Dynamic brain connectome analysis toolbox

Submitted by Wei Liao on Tue, 04/08/2014 - 08:25

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.

AttachmentSize
Package icon DynamicBC2.2_20181112.zip5.43 MB

Submitted by hoptman on Mon, 07/14/2014 - 23:20

Hi,

I'm interested to use the toolbox, but I do not know how to generate the plots that you show in your Manual (e.g., on page 51).  Could you please tell me how to do it? 

Thanks,
Matthew Hoptman
hoptman@nki.rfmh.org
 

Submitted by yubing on Mon, 09/28/2015 - 23:12

Dynamic EC模块
采用 Slide Window 模式

出错信息如下 ，请求指教，多谢！

Now DynamicBC is running on 0 workers.
Running now!
Default mode: fMRI(reading from NIFTI image), if not? choose "Set ROI/ ROI wise"
Default value 0/NaN is not in the mask/label!
Default value>0 is inside the mask!
There are 104388 voxels inside the mask
Running subject    1 (all    8 subjects)
abc
Subscripted assignment dimension mismatch.

Error in DynamicBC_sliding_window_GC (line 87)
                Matrix(GCM.indX{i},:) =  GCM.matrix{i,1};

Error in DynamicBC_run (line 265)
                DynamicBC_sliding_window_GC(ROI_sig,slw_winsize,slw_overlapsize,pvalue,slw_order,save_info);
               
Error in DynamicBC>wgr_run_check (line 1126)
    DynamicBC_run(F)
 
Error while evaluating uicontrol Callback

Submitted by bgpliting on Mon, 09/28/2015 - 09:50

 data directory输入文件夹为E:\analysis\FunImgARCWSDF，run的时候报错：

??? Error using ==> matlabpool

Too many output arguments.
 
Error in ==> DynamicBC>wgr_run_all at 944

mps = matlabpool('size');
 
??? Error while evaluating uicontrol Callback



不知是什么问题？检查过预处理文件，好像没有错误。非常期待老师的回复，谢谢！

Submitted by Chen0075 on Tue, 05/10/2016 - 07:08

A new feature "clustering" was added into the new vertion of "DynamicBC" tool, but what's the processes (principle) in your "clustering". In addtion, by your tool, can I obtain the "dwell time" in each state that is regared as the number of windows belonging to the special state related cluster? and the "transition times (numbers) between states"? how can I display these results in the matlab. thanks!

Submitted by Wei Liao on Tue, 05/10/2016 - 16:40

The cluster analysis in DynamicBC toolbox was a prelimeinary attempt, and it would be not well advised. Thank you for your good question. The principle of k-means is very simple. We just reshape the data into 2-dimension matrix (voxel/roi * time-window) and concatenate it subject by subject. Then we use kmean function in Matlab to generate k clusters in group level. After that, we use kmean to generate k clusters in every subject. Pearson correlation is used to re-order every subject's k clusters to match the order of group level. Well, the labels of every time-window map/matrix or the "dwell time" has been generated in the function of kmean. Unfortunately, we didn't save it out in the function. You could add this line of code, 'save([outputd,'mat_',CluMet,'_Kmeans_',num2str(k),'_Order.mat'],'IDX_all','IDX_subj','IDX_subjre');', to the end of the function "dynamicBC_clustermatrix_beta.m"/"dynamicBC_clustermaps_beta.m". The variable IDX_all would give us the distribution of k clusters in the whole maps/matrices. The variable IDX_subj is a 2-dimension matrix (subj num * time-window) The variable IDX_subjre is a 2-dimension matrix (subj num * time-window), which represents the re-ordered lables sorted according the group level by using the pearson correlation. The new version would come soon and it would fix the problem. Hope it could help you. If you have other questions or good ideas, please contract us. It would help us to make the toolbox better.

Submitted by Chen0075 on Fri, 10/07/2016 - 10:10

Could we use Dynamic brain connectome analysis toolbox to analyze the data and publish SCI paper, Since you said "The cluster analysis in DynamicBC toolbox was a prelimeinary attempt, and it would be not well advised". When will you update the version of this toolbox? 

Submitted by yubing on Fri, 01/12/2018 - 23:30

DyanmicBC 项目组的各位老师：
 
您好，我在用DyanmicBC 2.0的时候，程序报错信息如下（Linux，Matlab2013a，DyanmicBC 2.0）
 
Error using  -
Too many input arguments.

Error in DynamicBC_run (line 99)
    if any(v0(1).dim-vm.dim)

Error in DynamicBC>wgr_run_check (line 1067)
    DynamicBC_run(F)
 
Error while evaluating uicontrol Callbackd
 
 
运行设置如附件所示，不知道错在哪里，，麻烦请教，多谢！
 
微信图片_20180110134723.jpg

Submitted by ly666 on Sun, 05/20/2018 - 15:19

各位老师：

      您好。我最近在研究动态功能连接的相关课题。您提供的DynamicBC是一个简洁，实用的工具，十分感谢。不知道Dynamic使用的滑动窗是哪种类型，普通、海明、高斯？因为似乎有频谱泄露问题，大多用高斯窗，所以比较在意这个问题。

谢谢。

Submitted by ly666 on Sun, 05/20/2018 - 15:19

各位老师：

      您好。我最近在研究动态功能连接的相关课题。您提供的DynamicBC是一个简洁，实用的工具，十分感谢。不知道Dynamic使用的滑动窗是哪种类型，普通、海明、高斯？因为似乎有频谱泄露问题，大多用高斯窗，所以比较在意这个问题。

谢谢。

Submitted by ly666 on Sun, 05/20/2018 - 15:20

各位老师：

      您好。我最近在研究动态功能连接的相关课题。您提供的DynamicBC是一个简洁，实用的工具，十分感谢。不知道Dynamic使用的滑动窗是哪种类型，普通、海明、高斯？因为似乎有频谱泄露问题，大多用高斯窗，所以比较在意这个问题。

谢谢。

Submitted by bgpliting on Mon, 07/08/2019 - 16:08

When I use the toolbox to calculate FCD, the outcomes contains 4 Maps(Positive only/Absolute & Weight/Binary). What do these files mean? I used GRETNA before, it came out with short FCD and long FCD. What are the differences between DynamicBC and GRETNA? Thank you very much!

Submitted by Jxx on Fri, 01/19/2024 - 18:59

老师您好，想请教一下关于使用DynamicBC计算聚类分析的问题，是只可以用FLS的结果文件计算聚类分析吗，还是滑动窗的计算结果也可以用来计算聚类分析？如果可以的话应该用哪个结果文件进行呢？感谢您的答复！

Submitted by Jxx on Fri, 01/19/2024 - 19:01

您好，想请教一下使用DyanmicBC计算聚类分析时，是只能用FLS的结果文件进行吗？还是滑动窗的结果文件也可以 呢？如果都可以，可以辛苦告知一下结果文件具体使用哪个吗？感谢您的答复！