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Structure-Function Relationship in Complex Brain Networks Expressed by Hierarchical Synchronization

Changsong Zhou
The brain is one of the most complex systems in nature, with a structured complex connectivity. Recently, lar
ge-scale corticocortical connectivities, both structural and functional, have received a great deal of resear
ch attention, especially using the approach of complex network analysis. Understanding the relationship betw
een structural and functional connectivity is of crucial importance in neuroscience. Here we try to illuminat
e this relationship by studying synchronization dynamics in a realistic anatomical network of cat cortical c
onnectivity. We model the nodes (cortical areas) by a neural mass model (population model) or by a subnetwork
of interacting excitable neurons (multilevel model). We show that if the dynamics is characterized by well-d
efined oscillations (neural mass model and subnetworks with strong couplings), the synchronization patterns a
re mainly determined by the node intensity (total input strengths of a node) and the detailed network topolog
y is rather irrelevant. On the other hand, the multilevel model with weak couplings displays more irregular,
biologically plausible dynamics, and the synchronization patterns reveal a hierarchical cluster organization
in the network structure. The relationship between structural connectivity and functional connectivity at dif
ferent levels of synchronization is explored. Thus, the study of synchronization in a mutilevel complex netw
ork model of cortex can provide insights into the relationship between network topology and functional organi
zation of complex brain networks.
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