Hello there
I am using TBSS to examine whether differences in FA can account for
differences in % signal change in specific functionally defined ROIs.
Based on some of the postings I saw on the forum, I followed a series of
steps that I thought makes sense given my objectives.The outcome didn't
look very exciting and I am writing to check whether, atleast, what I
have done so far is correct. So here goes:
1. I ran the following commands for a data set comprising 8 subjects
tbss_1_preproc *.nii.gz
tbss_2_reg -T
tbss_3_postreg -S
tbss_4_prestats 0.2
2. For the correlation analysis, I used the GLM gui as follows
In the FSL main console:
Misc -> GLM setup - > Higher level non-time series design - > # time
points (inputs) = 8
In the EVs tab:
# of EVs = 1, Group = 1, Paste the EV1 (% signal change in ROI)
In the contrasts & F-tests tab:
Contrast = 1; F-test = 0
C1 enabled, Title = Group Mean, EV1 = 1
I saved this design in the stats folder and ran the following randomise
command:
randomise -i all_FA_skeletonised -o RH_OFC_M_BOLD_FA_results -m
mean_FA_skeleton_mask -d RH_OFC_M.mat -t RH_OFC_M.con -D -n 250 -T -V
To view the results:
fslview $FSLDIR/data/standard/MNI152_T1_1mm mean_FA_skeleton -l Green -b
0.2,0.8 RH_OFC_M_BOLD_FA_results_max_tstat1 -l Red-Yellow -b 3,6
My expectation was to see small patches of red-yellow in interesting
tract regions, which was not the case, all I could see was the mean FA
skeleton.
So it looks like either there were no correlations or I might have done
something wrong especially in setting up the stats design.
I would greatly appreciate it if someone could help me rule out the
latter possibility.
Many thanks in advance
Cibu Thomas
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