How anatomy shapes dynamics: a semi-analytical study of the brain at rest by a simple spin model - Deco, Gustavo; Senden, Mario; Jirsa, Viktor (Frontiers in Computational Neuroscience, 2012)
Resting state networks 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 based neuroanatomical connectivity into a brain model of Ising spin dynamics, we found the presence of latent “ghost” multi-stable attractors, which can be studied analytically. The multistable attractor landscape 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