Biophysical modeling of anatomically realistic prenatal cortical folding development
TL;DR
A whole-brain developmental framework that integrates region-specific, data-driven growth laws with anatomically realistic cortical geometry to enable biologically interpretable modeling of cortical morphogenesis during gestation is introduced.
Abstract
Cortical folds encode the architecture of human cognition, yet the mechanisms that transform the smooth fetal cortex into its convoluted geometry remain elusive. Biophysical modeling enables mechanistic insight into cortical morphogenesis, but existing models often lack anatomical realism and fail to capture key hallmarks and morphometrics of dynamic cortical folding in the developing human brain. Here, we introduce a whole-brain developmental framework that integrates region-specific, data-driven growth laws with anatomically realistic cortical geometry to enable biologically interpretable modeling of cortical morphogenesis during gestation. Growth fields derived from large-scale prenatal magnetic resonance imaging data capture spatiotemporal variations in cortical expansion and thickness across parcellated regions. Incorporating heterogeneous growth yields folding patterns that match key anatomical landmarks and quantitative morphometrics from human imaging. Systematic perturbations of geometry and growth attributes delineate control parameters that produce realistic morphological variability and replicate clinically atypical brain phenotypes consistent with lissencephaly, pachygyria, and polymicrogyria. This framework provides a quantitative foundation for elucidating the mechanisms of typical and atypical fetal brain development. Using fetal MRI data and biophysical simulations, this study shows that region-specific cortical growth helps shape realistic brain folding and provides insight into normal development and congenital malformations.