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Communication Efficiency and Congestion of Signal Traffic in Large-Scale Brain Networks

Overview of attention for article published in PLoS Computational Biology, January 2014
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Title
Communication Efficiency and Congestion of Signal Traffic in Large-Scale Brain Networks
Published in
PLoS Computational Biology, January 2014
DOI 10.1371/journal.pcbi.1003427
Pubmed ID
Authors

Bratislav Mišić, Olaf Sporns, Anthony R. McIntosh

Abstract

The complex connectivity of the cerebral cortex suggests that inter-regional communication is a primary function. Using computational modeling, we show that anatomical connectivity may be a major determinant for global information flow in brain networks. A macaque brain network was implemented as a communication network in which signal units flowed between grey matter nodes along white matter paths. Compared to degree-matched surrogate networks, information flow on the macaque brain network was characterized by higher loss rates, faster transit times and lower throughput, suggesting that neural connectivity may be optimized for speed rather than fidelity. Much of global communication was mediated by a "rich club" of hub regions: a sub-graph comprised of high-degree nodes that are more densely interconnected with each other than predicted by chance. First, macaque communication patterns most closely resembled those observed for a synthetic rich club network, but were less similar to those seen in a synthetic small world network, suggesting that the former is a more fundamental feature of brain network topology. Second, rich club regions attracted the most signal traffic and likewise, connections between rich club regions carried more traffic than connections between non-rich club regions. Third, a number of rich club regions were significantly under-congested, suggesting that macaque connectivity actively shapes information flow, funneling traffic towards some nodes and away from others. Together, our results indicate a critical role of the rich club of hub nodes in dynamic aspects of global brain communication.

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Geographical breakdown

Country Count As %
United States 3 2%
Netherlands 2 1%
United Kingdom 2 1%
Italy 1 <1%
Finland 1 <1%
France 1 <1%
Singapore 1 <1%
Chile 1 <1%
Japan 1 <1%
Other 1 <1%
Unknown 176 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 47 25%
Researcher 46 24%
Student > Master 17 9%
Professor 15 8%
Student > Doctoral Student 12 6%
Other 32 17%
Unknown 21 11%
Readers by discipline Count As %
Neuroscience 25 13%
Psychology 25 13%
Agricultural and Biological Sciences 23 12%
Computer Science 23 12%
Medicine and Dentistry 17 9%
Other 40 21%
Unknown 37 19%