Hi Anderson,

I am so grateful for your prompt response. I am new to FSL and in particular to PALM. So, sorry for any stupid questions.

Let me explain more about the experiment and the hypothesis. My time points are:

t1: pre-intervention
t2: mid-intervention
t3: post-intervention
t4: follow-up (8 weeks after stopping intervention to see whether effect is persisting or not)

And my three groups are:

G1: control (no effect hypothesized within time points)
G2: intervention1 (small effect hypothesized within t1-t2-t3 + NO persisting effect on t4)
G3: intervention2 (greater effect hypothesized within t1-t2-t3 + persisting effect on t4)

So according to my hypothesis, it seems I should follow your advice on using PALM and -ISE (without the assumption of compound symmetry).

So now a couple of questions arose in my mind:

1) Can I still use semi-autonomous FSLVBM process (i.e., fslvbm_1_bet - fslvbm_2_template - fslvbm_3_proc) and later use PALM?

2) I know that in the longitudinal VBM analysis with two time-points, I should treat each time point as an individual subject, and later before randomize subtract GM_mod_merg_s* files between two time-points. I wonder in my case should I compute all pairwise differences and do PALM for each? (i.e., t1-t2, t1-t3, t1-t4, t2-t3, t2-t4, t3-t4). Does the following command seem right?

palm -i diff_t1_t2_GM_mod_merg_s3.nii -d design.mat -t design.con -m GM_mask.nii -f design.fts -eb eb_file.csv -vg vg_file.csv -T -C 3.1 -n 5000 -save1-p -corrcon -o myresults -ise

3) Should I use [Pset, VG] = palm_quickperms(M, EB, P, ISE) or can I make my own vg.csv file (likewise attachment). If this command is necessary can I use design.mat for M?

4) Can I still use FSL GLM command for making the design matrix? Please see attached design matrix. Is it right matrix in my case?

5) Should I run PALM separately for permuting within-block (using -eb -vg and -within options) and permuting whole-block (using -eb -vg and -whole options)?

Best regards,
Kavous


On Thu, Jun 1, 2017 at 11:07 AM, Anderson M. Winkler <[log in to unmask]> wrote:
PS: If you choose to use PALM, with the 4 timepoints, consider using the "-ise" option. It doesn't require compound symmetry, but requires that the errors themselves are symmetrical (i.e., have a symmetrical distribution around zero).

On 30 May 2017 at 23:23, Anderson M. Winkler <[log in to unmask]> wrote:
Hi Kavous,

What are the research hypotheses? If it's about changes over timepoints, and interaction group by timepoint, then this needs the assumption of compound symmetry, which is fine for 2 timepoints, but becomes harder with 4. If you want to make that assumption, then you can use PALM, defining one exchangeablity block per subject, and permuting within-block and also whole-block (for the interactions.

If you can't make the compound symmetry assumption, consider Bryan Guillaume's toolbox called SwE. It seems the most recent version is on GitHub: https://github.com/BryanGuillaume/SwE-toolbox

If, however, the hypothesis is about group differences regardless of changes in time, then randomise can be used directly, with the option --permuteBlocks. This is the Example 6 of the randomise paper: http://www.sciencedirect.com/science/article/pii/S1053811914000913

Hope this helps!

All the best,

Anderson


On 30 May 2017 at 05:05, Kavous <[log in to unmask]> wrote:
Hi FSLers,

I'm going to analyze a longitudinal VBM between 3 groups and within 4 time-points.

By reading following discussions, I know that in 2 time-points analysis I have to use all my subjects' data to make a study-specific template and subtract pre-post data after smoothing for randomise analysis.

https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=FSL;d6651f48.1008
https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=FSL;3dc8868b.1408

However, my question is that is there any way to consider all 4 time-points in a single analysis?

Thanks,
Kavous