In this research, a number of popular network measurement algorithms have been applied to several brain networks (based on applicability of algorithms) for finding out statistical correlation among these popular network measurements which will help scientists to understand these popular network measurement algorithms and their applicability to brain networks. By analysing the results of correlations among these network measurement algorithms, statistical comparison among selected brain networks has also been summarized. Besides that, to understand each brain network, the visualization of each brain network and each brain network degree distribution histogram have been extrapolated. Six network measurement algorithms have been chosen to apply time to time on sixteen brain networks based on applicability of these network measurement algorithms and the results of these network measurements are put into a correlation method to show the relationship among these six network measurement algorithms for each brain network. At the end, the results of the correlations have been summarized to show the statistical comparison among these sixteen brain networks.

翻译：本研究针对若干脑网络（基于算法适用性）应用多种流行网络度量算法，旨在探究这些常用网络度量指标之间的统计相关性，以帮助科研人员理解这些流行网络度量算法及其在脑网络中的适用性。通过分析网络度量算法间的相关性结果，本文还对选定脑网络进行了统计比较。此外，为深入理解各脑网络特性，本研究还推演了各脑网络的可视化图谱及其度分布直方图。根据六种网络度量算法在不同脑网络中的适用性，我们逐一将其应用于十六个脑网络，并将度量结果纳入相关性分析方法，以揭示各脑网络中六种网络度量算法之间的关联。最终通过汇总相关性结果，对十六个脑网络进行了统计比较。