DPABI/DPABISurf/DPARSF

Dear All,

I and my colleague are quite new to resting-state fMRI data analysis, we followed the instructions in the R-fMRI Course V2.1 in our try. We have checked “Functional Connectivity” and “Extract ROI time courses” in DPARSF 4.3, and we used the AAL template with the “Multiple Labels in mask file” option checked. There are 35 subjects in our data.

Please Prof. Yan

I tried to process dicom images for fmri and nrrd images for structural mri
when i use Dpabi i have problem with nrrd image
error: there is no images inside the mask file
i use this setting

Thanks for your help.
 

Running job #1
------------------------------------------------------------------------
Running 'Normalise to MNI Space'

** "u_rc120171113164045_t1_mprage_tra_21_Template" **

I am using the DPARSF toolbox to run through 1 subject's data as my first case.

Dear experts

All files were in NIfTI format (FunImg and T1Img)

From the error message:

Removing First 10 Time Points: Sub_001 OKRemoving First 10 Time Points: Sub_002 OKRemoving First 10 Time Points: Sub_003 OK

Dear Experts

Here is a couple of questions regarding a covariate analysis for rsfMRI:

1. For motion regreseed (as Text Covariates) -> choose mean FD value in headmotion.tsv under the the directory of Realignment right?
2. For global iFC correlation (as Covariate images)-> which files should I pick up? (FC_FunImgARglobalCWF?)
3. Gray matter portion (as Covaraite images) ->choose wc*.
4. Any suggested reading or example for ANCOVA and repeat measure setup

Thanks for considering my request!

Cheers

Larry

Hi everyone,

after preprocessing I computed functional connectivity of one cluster (one node of the DMN predefined in the toolbox: x = -6 y = 52 z = -2). I did this for 20 subjects. Afterwards I computed a t-test versus zero (SPM contrast: 1) based on the connectivity map of each participant.

Hello,

I am new to using DPARSF and have watched the videos discussing how to you use it for both human and rat data. I still had a few questions though because I still cant get my data to process properly.

1) Do we need whole brain data? (I have 9 slices spanning 1 mm per slice in our interested regions)

2) Our data is in a 128 x 128 matrix, will this cause issues when using the 96x96x30 rat brain template?