摘要
在小世界网络基于我们的以前联合脉搏的 integrate-and-Gre 神经原模型,我们在这个模型生产的象 electroencephalographic 一样信号的复杂行为上调查不同连接拓扑学的效果。我们证明若干次,经常是的系列分析方法使用了分析 electroencephalographic-likesignals 的复杂行为,例如在重新可伸缩的范围分析(R/S ) 以内的阶段空间,关联尺寸,分数维的尺寸,和林中小丘代表的重建。我们发现不同连接拓扑学在 integrate-and-fire 神经原的模型导致不同动态行为。
Based on our previously pulse-coupled integrate-and-fire neuron model in small world networks, we investigate the effects of different connectivity topologies on complex behavior of electroencephalographic-like signals produced by this model. We show that several times series analysis methods that are often used for analyzing complex behavior of electroencephalographic-like signals, such as reconstruction of the phase space, correlation dimension, fractal dimension, and the Hurst exponent within the rescaled range analysis (R/S). We lind that the different connectivity topologies lead to different dynamical behaviors in models of integrate-and-fire neurons.
基金
*The project supported by National Natural Science Foundation of China under Grant No. 90203008 and the Doctoral Foundation of the Ministry of Education of China