论文标题
Rulkov神经网络破裂动力学制度的符号分析
Symbolic analysis of bursting dynamical regimes of Rulkov neural networks
论文作者
论文摘要
由Rulkov地图建模的神经元显示了各种动态状态，包括刺激性尖峰和混乱的爆发。在这里，我们研究了一个爆发神经元的合奏，以及瓦特 - 史特罗加兹（Watts-Strogatz）小世界拓扑结构。我们使用称为序数分析的时间序列分析的符号方法来表征爆发的序列，该方法检测非线性时间相关性。我们表明，不同符号的概率区分了不同的动力学制度，这取决于耦合强度和网络拓扑。这些机制具有不同的时空特性，可以用栅格图可视化。
Neurons modeled by the Rulkov map display a variety of dynamic regimes that include tonic spikes and chaotic bursting. Here we study an ensemble of bursting neurons coupled with the Watts-Strogatz small-world topology. We characterize the sequences of bursts using the symbolic method of time-series analysis known as ordinal analysis, which detects nonlinear temporal correlations. We show that the probabilities of the different symbols distinguish different dynamical regimes, which depend on the coupling strength and the network topology. These regimes have different spatio-temporal properties that can be visualized with raster plots.
