Department of Physics, Indian Institute of Technology Madras, Chennai, Tamil Nadu, 700036, India.
The Uncertainty Lab, Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai, Tamil Nadu, 700036, India.
Sci Rep. 2022 Jan 10;12(1):433. doi: 10.1038/s41598-021-03844-1.
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.
研究了耦合 Rulkov 神经元 Erdős-Rényi 网络中的老化跃迁 (AT) 现象，涉及到建模网络连接、耦合强度和网络中不活跃神经元的分数比例的参数。提出了一种通用的平均场耦合来模拟神经元的相互作用。定义了一个标准的序参量来量化网络动力学。研究了无噪声网络和随机网络两种情况，其中假设神经元间的耦合强度叠加了外加噪声。在无噪声和随机网络的参数空间中都观察到了平滑和爆炸 AT 的存在。研究了噪声对 AT 的影响，发现噪声在减轻不活跃神经元的影响和减少观察到爆炸 AT 的参数区域方面起着建设性的作用。
