title: Characterizing the connectome in schizophrenia with diffusion spectrum imaging.
abstract: Schizophrenia is a complex psychiatric disorder characterized by disabling symptoms and cognitive deficit. Recent neuroimaging findings suggest that large parts of the brain are affected by the disease, and that the capacity of functional integration between brain areas is decreased. In this study we questioned (i) which brain areas underlie the loss of network integration properties observed in the pathology, (ii) what is the topological role of the affected regions within the overall brain network and how this topological status might be altered in patients, and (iii) how white matter properties of tracts connecting affected regions may be disrupted. We acquired diffusion spectrum imaging (a technique sensitive to fiber crossing and slow diffusion compartment) data from 16 schizophrenia patients and 15 healthy controls, and investigated their weighted brain networks. The global connectivity analysis confirmed that patients present disrupted integration and segregation properties. The nodal analysis allowed identifying a distributed set of brain nodes affected in the pathology, including hubs and peripheral areas. To characterize the topological role of this affected core, we investigated the brain network shortest paths layout, and quantified the network damage after targeted attack toward the affected core. The centrality of the affected core was compromised in patients. Moreover the connectivity strength within the affected core, quantified with generalized fractional anisotropy and apparent diffusion coefficient, was altered in patients. Taken together, these findings suggest that the structural alterations and topological decentralization of the affected core might be major mechanisms underlying the schizophrenia dysconnectivity disorder.
authors.affiliation: Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Department of Radiology, Centre Hospitalier Universitaire Vaudois (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
authors.forename: Alessandra
authors.initials: A
authors.lastname: Griffa
authors.forename: Philipp Sebastian
authors.initials: PS
authors.lastname: Baumann
authors.forename: Carina
authors.initials: C
authors.lastname: Ferrari
authors.forename: Kim Quang
authors.initials: KQ
authors.lastname: Do
authors.forename: Philippe
authors.initials: P
authors.lastname: Conus
authors.forename: Jean-Philippe
authors.initials: JP
authors.lastname: Thiran
authors.forename: Patric
authors.initials: P
authors.lastname: Hagmann
mesh_terms: D000328:Adult; D016880:Anisotropy; D001921:Brain / Q000473:pathology*; D063132:Connectome; D056324:Diffusion Tensor Imaging; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009415:Nerve Net / Q000473:pathology; D009434:Neural Pathways / Q000473:pathology; D012559:Schizophrenia / Q000473:pathology*; D066127:White Matter / Q000473:pathology*
keywords: brain network; connectome; diffusion spectrum imaging; graph theory; magnetic resonance imaging; psychosis; schizophrenia