title: Identification of optimal structural connectivity using functional connectivity and neural modeling.
abstract: The complex network dynamics that arise from the interaction of the brain's structural and functional architectures give rise to mental function. Theoretical models demonstrate that the structure-function relation is maximal when the global network dynamics operate at a critical point of state transition. In the present work, we used a dynamic mean-field neural model to fit empirical structural connectivity (SC) and functional connectivity (FC) data acquired in humans and macaques and developed a new iterative-fitting algorithm to optimize the SC matrix based on the FC matrix. A dramatic improvement of the fitting of the matrices was obtained with the addition of a small number of anatomical links, particularly cross-hemispheric connections, and reweighting of existing connections. We suggest that the notion of a critical working point, where the structure-function interplay is maximal, may provide a new way to link behavior and cognition, and a new perspective to understand recovery of function in clinical conditions.
authors.affiliation: Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, 08018, Spain, Institució Catalana de la Recerca i Estudis Avançats (ICREA), Barcelona, 08010, Spain.
authors.forename: Gustavo
authors.initials: G
authors.lastname: Deco
authors.affiliation: Rotman Research Institute of Baycrest Center, University of Toronto, Toronto, Ontario M6A 2E1, Canada, rmcintosh@research.baycrest.org.
authors.forename: Anthony R
authors.initials: AR
authors.lastname: McIntosh
authors.affiliation: Rotman Research Institute of Baycrest Center, University of Toronto, Toronto, Ontario M6A 2E1, Canada.
authors.forename: Kelly
authors.initials: K
authors.lastname: Shen
authors.affiliation: Department of Physiology and Pharmacology and Robarts Research Institute, and.
authors.forename: R Matthew
authors.initials: RM
authors.lastname: Hutchison
authors.affiliation: Centre for Functional and Metabolic Mapping, The University of Western Ontario, London, Ontario N6A 5K8, Canada.
authors.forename: Ravi S
authors.initials: RS
authors.lastname: Menon
authors.affiliation: Department of Physiology and Pharmacology and Robarts Research Institute, and Centre for Functional and Metabolic Mapping, The University of Western Ontario, London, Ontario N6A 5K8, Canada.
authors.forename: Stefan
authors.initials: S
authors.lastname: Everling
authors.affiliation: Department of Radiology, Lausanne University Hospital and University of Lausanne (CHUV-UNIL), 1011 Lausanne, Switzerland and Signal Processing Laboratory 5, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland, and.
authors.forename: Patric
authors.initials: P
authors.lastname: Hagmann
authors.affiliation: Institut de Neurosciences des Systèmes, UMR INSERM 1106, Aix-Marseille Université, 13005 Marseille, France.
authors.forename: Viktor K
authors.initials: VK
authors.lastname: Jirsa
mesh_terms: D000465:Algorithms; D000818:Animals; D001921:Brain / Q000033:anatomy & histology*; D006801:Humans; D008251:Macaca; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009434:Neural Pathways / Q000502:physiology*; D009474:Neurons / Q000502:physiology*; D017711:Nonlinear Dynamics
keywords: anatomy; fMRI; functional connectivity; modeling