On 5/29/13 10:42 PM, Joseph Dien wrote:
On May 29, 2013, at 11:40 AM, Douglas N Greve
<gr...@nmr.mgh.harvard.edu <mailto:gr...@nmr.mgh.harvard.edu>> wrote:
Hi Joe,
On 05/29/2013 01:00 AM, Joseph Dien wrote:
I need to extract the beta weights from a cluster identified with
FS-Fast in order to compute percentage signal change.
1) I see a file called beta.nii.gz that appears to have the beta
weight information. It has a four dimensional structure and the
fourth dimension appears to be the beta weights. Is there an index
somewhere as to which beta weight is which? Or if not, how are they
organized?
For the first level analysis, the first N beta weights correspond to the
N conditions in the paradigm file. The rest are nuisance variables.
Ah, very good! In order to compute the percent signal change
statistic (I'm following the MarsBaR approach:
http://marsbar.sourceforge.net/faq.html#how-is-the-percent-signal-change-calculated)
I'm also going to need the beta weights for the session mean
regressors. How are the nuisance regressors organized?
You can just use the meanfunc.nii.gz. Also, each contrasts is computed
as the simple contrast (ces) and as a percent of the baseline at the
voxel (cespct, cesvarpct).
2) In order to extract the cluster, it looks like I would
use mri_label2vol to convert cache.th20.neg.sig.ocn.annot into a
volume where the voxels are tagged with the number of the
corresponding cluster.
Is that from a group analysis?
Yes, that's right.
I could then use that to generate masks to extract the information I
need for each cluster from beta.nii.gz.
If this is from a group analysis, then there should already be a file
there (something.y.ocn.dat) that has a value for each subject in the
rows and a value for each cluster in the columns.
I see it. Are these values already scaled as percent signal change?
If so, that would be wonderful! :)
Only if you specified it when you ran isxconcat-sess. Note that the
"non-scaled" values are actually scaled to percent of grand mean intensity.
Is that correct?
3) The final information that I would need is the canonical hrf shape
generated by FSFAST for a single event. I guess I could generate that
by setting up a dummy analysis run with a single event of the desired
duration and then look in the X variable in the resulting X.mat file?
try this
plot(X.runflac(1).flac.ev(2).tirf, X.runflac(1).flac.ev(2).Xirf)
Perfect! :)
Sorry for all the questions!
Joe
--------------------------------------------------------------------------------
Joseph Dien,
Senior Research Scientist
University of Maryland
E-mail: jdie...@mac.com <mailto:jdie...@mac.com>
<mailto:jdie...@mac.com>
Phone: 301-226-8848
Fax: 301-226-8811
http://joedien.com//
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--
Douglas N. Greve, Ph.D.
MGH-NMR Center
gr...@nmr.mgh.harvard.edu <mailto:gr...@nmr.mgh.harvard.edu>
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--------------------------------------------------------------------------------
Joseph Dien,
Senior Research Scientist
University of Maryland
E-mail: jdie...@mac.com <mailto:jdie...@mac.com>
Phone: 301-226-8848
Fax: 301-226-8811
http://joedien.com//
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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
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