DPABI/DPABISurf/DPARSF

SPM pre-processed data DPARSFA ReHo,ALFF,fALFF

Submitted by trabz on

Hi experts,

 

      I want to compute ALFF , ReHo and fALFF from SPM pre-processed (realigned,coregistered,normalized,smoothed,segmented) data. But when I try to do that analysis it throws normalizing error at DPARSFA step. It has produced fALFF,ALFF and ReHo even FC then after it has failed at normalize (Tried with EPI templates, T1, Dartel ). Here is my problem ; Result sets of this analyses are not fitting with anatomical sets why is that happening ?  How can I fix that ? 

 

Thanks

Abdullah

计算VMHC的时候老是报错及结果含义

Submitted by Jianglan on
各位老师好,这两天用DPARSF计算VMHC老是报错,看过了视频和论坛,还是没有找到答案,希望得到指导!
 
1.怕是数据有问题,我跑了两遍,每次都是到computing VMHC出现问题,说File doesn't exist: F:\my_fmri_data_hangzhou\123\FunImgARglobalCWFsymS\pat_001_A_01.nii.gz(两次说的不存在的被试对象还不一样),报错的红字我附在附件txt中,自己查看了下,这个文件夹中,pat_001不像其他被试,他是单独的一个文件,其他的都有文件夹,感觉他就像没被处理一样(见图1)(图2是我计算VMHC的勾选)
 
2.Results中有两个文件夹,VMHC_FunImgARCWFsymS 和 VMH

Questions about CWAS

Submitted by sha.zhiqiang@163.com on

Dear Dr. Yan,

Recently, I used y_CWAS.m to perform the CWAS analyis. I have several questions about the CWAS analysis.

[p_Brain, F_Brain, Header] = y_CWAS(DataUpDir, SubID, AResultFilename, AMaskFilename, Regressor, iter, IsNeedDetrend, Band, TR)

For the annotation of "Regressor", it said "the regressors, nDimTimePoints by nRegressor matrix".

请问一下DPABI生成的headmotion这个文件里面20列具体代表什么?

Submitted by doctorsol on

各位老师好,我是用DPABI里的friston24做的头动处理,请问一下headmotion里生成了一个矩阵,行我知道是被试,列有20列是代表什么呢? 

另外如果想报告FD的话,报告哪个值比较好呢?POWER还是jenkinson?有没有报告的样板文献推荐?

The interpretation of the TFCE results

Submitted by zuolonglotu@gm… on
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

计算REHO和ALFF前是否需要去全脑信号?

Submitted by doctorsol on
 
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?