Creative destruction: Sparse activity emerges on the mammal connectome under a simulated communication strategy with collisions and redundancy

Abstract

Collision dynamics in brain network communication have been little studied. We describe a novel interaction that shows how nonlinear collision rules can result in efficient activity dynamics on simulated mammal brain networks. We tested the effects of collisions in "information spreading" (IS) models in comparison to standard random walk (RW) models. Simulations employ synchronous agents on tracerbased mesoscale mammal connectomes at a range of signal loads. We find that RW routing models have high average activity, which increases substantially with load. Activity in RW models is densely distributed over nodes: a substantial fraction are highly active in a given time window, and this fraction increases with load. Surprisingly, while IS routing models make many more attempts to pass signals, they show lower net activity due to collisions compared to RW. Activity in IS increases relatively little over a wide range of loads. In addition, IS models have greater sparseness (which decreases slowly with load) compared to RW models. Results hold on two networks of the monkey cortex and one of the mouse wholebrain. We also find evidence that activity is lower and more sparse for empirical networks compared to degree-matched randomized networks in IS, suggesting network topology supports IS routing.A given topology can support a range of routing strategies, giving rise to different observable dynamics (see, e.g., Friston, 2011). To begin to understand what routing strategy is in use in the brain, one can look to design considerations in engineered systems (Graham and Rockmore, 2010;Graham 2014;Navlakha et al., 2015;Fornito et al., 2016). A fundamental challenge for any large-scale communication system is the management of collisions. Collisions are the price paid for the ability to route signals selectively and dynamically to many possible destinations. Collision dynamics are emergent: they are a nonlinear effect of node dynamics, topology, and current traffic. All large-scale engineered communication systems have a means of managing collisions, through redress, arbitration, and other strategies (see e.g., Kleinrock, 1976;Mišić and Mišić, 2014).

Evidence for increased parallel information transmission in human brain networks compared to macaques and mice

“…Shortest-path communication explains a limited portion of functional connectivity 10 and excludes a large fraction of brain network connections and near-optimal alternative pathways from the communication process 23 . Recent studies have started to account for more complex mechanisms of information routing, such as parallel communication (i.e., relay of information through multiple, parallel communication pathways) [23][24][25][26] or convergent routing (i.e., neural signals' interaction through convergent pathways) 27,28 . Indeed, in many real-world systems, information transmission unfolds through numerous alternative pathways 29 .…”