A spectrum of routing strategies for brain networks

TL;DR

This paper introduces a stochastic model for brain network communication that blends local and global information, revealing a spectrum of routing strategies that optimize efficiency and cost, and varies with network demands and resources.

Contribution

The study presents a novel model combining local and global network information, bridging shortest-path and diffusion communication, and applies it to human connectomes to explore efficiency and individual differences.

Findings

Routing strategies approaching shortest-path communication with limited global info.

Cost of message routing varies with hub nodes and global information levels.

Model reveals individual differences in brain communication dynamics.

Abstract

Communication of signals among nodes in a complex network poses fundamental problems of efficiency and cost. Routing of messages along shortest paths requires global information about the topology, while spreading by diffusion, which operates according to local topological features, is informationally "cheap" but inefficient. We introduce a stochastic model for network communication that combines varying amounts of local and global information about the network topology. The model generates a continuous spectrum of dynamics that converge onto shortest-path and random-walk (diffusion) communication processes at the limiting extremes. We implement the model on two cohorts of human connectome networks and investigate the effects of varying amounts of local and global information on the network's communication cost. We identify routing strategies that approach a (highly efficient) shortest-path communication process with a relatively small amount of global information. Moreover, we show that the cost of routing messages from and to hub nodes varies as a function of the amount of global information driving the system's dynamics. Finally, we implement the model to identify individual subject differences from a communication dynamics point of view. The present framework departs from the classical shortest paths vs. diffusion dichotomy, suggesting instead that brain networks may exhibit different types of communication dynamics depending on varying functional demands and the availability of resources.