Hello,

I am trying to do a VBM analysis using an amalgamated dataset but cannot get 'fslvbm_2_template -n" to get past the first step (fslvbm2a - FAST):

Due to the differences in imaging acquisitions some .nii.gz data have needed different fractional intensity thresholds for brain extraction than others, as well as a handful needing adjusting for neck. Since I can't account for these in 'fslvbm_1_bet' I used the bet command (normal BET, not fslvbm_1_bet) to make these files. I then ran 'fslvbm_1_bet' on the raw data in a separate folder to see what files were created and make sure the names on the masks/brain-extracted images I made were the same as the ones produced by 'fslvbm_1_bet.' Following that I simply replaced the masks/brain-extracted images created by 'fslvbm_1_bet' with my own.

When "fslvbm_2_template -n" is subsequently run a selection of the following files is created for some participants, but not others: *GM_to_T_init_warp.msf, *mixeltype.nii.gz, *pve_2.nii.gz, *pve_0.nii.gz, *pveseg.nii.gz, *GM.nii.gz, *seg.nii.gz, *GM_to_T.mat, *GM_to_T.nii.gz,

No errors show up in the terminal and the only errors in the error text files are "killed" in the fslvbm2a error files, and "No image files match: template_GM_init" in the fslvbm2d files which is a knock-on effect from fslvbm2a not working I presume. I did spend some time pouring over the scripts for the fslvbm_1/_2 scripts to try understand what went wrong but it's beyond my comprehension for now.

FSL 6.0.4 is the version I am using, although I have also tried it in 6.0.5.2, and I have also tried it with 'unset SGE_root' in case it was a cluster or memory issue.

Any advice on how to get fslvbm_2 to work after manually inserting brain extracted images instead of running from fslvbm_1 would be greatly appreciated.

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