FUNCTIONAL RANDOM EFFECTS MODELING OF BRAIN SHAPE AND CONNECTIVITY

We present a statistical framework that jointly models brain shape and functional connectivity which are two complex aspects of the brain that have been classically studied independently. We adopt a Riemannian modeling ap-proach to account for the non-Euclidean geometry of the space of shapes and the space of connectivity that constrains trajectories of covariation to be valid statistical estimates. In order to disentangle genetic sources of variabil-ity from those driven by unique environmental factors, we embed a functional random effects model in the Riemannian framework. We apply the proposed model to the Human Connectome Project dataset to explore spontaneous co -variation between brain shape and connectivity in young healthy individuals.