Xu Qiang, Zhang Qirui, Liu Gaoping, Dai Xi-Jian, Xie Xinyu, Hao Jingru, Yu Qianqian, Liu Ruoting, Zhang Zixuan, Ye Yulu, Qi Rongfeng, Zhang Long Jiang, Zhang Zhiqiang, Lu Guangming
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Department of Radiology, School of Medicine, Jinling Hospital, Nanjing University, Nanjing, China.
Front Hum Neurosci. 2021 Apr 20;15:641961. doi: 10.3389/fnhum.2021.641961. eCollection 2021.
Brain structural covariance network (SCN) can delineate the brain synchronized alterations in a long-range time period. It has been used in the research of cognition or neuropsychiatric disorders. Recently, causal analysis of structural covariance network (CaSCN), winner-take-all and cortex-subcortex covariance network (WTA-CSSCN), and modulation analysis of structural covariance network (MOD-SCN) have expended the technology breadth of SCN. However, the lack of user-friendly software limited the further application of SCN for the research. In this work, we developed the graphical user interface (GUI) toolkit of brain structural covariance connectivity based on MATLAB platform. The software contained the analysis of SCN, CaSCN, MOD-SCN, and WTA-CSSCN. Also, the group comparison and result-showing modules were included in the software. Furthermore, a simple showing of demo dataset was presented in the work. We hope that the toolkit could help the researchers, especially clinical researchers, to do the brain covariance connectivity analysis in further work more easily.
脑结构协方差网络（SCN）能够描绘出大脑在较长时间段内的同步变化。它已被用于认知或神经精神疾病的研究。最近，结构协方差网络的因果分析（CaSCN）、赢家通吃与皮层 - 皮层下协方差网络（WTA - CSSCN）以及结构协方差网络的调制分析（MOD - SCN）扩展了SCN的技术广度。然而，缺乏用户友好型软件限制了SCN在研究中的进一步应用。在这项工作中，我们基于MATLAB平台开发了脑结构协方差连接性的图形用户界面（GUI）工具包。该软件包含SCN、CaSCN、MOD - SCN和WTA - CSSCN的分析。此外，软件还包括组间比较和结果展示模块。此外，在这项工作中还展示了一个简单的演示数据集。我们希望该工具包能够帮助研究人员，特别是临床研究人员，在未来的工作中更轻松地进行脑协方差连接性分析。
