TY - JOUR
T1 - Diversity-sensitive brain clocks linked to biophysical mechanisms in aging and dementia
AU - Coronel-Oliveros, Carlos
AU - Moguilner, Sebastián
AU - Hernandez, Hernan
AU - Cruzat, Josephine
AU - Baez, Sandra
AU - Medel, Vicente
AU - Cuadros, Jhosmary
AU - Santamaria-Garcia, Hernando
AU - Valdes-Sosa, Pedro A.
AU - Lopera, Francisco
AU - Ochoa-Gómez, John Fredy
AU - González- Hernández, Alfredis
AU - Bonilla-Santos, Jasmin
AU - Gonzalez-Montealegre, Rodrigo A.
AU - Aktürk, Tuba
AU - Yıldırım, Ebru
AU - Anghinah, Renato
AU - Legaz, Agustina
AU - Fittipaldi, Sol
AU - Yener, Görsev G.
AU - Escudero, Javier
AU - Babiloni, Claudio
AU - Lopez, Susanna
AU - Whelan, Robert
AU - Fernández, Alberto
AU - Huepe, David
AU - Di Caterina, Gaetano
AU - Soto-Añari, Marcio
AU - Gonzalez-Gomez, Raul
AU - Herrera, Eduar
AU - Abasolo, Daniel
AU - Kilborn, Kerry
AU - Rubido, Nicolás
AU - Clark, Ruaridh
AU - Herzog, Rubén
AU - Yerlikaya, Deniz
AU - Güntekin, Bahar
AU - Deco, Gustavo
AU - Prado, Pavel
AU - Parra, Mario A.
AU - Orio, Patricio
AU - Tagliazucchi, Enzo
AU - Lawlor, Brian
AU - Ibanez, Agustin
PY - 2025/9/18
Y1 - 2025/9/18
N2 - Brain clocks track the deviations between predicted brain age and chronological age (brain age gaps, BAGs). These BAGs can be used to measure accelerated aging, monitoring deviations from the healthy brain trajectories associated with brain diseases and different cumulative burdens. However, the underlying biophysical mechanisms associated with BAGs in aging and dementia remain unclear. Here, we combine source space connectivity (EEG) with generative brain modeling in healthy controls (HCs) from the global south and north, alongside Alzheimer’s disease (AD) and behavioral variant frontotemporal dementia (bvFTD) patients (N=1,399). BAGs in aging were influenced by geography (south>north), income (low>high), sex (female>male), and education (low>high), with larger BAGs in patients, especially females with AD. Biophysical modeling revealed BAGs related to hyperexcitability and structural disintegration in aging, while hypoexcitability and severe disintegration were linked to dementia. Our work sheds light on the biophysical mechanisms of accelerated aging and dementia in diverse populations.
AB - Brain clocks track the deviations between predicted brain age and chronological age (brain age gaps, BAGs). These BAGs can be used to measure accelerated aging, monitoring deviations from the healthy brain trajectories associated with brain diseases and different cumulative burdens. However, the underlying biophysical mechanisms associated with BAGs in aging and dementia remain unclear. Here, we combine source space connectivity (EEG) with generative brain modeling in healthy controls (HCs) from the global south and north, alongside Alzheimer’s disease (AD) and behavioral variant frontotemporal dementia (bvFTD) patients (N=1,399). BAGs in aging were influenced by geography (south>north), income (low>high), sex (female>male), and education (low>high), with larger BAGs in patients, especially females with AD. Biophysical modeling revealed BAGs related to hyperexcitability and structural disintegration in aging, while hypoexcitability and severe disintegration were linked to dementia. Our work sheds light on the biophysical mechanisms of accelerated aging and dementia in diverse populations.
KW - brain clocks
KW - biophysical modeling
KW - dementia
KW - electroencephalography
KW - E/I balance
KW - structural disintegration
KW - Global South
UR - https://www.nature.com/natmentalhealth/
UR - https://github.com/carlosmig/EEG-Dementias
UR - https://doi.org/10.5281/zenodo.16420033
UR - https://github.com/fiuneuro/brainconn
M3 - Article
SN - 2731-6076
JO - Nature Mental Health
JF - Nature Mental Health
ER -