It is very hard to know what might be wrong from only this information.
Have you checked the pre-processed data by looking at it in FSLView – both as images and timeseries? If you see bad things in this then I suspect that the problem is with the pre-processing. If this looks OK but the output from FSL does not, then this
would indicate a different type of problem.
Also, double check that you do not have NaN values in the pre-processed data (you can use fslmaths to detect and/or remove these) as they cause problems for FSL.
Greetings FSL experts,
I have some data that has recently been preprocessed (standard steps) through other software. The study itself was a simple 2 condition block design. Upon entering each subjects' data through FEAT (with no prestats being done), the post-stat results look quite
bad. The data modeled for each one of my contrasts is extremely spiky, showing little match to the full/cope partial model fit (although some subjects are fine). I wanted to ask if these time series results most likely indicate something wrong with the preprocessing
of the data? Thank you.