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

By Bratislav Misic, Olaf Sporns, Anthony Randal McIntosh. 2014

113 citations recorded by the source corpus.

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.

Subfields: Cognitive Neuroscience, Statistical and Nonlinear Physics

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Citations in the corpus

Network neuroscience (2017, background): “…intriguingly, one can also exercise phenomenological models to gain an intuition regarding processes whose physiology is less well understood, such as the trans-synaptic spread of prions thought to cause dementia 83 or the propagation of information packets along parallel structural routes 84 .”
The Dynamics of Functional Brain Networks: Integrated Network States during Cognitive Task Performance (2015, unknown): “complete the behavioral tasks (21) (see Figure S10 for a movie of the fluctuations as a function of the N-‐‐back task).”
Communication dynamics in complex brain networks (2017, background): “A corollary is that the load of information flow on edges that comprise the shortest paths is disproportionately large, resulting in non-resilient communication that is prone to bottlenecks 53 and vulnerable to delays, loss of information and failure owing to damage 54,55 .”
Gradients of structure–function tethering across neocortex (2019, unknown): “…is arbitrary and there exist several other network-theoretic statistics that also capture the potential for 2 nodes to exchange signals with each other (40), including alternative forms of diffusion (10, 41, 42), contagion (11), parallel exchange via path ensembles (43), and navigation (30).”
Routing in the brain (2014, methodology): “Mišić et al. (2014) further show that posterior cingulate cortex/precuneus and medial temporal cortex demonstrate congestion characteristic of rich club hub nodes, which matches these regions’ proposed roles in integrative functions.”