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

我们探索了从神经元放电活动中提取突触网络结构特征的可能性，分析了突触网络与由成对棘波相关产生的功能网络之间的相似性。我们发展了一种基于成对棘波相关和关于每个神经元的功能连接数目的条件来构建功能网络的方法。我们的结果表明，该方法可以产生与突触网络具有相似结构特征的功能网络，这些功能网络在表征网络结构的统计方面表现出类似于突触网络的结构特征，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.