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揭示突发神经元网络的度分布。

Revealing degree distribution of bursting neuron networks.

机构信息

Department of Chemical Physics, University of Science and Technology of China, Hefei, Anhui 230026, People's Republic of China.

出版信息

Chaos. 2010 Mar;20(1):013110. doi: 10.1063/1.3300019.

Abstract

We present a method to infer the degree distribution of a bursting neuron network from its dynamics. Burst synchronization (BS) of coupled Morris-Lecar neurons has been studied under the weak coupling condition. In the BS state, all the neurons start and end bursting almost simultaneously, while the spikes inside the burst are incoherent among the neurons. Interestingly, we find that the spike amplitude of a given neuron shows an excellent linear relationship with its degree, which makes it possible to estimate the degree distribution of the network by simple statistics of the spike amplitudes. We demonstrate the validity of this scheme on scale-free as well as small-world networks. The underlying mechanism of such a method is also briefly discussed.

摘要

我们提出了一种从神经元网络的动力学推断突发神经元网络度分布的方法。在弱耦合条件下,研究了耦合 Morris-Lecar 神经元的突发同步(BS)。在 BS 状态下,所有神经元几乎同时开始和结束突发,而突发内的尖峰在神经元之间是不相干的。有趣的是,我们发现给定神经元的尖峰幅度与其度呈极好的线性关系,这使得通过简单的尖峰幅度统计来估计网络的度分布成为可能。我们在无标度网络和小世界网络上验证了该方案的有效性。还简要讨论了这种方法的潜在机制。

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