Dear Ludovica,
thanks again for the assistance. i have some further queries about how to best proceed with the analysis i am interested in. for input date, i have separate stage 1 dual regression output (activation time series) for 3 groups of subjects. the groups are: a patient group (14 subjects) before and then after an intervention, and a control group (10 subjects). what i would like to do is determine the nature of between-network relationships for each group separately first. the group_maps i am using are the 10 network templates from the PNAS smith 2009 paper. i am happy with how to set up this initial part of the nets_examples script, and how to specify the analysis i want, e.g. full vs partial correlation.
the script then asks for a glm. i have existing glms which i have used in other parts of my overall analysis (e.g. for randomise), but these specify btw-group comparisons (e.g. patients at baseline vs controls). since in the first step of FSLnets i am interested in the within-group situation, these existing glms would be innapropriate. i am then uncertain what form the glm being asked for should take? should it simply be the network matrix i am interested in, i.e. ten by ten networks? or the ten networks by number of subjects, prepared for each group?
as a second step, i would then like to compare network relationships found in step one differ between groups, specifically to look at any differences btw the patient group at baseline (before the intervention) and the control group, and also to compare the patient group before and after the intervention.
my impression is that the nets_examples script can help me with the first step only, but that the second i will need to do in some other way. is this correct?
so, for the second step to determine any differences in network relationships btw the different groups, what part of the FSLnets output should i use? and how to do this comparison, to determine the nature of the difference (e.g. DMN-executive control network becoming more or less correlated after the intervention) rather than simply the presence of a difference? should it be through calculating the presence and direction of the change in correlation co-efficients as apposed to say a t-test.
i hope i have explained my situation well.
any advice/guidance would be greatly appreciated.
thanks
joe starke
masters student
university of cape town
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