doug
On 10/04/2013 03:33 PM, Caspar M. Schwiedrzik wrote:
Hi Doug,I guess it boils down to the question how to get a group PCC map after a RFX GLM? Using -m PCC seems to only give me a map per subject. Are you calculating PCC from the t- values? Thanks,Caspar On Thursday, October 3, 2013, Caspar M. Schwiedrzik wrote: Hi Doug, On Thursday, October 3, 2013, Douglas N Greve wrote: It sounds like two issues: 1. p-values not consistent with your program. What did you use to compute? Did you do a two-sided (which is what fsfast uses)? I used ttest in Matlab, two sided. 2. Using pcc maps. Why not use -m pcc? Isn't that giving me a map per subject? How do I get the group map that is consistent with the results of mri_glmfit run on ces.nii? Thanks, Caspar doug On 10/03/2013 01:10 PM, Caspar M. Schwiedrzik wrote: Hi Doug, I loaded the pcc.nii file that I got from isxconcat-sess into Matlab and then ran a t-test against 0 over the 4th dimension. I converted the resulting p-values to -log10 and then compared them to the output of mri_glmfit, namely sig.vol. This was the mri_glmfit command: mri_glmfit \ --surf averagesubject hemisphere \ --y pcc.nii \ --no-cortex \ --osgm \ --glmdir analysisname I was expecting the p-values to be the same, which apparently is not the case, unless I am doing/understanding something wrong. By now, I am actually more inclined to use the regression coefficients instead. However, I'd still like to get pcc maps from them, if there is a way to do so in FSFAST. Thanks, Caspar 2013/10/3 Douglas N Greve <gr...@nmr.mgh.harvard.edu <mailto:gr...@nmr.mgh.harvard.edu>> On 10/03/2013 10:39 AM, Caspar M. Schwiedrzik wrote: Hi Doug, when I run a two-tailed t-test against 0 in Matlab on the Rs in pcc.nii that I get out of isxconcat-sess with -m pcc, and DOF from ffxdof.dat, I get different -log10(p) values than the ones that come out of mri_glmfit. I don't understand what you mean. Can you elaborate? I am not sure why this is happening. In principle, I just want pcc maps as final output to show them on the surface (instead of p-values). So I'd be happy to follow your advice regarding the biasing effects of noise and autocorrelation and use the regression coefficients. However, mri_glmfit (v5.1) does not seem to output pcc maps of the contrasts (contrary to selxavg3-sess on the single subject level). How would I get those? Thanks, Caspar 2013/10/1 Douglas N Greve <gr...@nmr.mgh.harvard.edu <mailto:gr...@nmr.mgh.harvard.edu> <mailto:gr...@nmr.mgh.harvard.edu <mailto:gr...@nmr.mgh.harvard.edu>>> On 10/01/2013 01:13 PM, Caspar M. Schwiedrzik wrote: > Hi Doug, > it would be great if you could give me some further advise on the > group analysis of functional connectivity maps. > Specifically, I am trying to get PCC maps for certain seeds, and am > not planning any comparison between groups. > Following your previous advise, I am running isxconcat-sess with -m > pcc to get the PCC maps. > I would then run > > mri_glmfit \ > --surf averagesubject hemisphere \ > --y pcc.nii \ > --no-cortex \ > --osgm \ > --glmdir analysisname > > *Could you please provide some more detail on what kind of analysis is > performed when I provide pcc.nii as an input for mri_glmfit? Is it a > t-test of the Fisher-transformed r-values against 0? I just run a t-test of the r-values. I don't have a program to convert them to z-values, however, there are z-values that are created in the first level analysis. These are generated from the p-values but I bet it would give you the same thing. Use -m z with isxconcat-sess if you want to use the z. > *Is the average r-value or z-value saved somewhere? Which level? For mri_glmfit, they are not, but it is not hard to get them with matlab. > *Do you take the autocorrelation into account (as in Vincent JL et > al., 2007. Intrinsic functional architecture in the anaesthetized > monkey brain. Nature. 447:83-86)? Not usually, but it could be done by not including -no-whiten when you run mkanalysis-sess. I usually use the regression coefficients instead of correlation coefficients because that they are at least unbiased with respect to noise level and autocorrelation. doug > I'd also be happy to look this up but I'd need to know where I can
-- Douglas N. Greve, Ph.D. MGH-NMR Center gr...@nmr.mgh.harvard.edu Phone Number: 617-724-2358 Fax: 617-726-7422 Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting FileDrop: https://gate.nmr.mgh.harvard.edu/filedrop2 www.nmr.mgh.harvard.edu/facility/filedrop/index.html Outgoing: ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/
mri_glmfit_pcc.m
Description: application/vnd.wolfram.mathematica.package
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