Impacts of clustering on noise-induced spiking regularity in the excitatory neuronal networks of subnetworks.

In this paper, we investigate how clustering factors influent spiking regularity of the neuronal network of subnetworks. In order to do so, we fix the averaged coupling probability and the averaged coupling strength, and take the cluster number M, the ratio of intra-connection probability and inter-connection probability R, the ratio of intra-coupling strength and inter-coupling strength S as controlled parameters. With the obtained simulation results, we find that spiking regularity of the neuronal networks has little variations with changing of R and S when M is fixed. However, cluster number M could reduce the spiking regularity to low level when the uniform neuronal network's spiking regularity is at high level. Combined the obtained results, we can see that clustering factors have little influences on the spiking regularity when the entire energy is fixed, which could be controlled by the averaged coupling strength and the averaged connection probability.

在本文中，我们研究聚类因素如何影响子网络的神经元网络的脉冲发放规律性。为此，我们固定平均耦合概率和平均耦合强度，并将聚类数\(M\)、内部连接概率与外部连接概率之比\(R\)、内部耦合强度与外部耦合强度之比\(S\)作为控制参数。通过获得的模拟结果，我们发现当\(M\)固定时，神经元网络的脉冲发放规律性随\(R\)和\(S\)的变化很小。然而，当均匀神经元网络的脉冲发放规律性处于较高水平时，聚类数\(M\)可使脉冲发放规律性降低到较低水平。综合所得结果，我们可以看到当总能量固定时，聚类因素对脉冲发放规律性影响很小，总能量可由平均耦合强度和平均连接概率控制。