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：在这一研究中,对若干大脑网络(基于算法的适用性)应用了一些广受欢迎的网络测量算法,以找出这些广受欢迎的网络测量方法之间的统计相关性,这将有助于科学家了解这些广受欢迎的网络测量算法及其对大脑网络的适用性。通过分析这些网络测量算法之间相互关系的结果,还总结了选定的脑网络之间的统计比较。此外,为了了解每个大脑网络,对每个脑网络和每个脑网络的可视化和每个脑网络学位分布直方图进行了外推推断。根据这些网络测量算法的适用性,选择了六个网络测量算法,对16个大脑网络的时间进行时间应用,并将这些网络测量结果纳入一个相关方法,以显示每个脑网络的这六个网络测量算法之间的关系。最后,对这些关联的结果进行了总结,以显示这16个脑网络之间的统计比较。