Hi Laura, I think yes, sounds right. Maybe run both ways and see if the results agree or differ. All the best, Anderson
2013/3/9 Laura M. Tully <tully.la...@googlemail.com> > 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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