Bhandary Subhendu, Kaur Taranjot, Banerjee Tanmoy, Dutta Partha Sharathi
Department of Mathematics, Indian Institute of Technology Ropar, Rupnagar 140 001, Punjab, India.
Chaos and Complex Systems Research Laboratory, Department of Physics, University of Burdwan, Burdwan 713 104, West Bengal, India.
Phys Rev E. 2021 Feb;103(2-1):022314. doi: 10.1103/PhysRevE.103.022314.
Many complex networks are known to exhibit sudden transitions between alternative steady states with contrasting properties. Such a sudden transition demonstrates a network's resilience, which is the ability of a system to persist in the face of perturbations. Most of the research on network resilience has focused on the transition from one equilibrium state to an alternative equilibrium state. Although the presence of nonequilibrium dynamics in some nodes may advance or delay sudden transitions in networks and give early warning signals of an impending collapse, it has not been studied much in the context of network resilience. Here we bridge this gap by studying a neuronal network model with diverse topologies, in which nonequilibrium dynamics may appear in the network even before the transition to a resting state from an active state in response to environmental stress deteriorating their external conditions. We find that the percentage of uncoupled nodes exhibiting nonequilibrium dynamics plays a vital role in determining the network's transition type. We show that a higher proportion of nodes with nonequilibrium dynamics can delay the tipping and increase networks' resilience against environmental stress, irrespective of their topology. Further, predictability of an upcoming transition weakens, as the network topology moves from regular to disordered.
许多复杂网络已知会在具有不同特性的交替稳态之间表现出突然转变。这种突然转变体现了网络的恢复力,即系统在面对扰动时持续存在的能力。大多数关于网络恢复力的研究都集中在从一个平衡态到另一个平衡态的转变上。尽管某些节点中存在非平衡动力学可能会提前或延迟网络中的突然转变,并给出即将崩溃的早期预警信号,但在网络恢复力的背景下对此研究不多。在这里,我们通过研究具有不同拓扑结构的神经元网络模型来弥合这一差距,在该模型中,即使在因环境压力导致外部条件恶化而从活跃状态转变为静息状态之前,网络中也可能出现非平衡动力学。我们发现,表现出非平衡动力学的未耦合节点的百分比在确定网络的转变类型中起着至关重要的作用。我们表明,无论其拓扑结构如何,具有非平衡动力学的节点比例越高,就越能延迟临界点并增强网络对环境压力的恢复力。此外,随着网络拓扑结构从规则变为无序,即将到来的转变的可预测性会减弱。