Dissecting heterogeneous brain development and aging using voxelwise normative models
Voxelwise normative modeling can highlight individualized brain alterations and deviations in brain morphology, but specific statistical measures are needed to understand their clinical significance.
Where it sits
this study against the rest of the pnc-27 corpusSummary and findings
This study investigated brain morphometry using voxelwise normative models across the lifespan, utilizing a large aggregated reference sample of 58,597 scans from 51,107 participants. The study examined brain development post-preterm birth in two cohorts (n=284, n=304) and identified individualized brain alterations. Additionally, it analyzed morphometric deviations in patients with rare genetic neurodegenerative disorders (n=29, n=15).
Abstract
Brain disorders are often characterized by biological heterogeneity that is poorly captured by group-average analyses. Normative modeling has emerged as a promising tool to parse out such heterogeneity, yet existing lifespan reference models rely on coarse parcellations, which may obscure individual variability. Using an aggregated reference sample (n=58,597 scans from n=51,107 participants), we provide openly available normative models of brain morphometry at the voxel level across the lifespan, and we illustrate their potential utility with two complementary applications. First, we investigated long-term brain development after preterm birth across two independent cohorts (n=284; n=304) and found individualized, replicable and persistent brain alterations. Second, we extracted high-resolution patient-level morphometric deviations in two samples with rare, genetic neurodegenerative disorders (spinocerebellar ataxia type 1 and 3; n=29, n=15), which showed marked heterogeneity. Together, our findings highlight that voxelwise normative modeling can detect clinically relevant, individualized deviations from a reference model with high spatial precision.