How anatomy shapes dynamics: a semi-analytical study of the brain at rest by a simple spin model

Deco, Gustavo; Senden, Mario; Jirsa, Viktor K.

doi:http://dx.doi.org/10.3389/fncom.2012.00068

How anatomy shapes dynamics: a semi-analytical study of the brain at rest by a simple spin model

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Deco G, Senden M, Jirsa V. How anatomy shapes dynamics: a semi-analytical study of the brain at rest by a simple spin model. Front Comput Neurosci. 2012 Sep 20;6(68):1-7. DOI: 10.3389/fncom.2012.00068

Abstract

Resting state networks (RSNs) show a surprisingly coherent and robust spatiotemporal/norganization. Previous theoretical studies demonstrated that these patterns can be/nunderstood as emergent on the basis of the underlying neuroanatomical connectivity/nskeleton. Integrating the biologically realistic DTI/DSI-(Diffusion Tensor Imaging/Diffusion/nSpectrum Imaging)based neuroanatomical connectivity into a brain model of Ising/nspin dynamics, we found a system with multiple attractors, which can be studied/nanalytically. The multistable attract/nor landscape thus defines a functionally meaningful/ndynamic repertoire of the brain network that is inherently present in the neuroanatomical/nconnectivity. We demonstrate that the more entropy of attractors exists, the richer is the/ndynamical repertoire and consequently the brain network displays more capabilities of/ncomputation. We hypothesize therefore tha/nt human brain connectivity developed a scale/nfree type of architecture in order to be able to store a large number of different and flexibly/naccessible brain functions.