Hi all,

I have 2 groups scanned with fMRI twice. Due to the known high within subject variability which approaches between-subject values, my group decided to first perform a correlation test between baseline and follow-up measurements. If there is a significant correlation between baseline & follow-up then we would like to perform a 2-sample t-test using the follow-up data while adjusting for baseline data. If the correlation test is negative i.e. the baseline cannot predict the follow-up, then we would just do the 2-sample follow-up t-test without baseline correction. Instead we would simply check that whatever we find between groups at follow-up was not present between groups at baseline.

Now, the question is, do you think this is a sensible approach? Can the correlation analysis be made in FEAT somehow using voxelwise covariates? I guess if I find the answer to this question I can also move on and similarly adjust the data by the baseline data as covariate.

Julian

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