Hi everyone,

I have a study where participants underwent 3 runs of rs-fMRI. I have performed a sliding window analysis by specifying the temporal decomposition parameters in setup.Conditions (window length of 45s, overlap of 15s). This gives me 28 conditions per run (where the first condition is the full period and the other conditions correspond to 27 windows per run). I have specified my ROI's and performed seed-voxel analysis. At this point, I get the BETA_Subjectx_Conditionx_Sourcex.nii images which I believe correspond to the z-transformed correlation coefficient for each ROI/Source and each window/Condition. However, I only get 27 conditions for each subject. I have two questions about this. The first is to clarify exactly what each of these images contains. I believe Condition 1 contains the correlation coefficient over the temporally concatenated signal of the three runs without any temporal decomposition. However am I right to assume that each other BETA_Subjectx_Conditionx_Sourcex.nii image is an average of the corresponding window of the 3 runs (so that BETA_Subjectx_Condition2_Source1 is an average of window 1 from run 1, window 1 from run2 and window1 from run 3)? Is this a valid thing to do?
The second question is how do I get the correlation images for each window of each run separately- so that I get 81 correlation images per subject (a separate image for each window of each run) instead of 27? 
I know I could enter each run into a separate experiment but I am hoping there is a more straight forward way. 

I hope this is clear, and any help would be appreciated.
Thanks

Stefan