Optimal navigability of weighted human brain connectomes in physical space

Fuente: arXiv
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Main Authors: Barjuan, Laia, Soriano, Jordi, Serrano, M. Ángeles
Format: Preprint
Published: 2023
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author Barjuan, Laia
Soriano, Jordi
Serrano, M. Ángeles
author_facet Barjuan, Laia
Soriano, Jordi
Serrano, M. Ángeles
contents The architecture of the human connectome supports efficient communication protocols relying either on distances between brain regions or on the intensities of connections. However, none of these protocols combines information about the two or reaches full efficiency. Here, we introduce a continuous spectrum of decentralized routing strategies that combine link weights and the spatial embedding of connectomes to transmit signals. We applied the protocols to individual connectomes in two cohorts, and to cohort archetypes designed to capture weighted connectivity properties. We found that there is an intermediate region, a sweet spot, in which navigation achieves maximum communication efficiency at low transmission cost. Interestingly, this phenomenon is robust and independent of the particular configuration of weights.Our results indicate that the intensity and topology of neural connections and brain geometry interplay to boost communicability, fundamental to support effective responses to external and internal stimuli and the diversity of brain functions.
format Preprint
id arxiv_https___arxiv_org_abs_2311_10669
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Optimal navigability of weighted human brain connectomes in physical space
Barjuan, Laia
Soriano, Jordi
Serrano, M. Ángeles
Neurons and Cognition
Biological Physics
Physics and Society
The architecture of the human connectome supports efficient communication protocols relying either on distances between brain regions or on the intensities of connections. However, none of these protocols combines information about the two or reaches full efficiency. Here, we introduce a continuous spectrum of decentralized routing strategies that combine link weights and the spatial embedding of connectomes to transmit signals. We applied the protocols to individual connectomes in two cohorts, and to cohort archetypes designed to capture weighted connectivity properties. We found that there is an intermediate region, a sweet spot, in which navigation achieves maximum communication efficiency at low transmission cost. Interestingly, this phenomenon is robust and independent of the particular configuration of weights.Our results indicate that the intensity and topology of neural connections and brain geometry interplay to boost communicability, fundamental to support effective responses to external and internal stimuli and the diversity of brain functions.
title Optimal navigability of weighted human brain connectomes in physical space
topic Neurons and Cognition
Biological Physics
Physics and Society
url https://arxiv.org/abs/2311.10669