On May 31, 2013, at 12:09 PM, Douglas N Greve <greve@nmr.mgh.harvard.edu> wrote:

On 05/30/2013 04:37 PM, Joseph Dien wrote:
Just to make sure I'm doing this right, I'm going to summarize what
I've taken away from your answers and to ask some new questions. In
order to present the results, I need two things:

1) A set of histograms (with error bars) for each cluster figure to
show the % signal change for each of the four contrasts of interest.
The cache.th20.pos.y.ocn.dat file only gives it for the condition
where the cluster was significant so I can't use that.
So I could use mri_label2vol to convert cache.th20.neg.sig.ocn.annot
from the group level analysis to generate a mask for each cluster of
interest.
Then I could extract the value of the voxels from each
subject's cespct file for each contrast, average them across the
cluster ROI, then average them across each subject, to generate the
histogram?
This would suffice to give me the %age signal change?
I would be doing these computations in Matlab using MRIread.
I don't understand. If you don't have a cluster for a contrast, how are
you defining the cluster? From another contrast?

Well, what the reviewer told me to do is if I present a figure with a significant cluster for one condition, I should use that as an ROI to calculate the %age signal change for all four conditions and present it as a bar chart as part of the figure. I think she wanted to be able to get a more qualitative sense of the data patterns.

2) A results table with the headings:

Cluster p (FWE corrected)
Cluster size
Peak Voxel p (FWE corrected)
Peak Voxel T
Peak Voxel Coords
BA
Anatomical Landmark

I can get the first two from
the cache.th20.pos/neg.sig.cluster.summary files from the group level
analysis.
I can get the peak voxel coordinates from the summary files as well.
I can use this to get the peak voxel p from the group level sig.nii.gz
file. Is this FWE corrected? If not, how can I get this information?
What do you mean? The cluster p-value is corrected, why do you need the
max p and why does it need to be corrected?

Well, as I understand it, the drawback of clusterwise statistics is that while it assures you that the cluster passes muster as not being due to random chance (at 95% confidence), it doesn't provide any assurances at the voxel level (or in this case the vertex level) as it is likely that a cluster is composed of both signal and noise and you don't know which part is which. So if a cluster covers both BA44 and BA45 (for example), you can't be sure whether the activation involves BA44, BA45, or both. A voxelwise correction is more conservative but if it provides significance, it does allow for this kind of interpretation.

I can use these coordinates to get the peak voxel T by getting the
value from the group level F.nii.gz file and taking its square root.
How can I get the sign of the T statistic?
Same as the sign of gamma.mgh

Ah, great!

I can use the Lancaster transform to convert the MNI305 peak voxel
coordinates into the Atlas coordinates to look up the putative BA and
landmarks (unless there is a better way with Freesurfer? I'm seeing
some references to some BA labels in the forum but it doesn't look
like this is a complete set yet?).
Some of the BA labels are in FS, but not nearly all of them
doug

No problem! I worked out that I can use the talairach.nii file made available by the Talairach Daemon folks.

Sorry for all these questions! I got some nice results from FSFAST
and would like to get them written up.

Cheers!

Joe

On May 29, 2013, at 10:53 PM, Douglas Greve <greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>> wrote:

On 5/29/13 10:42 PM, Joseph Dien wrote:

On May 29, 2013, at 11:40 AM, Douglas N Greve
<greve@NMR.MGH.HARVARD.EDU <mailto:greve@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: jdien07@mac.com <mailto:jdien07@mac.com>
<mailto:jdien07@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
greve@nmr.mgh.harvard.edu <mailto:greve@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
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--------------------------------------------------------------------------------

Joseph Dien,
Senior Research Scientist
University of Maryland

E-mail: jdien07@mac.com <mailto:jdien07@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
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.

--------------------------------------------------------------------------------

Joseph Dien,
Senior Research Scientist
University of Maryland

E-mail: jdien07@mac.com <mailto:jdien07@mac.com>
Phone: 301-226-8848
Fax: 301-226-8811
http://joedien.com//

--
Douglas N. Greve, Ph.D.
MGH-NMR Center
greve@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/

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