Diversity-sensitive brain clocks linked to biophysical mechanisms in aging and dementia

Carlos Coronel-Oliveros; Sebastián Moguilner; Hernan Hernandez; Josephine Cruzat; Sandra Baez; Vicente Medel; Jhosmary Cuadros; Hernando Santamaria-Garcia; Pedro A. Valdes-Sosa; Francisco Lopera; John Fredy Ochoa-Gómez; Alfredis González-Hernández; Jasmín Bonilla-Santos; Rodrigo A. Gonzalez-Montealegre; Tuba Aktürk; Ebru Yıldırım; Renato Anghinah; Agustina Legaz; Sol Fittipaldi; Görsev G. Yener; Javier Escudero; Claudio Babiloni; Susanna Lopez; Robert Whelan; Alberto Fernández; David Huepe; Gaetano Di Caterina; Marcio Soto-Añari; Raul Gonzalez-Gomez; Eduar Herrera; Daniel Abasolo; Kerry Kilborn; Nicolás Rubido; Ruaridh Clark; Rubén Herzog; Deniz Yerlikaya; Bahar Güntekin; Gustavo Deco; Pavel Prado; Mario A. Parra; Patricio Orio; Enzo Tagliazucchi; Brian Lawlor; Agustin Ibanez

doi:10.1038/s44220-025-00502-7

Diversity-sensitive brain clocks linked to biophysical mechanisms in aging and dementia

Carlos Coronel-Oliveros
, Sebastián Moguilner
, Hernan Hernandez
, Josephine Cruzat
, Sandra Baez
, Vicente Medel
, Jhosmary Cuadros
, Hernando Santamaria-Garcia
, Pedro A. Valdes-Sosa
, Francisco Lopera
, John Fredy Ochoa-Gómez
, Alfredis González-Hernández
, Jasmín Bonilla-Santos
, Rodrigo A. Gonzalez-Montealegre
, Tuba Aktürk
, Ebru Yıldırım
, Renato Anghinah
, Agustina Legaz
, Sol Fittipaldi
, Görsev G. Yener

Javier Escudero, Claudio Babiloni, Susanna Lopez, Robert Whelan, Alberto Fernández, David Huepe, Gaetano Di Caterina, Marcio Soto-Añari, Raul Gonzalez-Gomez, Eduar Herrera, Daniel Abasolo, Kerry Kilborn, Nicolás Rubido, Ruaridh Clark, Rubén Herzog, Deniz Yerlikaya, Bahar Güntekin, Gustavo Deco, Pavel Prado, Mario A. Parra, Patricio Orio, Enzo Tagliazucchi, Brian Lawlor, Agustin Ibanez^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

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 (via electroencephalography) with generative brain modeling in healthy controls from the global south and north, alongside patients with Alzheimer’s disease and behavioral variant frontotemporal dementia (bvFTD) (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 Alzheimer’s disease. 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.

Original language	English
Pages (from-to)	1214–1229
Number of pages	15
Journal	Nature Mental Health
Volume	3
Early online date	18 Sept 2025
DOIs	https://doi.org/10.1038/s44220-025-00502-7
Publication status	Published - Oct 2025

Data Availability Statement

Raw data are available upon request from the corresponding authors. Functional and structural connectivity matrices, demographics and the data required to reproduce the results of this work are available at https://github.com/carlosmig/EEG-Dementias, with a link to Zenodo at https://doi.org/10.5281/zenodo.16420033 ref. 139.

Code availability
Analyses were conducted in MATLAB R2022a and Python (v.3.12.3). Machine learning and modeling used scikit-learn (v.1.4.2) and Numba (v.0.59.1). Statistical analysis used numpy (v.1.26.4), scipy (v.1.15.2), pandas (v.2.2.2) and statsmodels (v.0.14.2). Image processing used scikit-image (v.0.23.2). Visualization used matplotlib (v.3.8.4). Brain network analyses were performed using Brain Connectivity Toolbox (BCT, v.0.6.0) and NetworkX (v.3.2.1). EEG preprocessing used EEGLAB (v.2022.1). The codes for simulations are available at https://github.com/carlosmig/EEG-Dementias, and mirrored to a Zenodo repository at https://doi.org/10.5281/zenodo.16420033 ref. 139. The Brain Connectivity Toolbox for Python (https://github.com/fiuneuro/brainconn)133 was used for graph analysis and the BrainNet Viewer toolbox140 for visualization.

Funding

This work was supported by Latin American Brain Health Institute (BrainLat) award BL-SRGP2020-02 to M.A.P. and A.I. A.I. is supported by grants from ReDLat (National Institutes of Health and the Fogarty International Center (FIC), the National Institutes of Aging (R01 AG057234, R01 AG075775, AG021051, R01 AG083799, CARDS-NIH 75N95022C00031), Alzheimer\u2019s Association (SG-20-725707), Rainwater Charitable Foundation, The Bluefield project to cure FTD and the Global Brain Health Institute), ANID/FONDECYT Regular (1210195, 1210176 and 1220995) and ANID/FONDAP/15150012. A.M.G. is partially supported by the National Institute On Aging of the National Institutes of Health (R01 AG075775, R01 AG083799, 2P01AG019724), ANID (FONDECYT Regular 1210176, 1210195) and DICYT-USACH (032351G_DAS). The contents of this publication are solely the author\u2019s responsibility and do not represent the official views of these institutions.

