New subject: Reposting: interpreting clusters from 2 and 3 way interactions

20 Mar 2013

      Sorry -  meant to respond to list.
Thanks for the response Doug - I have a few follow up questions I hope you
can clarify:
...

is the xxx.ocn.annot file created by mri_glmfit-sim considered a

"label" by freesurfer? or does it need to be converted to a label before I
   can use mri_segstats to extract the betas from the cluster(s) in the
   xxx.ocn.annot? I tried using the following command line to attempt to
   extract the betas from the cluster annotation file created by
   mri_glmfit-sim, but received an error:
mri_segstats --i beta.mgh --annot fsaverage hemi contrast/xxx.ocn.annot
--avgwf avgwf.dat

how does one convert an xxx.ocn.annot file to a label?

If I have run 3 different glms looking at the relationship between

thickness and 3 different behavioral variables, and found 1 (or more)
   cluster in each glm using mri_glmfit-sim can I create 1 annotation/label
   with all the clusters from the separate glms and then extract the betas
   from that one annotation using mri_segstats? Or do I need to treat each glm
   separately?

I saw on the listserv some references to matlab functions that

can calculate r square and partial correlations for glms with more than one
   predictor variable (e.g pcc between thickness and behavioral variable 1;
   pcc between thickness and behavioral variable2; Rsq for overall model) but
   I could not find the .m scripts for the functions (MRIread
   or fast_glm_pcc?) - would these functions be appropriate and if so where
   might I find them?
Thanks in advance for your help!
Laura.
On Wed, Mar 20, 2013 at 8:29 AM, Douglas N Greve <
greve@nmr.mgh.harvard.edu> wrote:
...
On 03/20/2013 10:17 AM, Laura M. Tully wrote:
...
Hi,
I wanted to re-post my questions from a couple of days ago below, but
with some more specific questions following a search through the
archives.
I want to be able to extract the beta values from a cluster identified
using mc-z in a group by behavioral variable interaction so that I can

plot the relationship of thickness to behavioral variable data by

group in that cluster, 2) conduct post hoc tests to examine the
interaction, and 3) calculate the Rsquare and partial correlations for
each variable in the glm (i.e. how much variation in thickness is
explained by my behavioral variable).
To extract the beta values from a cluster identified by mc-z would I
treat the cluster like a label and use mri_segstats to extract the
beta weights from the cluster? Would I need to make a label of all the
clusters that I want to do this for first?
You can do it label by label. Or, if the annotation created by
mri_glmfit-sim has all the clusters you want, you can use that (also in
mri_segstats). You can also create an annotation from individual labels
with mris_label2annot.
...
Is there a way to calculate the basic statistics for the glm and
extract in table form? i.e. Fs and ps for peaks of each cluster? What
about Rsquare, or the correlation between thickness and my behavioral
variable in the clusters? or would I need to compute these outside of
freesurfer using the extracted betas?
You will need to do it outside of FS. What are Fs and ps?
doug
...
Thank you!
Laura.
On Mon, Mar 18, 2013 at 5:05 PM, Laura M. Tully
<tully.laura@googlemail.com mailto:tully.laura@googlemail.com> wrote:
Hi Freesurfer experts,

I'm hoping you can help me understand how to interpret
interactions in clusters identified in whole brain analysis using
glmfit and glmfit-sim. Below I describe what I've done and what
I'd like to be able to do. Any suggestions would be most

appreciated!
...
  * I have two groups (patients, controls) and a behavioral
    variable of interest (social functioning). I am interested in
    cortical thickness differences between groups (main effect of
    group), whether cortical thickness relate to social
    functioning across the group (main effect of social
    functioning), and whether this relationship differs by group
    (group x social functioning interaction).
  * I ran whole brain analysis using mri_glmfit with group and
    functioning as variables of interest whilst controlling
    for/regressing out gender, age, and mean thickness. i.e. 4
    classes (conmale,confemale, ptmale, ptfemale) and 3 continuous
    variables (age, AvgThickness, Functioning) = 16 regressors.
  * I tested the group x functioning interaction with the
    following contrast - is it correct?

0000000000000.50.5-0.5-0.5

  * I then ran mri_glmfit-sim to identify clusters that survive
    multiple comparisons. This revealed 4 clusters (3 in LH; 1 in
    RH) that represent regions showing significant group x
    functioning interaction.
  * I visualized the clusters in tksurfer, and by loading the
    y.fsgd file was able to visualize the plotted data to get a
    sense of the interaction, but this is as much as I know in
    terms of how to examine interactions in the cluster data......

My specifc questions include:

  * I understand that the values in xxx.sig.cluster.mgh overlay
    reflect log10 p values, the signs of which indicate the
    direction of the relationship (i.e. -3 = negative correlation
    between thickness & variable) but I'm not sure how to
    interpret this in the context of an interaction with group?
  * I understand that the values in xxx.y.ocn.dat contain the
    average thickness value for each subject in that cluster and
    that in a simple between groups test this data could be used
    to conduct post hoc t-tests to show the direction of the
    difference, but again I'm not sure how to use this data in the
    context of the interaction. What do the values represent in a
    group x variable interaction?

Ideally, I'd like to extract the contrast estimates for each
subject in the group x functioning contrast and plot it in another
program and conduct pairwise comparisons (t-tests) in order to get
a better understanding of the interaction). I'm not sure how to do
this - is it possible? My thinking is that I do something similar
in fMRI analysis in spm where I can plot the contrasts in a
significant cluster and then extract both the average contrast
estimates for each group and the contrast estimates for each
individual subject.

Thanks in advance!

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>
ltully@fas.harvard.edu <mailto:ltully@fas.harvard.edu>
310-267-0170 <tel:310-267-0170>
--
My musings as a young clinical scientist:
http://theclinicalbrain.blogspot.com/
Follow me on Twitter: @tully_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
ltully@fas.harvard.edu mailto:ltully@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
--
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: www.nmr.mgh.harvard.edu/facility/filedrop/index.html
Outgoing: ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/

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
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
-- 
--
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

Re: [Freesurfer] Reposting: interpreting clusters from 2 and 3 way interactions

--

--

--

--

--