论文标题
神经元网络中的随机群体渗透和噪声聚焦
Stochastic quorum percolation and noise focusing in neuronal networks
论文作者
论文摘要
最近的实验表明，由于噪声活性的定位，即噪声焦点的定位，年轻分离神经元培养物的自发活性可以描述为高度不均匀成核和前繁殖的过程。但是，对导致成核的噪声积累机理的基本理解仍然是一个开放的基本问题。在这里，我们提出了一个最小的动力学模型，称为随机群体渗透，可以解释观察到的现象，同时提供强大的理论框架。该模型分别重现了爆发动力学和神经元雪崩的第一阶和二阶阶段，并捕获了网络拓扑中的深刻效应度量相关性，可以对动态产生。讨论了我们的结果在其他系统中的应用，例如传播传染病和谣言。
Recent experiments have shown that the spontaneous activity of young dissociated neuronal cultures can be described as a process of highly inhomogeneous nucleation and front propagation due to the localization of noise activity, i.e., noise focusing. However, the basic understanding of the mechanisms of noise build-up leading to the nucleation remain an open fundamental problem. Here we present a minimal dynamical model called stochastic quorum percolation that can account for the observed phenomena, while providing a robust theoretical framework. The model reproduces the first and second order phase--transitions of bursting dynamics and neuronal avalanches respectively, and captures the profound effect metric correlations in the network topology can have on the dynamics. The application of our results to other systems such as in the propagation of infectious diseases and of rumors is discussed.