Funders	Funder number
National Policing Institute	2P01AG019724
Latin American Brain Health Institute	BL-SRGP2020-02
Departamento de Investigaciones Científicas y Tecnológicas, Universidad de Santiago de Chile	032351G_DAS
National Institute on Aging	AG021051, CARDS-NIH 75N95022C00031, R01 AG057234, R01 AG083799, R01 AG075775
National Alzheimer's Association	SG-20-725707
Fondo Nacional de Desarrollo Científico y Tecnológico	1210195, ANID/FONDAP/15150012, 1220995, 1210176

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Alzheimer's disease
Biophysical models
Developing world

Access to Document

10.1038/s44220-025-00502-7

Cite this

Coronel-Oliveros, C., Moguilner, S., Hernandez, H., Cruzat, J., Baez, S., Medel, V., Cuadros, J., Santamaria-Garcia, H., Valdes-Sosa, P. A., Lopera, F., Ochoa-Gómez, J. F., González-Hernández, A., Bonilla-Santos, J., Gonzalez-Montealegre, R. A., Aktürk, T., Yıldırım, E., Anghinah, R., Legaz, A., Fittipaldi, S., ... Ibanez, A. (2025). Diversity-sensitive brain clocks linked to biophysical mechanisms in aging and dementia. Nature Mental Health, 3, 1214–1229. https://doi.org/10.1038/s44220-025-00502-7

Coronel-Oliveros, C, Moguilner, S, Hernandez, H, Cruzat, J, Baez, S, Medel, V, Cuadros, J, Santamaria-Garcia, H, Valdes-Sosa, PA, Lopera, F, Ochoa-Gómez, JF, González-Hernández, A, Bonilla-Santos, J, Gonzalez-Montealegre, RA, Aktürk, T, Yıldırım, E, Anghinah, R, Legaz, A, Fittipaldi, S, Yener, GG, Escudero, J, Babiloni, C, Lopez, S, Whelan, R, Fernández, A, Huepe, D, Di Caterina, G, Soto-Añari, M, Gonzalez-Gomez, R, Herrera, E, Abasolo, D, Kilborn, K, Rubido, N, Clark, R, Herzog, R, Yerlikaya, D, Güntekin, B, Deco, G, Prado, P, Parra, MA, Orio, P, Tagliazucchi, E, Lawlor, B & Ibanez, A 2025, 'Diversity-sensitive brain clocks linked to biophysical mechanisms in aging and dementia', Nature Mental Health, vol. 3, pp. 1214–1229. https://doi.org/10.1038/s44220-025-00502-7

@article{3c32fcd537dd40a2953ca6d9ff5c1a31,

title = "Diversity-sensitive brain clocks linked to biophysical mechanisms in aging and dementia",

abstract = "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 (via electroencephalography) with generative brain modeling in healthy controls from the global south and north, alongside patients with Alzheimer{\textquoteright}s disease and behavioral variant frontotemporal dementia (bvFTD) (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 Alzheimer{\textquoteright}s disease. 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.",

keywords = "Alzheimer's disease, Biophysical models, Developing world",

author = "Carlos Coronel-Oliveros and Sebasti{\'a}n Moguilner and Hernan Hernandez and Josephine Cruzat and Sandra Baez and Vicente Medel and Jhosmary Cuadros and Hernando Santamaria-Garcia and Valdes-Sosa, \{Pedro A.\} and Francisco Lopera and Ochoa-G{\'o}mez, \{John Fredy\} and Alfredis Gonz{\'a}lez-Hern{\'a}ndez and Jasm{\'i}n Bonilla-Santos and Gonzalez-Montealegre, \{Rodrigo A.\} and Tuba Akt{\"u}rk and Ebru Yıldırım and Renato Anghinah and Agustina Legaz and Sol Fittipaldi and Yener, \{G{\"o}rsev G.\} and Javier Escudero and Claudio Babiloni and Susanna Lopez and Robert Whelan and Alberto Fern{\'a}ndez and David Huepe and \{Di Caterina\}, Gaetano and Marcio Soto-A{\~n}ari and Raul Gonzalez-Gomez and Eduar Herrera and Daniel Abasolo and Kerry Kilborn and Nicol{\'a}s Rubido and Ruaridh Clark and Rub{\'e}n Herzog and Deniz Yerlikaya and Bahar G{\"u}ntekin and Gustavo Deco and Pavel Prado and Parra, \{Mario A.\} and Patricio Orio and Enzo Tagliazucchi and Brian Lawlor and Agustin Ibanez",

year = "2025",

month = oct,

doi = "10.1038/s44220-025-00502-7",

language = "English",

volume = "3",

pages = "1214–1229",

journal = "Nature Mental Health",

issn = "2731-6076",

publisher = "Springer Nature",

}

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, Jasmín

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 - 2025/10

Y1 - 2025/10

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 (via electroencephalography) with generative brain modeling in healthy controls from the global south and north, alongside patients with Alzheimer’s disease and behavioral variant frontotemporal dementia (bvFTD) (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 Alzheimer’s disease. 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 (via electroencephalography) with generative brain modeling in healthy controls from the global south and north, alongside patients with Alzheimer’s disease and behavioral variant frontotemporal dementia (bvFTD) (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 Alzheimer’s disease. 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 - Alzheimer's disease

KW - Biophysical models

KW - Developing world

UR - https://www.scopus.com/pages/publications/105016555788

UR - https://www.research.ed.ac.uk/en/publications/diversity-sensitive-brain-clocks-linked-to-biophysical-mechanisms/

U2 - 10.1038/s44220-025-00502-7

DO - 10.1038/s44220-025-00502-7

M3 - Article

AN - SCOPUS:105016555788

SN - 2731-6076

VL - 3

SP - 1214

EP - 1229

JO - Nature Mental Health

JF - Nature Mental Health

ER -

Diversity-sensitive brain clocks linked to biophysical mechanisms in aging and dementia

Abstract

Data Availability Statement

Funding

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this