Hello,

I've spent a lot of time going through the message boards, however, I'm still not sure if I'm running my correlational analysis the correct way so I included it below.

Basically, I want to find the correlation relative to a seed region for two different conditions. For each subject I have 7 runs. I'm basically running the GLM 14x for each subject -> 7x because I have 7 runs of data, and then I'm doing this twice i.e. 7x using regressors for condition_A to regress out condition_A (and then finding the correlation with the seed) and then 7x using regressors to regress out condition_B (and then finding the correlation with the seed).

For example,

Run 3dDeconvolve 7x (once for each run), regressing out condition_A

3dDeconvolve
-input run_1.nii
-stim_times run_1_condition_A_regessor
-stim_file run_1_whole_brain_regressor_no_interest
-stim_file run_1_seed_region
-bucket run_1_condition_B_correlation

3dDeconvolve
-input run_2.nii
-stim_times run_2_condition_A_regessor
-stim_file run_2_whole_brain_regressor_no_interest
-stim_file run_2_seed_region
-bucket run_2_condition_B_correlation

etc. (5 more times)


Run 3dDeconvolve 7x (once for each run), regressing out condition_B

3dDeconvolve
-input run_1.nii
-stim_times run_1_condition_B_regessor
-stim_file run_1_whole_brain_regressor_no_interest
-stim_file run_1_seed_region
-bucket run_1_condition_A_correlation

etc. (6 more times)



Then I use 3dcalc to take the mean of the 7 condition_B_correlation t-maps and the mean of the 7 condition_A_correlation t-maps. Once I have these for all my subjects I can t-test them with 3dtest.

I guess the other way to approach this would be to concatenate all 7 runs, concatenate the stim_files, and concatenate the stim_times. However, I choose to do each run separately since it would take some time to reorganize my stim_times files to be global since they are currently in local format.

Although this may not be the most efficient way to do this, is this still correct? Any thoughts would be greatly appreciated!

Thanks,
Drew