from Tom....
---------- Forwarded message ---------- Date: Thu, 12 Jul 2018 16:51:31 +0100 From: Thomas Nichols thomas.nichols@bdi.ox.ac.uk To: Bruce Fischl fischl@nmr.mgh.harvard.edu Cc: freesurfer@nmr.mgh.harvard.edu Subject: Re: [Freesurfer] Cortical Thickness at Individual Vertices
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Hi Bruce! James: I don't have any particular deep thoughts except, all things equal, if you have a tenable continuous summary of the mTBI deficits it will probably be more sensitivity than a discrete count-based summary of the deficits.
Bruce's idea of comparing distributions is sound but probably will only work well for mTBI effect that are diffuse. For localised effects (that are not spatially consistent), finding some summary measure of the deficits are probably the best way forward.
-Tom
On Thu, Jul 12, 2018 at 4:31 PM Bruce Fischl fischl@nmr.mgh.harvard.edu wrote: 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:
> > External Email - Use Caution > > 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 > >
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-- __________________________________________________________ Thomas Nichols, PhD Professor of Neuroimaging Statistics Nuffield Department of Population Health | University of Oxford Big Data Institute | Li Ka Shing Centre for Health Information and Discovery Old Road Campus | Headington | Oxford | OX3 7LF | United Kingdom T: +44 1865 743590 | E: thomas.nichols@bdi.ox.ac.uk W: http://nisox.org | http://www.bdi.ox.ac.uk