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/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.nich...@bdi.ox.ac.uk
W: http://nisox.org | http://www.bdi.ox.ac.uk
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