Quantifying synergy and redundancy between networks
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
Understanding how different networks relate to each other is key for understanding complex systems. We introduce an intuitive yet powerful framework to disentangle different ways in which networks can be (dis)similar and complementary to each other. We decompose the shortest paths between nodes as uniquely contributed by one source network, or redundantly by either, or synergistically by both together. Our approach considers the networks’ full topology, providing insights at multiple levels of resolution: from global statistics to individual paths. Our framework is widely applicable across scientific domains, from public transport to brain networks. In humans and 124 other species, we demonstrate the prevalence of unique contributions by long-range white-matter fibers in structural brain networks. Across species, efficient communication also relies on significantly greater synergy between long-range and short-range fibers than expected by chance. Our framework could find applications for designing network systems or evaluating existing ones.
Date Issued
2024-04-17
Date Acceptance
2024-03-01
Citation
Cell Reports Physical Science, 2024, 5 (4)
ISSN
2666-3864
Publisher
Elsevier
Journal / Book Title
Cell Reports Physical Science
Volume
5
Issue
4
Copyright Statement
© 2024 The Authors.
This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
License URL
Identifier
https://www.sciencedirect.com/science/article/pii/S2666386424001280?via%3Dihub
Subjects
BRAIN
Chemistry
Chemistry, Multidisciplinary
CONNECTOME
Energy & Fuels
Materials Science
Materials Science, Multidisciplinary
Physical Sciences
Physics
Physics, Multidisciplinary
Science & Technology
SPECIFICITY
Technology
Publication Status
Published
Article Number
101892
Date Publish Online
2024-03-28