Hi,
I have a learning protocol in which each subject performs several training runs. There is some slight misalignment between the filtered_func_data files across the runs, which I would like to correct in order to perform some ROIs based analyses. I have a mask from a localiser that I can overlay on each training dataset but it appears a bit misaligned too when overlaid across the runs.
I tried to co-register the training data across the runs with the localiser data but without success, I did this in the FEAT preprocessing by introducing the scans from training run 1 as the alternative reference image when I preprocessed each dataset from training and localiser runs
This seems like a trivial thing to do but I have not came across to a solution in the list, sorry If I have missed something
could you please help?
thanks!
david
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