Fig. 1: Study overview.

The workflow of the present study, from data sources (left side) to data processing and analysis method (middle) to the research questions and results (right side). A A collection of postmortem “cellular” and in vivo “molecular” brain atlases was parcellated and dimensionality reduced. B “Modeled” predicted CT data was extracted from a normative model. C We calculated the colocalization between neurobiological markers and CT at each point throughout the lifespan (see Fig. 2). D We evaluated how combined and individual neurobiological markers could explain lifespan CT change (see Figs. 3 and 4). E The strongest associated markers were examined in detail, accounting for shared spatial patterns (see Fig. 5). F A developmental gene expression dataset was used to generate trajectories of gene expression associated with each neurobiological marker. G Periods in which CT change was significantly explained were validated in developmental gene expression data (see Fig. 7). H Single-subject longitudinal data was extracted from two developmental cohorts. I Findings based on the normative model were validated in single-subject data (see Fig. 8). Abbreviations: CT = cortical thickness, ABA = Allen Brain Atlas, MRI = magnetic resonance imaging. Here, data plots are employed for demonstration purposes; for definitions of plot elements, please refer to the individual figures as refererred to above, similarly, source data are provided in Source Data files of each following figure. ABCD Study®, Teen Brains. Today’s Science. Brighter Future.® and the ABCD Study Logos are registered marks of the U.S. Department of Health & Human Services (HHS).