Abstract：
:Identifying how spatially distributed information becomes integrated in the brain is essential to understanding higher cognitive functions. Previous computational and empirical studies suggest a significant influence of brain network structure on brain network function. However, there have been few analytical approaches to explain the role of network structure in shaping regional activities and directionality patterns. In this study, analytical methods are applied to a coupled oscillator model implemented in inhomogeneous networks. We first derive a mathematical principle that explains the emergence of directionality from the underlying brain network structure. We then apply the analytical methods to the anatomical brain networks of human, macaque, and mouse, successfully predicting simulation and empirical electroencephalographic data. The results demonstrate that the global directionality patterns in resting state brain networks can be predicted solely by their unique network structures. This study forms a foundation for a more comprehensive understanding of how neural information is directed and integrated in complex brain networks.
journal_name
Sci Repjournal_title
Scientific reportsauthors
Moon JY,Kim J,Ko TW,Kim M,Iturria-Medina Y,Choi JH,Lee J,Mashour GA,Lee Udoi
10.1038/srep46606subject
Has Abstractpub_date
2017-04-20 00:00:00pages
46606issn
2045-2322pii
srep46606journal_volume
7pub_type
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