期刊
FRONTIERS IN COMPUTATIONAL NEUROSCIENCE
卷 6, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fncom.2012.00068
关键词
computational neuroscience; fMRI modeling; ongoing activity; resting state; connectivity matrix
资金
- Spanish Research Project
- CONSOLIDER-INGENIO
- ERC
- Brain Network Recovery Group through the James S. McDonnell Foundation
- FP7-ICT BrainScales
- ICREA Funding Source: Custom
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.
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