Hi Chris,

Please see below:

On 11 February 2016 at 00:20, Chris Hardy <[log in to unmask]> wrote:

Hey FSLers,

I have a multi-session question, for which I could not find an exact answer in the archives nor the multi-session / repeated measures example given in the documentation: http://fsl.fmrib.ox.ac.uk/fslcourse/lectures/practicals/feat2/index.html#multisession , although it is closely related to the example.

Specifically, for each subject, I have three different conditions (A, B, & C), and each is it's own entire functional session (one run for A w/ no other EVs, one run for B and no EVs, etc).  I simply want to end up with the group level copes A-B, B-C, & A-C.  Judging from the example, I should run 3 levels of FEATs (since there is no multi-session functionality built in):  

1) 3 separate FEATs for each subject - 1 for each session - and make a 'contrast' that is just 1 for the one regression since there's nothing to subtract against.  This essentially is asking if the parameters measured are greater than 0.

2) a FEAT within each subject using these 3 1st level FEATs to create the contrasts.

3) a group-level feat

Essentially just a paired t-test where the variables are different session blocks.

Yes, everything fine until here. Note that the multi-level in FEAT is precisely for multi-session, so there is a such built-in functionality. At any rate, please see below:

 

My concern is that upon following this logic and running the level 1 for each subject is that my A-nothing contrast showed no significant voxels, but it seems like there absolutely should be, given the person was alive.

Subject living or not, there may be no significant activity, even with a simple contrast as this. This isn't really a problem.

A suggestion is to continue with the analysis. It may well be that none or very few of the subjects actually display activity, but at the group level, some results may be seen (or still not).

 

Previously, I had tried concatenating the runs into one functional, and then having A, B, and C in each subject's initial model, but from what I can tell about FSL (I come from SPM), that creates issues with movement b/n sessions and temporal filtering problems.

Exactly.

All the best,

Anderson

 

Thank you for any input!

sincerely,

Chris