Hi James
you could use techniques that compare the whole distribution of thicknesses across subject populations. You could do a t-test or something non-parametric like a Kolmogorov-Smirnov or use permutation testing. I'll cc Tom Nichols so he can chime in with something more sophisticated or specific.
cheers Bruce
On Wed, 11 Jul 2018, James Gullickson wrote:
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All, 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 groups.
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. https://www.sciencedirect.com/science/article/pii/S1053811911012146
Thanks,
James