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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Bibliographic Details
Published in:Nature communications 2022-01, Vol.13 (1), p.122-122, Article 122
Main Authors: Rapisardi, Giacomo, Kryven, Ivan, Arenas, Alex
Format: Article
Language:English
Subjects:
631/378/1831
639/766/530/2801
Aging
Algorithms
Animals
Computer Simulation
Damage
Epidemics
Homeostasis - physiology
Homeostatic plasticity
Humanities and Social Sciences
Humans
Mathematical models
Models, Statistical
multidisciplinary
Nerve Net - physiology
Neural Networks, Computer
Percolation
Perturbation
Phase transitions
Rescaling
Robustness (mathematics)
Scaling
Science
Science (multidisciplinary)
Transportation networks
Transportation systems
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Summary: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. Link damages and failures can break the functionality of the whole complex network. Inspired by biological systems that respond to damages, the authors propose a mathematical model revealing the effect of homeostatic response to damage of links to keep the network’s global function.
ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-021-27736-0