Hi Sheena,

Please, see below:

On 14 June 2016 at 02:13, Sheena Sharma <[log in to unmask]> wrote:

Hi FSL experts,

I have just carried out TBSS analysis of 20 subjects that were analysed pre and post intervention. I set up a GLM for a paired ttest as described in the GLM User Guide. There were 2 contrasts (Pre-Post , and Post -Pre)

Next I carried out randomise:

randomise -i all_FA_skeletonised.nii.gz -o tbss -m mean_FA_skeleton_mask -d design_pairedt.mat -t design_pairedt.con --T2

Finally, I viewed the resulting tfce files (tbss_tfce_corrp_tstat1 and tbss_tfce_corrp_tstat2). Nothing survived the significance testing (fslview $FSLDIR/data/standard/MNI152_T1_1mm mean_FA_skeleton -l Green -b .3,.7 tbss_tfce_corrp_tstat1.nii.gz -l Blue-Lightblue -b 0.949,1)

However, at this point I began experimenting with the cluster command and varying thresholds to get a feel for the level at which the two groups are significantly different. Just to play around I entered 50% (cluster -i tbss_tfce_corrp_tstat1.nii.gz -t 0.50 --mm > cluster_t1_50.txt). 

At 50%, the two groups of course have some differences. However, the significant clusters are not the same for both contrasts, T1 and T2 (Just to check: Does T1 indeed correspond with contrast1 and T2 with contrast2?).

Yes.

 

 Why is this? I expected cluster_t2_50 to be the same as cluster_t1_50 but with the opposite sign. Perhaps I have made an error in calculations or is this what you would expect?

The test statistic (t) for a contrast such as [1 -1] has the opposite sign when compared to a contrast such as [-1 1]. The p-values not. If the distribution of the test statistic happens to be perfectly symmetric around zero, then the p-value for [1 -1] is the same as 1-p+1/nPerm for [-1 1], although there might be slight variation given that we rarely do all permutations exhaustively.

Now, these relationships don't hold anymore for the corrected p-values, as the distribution of the maximum is skewed, and don't hold for TFCE, which is a non-linear function of the original test statistic.

All the best,

Anderson

 

Thanks very much,

Sheena