you will want to use the -no-prune flag.If thisis a group analysis, you should be very, very careful that you know what you are doing. In general, setting values to 0 prior to group analysis will create biased results. What you really need to do is have adifferent model for each voxel that includes/excludes certain subjects at certain voxels. If this is what you want, let me know and I'll give you instructions on how to do it.

doug

On 11/08/2013 12:46 PM, celine@nmr.mgh.harvard.edu wrote:

Hi, When using glm_fit with an input volume that has many voxels with a 0 value (due to a previous thresholding for quality reasons), and the voxel removes might be distributed randomly across our population, is there a way not to take into account those voxels in the glm_fit model? I saw the --pune flag, but I am not sure if it is the one to use. Thanks Celine _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer