Dear fsl experts,
I'm quite new here
and I'm writing to ask you an opinion about the following analysis:
resting state data, 9 patients and 9 healthy controls,
each subject has got 2 runs.
Following http://fsl.fmrib.ox.ac.uk/fslcourse/lectures/practicals/feat2/index.html#multisession I ran level 1 (seed-based functional connectivity for each run) and level 2 (mean across each subject's runs) on my data.
As for level 3, instead of the cluster thresholding that can be set from the Feat GUI, I'd like use randomise on these data to perform a 2-sample unpaired T-test to investigate differences in connectivity between the two groups.
The steps that I'd do are the following:
- concatenate (with fslmerge) in a 4D image (4Dimage_ztats) the zstat images of each subject (obtained in the 2nd level of the analysis)
- use the following design.mat:
/NumWaves 2
/NumPoints 18
/PPheights 1.000000e+00 1.000000e+00
/Matrix
1.000000e+00 0.000000e+00
1.000000e+00 0.000000e+00
1.000000e+00 0.000000e+00
1.000000e+00 0.000000e+00
1.000000e+00 0.000000e+00
1.000000e+00 0.000000e+00
1.000000e+00 0.000000e+00
1.000000e+00 0.000000e+00
1.000000e+00 0.000000e+00
0.000000e+00 1.000000e+00
0.000000e+00 1.000000e+00
0.000000e+00 1.000000e+00
0.000000e+00 1.000000e+00
0.000000e+00 1.000000e+00
0.000000e+00 1.000000e+00
0.000000e+00 1.000000e+00
0.000000e+00 1.000000e+00
0.000000e+00 1.000000e+00
and the following design.con
/ContrastName1 group A > group B
/ContrastName2 group B > group A
/ContrastName3 group A mean
/ContrastName4 group B mean
/NumWaves 2
/NumContrasts 4
/PPheights 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00
/RequiredEffect 2.801 2.801 1.981 1.981
/Matrix
1.000000e+00 -1.000000e+00
-1.000000e+00 1.000000e+00
1.000000e+00 0.000000e+00
0.000000e+00 1.000000e+00
- run the following command:
randomise -i 4Dimage_ztats -o ttest_randomise -d design.mat - t design.con -n 5000 -D -T
Am I making any conceptual mistake due to my inexperience?
Thank you very much for any suggestion.
Stefania
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