Optimal navigability of weighted human brain connectomes in physical space

• Published in: NeuroImage (Orlando, Fla.) Fla.), 2024-08, Vol.297, p.120703, Article 120703
• Main Authors: Barjuan, Laia, Soriano, Jordi, Serrano, M. Ángeles
• Format: Article
• Language: English
• Subjects: Brain; Brain connectomes; Cognition & reasoning; Communication; Complex networks; Datasets; Efficiency; Embedding; Euclidean space; Navigability; Navigation behavior; Network neuroscience; Neural networks; Seeds; Spatial embedding; Stochasticity; Weighted structure
• ISSN: 1053-8119; 1095-9572; 1095-9572
• DOI: 10.1016/j.neuroimage.2024.120703

Communication protocols in the brain connectome describe how to transfer information from one region to another. Typically, these protocols hinge on either the spatial distances between brain regions or the intensity of their connections. Yet, none of them combine both factors to achieve optimal efficiency. Here, we introduce a continuous spectrum of decentralized routing strategies that integrates link weights and the spatial embedding of connectomes to route signal transmission. We implemented the protocols on connectomes from individuals in two cohorts and on group-representative connectomes designed to capture weighted connectivity properties. We identified an intermediate domain of routing strategies, a sweet spot, where navigation achieves maximum communication efficiency at low transmission cost. This phenomenon is robust and independent of the particular configuration of weights. Our findings suggest an interplay between the intensity of neural connections and their topology and geometry that amplifies communicability, where weights play the role of noise in a stochastic resonance phenomenon. Such enhancement may support more effective responses to external and internal stimuli, underscoring the intricate diversity of brain functions. [Display omitted] •Geometry, topology, and weights in human connectomes determine communicability.•Decentralized high-weight short-distance routing results in optimal navigability.•Information transfer is maximal when weights and spatial distances are balanced.•Maximum navigability is robust to severe injury in brain regions.•Maximum navigability is independent of the particular configuration of weights.