Post-doctoral Research Visit F/m Longitudinal Atlas and Regional Growth Charts of Early Brain Development

Le descriptif de l’offre ci-dessous est en Anglais_ **Type de contrat**: CDD **Niveau de diplôme exigé**: Thèse ou équivalent **Fonction**: Post-Doctorant **A propos du centre ou de la direction fonctionnelle**: The Inria Centre at Rennes University is one of Inria's nine centres and has more than thirty research teams. The Inria Centre is a major and recognized player in the field of digital sciences. It is at the heart of a rich R&D and innovation ecosystem: highly innovative PMEs, large industrial groups, competitiveness clusters, research and higher education players, laboratories of excellence, technological research institute, etc. **Contexte et atouts du poste**: **Scientific context.**This postdoctoral project is part of the JCJC ANR funded project CoYoKi (PI: F. Dégeilh). CoYoKi addresses the methodological challenges of studying brain development and concussion in early childhood (i.e., uniqueness of young child’s brain, individual variability of brain development and injury). It combines cutting-edge advanced neuroimaging, computational and longitudinal statistical models to propose novel individualised and longitudinal neuroimaging methods. To study deviations in brain development, it is essential to understand typical development and its individual variability, a knowledge still lacking, particularly in early childhood due to the absence (until recently) of sufficiently large datasets. This postdoctoral projet will address this gap of knowledge throughout 2 specific aims : 1) Computing a longitudinal atlas of early brain development. A new algorithm will be developed to compute the first longitudinal brain atlas extending from 0 to 5 years. 2) Modelling regional growth charts of early brain structure development. Computational and longitudinal models will be coupled to model the typical trajectories of early brain structure development and their individual variability at the brain regions level. **Project team.**The postdoctoral researcher will work with F. Dégeilh (CRCN Inserm, CoYoKi PI), expert in paediatric neuroimaging, and with C. Cury (CRCN Inria) and P. Maurel (Prof., University of Rennes), both researchers at Empenn and experts in computational neuroscience. In addition, he/she will benefit from the expertise of A. Legouhy (Dr., University College London, UK) and F. Rousseau (Prof., IMT Atlantic, Brest, France) experts in computational neuroscience and collaborators on the project. **Mission confiée**: This postdoctoral project will focus on characterising typical brain development and its inter-individual variability in young children using an existing publicly and freely available large longitudinal paediatric MRI dataset (>3,000 MRI from 343 typically developing 0-to-5-year-olds). It includes 2 specific aims and associated work packages (WP): **WP1**:Computing a longitudinal atlas of early developing brain.**Brain atlases are a crucial neuroimaging tool for automatically processing MRI data, including estimation of brain metrics (e.g., volumes, surfaces, shapes of brain regions). Using an age-inappropriate brain atlas (i.e., adult, older children) can result in misestimation of these metrics. However, there is currently no brain atlas extending from ages 0 to 5 years and based on longitudinal MRI data, hindering to accurately model the intense brain development occurring at this age. _Approach:_ Cross-sectional Atlasing, an algorithm developed at Empenn for computing cross-sectional (1 MRI per participant) unbiased paediatric brain atlas (i.e., accounting for brains of different sizes and providing topologically realistic transformations) will be adapted and applied, for the first time, to longitudinal data (Atlasing-long). Then, the longitudinal structural MRI will be processed using Atlasing-long to create a longitudinal brain atlas extending from 0-to-5-year. **WP2: Modelling regional growth charts of early brain structure development.** Brain growth charts (i.e., reference standards of typical brain development) have been recently published. However, they provide brain development trajectory at the global level (e.g., total volume, area, thickness), rather than at the level of brain regions, that masks the regional variability of brain development and prevents to detect region-specific atypical brain development. _Approach:_ Novel mathematical model coupling cutting-edge longitudinal statistical methods and advanced computational neuroscience analyses will be developed to model neurodevelopmental trajectories. This novel mathematical model will allow us to model 4 dimensional (3D space + time) changes in brain structure by simultaneously modelling individual-level and group-level trajectories complying with brain anatomy constraints by allowing elastic deformations. The model will be applied to longitudinal MRI data to estimate typical spatiotemporal trajectories and their variability. **Principales activités**: **Main activities** - Propose and develop a new atlasing a