LabelMap an user friendly plugin to present rest-fMRI images computed with DPABI

LabelMap is a plugin software for DPABI to present rest-fMRI images computed with DPABI  in an easy-to-use layout format.

 

 

 

LabelMap was developed in May 2019 by PhD. Ing. G. Parla and Prof. Dr. G. Sparacia at NeuroLab - Palermo, Italy

Click here to view a video demonstration of LabelMap at work https://youtu.be/dF3KEwRhZaU

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Why

While I input the data for fMRI into DPARSF in matlab, then clicked "run" button, outcomes could not be produced. Warnings often pop out . what are  the reasons?  look forward to  expertise:)

Error information about two sample t-test of dynamic ALFF

Dear Prof. Yan,
 
When I did two sample t-test of dynamic ALFF, the error information showed as follows,
 
Reading images from "F:\exp\ALFF_sub_10001.nii" etc.
Assignment has more non-singleton rhs dimensions than non-singleton
subscripts
Error in y_ReadAll (line 109)

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Asking Professor Yan for advice from a doctor

   Using the DPARSF for first time, I have few knowledge of  it.
    so confusions as follows exist:
   I have a query on whether basic version of DPARSF could process all signals for fMRI well? 
   Where the advanced vesion of DPARSF can be downloaded?

Concordance_VolumeWise results

Dear  Prfo. Yan and Colleagues,

Hi! There are NaN in the results of Concordance_VolumeWise in some subjects. How can I solve this problem? Thanks!

Best wishes,

Lotus

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The interpretation of the TFCE results

Dear Prof. Yan,
 
I would like to know how the TFCE results can be used, the names of the files are listed as follows. 
 
T2_vox_tstat_uncp
T2_vox_tstat_fwep
T2_clustere_tstat
T2_clustere_tstat_fwep
T2_tfce_tstat
T2_tfce_tstat_uncp
 T2_tfce_tstat_fwep
 
Thank you!
 
Best wishes,
 
Lotus

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计算REHO和ALFF前是否需要去全脑信号?

 
各位老师,我在同一项研究中,功能连接的组间差异结果是基于去除全脑信号的文件得出的。现在又要补充分析ReHo和Alff的结果,是否应该继续使用去除全脑信号的文件进行分析?
 
我查看到DPABI自动生成的ResultsS下面的文件,smReHo代表(除全脑均值, Zang et al., 2004)或szReHo代表 (减全脑均值,除全脑标准差,Zuo et al., 2013).这两个结果本身会对全脑均值进行处理?所以有些疑惑了。如果我用去除全脑信号的文件进行分析是否会对结果造成影响?所以是否还是应该使用包含全脑信号的文件进行处理?但是又是否会因为功能连接的结果是基于去除全脑信号的文件得出的,而使审稿人疑惑?
这种情况下如何决策比较好?

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请问采用不同mask计算功能连接矩阵

老师,您好:

最近在用DPARSF分析一组数据,在处理步骤上存在一些疑问:

1.请问在做scrubbing的时候,勾选了Head motion scrubbing regressors后,还需要在后面勾选Scrubbing吗?

2.请问在采用不同mask计算功能连接矩阵的时候,需要事先将不同模板进行配准么?DPARSF有做相应的处理么?

3.如果想要一个mask一个mask的计算功能连接矩阵的时候,我们的starting Directory Name是选择FunImgARCWSF吗?

4.因为在计算前已经勾选了Smooth,在计算完指标后是否还需要进行Smooth Derivatives呢?

 

还望老师百忙之中可以给予解答,十分感谢!!

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Input data for PT TFCE

Hello,

I am doing second-level rsfMRI analysis with fALFF data in ~530 participants and try to use PT with TFCE for multiple comparison. I´have a very basic problem: I didn't understand which file/folder to chose for 'Group Images' at the section statistical analysis of DPABI Toolbox.

I've already check the slides, which don't mention about input.

rfmri.org/content/permutation-test-dpabi website also doesn't give the clue.

Should I use fALFF maps? I would be happy to hear the right way to do it, before MATLAB would be unresponsive for hours..

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同一組被試,不同天介入前後的比較應該使用Paired-t test或是Mixed Effect Analysis或是ANCOVA?

老師您好!

想和您請教一下,

我的實驗設計是同一批人,在某一天做一特定介入的介入前以及介入之後的靜息態腦影像掃描(兩組掃描),另外一天換成另外一項不同的介入,但是一樣是做介入前以及介入之後的靜息態腦影像掃描(另外兩組)

這樣的實驗設計,希望去分析比較全腦ReHo在兩種不同介入之後的差異

(1)應該是以Paired-t test分別去比較兩天介入後減前的結果去解釋即可。另外,如果想證明不同天的介入前Baseline有無差異,則做兩天的Baseline之Paired-t test (如果這些結果均經過GRF correction,是否即可避免type I error?)

(2)或是應該做Mixed Effect Analysis 或是 ANCOVA 去分析4組數據的差異呢?

 

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