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Updated: Feb 12, 2026

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Predicting developmental norms from baseline cortical thickness in longitudinal studies.

Philipp Seidel1,2, Tobias Kaufmann3,4,5, Thomas Wolfers3,4,6

  • 1Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health, University of Tübingen, Tübingen, Germany. philipp.seidel@med.uni-tuebingen.de.

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Summary

New Baseline-Conditioned Norms (B-Norms) more accurately track brain thickness changes over time in adolescents. These advanced normative models improve predictions compared to traditional Cross-Sectional Norms (C-Norms), especially for detecting pubertal brain development.

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Area of Science:

  • Neuroscience
  • Developmental Psychology
  • Computational Psychiatry

Background:

  • Normative modeling is crucial for understanding individual differences in brain development using measures like cortical thickness.
  • Existing models primarily use cross-sectional data, limiting their ability to capture longitudinal brain changes.
  • Longitudinal data, while more informative, is challenging and costly to acquire.

Purpose of the Study:

  • To develop and evaluate a novel normative modeling approach, Baseline-Conditioned Norms (B-Norms), for longitudinal brain development.
  • To compare the predictive accuracy of B-Norms against traditional Cross-Sectional Norms (C-Norms) using longitudinal data.
  • To assess the sensitivity of B-Norms in detecting developmental changes, particularly those related to puberty and sex differences.

Main Methods:

  • Utilized longitudinal brain imaging data from the Adolescent Brain Cognitive Development (ABCD) study, including cortical thickness measurements at baseline, 2-year, and 4-year follow-ups.
  • Developed sex-specific B-Norms predicting follow-up cortical thickness based on baseline thickness, baseline age, and follow-up age.
  • Compared B-Norms with sex-specific C-Norms that predict thickness based on age alone, using independent test sets.

Main Results:

  • B-Norms demonstrated superior prediction accuracy and explained variance for cortical thickness compared to C-Norms across nearly all cortical regions.
  • B-Norms showed enhanced sensitivity to developmental processes, identifying four regions associated with pubertal changes not detected by C-Norms.
  • No significant differences in model performance were observed between the 2-year and 4-year follow-up time points.

Conclusions:

  • Baseline-Conditioned Norms (B-Norms) effectively capture normative variations in longitudinal structural brain changes.
  • B-Norms offer improved accuracy and sensitivity for studying developmental trajectories compared to traditional cross-sectional approaches.
  • B-Norms represent a valuable advancement and complement to existing normative modeling techniques in neuroscience.