title: Decoding Time-Varying Functional Connectivity Networks via Linear Graph Embedding Methods.
abstract: An exciting avenue of neuroscientific research involves quantifying the time-varying properties of functional connectivity networks. As a result, many methods have been proposed to estimate the dynamic properties of such networks. However, one of the challenges associated with such methods involves the interpretation and visualization of high-dimensional, dynamic networks. In this work, we employ graph embedding algorithms to provide low-dimensional vector representations of networks, thus facilitating traditional objectives such as visualization, interpretation and classification. We focus on linear graph embedding methods based on principal component analysis and regularized linear discriminant analysis. The proposed graph embedding methods are validated through a series of simulations and applied to fMRI data from the Human Connectome Project.
authors.affiliation: Department of Mathematics, Imperial College London London, UK.
authors.forename: Ricardo P
authors.initials: RP
authors.lastname: Monti
authors.affiliation: Computational, Cognitive and Clinical Neuroimaging Laboratory, Imperial College London, The Hammersmith HospitalLondon, UK; Department of Bioengineering, Imperial College LondonLondon, UK.
authors.forename: Romy
authors.initials: R
authors.lastname: Lorenz
authors.affiliation: Computational, Cognitive and Clinical Neuroimaging Laboratory, Imperial College London, The Hammersmith HospitalLondon, UK; Department of Bioengineering, Imperial College LondonLondon, UK; Center for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondon, UK.
authors.forename: Peter
authors.initials: P
authors.lastname: Hellyer
authors.affiliation: Computational, Cognitive and Clinical Neuroimaging Laboratory, Imperial College London, The Hammersmith Hospital London, UK.
authors.forename: Robert
authors.initials: R
authors.lastname: Leech
authors.affiliation: Department of Mathematics, Imperial College London London, UK.
authors.forename: Christoforos
authors.initials: C
authors.lastname: Anagnostopoulos
authors.affiliation: Department of Mathematics, Imperial College LondonLondon, UK; Department of Biomedical Engineering, King's College London, St Thomas' HospitalLondon, UK.
authors.forename: Giovanni
authors.initials: G
authors.lastname: Montana
keywords: brain decoding; dynamic networks; functional connectivity; graph embedding; visualization