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Thanks for the input, all. Much appreciated.

On Thu, Jul 12, 2018 at 11:01 AM, Bruce Fischl <fis...@nmr.mgh.harvard.edu>
wrote:

>
> from Tom....
>
> ---------- Forwarded message ----------
> Date: Thu, 12 Jul 2018 16:51:31 +0100
> From: Thomas Nichols <thomas.nich...@bdi.ox.ac.uk>
> To: Bruce Fischl <fis...@nmr.mgh.harvard.edu>
> Cc: freesurfer@nmr.mgh.harvard.edu
> Subject: Re: [Freesurfer] Cortical Thickness at Individual Vertices
>
>
>         External Email - Use Caution
>
> 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 <fis...@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/S105381191
> 1012146
>       >
>       > 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.nich...@bdi.ox.ac.uk
> W: http://nisox.org | http://www.bdi.ox.ac.uk
>
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