Thank you Michael! LT
On Mon, Mar 11, 2013 at 8:54 AM, Michael Harms <mha...@conte.wustl.edu>wrote: > > 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 > _______________________________________________ Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer The > information in this e-mail is intended only for the person to whom it is > addressed. If you believe this e-mail was sent to you in error and the > e-mail contains patient information, please contact the Partners Compliance > HelpLine at http://www.partners.org/complianceline . If the e-mail was > sent to you in error but does not contain patient information, please > contact the sender and properly dispose of the e-mail. > -- -- 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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