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Hi, 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. All the best, Mark From: Paul Dhami <[log in to unmask]<mailto:[log in to unmask]>> Reply-To: FSL - FMRIB's Software Library <[log in to unmask]<mailto:[log in to unmask]>> Date: Thursday, 8 January 2015 05:07 To: "[log in to unmask]<mailto:[log in to unmask]>" <[log in to unmask]<mailto:[log in to unmask]>> Subject: [FSL] 1st Level FEAT Poststats results coming out extremely poor - bad preprocessing? 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.