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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Communication structure of cortical networks

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Author(s):
Costa, Luciano da Fontoura [1, 2] ; Batista, Joao Luiz B. [1] ; Ascoli, Giorgio A. [3, 4]
Total Authors: 3
Affiliation:
[1] Univ Sao Paulo, Inst Phys Sao Carlos, BR-13560970 Sao Paulo - Brazil
[2] Natl Inst Sci & Technol Complex Syst, Rio De Janeiro - Brazil
[3] George Mason Univ, Ctr Neural Informat Struct & Plast, Krasnow Inst Adv Study, Fairfax, VA 22030 - USA
[4] George Mason Univ, Mol Neurosci Dept, Krasnow Inst Adv Study, Fairfax, VA 22030 - USA
Total Affiliations: 4
Document type: Journal article
Source: FRONTIERS IN COMPUTATIONAL NEUROSCIENCE; v. 5, MAR 4 2011.
Web of Science Citations: 7
Abstract

Large-scale cortical networks exhibit characteristic topological properties that shape communication between brain regions and global cortical dynamics. Analysis of complex networks allows the description of connectedness, distance, clustering, and centrality that reveal different aspects of how the network's nodes communicate. Here, we focus on a novel analysis of complex walks in a series of mammalian cortical networks that model potential dynamics of information flow between individual brain regions. We introduce two new measures called absorption and driftness. Absorption is the average length of random walks between any two nodes, and takes into account all paths that may diffuse activity throughout the network. Driftness is the ratio between absorption and the corresponding shortest path length. For a given node of the network, we also define four related measurements, namely in-and out-absorption as well as in-and out-driftness, as the averages of the corresponding measures from all nodes to that node, and from that node to all nodes, respectively. We find that the cat thalamo-cortical system incorporates features of two classic network topologies, Erdos-Renyi graphs with respect to in-absorption and in-driftness, and configuration models with respect to out-absorption and out-driftness. Moreover, taken together these four measures separate the network nodes based on broad functional roles (visual, auditory, somatomotor, and frontolimbic). (AU)

FAPESP's process: 05/00587-5 - Mesh (graph) modeling and techniques of pattern recognition: structure, dynamics and applications
Grantee:Roberto Marcondes Cesar Junior
Support Opportunities: Research Projects - Thematic Grants