Hi!

I am searching for information about the best way of analysing my Voxel-to-Voxel-data. Maybe there is somone here who can give me advise.

I want to explore the connectivity on the whole-brain-level without using a-priori-chosen ROI's, and also see if there is a difference in connectivity between 3 groups.
I am not quite sure which of the measures "connectome-MVPA", "ILC", "RCC", ICC" and "RCS" is best for my purposes. Also I can find some info on the latter 4, but not really what "connectome-MVPA" measures. What does the "multivariate representation" include?
Because I didn't know which one to choose I included all of them :) and I wonder why each one of them gives 1, 3 or 5 versions in the list of Voxel-to-Voxel Measures in second-level Results... Is that the different components?


The participants in each group have done a rsfMRI-scan before and after an intervention (one sham-group and two different versions of intervention), 25 participants in total.
I have entered the two sessions and created two conditions called T1 and T2 with Onset = 0 and Duration = Inf for Session 1 and Onset = [] and Duration = [] for Session 2 (the opposite for T2). I also removed the condition "rest" that was there as a default.
I have created 3 extra Second-level-covariates (in addition to the "AllSubjects") with the names of my groups and 1:s and 0:s accordingly.

To clearify my question; How do I best explore between-group differences in connectivity when i hypothesise that there are no differences at T1, but hope that there are at T2?
I have been reading some older forum-posts but can't really make sense of it...

Any help is deeply appreciated!
/Annie