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Inducing Long-Term Plasticity of Intrinsic Neuronal Excitability in Neurons of the Dorsal Lateral Geniculate Nucleus

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Percolation in networks with local homeostatic plasticity.

Giacomo Rapisardi^1,2, Ivan Kryven^3,4, Alex Arenas⁵

¹Departament d'Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, E-43007, Tarragona, Spain.

Nature Communications

|January 11, 2022

Summary

Active networks resist damage better than passive ones by actively responding to link failures, maintaining connectivity and information flow. This resilience is key for biological systems and smart infrastructure design.

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Area of Science:

Network science
Complex systems
Biological systems

Background:

Percolation theory describes network damage and phase transitions.
Biological networks like neural cells actively respond to damage.
Existing models often overlook active network responses.

Purpose of the Study:

To investigate percolation in active networks with synaptic scaling-like mechanisms.
To explain critical transitions in these responsive networks.
To assess the resilience and information spreading capabilities of active networks.

Main Methods:

Simulating percolation on networks with active link repair/adaptation.
Analyzing phase transitions and network connectedness.
Comparing active versus passive network responses to damage.

Main Results:

Active networks exhibit enhanced resilience to damage.
Synaptic scaling-like mechanisms maintain network connectedness.
Active networks show improved information spreading capacity.
Local rescaling strategies play a crucial role.

Conclusions:

Active network responses significantly improve robustness to perturbations.
Synaptic scaling is a key mechanism for maintaining function in degrading biological systems.
Findings suggest principles for designing resilient smart infrastructures.