Hello,
After preprocessing resting-state data using DPARSF I accidentally deleted the PicturesForChkNormalization folder.
Is there a way using DPARSF to generate the folder and associated data again, without re-running all the preprocessing?
The data I am using has 150 cases so re-running preprocessing would take quite some time.
Thank you in advance for your help!
Florence
Hello,
When I used DARSFA2.3 to compute interegional functional connectivity following the steps Calculate in Original Space (warp by information from unified segmentation), I found that I just got "NaN" for some ROIs for some subjects. For example, we got "NaN" in a few of subjects, but got values related to ROI1 in the rest of subjects. I checked the ROI1 masks of these wrong "subjects", and found the images of these masks were empty.
These ROIs are in MNI space.
Hello everyone
Warning for a confused post.
I have a question regarding which kind of normalization procedure to use. In my preprocessing I'm using New segment + Dartel and the "normalize using Dartel" options. Is this correct or are there certain criterias important to fulfill before using the Dartel normalization procedure? What is the main reason for using DARTEL overall?
Dear Dr. Yan,
Everything is OK when I use normalize by DARTEL and voxel size being set up to [3 3 3]. However, when I changed the voxel size to [2 2 2], there are a lot of dark stripe on the normalized image. I have attached those two pictures from "PicturesForChkNormalization". Your kind help will be highly appreciated.
Best,
Jo
Dear all,
I've been using DPARSF v2.3 to extract AAL time courses from fMRI data.
I have a couple of subjects that seem to show signal dropout in the frontal lobe.
I would like to overlay the AAL atlas on the preprocessed fMRI images of these subjects to see if the AALs' frontal labels are affected.
I tried to do this by overlaying the preprocessed fMRI images on the AAL template of DPARSF but the problem is they have different dimensions.
Dear sir(s),
I want to use the data released at NITRC as my database (normal control) to further my study about resting network.
However, some bias I should correct.
As I have known, a strategy like de-mean might solve my problem.
The detailing might be like (take an example like: I would like to check clevealnd case<cle1>'s resting network in comparison to leipzig--lpz1,2,3...)
I should calculate lpz1-lpz1(mean), lpz2-lpz2(mean), lpz3-lpz3(mean).......lpzn-lpzn(mean) -----> De-mean
Dear Experts,
I was wondering if any of you came across this (reproducible) segfault:
老师您好，请问，我用DPARSFA做任务fMRI数据预处理时报错，我是选的模板里面的Task fMRI data preprocessing 这一项，根据我的扫描参数修改了一下，结果报错如下，请问该如何解决？谢谢！！
错误使用 file_array/subsref>subfun (line 80)
在 'file2mat' 的工作进程上引发了 UndefinedFunction 错误。这可能是因为在这些工作进程上无法访问包含 'file2mat' 的文件。使用 addAttachedFiles(pool, files)
指定要附加的必要文件。请参阅 'parallel.Pool/addAttachedFiles'的相关文档以获取更多详细信息。
出错 file_array/subsref (line 60)
t = subfun(sobj,args{:});
出错 nifti/subsref>rec (line 219)
t = subsref(t,subs(2:end));
Hi all
First of all I have to say that I'm really liking the DPARSF extension, it's very cool.
I've used DPARSF to calculate FC using 4 user-defined ROIs. In the textfile "ROISignals_subjectname.txt" I find the extracted time courses for my 4 ROIs in 4 columns, each row representing my number of time points. However, when looking at the "ROICCorrelation_subjectname.txt" I only find 4 columns and 4 rows. I'm not really sure how to read this data and use it in further analysis.
If someone could give me some pointers I would be deeply grateful!
/Eva
Hi,
I am seeing some strange behavior in my Masks directory. I have images that look reasonable to being with, and reasonable as normalized, but do not look reasonable in the Masks directory (see attached for mask image superimposed on corresponding FunImgR). Is this problematic? What do the images in Masks represent?
Thanks,
Matt