Ageing transitions in a network of Rulkov neurons

Abstract

The phenomenon of ageing transitions (AT) in a Erdős–Rényi network of coupled Rulkov neurons is studied with respect to parameters modelling network connectivity, coupling strength and the fractional ratio of inactive neurons in the network. A general mean field coupling is proposed to model the neuronal interactions. A standard order parameter is defined for quantifying the network dynamics. Investigations are undertaken for both the noise free network as well as stochastic networks, where the interneuronal coupling strength is assumed to be superimposed with additive noise. The existence of both smooth and explosive AT are observed in the parameter space for both the noise free and the stochastic networks. The effects of noise on AT are investigated and are found to play a constructive role in mitigating the effects of inactive neurons and reducing the parameter regime in which explosive AT is observed.

Fault resilience in network of energy harvesters

“…Recent research, such as that by Kurths et al [17], illustrate how cutting connections between nodes compromises the stability of power grids, emphasizing the crucial role of individual connections in overall network robustness. Additionally, investigations into ageing effects on biological neuron networks [18] reveal the gradual loss of node functionality during ageing transitions. Furthermore, the application of complex network theory in assessing power grid resilience, as seen in Indian contexts [19], showcases the adaptability of this theory across diverse domains.…”