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Percolation in networks with local homeostatic plasticity

Percolation is a process that impairs network connectedness by deactivating links or nodes. This process features a phase transition that resembles paradigmatic critical transitions in epidemic spreading, biological networks, traffic and transportation systems. Some biological systems, such as netwo...

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Autores principales: Rapisardi, Giacomo, Kryven, Ivan, Arenas, Alex
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8748765/
https://www.ncbi.nlm.nih.gov/pubmed/35013243
http://dx.doi.org/10.1038/s41467-021-27736-0
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author Rapisardi, Giacomo
Kryven, Ivan
Arenas, Alex
author_facet Rapisardi, Giacomo
Kryven, Ivan
Arenas, Alex
author_sort Rapisardi, Giacomo
collection PubMed
description Percolation is a process that impairs network connectedness by deactivating links or nodes. This process features a phase transition that resembles paradigmatic critical transitions in epidemic spreading, biological networks, traffic and transportation systems. Some biological systems, such as networks of neural cells, actively respond to percolation-like damage, which enables these structures to maintain their function after degradation and aging. Here we study percolation in networks that actively respond to link damage by adopting a mechanism resembling synaptic scaling in neurons. We explain critical transitions in such active networks and show that these structures are more resilient to damage as they are able to maintain a stronger connectedness and ability to spread information. Moreover, we uncover the role of local rescaling strategies in biological networks and indicate a possibility of designing smart infrastructures with improved robustness to perturbations.
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spelling pubmed-87487652022-01-20 Percolation in networks with local homeostatic plasticity Rapisardi, Giacomo Kryven, Ivan Arenas, Alex Nat Commun Article Percolation is a process that impairs network connectedness by deactivating links or nodes. This process features a phase transition that resembles paradigmatic critical transitions in epidemic spreading, biological networks, traffic and transportation systems. Some biological systems, such as networks of neural cells, actively respond to percolation-like damage, which enables these structures to maintain their function after degradation and aging. Here we study percolation in networks that actively respond to link damage by adopting a mechanism resembling synaptic scaling in neurons. We explain critical transitions in such active networks and show that these structures are more resilient to damage as they are able to maintain a stronger connectedness and ability to spread information. Moreover, we uncover the role of local rescaling strategies in biological networks and indicate a possibility of designing smart infrastructures with improved robustness to perturbations. Nature Publishing Group UK 2022-01-10 /pmc/articles/PMC8748765/ /pubmed/35013243 http://dx.doi.org/10.1038/s41467-021-27736-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Rapisardi, Giacomo
Kryven, Ivan
Arenas, Alex
Percolation in networks with local homeostatic plasticity
title Percolation in networks with local homeostatic plasticity
title_full Percolation in networks with local homeostatic plasticity
title_fullStr Percolation in networks with local homeostatic plasticity
title_full_unstemmed Percolation in networks with local homeostatic plasticity
title_short Percolation in networks with local homeostatic plasticity
title_sort percolation in networks with local homeostatic plasticity
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8748765/
https://www.ncbi.nlm.nih.gov/pubmed/35013243
http://dx.doi.org/10.1038/s41467-021-27736-0
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