title: How anatomy shapes dynamics: a semi-analytical study of the brain at rest by a simple spin model.
abstract: Resting state networks (RSNs) show a surprisingly coherent and robust spatiotemporal organization. Previous theoretical studies demonstrated that these patterns can be understood as emergent on the basis of the underlying neuroanatomical connectivity skeleton. Integrating the biologically realistic DTI/DSI-(Diffusion Tensor Imaging/Diffusion Spectrum Imaging)based neuroanatomical connectivity into a brain model of Ising spin dynamics, we found a system with multiple attractors, which can be studied analytically. The multistable attractor landscape thus defines a functionally meaningful dynamic repertoire of the brain network that is inherently present in the neuroanatomical connectivity. We demonstrate that the more entropy of attractors exists, the richer is the dynamical repertoire and consequently the brain network displays more capabilities of computation. We hypothesize therefore that human brain connectivity developed a scale free type of architecture in order to be able to store a large number of different and flexibly accessible brain functions.
authors.affiliation: Computational Neuroscience Group, Department of Information and Communication Technologies, Center for Brain and Cognition, Universitat Pompeu Fabra Barcelona, Spain ; Institució Catalana de la Recerca i Estudis Avançats, Universitat Pompeu Fabra Barcelona, Spain.
authors.forename: Gustavo
authors.initials: G
authors.lastname: Deco
authors.forename: Mario
authors.initials: M
authors.lastname: Senden
authors.forename: Viktor
authors.initials: V
authors.lastname: Jirsa