title: A probabilistic framework to infer brain functional connectivity from anatomical connections.
abstract: We present a novel probabilistic framework to learn across several subjects a mapping from brain anatomical connectivity to functional connectivity, i.e. the covariance structure of brain activity. This prediction problem must be formulated as a structured-output learning task, as the predicted parameters are strongly correlated. We introduce a model selection framework based on cross-validation with a parametrization-independent loss function suitable to the manifold of covariance matrices. Our model is based on constraining the conditional independence structure of functional activity by the anatomical connectivity. Subsequently, we learn a linear predictor of a stationary multivariate autoregressive model. This natural parameterization of functional connectivity also enforces the positive-definiteness of the predicted covariance and thus matches the structure of the output space. Our results show that functional connectivity can be explained by anatomical connectivity on a rigorous statistical basis, and that a proper model of functional connectivity is essential to assess this link.
authors.affiliation: Department of Computing, Imperial College London, UK.
authors.forename: Fani
authors.initials: F
authors.lastname: Deligianni
authors.forename: Gael
authors.initials: G
authors.lastname: Varoquaux
authors.forename: Bertrand
authors.initials: B
authors.lastname: Thirion
authors.forename: Emma
authors.initials: E
authors.lastname: Robinson
authors.forename: David J
authors.initials: DJ
authors.lastname: Sharp
authors.forename: A David
authors.initials: AD
authors.lastname: Edwards
authors.forename: Daniel
authors.initials: D
authors.lastname: Rueckert
mesh_terms: D000328:Adult; D000465:Algorithms; D001185:Artificial Intelligence; D001931:Brain Mapping / Q000379:methods*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008953:Models, Anatomic; D008959:Models, Neurological; D015233:Models, Statistical; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity