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Hello FSL experts, I am having an issue using pre-thresholding masking in FEAT, and I was wondering if anyone could lend some advice or expertise. I am applying the mask in fixed effects and mixed effects higher-level analyses. Although registration to the high-res T1 and MNI brain seem to work fine for the functional scans, based on the inspection of the rendered_thresh_zstat images, the application of the mask seems to be incorrect. The visual inspection of report and images shows activation in regions outside the mask and a weird conglomeration of activation in the middle of the brain that is nearly identical across runs and subjects. Hence, it’s safe to say that something is wrong with small volume correction that we are trying to do using the mask. Another related question that I have is whether we gain any power by back-transforming the mask into native space for each of the runs, and then applying the mask in the lower-level, fixed effects and mixed-effects analyses? Or is it best to only apply the mask at the final group comparison stage (mixed effects)? More generally, how does the FSL implement mask in FEAT? Has anyone had similar issues? Is there a recommended way to get the mask into MNI space other than using FLIRT? I am including the specs for the relevant file types, in case they are useful. fslinfo for the binarized mask (.nii.gz file): data_type FLOAT32 dim1 91 dim2 109 dim3 91 dim4 1 datatype 16 pixdim1 2.000000 pixdim2 2.000000 pixdim3 2.000000 pixdim4 1.000000 cal_max 0.0000 cal_min 0.0000 file_type NIFTI-1+ fslinfo for the anatomical T1w image (.nii.gz): data_type INT16 dim1 256 dim2 256 dim3 132 dim4 1 datatype 4 pixdim1 1.000000 pixdim2 1.000000 pixdim3 1.200000 pixdim4 0.000000 cal_max 0.0000 cal_min 0.0000 file_type NIFTI-1+ fslinfo for the functional bold file (.nii.gz): data_type INT16 dim1 64 dim2 64 dim3 24 dim4 342 datatype 4 pixdim1 3.437500 pixdim2 3.437500 pixdim3 4.500000 pixdim4 1.500000 cal_max 10119.0000 cal_min 0.0000 file_type NIFTI-1+ Any help with this would be much appreciated!! Best, Andrzej ######################################################################## To unsubscribe from the FSL list, click the following link: https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=FSL&A=1