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Functional random effects modeling of brain shape and connectivity

Accepted version
Peer-reviewed

Type

Article

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Authors

Lila, Eardi 
Aston, John AD 

Abstract

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.

Description

Keywords

49 Mathematical Sciences, 4905 Statistics

Journal Title

The Annals of Applied Statistics

Conference Name

Journal ISSN

1932-6157

Volume Title

Publisher

Institute of Mathematical Statistics
Sponsorship
EPSRC (EP/T017961/1)