Brain clocks capture diversity and disparity in aging and dementia DOI Creative Commons
Agustín Ibáñez, Sebastián Moguilner,

Sandra Baez

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: June 25, 2024

Abstract Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding health disease. However, the impact of multimodal diversity (geographical, socioeconomic, sociodemographic, sex, neurodegeneration) on gap (BAG) is unknown. Here, we analyzed datasets from 5,306 participants across 15 countries (7 Latin American -LAC, 8 non-LAC). Based higher-order interactions in signals, developed a BAG deep learning architecture functional magnetic resonance imaging (fMRI=2,953) electroencephalography (EEG=2,353). The comprised healthy controls, individuals with mild cognitive impairment, Alzheimer’s disease, behavioral variant frontotemporal dementia. LAC models evidenced older ages (fMRI: MDE=5.60, RMSE=11.91; EEG: MDE=5.34, RMSE=9.82) compared to non-LAC, associated frontoposterior networks. Structural socioeconomic inequality other disparity-related factors (pollution, disparities) were influential predictors increased gaps, especially (R²=0.37, F²=0.59, RMSE=6.9). A gradient increasing controls impairment disease was found. In LAC, observed larger BAGs females control groups respective males. Results not explained by variations signal quality, demographics, or acquisition methods. Findings provide quantitative framework capturing accelerated aging.

Language: Английский

Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations DOI Creative Commons
Sebastián Moguilner, Sandra Báez, Hernán Hernandez

et al.

Nature Medicine, Journal Year: 2024, Volume and Issue: 30(12), P. 3646 - 3657

Published: Aug. 26, 2024

Abstract Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding health disease. However, the impact of diversity (including geographical, socioeconomic, sociodemographic, sex neurodegeneration) on brain-age gap is unknown. We analyzed datasets from 5,306 participants across 15 countries (7 Latin American Caribbean (LAC) 8 non-LAC countries). Based higher-order interactions, we developed a deep learning architecture functional magnetic resonance imaging (2,953) electroencephalography (2,353). The comprised healthy controls individuals with mild cognitive impairment, Alzheimer disease behavioral variant frontotemporal dementia. LAC models evidenced older ages (functional imaging: mean directional error = 5.60, root square (r.m.s.e.) 11.91; electroencephalography: 5.34, r.m.s.e. 9.82) associated frontoposterior networks compared models. Structural socioeconomic inequality, pollution disparities were influential predictors increased gaps, especially in ( R ² 0.37, F 0.59, 6.9). An ascending to impairment was found. In LAC, observed larger gaps females control groups respective males. results not explained by variations signal quality, demographics or acquisition methods. These findings provide quantitative framework capturing accelerated aging.

Language: Английский

Citations

22
Viscous dynamics associated with hypoexcitation and structural disintegration in neurodegeneration via generative whole‐brain modeling DOI Creative Commons
Carlos Coronel‐Oliveros, Raúl González-Gómez, Kamalini G. Ranasinghe

et al.

Alzheimer s & Dementia, Journal Year: 2024, Volume and Issue: 20(5), P. 3228 - 3250

Published: March 19, 2024

Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) lack mechanistic biophysical modeling in diverse, underrepresented populations. Electroencephalography (EEG) is a high temporal resolution, cost-effective technique for studying globally, but lacks models produces non-replicable results.

Language: Английский

Citations

7
Electroencephalography (EEG) and the Quest for an Inclusive and Global Neuroscience DOI Creative Commons
Faisal Mushtaq, Agustín Ibáñez

European Journal of Neuroscience, Journal Year: 2025, Volume and Issue: 61(6)

Published: March 1, 2025

ABSTRACT The current lack of diversity in neuroimaging datasets limits the potential generalisability research findings. This situation is also likely to have a downstream impact on our ability translate fundamental into effective interventions and treatments for global population. We propose that electroencephalography (EEG) viable delivering truly inclusive neuroscience. Over past two decades, advances portability, affordability, computational sophistication created tool can readily reach underrepresented communities scale across low‐resource contexts—advantages surpass those other modalities. However, skepticism persists within neuroscience community regarding feasibility realizing EEG's full studying brain shortly. highlight several challenges impeding progress, including need amalgamate large‐scale, harmonized provide statistical power robust frameworks necessary examining subtle differences between populations; advancement EEG technology ensure high‐quality data acquisition from all individuals—irrespective hair type—and operable by nonspecialists; importance engaging directly with cocreate culturally sensitive ethically appropriate methodologies. By tackling these technical social building initiatives dedicated inclusivity collaboration, we harness deliver genuinely representative

Language: Английский

Citations

0
Gaming expertise induces meso-scale brain plasticity and efficiency mechanisms as revealed by whole-brain modeling DOI Creative Commons
Carlos Coronel‐Oliveros, Vicente Medel, Sebastián Orellana

et al.

NeuroImage, Journal Year: 2024, Volume and Issue: 293, P. 120633 - 120633

Published: May 3, 2024

Video games are a valuable tool for studying the effects of training and neural plasticity on brain. However, underlying mechanisms related to plasticity-associated brain structural changes their impact dynamics unknown. Here, we used semi-empirical whole-brain model study linked video game expertise. We hypothesized that expertise is associated with plasticity-mediated in connectivity manifest at meso‑scale level, resulting more segregated functional network topology. To test this hypothesis, combined data StarCraft II players (VGPs, n = 31) non-players (NVGPs, 31), generic fMRI from Human Connectome Project computational models, generate simulated recordings. Graph theory analysis was performed during both resting-state conditions external stimulation. VGPs' characterized by integration, increased local frontal, parietal, occipital regions. The same analyses level showed no differences between VGPs NVGPs. Regions strength known be involved cognitive processes crucial task performance such as attention, reasoning, inference. In-silico stimulation suggested FC NVGPs emerge noisy contexts, specifically when increased. This indicates connectomes may facilitate filtering noise stimuli. These alterations drive observed individuals gaming Overall, our work sheds light triggered experiences.

