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

On 03/20/2013 12:09 PM, Laura M. Tully wrote:

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?

It is an annotation

  * 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?

No

  * 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

That looks correct. Did it work? Add --excludeid 0 to keep it from reporting on non-clusters

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

If needed, use mri_annotation2label

  * 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?

It is probably easiest if you treat each glm separately. You can break the annotations into separate labels, then recombine the labels into another annotation (mris_label2annot), but it is a lot of work.

 *


  * 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?

Yes. They are in $FREESURFER_HOME/matlab and $FREESURFER_HOME/fsfast/toolbox doug

 *

Thanks in advance for your help!

Laura.


On Wed, Mar 20, 2013 at 8:29 AM, Douglas N Greve
<greve@nmr.mgh.harvard.edu <mailto: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
    > 1) 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>
    <mailto: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>
    <mailto:ltully@mednet.ucla.edu <mailto:ltully@mednet.ucla.edu>>
    > ltully@fas.harvard.edu <mailto:ltully@fas.harvard.edu>
    <mailto:ltully@fas.harvard.edu <mailto:ltully@fas.harvard.edu>>
    > 310-267-0170 <tel:310-267-0170> <tel: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>
    <mailto:ltully@mednet.ucla.edu <mailto:ltully@mednet.ucla.edu>>
    > ltully@fas.harvard.edu <mailto:ltully@fas.harvard.edu>
    <mailto: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
    >
    >
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    Douglas N. Greve, Ph.D.
    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>
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