TY - JOUR T1 - Communication Efficiency and Congestion of Signal Traffic in Large-Scale Brain Networks A1 - Mišić, Bratislav A1 - Sporns, Olaf A1 - McIntosh, Anthony R. Y1 - 2014/01/09 N2 - Author Summary A fundamental question in systems neuroscience is how the structural connectivity of the cerebral cortex shapes global communication. Here, using computational modeling in conjunction with an anatomically realistic structural network, we show that cortico-cortical communication is constrained by high-level features of brain network topology. We find that neural network topology is configured in a way that prioritizes speed of information flow over reliability and total throughput. The defining characteristic of the information processing architecture of the network is a densely interconnected rich club of hub nodes. Namely, rich club nodes and connections between rich club nodes absorb the greatest proportion of total signal traffic. In addition, rich club connectivity appears to actively shape information flow, whereby signal traffic is biased towards some nodes and away from others. Finally, synthetic networks containing a rich club could almost perfectly reproduce the information flow patterns of the real anatomical network. Altogether, our data demonstrate that a central collective of highly interconnected hubs serves to facilitate cortico-cortical communication. By simulating communication on a static structural network we have revealed a dynamic aspect of the global information processing architecture and the critical role played by the rich club of hub nodes. JF - PLOS Computational Biology JA - PLOS Computational Biology VL - 10 IS - 1 UR - https://doi.org/10.1371/journal.pcbi.1003427 SP - e1003427 EP - PB - Public Library of Science M3 - doi:10.1371/journal.pcbi.1003427 ER -