Articles producció científicaEnginyeria Informàtica i Matemàtiques

Percolation in networks with local homeostatic plasticity

  • Identification data

    Identifier:  imarina:9381081
    Authors:  Rapisardi, G; Kryven, I; Arenas, A
    Abstract:
    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.
  • Others:

    Link to the original source: https://www.nature.com/articles/s41467-021-27736-0
    APA: Rapisardi, G; Kryven, I; Arenas, A (2022). Percolation in networks with local homeostatic plasticity. Nature Communications, 13(1), 122-. DOI: 10.1038/s41467-021-27736-0
    Paper original source: Nature Communications. 13 (1): 122-
    Article's DOI: 10.1038/s41467-021-27736-0
    Journal publication year: 2022-01-10
    Entity: Universitat Rovira i Virgili
    Paper version: info:eu-repo/semantics/publishedVersion
    Record's date: 2026-05-09
    URV's Author/s: Arenas Moreno, Alejandro / Rapisardi, Giacomo
    Department: Enginyeria Informàtica i Matemàtiques
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Publication Type: Journal Publications
    Author, as appears in the article.: Rapisardi, G; Kryven, I; Arenas, A
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Thematic Areas: Physics and astronomy (miscellaneous), Physics and astronomy (all), Multidisciplinary sciences, Multidisciplinary, General physics and astronomy, General medicine, General chemistry, General biochemistry,genetics and molecular biology, Ciencias sociales, Ciencias humanas, Chemistry (miscellaneous), Chemistry (all), Biochemistry, genetics and molecular biology (miscellaneous), Biochemistry, genetics and molecular biology (all), Astronomia / física, Antropologia / arqueologia
    Author's mail: alexandre.arenas@urv.cat, alexandre.arenas@urv.cat
  • Keywords:

    Neural networks
    computer
    Nerve net
    Models
    statistical
    Humans
    Homeostasis
    Computer simulation
    Animals
    Algorithms
    Biochemistry
    Genetics and Molecular Biology (Miscellaneous)
    Chemistry (Miscellaneous)
    Multidisciplinary
    Multidisciplinary Sciences
    Physics and Astronomy (Miscellaneous)
    Physics and astronomy (all)
    General physics and astronomy
    General medicine
    General chemistry
    General biochemistry
    genetics and molecular biology
    Ciencias sociales
    Ciencias humanas
    Chemistry (all)
    genetics and molecular biology (all)
    Astronomia / física
    Antropologia / arqueologia
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