title: Differential Effects of Brain Disorders on Structural and Functional Connectivity.
abstract: Different measures of brain connectivity can be defined based on neuroimaging read-outs, including structural and functional connectivity. Neurological and psychiatric conditions are often associated with abnormal connectivity, but comparing the effects of the disease on different types of connectivity remains a challenge. In this paper, we address the problem of quantifying the relative effects of brain disease on structural and functional connectivity at a group level. Within the framework of a graph representation of connectivity, we introduce a kernel two-sample test as an effective method to assess the difference between the patients and control group. Moreover, we propose a common representation space for structural and functional connectivity networks, and a novel test statistics to quantitatively assess differential effects of the disease on different types of connectivity. We apply this approach to a dataset from BTBR mice, a murine model of Agenesis of the Corpus Callosum (ACC), a congenital disorder characterized by the absence of the main bundle of fibers connecting the two hemispheres. We used normo-callosal mice (B6) as a comparator. The application of the proposed methods to this data-set shows that the two types of connectivity can be successfully used to discriminate between BTBR and B6, meaning that both types of connectivity are affected by ACC. However, our novel test statistics shows that structural connectivity is significantly more affected than functional connectivity, consistent with the idea that functional connectivity has a robust topology that can tolerate substantial alterations in its structural connectivity substrate.
authors.affiliation: NeuroInformatics Laboratory, Fondazione Bruno KesslerTrento, Italy; Centro Interdipartimentale Mente e Cervello, Università di TrentoTrento, Italy; Pattern Analysis and Computer Vision, Istituto Italiano di TecnologiaGenova, Italy.
authors.forename: Sandro
authors.initials: S
authors.lastname: Vega-Pons
authors.affiliation: NeuroInformatics Laboratory, Fondazione Bruno KesslerTrento, Italy; Centro Interdipartimentale Mente e Cervello, Università di TrentoTrento, Italy.
authors.forename: Emanuele
authors.initials: E
authors.lastname: Olivetti
authors.affiliation: NeuroInformatics Laboratory, Fondazione Bruno KesslerTrento, Italy; Centro Interdipartimentale Mente e Cervello, Università di TrentoTrento, Italy.
authors.forename: Paolo
authors.initials: P
authors.lastname: Avesani
authors.affiliation: Pattern Analysis and Computer Vision, Istituto Italiano di TecnologiaGenova, Italy; Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @UniTnRovereto, Italy.
authors.forename: Luca
authors.initials: L
authors.lastname: Dodero
authors.affiliation: Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @UniTn Rovereto, Italy.
authors.forename: Alessandro
authors.initials: A
authors.lastname: Gozzi
authors.affiliation: Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @UniTn Rovereto, Italy.
authors.forename: Angelo
authors.initials: A
authors.lastname: Bifone
keywords: agenesis of the corpus callosum; functional connectivity; graph kernel; kernel two-sample test; structural connectivity; test statistic