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Charting brain growth and aging at high spatial precision
- Rutherford, Saige;
- Fraza, Charlotte;
- Dinga, Richard;
- Kia, Seyed Mostafa;
- Wolfers, Thomas;
- Zabihi, Mariam;
- Berthet, Pierre;
- Worker, Amanda;
- Verdi, Serena;
- Andrews, Derek;
- Han, Laura KM;
- Bayer, Johanna MM;
- Dazzan, Paola;
- McGuire, Phillip;
- Mocking, Roel T;
- Schene, Aart;
- Sripada, Chandra;
- Tso, Ivy F;
- Duval, Elizabeth R;
- Chang, Soo-Eun;
- Penninx, Brenda WJH;
- Heitzeg, Mary M;
- Burt, S Alexandra;
- Hyde, Luke W;
- Amaral, David;
- Nordahl, Christine Wu;
- Andreasssen, Ole A;
- Westlye, Lars T;
- Zahn, Roland;
- Ruhe, Henricus G;
- Beckmann, Christian;
- Marquand, Andre F
- et al.
Abstract
Defining reference models for population variation, and the ability to study individual deviations is essential for understanding inter-individual variability and its relation to the onset and progression of medical conditions. In this work, we assembled a reference cohort of neuroimaging data from 82 sites (N=58,836; ages 2-100) and used normative modeling to characterize lifespan trajectories of cortical thickness and subcortical volume. Models are validated against a manually quality checked subset (N=24,354) and we provide an interface for transferring to new data sources. We showcase the clinical value by applying the models to a transdiagnostic psychiatric sample (N=1985), showing they can be used to quantify variability underlying multiple disorders whilst also refining case-control inferences. These models will be augmented with additional samples and imaging modalities as they become available. This provides a common reference platform to bind results from different studies and ultimately paves the way for personalized clinical decision-making.
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