Using normative models pre-trained on cross-sectional data to evaluate intra-individual longitudinal changes in neuroimaging data.

ABSTRACT: Longitudinal neuroimaging studies offer valuable insight into brain development, ageing, and disease progression over time. However, prevailing analytical approaches rooted in our understanding of population variation are primarily tailored for cross-sectional studies. To fully leverage the potential of longitudinal neuroimaging, we need methodologies that account for the complex interplay between population variation and individual dynamics. We extend the normative modelling framework, which evaluates an individual's position relative to population standards, to assess an individual's longitudinal change compared to the population's standard dynamics. Using normative models pre-trained on over 58,000 individuals, we introduce a quantitative metric termed 'z-diff' score, whic

SUBMITTER: Rehak Buckova B 

PROVIDER: S-EPMC11903031 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature