Charting the velocity of brain growth and development.

Brain charts have emerged as a highly useful approach for understanding brain development and aging on the basis of brain imaging and have shown substantial utility in describing typical and atypical brain development with respect to a given reference model. However, all existing models are fundamentally cross-sectional and cannot capture change over time at the individual level. We address this using velocity centiles, which directly map change over time and can be overlaid onto cross-sectionally derived population centiles. We demonstrate this by modelling rates of change for 24,062 scans from 10,795 healthy individuals with up to 8 longitudinal measurements across the lifespan. We provide a method to detect individual deviations from a stable trajectory, generalising the notion of 'thrive lines', which are used in pediatric medicine to declare 'failure to thrive'. Using this approach, we predict transition from mild cognitive impairment to dementia more accurately than by using either time point alone, replicated across two datasets. Last, by taking into account multiple time points, we improve the sensitivity of velocity models for predicting the future trajectory of brain change. This highlights the value of predicting change over time and makes a fundamental step towards precision medicine.

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Journal
PubMed
Published
2026-01-12
Primary Topic
Dementia and Cognitive Impairment Research
Type
article
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article

Charting the velocity of brain growth and development.

Ruediger Bruehl, Charlotte Fraza, Nick Ortiz, Hugh P. Garavan et al.
PubMed
Dementia and Cognitive Impairment Research
article

Charting the velocity of brain growth and development.

Ruediger Bruehl, Charlotte Fraza, Nick Ortiz, Hugh P. Garavan, Luise Poustka, Tomas Paus, Andreas Heinz, Augustijn A. A. de Boer, Barbora Rehak-Bucova, Eric Artigues, Herve Lemaitre, Paul Wirsching, Johanna M. M. Bayer, Marie-Laure Paillere Martinot, Christian F Beckmann, Robert Whelan, Tobias Banaschewski, Michael N. Smolka, Gareth J Barker, Sylvane Desrivières, Henrik Walter, Jean-Luc Martinot, Dimitri Papadopoulos Orfanos, Penny A. Gowland, Herta Flor, Gunter Schumann, Nilakshi Vaidya, Arun L. Bokde, Nathalie Holz
article en

Abstract

Brain charts have emerged as a highly useful approach for understanding brain development and aging on the basis of brain imaging and have shown substantial utility in describing typical and atypical brain development with respect to a given reference model. However, all existing models are fundamentally cross-sectional and cannot capture change over time at the individual level. We address this using velocity centiles, which directly map change over time and can be overlaid onto cross-sectionally derived population centiles. We demonstrate this by modelling rates of change for 24,062 scans from 10,795 healthy individuals with up to 8 longitudinal measurements across the lifespan. We provide a method to detect individual deviations from a stable trajectory, generalising the notion of 'thrive lines', which are used in pediatric medicine to declare 'failure to thrive'. Using this approach, we predict transition from mild cognitive impairment to dementia more accurately than by using either time point alone, replicated across two datasets. Last, by taking into account multiple time points, we improve the sensitivity of velocity models for predicting the future trajectory of brain change. This highlights the value of predicting change over time and makes a fundamental step towards precision medicine.

PubMed
University of Vermont (US), Physikalisch-Technische Bundesanstalt (DE), Centre National de la Recherche Scientifique (FR), Netherlands Institute for Neuroscience (NL), University of Nottingham (GB), Radboud University Nijmegen (NL), Université de Bordeaux (FR), Inserm (FR), Columbus State Community College (US), University of Mannheim (DE), King's College London (GB), University of Toronto (CA), Trinity College Dublin (IE), Heidelberg University (DE), Fudan University (CN), Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR), Université Paris-Saclay (FR), University Hospital Heidelberg (DE), Centre Hospitalier Universitaire Sainte-Justine (CA), Radboud University Medical Center (NL), El Hospital General de Agudos Carlos G. Durand (AR), Humboldt-Universität zu Berlin (DE), Sorbonne Université (FR), Institut des Maladies Neurodégénératives (FR), Assistance Publique – Hôpitaux de Paris (FR), Central Institute of Mental Health (DE), Pitié-Salpêtrière Hospital (FR), CEA Paris-Saclay (FR), GFZ Helmholtz Centre for Geosciences (DE), Shanghai Center for Brain Science and Brain-Inspired Technology (CN), Université de Montréal (CA), Freie Universität Berlin (DE), Technische Universität Dresden (DE), Charité - Universitätsmedizin Berlin (DE), University of Tübingen (DE), Ludwig-Maximilians-Universität München (DE)
Openalex Percentile: Top 66%
Dementia and Cognitive Impairment Research
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