Role of data-driven regional growth model in shaping brain folding patterns.

ABSTRACT: The surface morphology of the developing mammalian brain is crucial for understanding brain function and dysfunction. Computational modeling offers valuable insights into the underlying mechanisms for early brain folding. Recent findings indicate significant regional variations in brain tissue growth, while the role of these variations in cortical development remains unclear. In this study, we explored how regional cortical growth affects brain folding patterns using computational simulation. We first developed growth models for typical cortical regions using machine learning (ML)-assisted symbolic regression, based on longitudinal real surface expansion and cortical thickness data from prenatal and infant brains derived from over 1000 MRI scans of 735 pediatric subjects with ages ranging

SUBMITTER: Hou J 

PROVIDER: S-EPMC11718650 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature