title: Hierarchical organization of functional connectivity in the mouse brain: a complex network approach.
abstract: This paper represents a contribution to the study of the brain functional connectivity from the perspective of complex networks theory. More specifically, we apply graph theoretical analyses to provide evidence of the modular structure of the mouse brain and to shed light on its hierarchical organization. We propose a novel percolation analysis and we apply our approach to the analysis of a resting-state functional MRI data set from 41 mice. This approach reveals a robust hierarchical structure of modules persistent across different subjects. Importantly, we test this approach against a statistical benchmark (or null model) which constrains only the distributions of empirical correlations. Our results unambiguously show that the hierarchical character of the mouse brain modular structure is not trivially encoded into this lower-order constraint. Finally, we investigate the modular structure of the mouse brain by computing the Minimal Spanning Forest, a technique that identifies subnetworks characterized by the strongest internal correlations. This approach represents a faster alternative to other community detection methods and provides a means to rank modules on the basis of the strength of their internal edges.
authors.affiliation: Istituto dei Sistemi Complessi ISC-CNR, Università "Sapienza" di Roma, P.le A. Moro 5, 00185 Rome, Italy.
authors.forename: Giampiero
authors.initials: G
authors.lastname: Bardella
authors.affiliation: Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, C.so Bettini 31, I-38068 Rovereto (TN), Italy.
authors.forename: Angelo
authors.initials: A
authors.lastname: Bifone
authors.affiliation: Istituto dei Sistemi Complessi ISC-CNR, Università "Sapienza" di Roma, P.le A. Moro 5, 00185 Rome, Italy.|IMT School for Advanced Studies Lucca, P.zza S. Ponziano 6, 55100 Lucca, Italy.
authors.forename: Andrea
authors.initials: A
authors.lastname: Gabrielli
authors.affiliation: Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, C.so Bettini 31, I-38068 Rovereto (TN), Italy.
authors.forename: Alessandro
authors.initials: A
authors.lastname: Gozzi
authors.affiliation: Istituto dei Sistemi Complessi ISC-CNR, Università "Sapienza" di Roma, P.le A. Moro 5, 00185 Rome, Italy.|IMT School for Advanced Studies Lucca, P.zza S. Ponziano 6, 55100 Lucca, Italy.
authors.forename: Tiziano
authors.initials: T
authors.lastname: Squartini
mesh_terms: D000465:Algorithms; D000818:Animals; D001921:Brain / Q000000981:diagnostic imaging / Q000502:physiology*; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D051379:Mice; D008810:Mice, Inbred C57BL; D008962:Models, Theoretical