Estimation of structural characteristics of synaptic networks based on the functional networks derived from neural activity

我们探讨了从神经元的发放活动中提取突触网络的结构特征的可能性，分析了突触网络和由成对发放相关产生的功能网络之间的相似性。我们提出了一种基于成对发放相关性和每个神经元功能连接数的条件来构造功能网络的方法。我们的结果表明，所提出的方法可以产生的功能网络，表现出类似的结构特征的突触网络的统计特征的网络结构，如聚类系数和平均最短路径长度。

We explored the possibility to extract structural characteristics of a synaptic network from neuronal spiking activity analyzing similarity between the synaptic network and the functional network generated by pairwise spike correlation. We developed the method to construct a functional network based on pairwise spike correlation and a condition about the number of functional connections per a neuron. Our result indicated that the proposed method could yield the functional networks that showed similar structural characteristics to synaptic networks with respect to statistics characterizing network structure such as clustering coefficients and average shortest path length.