Thank you!

On Thu, Mar 21, 2013 at 10:56 AM, Douglas N Greve <greve@nmr.mgh.harvard.edu> wrote:

Yes, the average thickness over the cluster for each subject.
doug

On 03/21/2013 01:54 PM, Laura M. Tully wrote:

Thanks - one last clarification: just to confirm - the values of thickness.ocn.y.dat (i.e. analyses with thickness as input) are avg thickness over the whole cluster for each subject? If not, how would I get the avg thickness value for that cluster for each subject?

LT

On Thu, Mar 21, 2013 at 10:49 AM, Douglas N Greve <greve@nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu>> wrote:

On 03/21/2013 01:11 PM, Laura M. Tully wrote:

yes the input is area - so to clarify, in order to get the
average area for each subject in that cluster I would multiply
each subject's values in the xxx.ocn.y.dat file by the number
of vertices in the cluster (denoted as NVtxs in the cluster
summary?) e.g. 0.761374 * 998 = 759.85mmsq?

Yes, correct

Does the same hold for the y values in a thickness analysis,
i.e. when thickness is the input, does each value in the
xxx.ocn.y.dat file (e.g. 2.54) represent the average thickness
of each vertex and so I must multiply that by the number of
vertices to get the average thickness for each subject for
that cluster?

No, you probably just want to report the average thickness, not
the sum of the thicknesses within the cluster

I'm using 5.1.0 - I have no idea if I have the patch for area
and volume analyses because I run all my analyses remotely on
the harvard imaging server (ncf) - how would I know? And what
are the bugs in area/volume analyses in 5.1.0(how could I
detect them)?

You will need a new version of mris_preproc which you can get from
here:
ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/mris_preproc
You can compare this version against the one you have. If they are
different, then copy this version into $FREESURFER_HOME/bin. If
you are using QDEC, then rerun qcache (recon-all -qcache ...). If
you are using the command-line stream, re-run it starting at
mris_preproc.

doug

LT

On Thu, Mar 21, 2013 at 10:02 AM, Douglas N Greve
<greve@nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu>

<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>>> wrote:

Hi Laura, I assume the input is area? Then this will
compute the
average area of each vertex. The area of a vertex is the
average
area of the triangles around it. To get total area, you can
multiple the number that you get from xxx.ocn.y.dat by the
number
of vertices in the cluster.

doug

ps. What version of FS are you using? If not 5.2, do you
have the
patch to fix the area and volume analysis?

On 03/21/2013 12:52 PM, Laura M. Tully wrote:

hi Doug,
A follow up question: when I look at the
xxx.ocn.y.dat for a
cluster where group differences in surface area have been
identified the values are all less than 1 (e.g.
0.761374) even
though the cluster size is reported as 680 mmsq. does
the y
value correspond to .76 mmsq average area for that
subject in
that cluster or does the y value in the context of surface
area analyses represent something else? (or does it
need to be
multiplied by some factor?)

Thanks!

On Wed, Mar 20, 2013 at 2:39 PM, Douglas N Greve
<greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>
<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>>
<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>

<mailto:greve@nmr.mgh.harvard.edu
<mailto:greve@nmr.mgh.harvard.edu>>>> wrote:

They are the input (mri_glmfit --y y.mgh) averaged
over
the clusters.
They are raw input, no detrending.
doug
On 03/20/2013 05:16 PM, Laura M. Tully wrote:
> Hello experts,
>
> could someone clarify for me what the y values
in the
xxx.ocn.y.dat
> files represent following glmfit-sim? are they the
residualized y
> values of avg cortical thickness in that specific
cluster after
> regressing out the effect of any predictor
variables in
the glm?
>
> Thanks!
>
> Laura.
> --
> --
> Laura M. Tully, MA
> Social Neuroscience & Psychopathology, Harvard
University
> Center for the Assessment and Prevention of
Prodromal
States, UCLA
> Semel Institute of Neuroscience
> ltully@mednet.ucla.edu
<mailto:ltully@mednet.ucla.edu> <mailto:ltully@mednet.ucla.edu
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> --
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> Follow me on Twitter: @tully_laura
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Laura M. Tully, MA
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Center for the Assessment and Prevention of Prodromal
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UCLA Semel Institute of Neuroscience
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MGH-NMR Center
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-- --
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UCLA Semel Institute of Neuroscience
ltully@mednet.ucla.edu <mailto:ltully@mednet.ucla.edu>
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Follow me on Twitter: @tully_laura

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MGH-NMR Center
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--
--
Laura M. Tully, MA
Social Neuroscience & Psychopathology, Harvard University
Center for the Assessment and Prevention of Prodromal States, UCLA Semel Institute of Neuroscience
ltully@mednet.ucla.edu <mailto:ltully@mednet.ucla.edu>
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--
My musings as a young clinical scientist: http://theclinicalbrain.blogspot.com/
Follow me on Twitter: @tully_laura

--
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MGH-NMR Center
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--
--
Laura M. Tully, MA
Social Neuroscience & Psychopathology, Harvard University
Center for the Assessment and Prevention of Prodromal States, UCLA Semel Institute of Neuroscience
ltully@mednet.ucla.edu
ltully@fas.harvard.edu
310-267-0170
--

My musings as a young clinical scientist: http://theclinicalbrain.blogspot.com/

Follow me on Twitter: @tully_laura