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 approach to account for the non-Euclidean geometry of the space of shapes and the space of connectivity that constrains trajectories of co-variation to be valid statistical estimates. In order to disentangle genetic sources of variability 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.
@article{arxiv.2009.06059,
title = {Functional random effects modeling of brain shape and connectivity},
author = {Eardi Lila and John A. D. Aston},
journal= {arXiv preprint arXiv:2009.06059},
year = {2024}
}