Charting brain growth and aging at high spatial precision.

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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© 2022, Rutherford et al.

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SR, CF, RD, SK, TW, MZ, PB, AW, SV, DA, LH, JB, PD, PM, RM, AS, CS, IT, ED, SC, BP, MH, SB, LH, DA, CW, LW, RZ, AM No competing interests declared, OA is a consultant for HealthLytix and received speaker's honorarium from Lundbeck and Sunovion, HR received speaker's honorarium from Lundbeck and Janssen, CB is director and shareholder of SBGNeuro Ltd