Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
Nat Commun. 2022 Sep 8;13(1):5301. doi: 10.1038/s41467-022-32913-w.
Many collective phenomena such as epidemic spreading and cascading failures in socioeconomic systems on networks are caused by perturbations of the dynamics. How perturbations propagate through networks, impact and disrupt their functions may depend on the network, the type and location of the perturbation as well as the spreading dynamics. Previous work has analyzed the retardation effects of the nodes along the propagation paths, suggesting a few transient propagation "scaling" regimes as a function of the nodes' degree, but regardless of motifs such as triangles. Yet, empirical networks consist of motifs enabling the proper functioning of the system. Here, we show that basic motifs along the propagation path jointly determine the previously proposed scaling regimes of distance-limited propagation and degree-limited propagation, or even cease their existence. Our results suggest a radical departure from these scaling regimes and provide a deeper understanding of the interplay of self-dynamics, interaction dynamics, and topological properties.
许多集体现象,如网络上的流行病传播和社会经济系统中的级联故障,都是由动力学的扰动引起的。扰动如何在网络中传播,影响和破坏它们的功能,可能取决于网络、扰动的类型和位置以及传播动力学。以前的工作已经分析了沿传播路径的节点的延迟效应,提出了几个作为节点度的函数的瞬态传播“标度”区域,但不考虑三角形等模式。然而,经验网络由模式组成,这些模式使系统能够正常运行。在这里,我们表明,传播路径上的基本模式共同决定了以前提出的距离限制传播和度限制传播的标度区域,甚至使其不存在。我们的结果表明,这与这些标度区域有很大的不同,并提供了对自动力学、相互作用动力学和拓扑性质相互作用的更深入的理解。