After running the individual segmentations, checking the output, and creating the files, we are ready to run the "Vertex Analysis." A model is created with a single command, but there are several options.
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Creating The Vertex Data
This step creates a file with the size difference of each individual study shape relative to the mean shape. The size differences are calculated only on the surface of the shape, and consist of numbers that indicate the distance in voxels out (positive) or in (negative) from the mean.
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For reasons that are not clear, this vertext analysis step requires the design files, so the design matrices etc. are copied as subfolders for each shape analysis type, and the vertex creation is performed within that design subfolder.
Details
first_utils --vertexAnalysis --usebvars -i concatenated_bvars -d design.mat -o output_basename [--useReconNative --useRigidAlign ] [--useReconMNI] [--usePCAfilter -n number_of_modes]
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The 4D file contains values for each subject at the voxels on the boundary of the mean surface (defined by the mask file) as distance from the mean, in voxel units. (Note that the FSL person posted in 2013 that he may change the units to mm at some point.) Here is an example from the hippocampus, where the distance is positive (values can be negative as well).
Analysis options (from UserGuide)
The --useReconNative option carries out vertex analysis in native space, along with the --useRigidAlign option. The --useReconMNI option may also be used to carry out vertex analysis, it will do it in the MNI standard space instead, which normalises for brain size. It is difficult to say which will be more sensitive to changes in shape, and so it may be interesting to try both the --useReconNative and the --useReconMNI options. Also note that the --useScale option will not be used. Without the --useScale option, changes in both local shape and size can be found in shape analysis. This type of finding can be interpreted, for example, as local atrophy. With the--useScale option, overall changes in size are lost.
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