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Dynamic brain connectome analysis toolbox

Dynamic brain connectome (DynamicBC) analysis toolbox is a Matlab toolbox to calculate Dynamic Functional Connectivity (d-FC) and Dynamic Effective Connectivity (d-EC). Sliding window analysis (Bivariate Pearson correlation and Granger causality) and time varying parameter regression method (Flexible Least Squares) are two dynamic analysis strategies for time-variant connectivity analysis in the DynamicBC. Granger causality density/strength (GCD/GCS) and functional connectivity density/strength (FCD/FCS) analysis would be performed in this toolbox. Add DynamicBC's directory to MATLAB's path and enter "DynamicBC" in the command window of MATLAB to enjoy it.

The latest release is DynamicBC2.2_20181112

Manual could also be downloaded here

New features of DynamicBC 2.0 release 20180311:
New features of DynamicBC2.2 release 20181112:
--Added a visualization module for connectogram.
--Added a demo for visualization a connectogram.
--Added new feature for cluster number estimation.
--Fixed a bug for clustering the ALFF maps.

 

New features of DynamicBC 2.0 release 20180311:
   --Fixed minor bugs in the Clustering module.

New features of DynamicBC 2.0 release 20171228:
1. Changed the toolbox cover.
2. Added the new module for dynamic intrinsic brain activity (dynamic ALFF).  

 

New features of DynamicBC 1.2 release 20160415

Fixed the step bugs when selecting window size.

 

New features of DynamicBC 1.1 release 20140710:
1. Added the new utilties including the ‘Clustering’ and 'Spectrum' for dynamic FC/EC time series.
2. Added the new output of variance of dynamic FC/EC time series.  
 

New features of DynamicBC 1.0 release 20140429
This release fixed some minor bugs in dynamic FCD.

rest

老师您好,我刚刚开始学习应用这些软件。看了您的视频教程,在用REST处理原始数据的时候,选择REST—UTILITIES__REST DICOM SORTER,选择文件之后,不在空白那里出现,点击RUN,之后就出现这个
 
那个后缀名三种都试过,IMA,dcm,none都是这样结果。后来直接用光盘里面的数据也是这样。请问老师这是哪里出错了呢?多谢老师指教
另外,如果不用rest批处理的话,还可以用什么软件做批处理的呢?
再次感谢老师指教

回归与方差分析协变量问题请教各位老师

各位老师好,
我有一个关于三组病人单因素三水平方差分析FA的问题,考虑到年龄可能对白质改变起影响,所以就想在做方差分析的时候设年龄为协变量。之前试验性地比较了有无协变量情况的主效应,发现F-map还是不一样的。

首先,我不是很确定这算不算协方差分析。
其次,如果按照协方差的分析,前提需要满足年龄这个协变量与三组病人图像的回归系数,也就是斜率是一致的,才可行协方差分析。
第三,如果要评价三组病人图像跟各自年龄的回归系数,该在SPM里怎么操作?另外,如果三者的回归系数不一致,也就是说三条回归方程线有交叉,那我应该怎么处理年龄这个因素呢?
最后,如果在anova当中加了年龄做协变量,那么在随后的组间比较(事后分析)的时候,我还需要在T检验的时候加每两组的年龄作为他们的协变量吗?

不知道表述的清不清楚,问题有点繁琐,先谢谢各位老师啦~