Language: Английский

Citations

2
Author Correction: Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations DOI Creative Commons
Sebastián Moguilner, Sandra Báez, Hernán Hernandez

et al.

Nature Medicine, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 16, 2024

Brain clocks capture diversity and disparities in aging dementia across geographically diverse populationsBrain clocks, which quantify discrepancies between brain age chronological age, hold promise for understanding health disease.However, the impact of (including geographical, socioeconomic, sociodemographic, sex neurodegeneration) on brain-age gap is unknown.We analyzed datasets from 5,306 participants 15 countries (7 Latin American Caribbean (LAC) 8 non-LAC countries).Based higher-order interactions, we developed a deep learning architecture functional magnetic resonance imaging (2,953) electroencephalography (2,353).The comprised healthy controls individuals with mild cognitive impairment, Alzheimer disease behavioral variant frontotemporal dementia.LAC models evidenced older ages (functional imaging: mean directional error = 5.60, root square (r.m.s.e.) 11.91;electroencephalography: 5.34, r.m.s.e.= 9.82) associated frontoposterior networks compared models.Structural socioeconomic inequality, pollution were influential predictors increased gaps, especially LAC (R² 0.37, F² 0.59, 6.9).An ascending to impairment was found.In LAC, observed larger gaps females control groups respective males.The results not explained by variations signal quality, demographics or acquisition methods.These findings provide quantitative framework capturing accelerated aging.The undergoes dynamic changes 1-3 .Accurately mapping trajectory these how they relate critical process, multilevel 4,5 disorders 1 such as Alzheimer's continuum, includes (MCI) related like (bvFTD) 6 .Brain have emerged dimensional, transdiagnostic metrics that measure influenced range factors [7][8][9] , suggesting may be able multimodal 10 .Populations exhibit higher genetic distinct physical, social internal exposomes 11,12 phenotypes 4,13,14 .Income inequality 15,16 high levels air 17 limited access timely effective healthcare 18 rising prevalence communicable noncommunicable diseases 19,20 low education attainment 21,22 are determinants .Thus, although measuring could enhance our risk its 23 there lack research

Language: Английский

Citations

2
Homeodynamic feedback inhibition control in whole-brain simulations DOI Creative Commons
Jan Stasinski, Halgurd Taher, J. Meier

et al.

PLoS Computational Biology, Journal Year: 2024, Volume and Issue: 20(12), P. e1012595 - e1012595

Published: Dec. 2, 2024

Simulations of large-scale brain dynamics are often impacted by overexcitation resulting from heavy-tailed structural network distributions, leading to biologically implausible simulation results. We implement a homeodynamic plasticity mechanism, known other modeling work, in the widely used Jansen-Rit neural mass model for The Virtual Brain (TVB) framework. aim at heterogeneously adjusting inhibitory coupling weights reach desired dynamic regimes each region. show that, using this approach, we can control target activity level obtain plausible simulations, including post-synaptic potentials and blood-oxygen-level-dependent functional magnetic resonance imaging (fMRI) activity. demonstrate that derived Feedback Inhibitory Control (dFIC) be enable increased variability dynamics. derive conditions under which simulated converges predefined analytically via simulations. highlight benefits dFIC context fitting TVB static measures fMRI empirical data, accounting global synchronization across whole brain. proposed novel method helps computational neuroscientists, especially users, easily “tune” models dynamical depending on specific requirements study. presented is steppingstone towards biological realism valuable tool better understand their underlying behavior.

Language: Английский

Citations

1
Brain clocks capture diversity and disparity in aging and dementia DOI Creative Commons
Agustín Ibáñez, Sebastián Moguilner,

Sandra Baez

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: June 25, 2024

Abstract Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding health disease. However, the impact of multimodal diversity (geographical, socioeconomic, sociodemographic, sex, neurodegeneration) on gap (BAG) is unknown. Here, we analyzed datasets from 5,306 participants across 15 countries (7 Latin American -LAC, 8 non-LAC). Based higher-order interactions in signals, developed a BAG deep learning architecture functional magnetic resonance imaging (fMRI=2,953) electroencephalography (EEG=2,353). The comprised healthy controls, individuals with mild cognitive impairment, Alzheimer’s disease, behavioral variant frontotemporal dementia. LAC models evidenced older ages (fMRI: MDE=5.60, RMSE=11.91; EEG: MDE=5.34, RMSE=9.82) compared to non-LAC, associated frontoposterior networks. Structural socioeconomic inequality other disparity-related factors (pollution, disparities) were influential predictors increased gaps, especially (R²=0.37, F²=0.59, RMSE=6.9). A gradient increasing controls impairment disease was found. In LAC, observed larger BAGs females control groups respective males. Results not explained by variations signal quality, demographics, or acquisition methods. Findings provide quantitative framework capturing accelerated aging.

Language: Английский

Citations

1