Modélisation du développement cérébral à partir de données IRM

Cortical folding refers to the formation of convolutions on the surface of the cortex during brain development. When atypical, such folding can be associated with neurodevelopmental disorders, including epilepsy, autism, or cerebral palsy. The development of cortical folds arises from the interplay between multiple spatial scales, encompassing genetic, cellular, and mechanical factors. While certain mechanical processes are pivotal in the emergence of primary folds, the detailed mechanisms governing the gradual development of cortical folding remain incompletely understood. Recent so-called multi-scale models enable to explore the respective contributions of different scales and their influence on cortical folding. Furthermore, advances in fetal brain imaging now pave the way for personalized modeling. Ensuring reproducibility, interpretability, and reliability is fundamental for the advancement of the novel cortical folding models. In this thesis, we present a biomechanical model of cortical folding on whole-brain geometry formulated within a finite element context. We introduce an open-source simulation framework that enables mesh generation and model parameterization from MRI data, incorporating cortical surface biometrics used for model calibration. Finally, we propose a multi-scale approach to cortical folding modeling that integrates anatomical and diffusion MRI data to inform model parameters.