Hi Charlie,

Your randomise call looks correct to me. You can drop the option -V, as it has no effect in recent version (it was to produce verbose outputs).

For the histograms, it depends. For a global histogram (all subjects and across space), probably the simplest is just to load the images directly into R. I don't use R myself so I can't help. In any case, you'd then load the 4D and the mask, then mask the data inside R before making the histograms or any other plot.
Using fslmeants will give too few data: for 10 subjects, just 10 values). I think I wouldn't use it for this purpose.

All the best,

Anderson

Am 27.01.14 21:56, schrieb Charles Leger:

Thank you Anderson for replying so promptly and in such detail. First, I will have access to additional diffusion-weighted data which will increase the number of participants to 10 (n=10) , still too low a number to have much statistical power but better than the previously planned  n=4.

At this stage , my understanding of TBSS and FSL is only elementary, and based on what you have conveyed, and in respect to tbss_sym, I would prefer to start with just a basic left-right ( or the reverse) test.

Following from the TBSS guide,  and after completing steps 1 to 4, would this be correct for a simple left-right test of asymmetry?

randomise -i all_FA_skeletonised_left_minus_right.nii.gz -o tbss -m mean_FA_symmetrised_skeleton_mask.nii.gz -1 -n 5000 --T2 -V

Also, if I want to complete a histographic analysis of the FA data in R statistics, would you recommend fslmeants and if so would an appropriate string be

fslmeants  -i all_FA_skeletonised_left_minus_right.nii.gz -o mean_values_file.txt

Thank you,

Charlie

On Mon, Jan 27, 2014 at 3:19 PM, Anderson M. Winkler <[log in to unmask]> wrote:

Hi Charlie,

To run this as a single design on its full generality, with the 3 contrasts (effect of side, effect of time, and interaction), and taking the repeated measures into account (something as a 2x2 ANOVA, with the repeated measures), it'd be necessary a certain permutation strategy that, as of today, isn't available in randomise. However, you can still investigate differences, but you'll need to tweak a bit the pipeline and run randomise 3 times:

- To test the effect of side regardless of time: average the two timepoints for each subject (or just sum t1+t2), then subtract L-R, and run randomise with the option -1.
- To test the effect of time regardless of side: average each image with itself after flipping (or just sum, L+R), then compute t2-t1, and run randomise with the option -1.
- To test the interaction of side and time, compute L-R, then t2-t1, then run randomise with the option -1.

To do this, you'll have to take the file all_FA_symmetrised_skeletonised.nii.gz, which is a 4D file, disassemble it (with fslsplit), rename the outputs with meaningful names, e.g. L_subj01_t1.nii.gz, etc, then flip each one (fslswapdim -y) to have the corresponding R_subj01_t1.nii.gz, etc, then compute the sums and differences as above (use fslmaths -add and -sub), then assemble back as 3 new 4D files (fslmerge), and only them run randomise. Note that the file all_FA_skeletonised_left_minus_right.nii.gz already contains the L-R differences, but it's probably simpler to begin and do all starting with the all_FA_symmetrised_skeletonised.nii.gz.

For each randomise run you'll have only 4 images in each 4D file, so only 2^4=16 possible sign-flips, which isn't much even for a pilot study. Replacing randomise with a parametric test wouldn't help much either, as you'd have only 3 degrees of freedom per run. I suggest that you try to have more images, even for a pilot.

Hope this helps.

All the best,

Anderson


Am 27.01.14 18:24, schrieb charlie Leger:

A few questions regarding tbss_sym FA (pilot project) with a repeated-measures design (within-subjects) 4 subjects (n=4), scanned at two time points; initially and 8 months later.

The tbss guide suggests using the option -1 for left-right testing in randomise. I don’t think this randomise setting can be used for this project which has two factors: left vs right and time which is a total of 4 levels. This could be set-up as a 2 factor, 2-level Anova (asymmetry: left vs right, time: before and after 8 months), though pairwise test are ultimately needed.

I did use the glm_gui to attempt make 2-factor, 2-level design (n=4) and can forward it.

Any suggestions in helping to set up the appropriate design and “randomise” call (e.g. randomise -i all_FA_skeletonised_left_minus_right.nii.gz -o tbss -m mean_FA_symmetrised_skeleton_mask.nii.gz -1 -n 5000 --T2 -V) would be much appreciated.

Charlie