Hi Laura,
If you're looking for another reference that has used this approach, you
could see our 2010 paper:
http://www.ncbi.nlm.nih.gov/pubmed/20118463

cheers,
-MH

-- 
Michael Harms, Ph.D.
-----------------------------------------------------------
Conte Center for the Neuroscience of Mental Disorders
Washington University School of Medicine
Department of Psychiatry, Box 8134
660 South Euclid Ave. Tel: 314-747-6173
St. Louis, MO  63110 Email: mha...@wustl.edu

From:  "Laura M. Tully" <tully.la...@googlemail.com>
Date:  Saturday, March 9, 2013 5:58 PM
To:  "Anderson M. Winkler" <wink...@fmrib.ox.ac.uk>
Cc:  free <freesurfer@nmr.mgh.harvard.edu>
Subject:  Re: [Freesurfer] mean thickness covariate, mean area covariate, &
mri_anatomical_stats for multiple subjects

Hi Anderson, 

Thanks, that reference is particularly helpful.

Re: the usage of the white versus pial area question - I believe that the
default area calculation in freesurfer is the white surface area, so unless
one specifies the pial in calculations, the standard surface area output for
surface area by parcellation will be white. This suggests the use of the
global measurement of white surface area as a covariate would be an
appropriate, whereas if one was specifically using pial surface area in the
aparc calculations, it may make more sense to use the global measure of pial
surface area as a covariate, correct? As for which one to use in analysis,
I'm not sure - conceptually it might be that the pial surface area is more
sensitive to atrophy but I don't know if that is born out in the data...

Laura. 


On Sat, Mar 9, 2013 at 11:49 AM, Anderson M. Winkler
<wink...@fmrib.ox.ac.uk> wrote:
> Hi Laura,
> 
> 
>> 1. Is there a paper that I could cite that recommends using mean cortical
>> thickness rather than ICV?
>  
> If it helps, we used cortical thickness and area as covariate for the
> respective analysis of regional thickness and area. Brain volume, which is
> more closely related to ICV, correlates well with area, but not with
> thickness. We computed a global thickness average by weighting the thickness
> of each region by their respective areas. The paper is this:
> http://surfer.nmr.mgh.harvard.edu/ftp/articles/Winkler2010_Neuroimage.pdf
>  
>> 1. Would the same logic be applied to surface area analyses? i.e. would it
>> make more sense to use mean surface area as a covariate in surface area
>> analyses? If so, which mean surface area calculation should be used?
>> mri_anatomical_stats can produce both pial and white matter mean surface area
>> stats. 
> 
> Yes, I think so. It seems more logical to have a global measurement of area in
> the model than a measurement of brain volume. On the other hand, area and
> thickness are not correlated one to another (as shown in the paper above and
> also in Panizzon et al, 2009, in Cereb Cortex). I don't think there is a clear
> answer on which, pial or white, should be used. I'd probably go with the
> white, as I think it may be more robust to image quality, but I admit this is
> a rather weak justification and if the images are good, perhaps the pial could
> be just as good, despite the fact that it somewhat depends on the white for
> its construction.
> 
>  
>> 1. Is there a way to run mri_anatomical_stats on multiple subjects at once
>> and write to a tablefile (similar to asegstats2table output)?
> 
> I think you can use aparcstats2table, then add up all regions in a spreadsheet
> (or even with awk/gawk). Alternatively, you can use "grep" to pick the
> WhiteSurfArea for each hemisphere from the ?h.aparc.stats file for each
> subject.
> 
> Hope this helps!
> 
> All the best,
> 
> Anderson
> 



-- 
--
Laura M. Tully, MA
Social Neuroscience & Psychopathology, Harvard University
Center for the Assessment and Prevention of Prodromal States, UCLA Semel
Institute of Neuroscience
ltu...@mednet.ucla.edu
ltu...@fas.harvard.edu
310-267-0170
--
My musings as a young clinical scientist:
http://theclinicalbrain.blogspot.com/
Follow me on Twitter: @tully_laura
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