Charting brain growth and aging at high spatial precision

Area of Science:

• Neuroscience
• Medical Imaging
• Population Health

Background:

• Understanding inter-individual variability in brain structure is crucial for medical research.
• Reference models are needed to study deviations from population norms and their relation to health and disease.

Purpose of the Study:

• To develop normative models of brain structure (cortical thickness and subcortical volume) across the lifespan.
• To validate these models and demonstrate their clinical utility in psychiatric research.

Main Methods:

• Assembled a large neuroimaging cohort (N=58,836) from 82 sites, covering ages 2-100.
• Applied normative modeling to characterize lifespan trajectories of brain structure.
• Validated models against a quality-controlled subset (N=24,354) and applied them to a psychiatric sample (N=1985).

Main Results:

• Established normative models for cortical thickness and subcortical volume across the lifespan.
• Demonstrated the models' ability to quantify individual variability in brain structure.
• Showcased clinical value by refining case-control inferences in a transdiagnostic psychiatric sample.

Conclusions:

• The developed reference models provide a common platform for analyzing neuroimaging data and understanding population variation.
• These models facilitate the quantification of individual deviations relevant to medical conditions and support personalized clinical decision-making.
• Future work will augment models with more data and imaging modalities.