dorsal/arxiv
View SchemaCharting the velocity of brain growth and development
| Authors | Johanna M. M. Bayer, Augustijn A. A. de Boer, Barbora Rehak-Bucova, Charlotte J. Fraza, Tobias Banaschewski, Gareth J. Barker, Arun L. W. Bokde, Ruediger Bruehl, Sylvane Desrivieres, Herta Flor, Hugh Garavan, Penny Gowland, Antoine Grigis, Andreas Heinz, Herve Lemaitre, Jean-Luc Martinot, Marie-Laure Paillere Martinot, Eric Artigues, Frauke Nees, Dimitri Papadopoulos Orfanos, Tomas Paus, Luise Poustka, Michael N. Smolka, Nathalie Holz, Nilakshi Vaidya, Henrik Walter, Robert Whelan, Paul Wirsching, Gunter Schumann, Alzheimers Disease Neuroimaging Initiative, Nina Kraguljac, Christian F. Beckmann, Andre F. Marquand |
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| Categories | |
| ArXiv ID | 2601.07591vv1 |
| URL | https://arxiv.org/abs/2601.07591 |
| License | http://creativecommons.org/licenses/by-nc-sa/4.0/ |
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 24062 scans from 10795 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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"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 24062 scans from 10795 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.",
"arxiv_id": "2601.07591",
"authors": [
"Johanna M. M. Bayer",
"Augustijn A. A. de Boer",
"Barbora Rehak-Bucova",
"Charlotte J. Fraza",
"Tobias Banaschewski",
"Gareth J. Barker",
"Arun L. W. Bokde",
"Ruediger Bruehl",
"Sylvane Desrivieres",
"Herta Flor",
"Hugh Garavan",
"Penny Gowland",
"Antoine Grigis",
"Andreas Heinz",
"Herve Lemaitre",
"Jean-Luc Martinot",
"Marie-Laure Paillere Martinot",
"Eric Artigues",
"Frauke Nees",
"Dimitri Papadopoulos Orfanos",
"Tomas Paus",
"Luise Poustka",
"Michael N. Smolka",
"Nathalie Holz",
"Nilakshi Vaidya",
"Henrik Walter",
"Robert Whelan",
"Paul Wirsching",
"Gunter Schumann",
"Alzheimers Disease Neuroimaging Initiative",
"Nina Kraguljac",
"Christian F. Beckmann",
"Andre F. Marquand"
],
"categories": [
"q-bio.NC",
"q-bio.QM"
],
"license": "http://creativecommons.org/licenses/by-nc-sa/4.0/",
"title": "Charting the velocity of brain growth and development",
"url": "https://arxiv.org/abs/2601.07591",
"version": "v1"
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