可嵌入欧氏空间的可激发节点随机网络中的延迟效应
The effect of retardation in the random networks of excitable nodes embeddable in the Euclidean space
摘要：
随机网络中的可激发节点嵌入欧氏空间，其某些特征不能用传统的积分点火模型（IFM）来描述，需要进一步研究。在本文中，我们考虑的延迟，即所需的时间，信号之间的两个代理之间的遍历的效果。这种效应对于发现例如具有低轴突传导时间和快速轴突传导时间的神经网络之间的差异变得重要。我们表明，列入延迟效应使一些重要的变化，系统的统计特性。它大大抑制/限制了随机网络中可能振荡的幅度。此外，它还导致临界状态下的临界指数发生相当大的变化。
英文摘要：
Some features of random networks with excitable nodes that are embeddable in the Euclidean space are not describable in terms of the conventional integrate and fire model (IFM) alone, and some further details should be involved. In the present paper we consider the effect of the retardation, i.e. the time that is needed for a signal to traverse between two agents. This effect becomes important to discover the differences between e.g. the neural networks with low and fast axon conduct times. We show that the inclusion of the retardation effects makes some important changes in the statistical properties of the system. It considerably suppresses/restricts the amplitude of the possible oscillations in the random network. Additionally, it causes the critical exponents in the critical regime to considerably change.
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