otero, Nicolás Rubido et al.
Communications Biology
Functional Brain Connectivity Studies
article

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

Agustina Birba, İlayda Kıyı, Mónica Otero, Nicolás Rubido, Renato Anghinah, Tuba Aktürk, Sol Fittipaldi, Susanna Lopez, Jesús M. Cortés, Eduar Herrera, Jhosmary Cuadros, Agustín Sainz‐Ballesteros, Alfredis González‐Hernández, Görsev G. Yener, Jasmin Bonilla‐Santos, Wael El-Deredy, Ruaridh A. Clark, Alberto Fernández, John Ochoa-Gómez, David Huepe, Marcio Soto-Añari, Mario A. Parra, Felipe I. Carriel-Rubilar, Javier Escudero, David Aguillon, Agustina Legaz, Francisco Lopera, Ronaldo Garcia-Reyes, Robert Whelan, Agustin Ibanez, Lütfü Hanoğlu, Rodrigo A. Gonzalez-Montealegre, Claudio Babiloni, Jorge G. Condado, Ebru Yıldırım, Hernando Santamaria-Garcia, Pavel Prado, Pedro A. Valdes-Sosa, Hernan Hernandez, Adolfo M. García, Bahar Güntekin, Daniel Abasolo
article en

Abstract

Brain 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) α-oscillations, a well-established marker of brain functional aging. It also explores whether α-based brain clocks reflect sociodemographic diversity and structural inequality. The BAG was computed using spectral descriptors of α-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 α-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.

Communications Biology
Universidad de Santiago de Chile (CL), Universidad Complutense de Madrid (ES), Izmir University (TR), University of Electronic Science and Technology of China (CN), Işık University (TR), Universidade de São Paulo (BR), University of Strathclyde (GB), Università degli studi di Cassino e del Lazio Meridionale (IT), MRC Cognition and Brain Sciences Unit (GB), Dokuz Eylül University (TR), University of Aberdeen (GB), Trinity College Dublin (IE), Adolfo Ibáñez University (CL), Pontificia Universidad Javeriana (CO), Cuban Neuroscience Center (CU), University of Surrey (GB), San Sebastián University (CL), Istanbul Medipol University (TR), Maastricht University (NL), Universidad de Antioquia (CO), University of San Andrés (AR), BioCruces Health research Institute (ES), Pasqual Maragall Foundation (ES), Instituto de Neurología Cognitiva (AR), Universidad Católica San Pablo (PE), Universidad Cooperativa de Colombia (CO), Hospital Universitario San Ignacio (CO), Global Brain Health Institute (US), Hospital Universitario Nacional de Colombia (CO), Gedik University (TR), Universidad Surcolombiana (CO), Icesi University (CO), University of Valparaíso (CL), Sapienza University of Rome (IT), University of Edinburgh (GB)
Alzheimer's Association, Wellcome Trust, EU Joint Programme – Neurodegenerative Disease Research, Universidad ICESI, Ikerbasque, Basque Foundation for Science, Agencia Nacional de Investigación y Desarrollo, National Institutes of Health, HORIZON EUROPE Framework Programme, Fogarty International Center, Fondo de Fomento al Desarrollo Científico y Tecnológico, Fondo de Financiamiento de Centros de Investigación en Áreas Prioritarias, H2020 Marie Skłodowska-Curie Actions
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