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I am comparing cortical thickness between subjects with and without mild
traumatic brain injury (mTBI). So far the contrasts in QDEC have not been
significant after correcting for multiple comparisons. I am not necessarily
surprised at this due to the heterogeneous nature of mTBI in our sample,
i.e. we do not expect any two subjects to have damage in the same area. I
am interested in ways to compare cortical thickness that are not dependent
on a single ROI having an effect across subjects. One way I have tried is
calculating z-scores for the values in the aparc.stats file, and using the
number of abnormally low ROIs as a dependant variable to compare between

Is there a way to look at thickness differences at an even more general
level? E.g. by comparing the number of vertices with abnormally low
thickness? If so how would one go about that with Freesurfer data?

This paper takes a similar approach with DTI. I'd like to do something
analogous to their "number of voxels with low FA" analysis.


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