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：转化后的摘要:
在本研究中，已经应用了多种流行度量算法来分析多个脑网络（基于算法的适用性），以找出这些流行度量算法之间的统计相关性，这将有助于科学家了解这些流行度量算法及其在脑网络中的适用性。通过分析这些网络度量算法之间的相关性结果，还总结了在所选脑网络之间进行统计比较。此外，为了了解每个脑网络，已推导出了每个脑网络的可视化和每个脑网络度数分布直方图。根据算法的适用性，选择了6种网络度量算法，时间轴上应用于16个脑网络进行度量，将这些网络度量的结果放入相关方法中，以显示每个脑网络中这6种网络度量算法的关系。最后，总结了这些脑网络之间的统计比较结果。
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