Re: [Freesurfer] create mask from cluster number?

2017-04-10 Thread Douglas N Greve
mri_binarize --i HC.43.rh/v1.slope/results.ocn.mgh --match 1 --o 
cluster1mask.mgh

You can concatenate all your subjects together in fsaverage space 
(mris_preprpoc), optionally smooth it, then

mri_segstats ---i yourstackallsubjects.mgh --excludeid 0 --seg 
HC.43.rh/v1.slope/results.ocn.mgh --avgwf ocn.avgwf.dat

ocn.avgwf.dat will be a text file with number of rows = number of 
subjects in the stack, and number of columns equal to the number of clusters


On 04/09/2017 12:01 PM, lindsay hanford wrote:
> Hello Freesurfer Developers,
>
> The main point of my post is to determine whether its possible to 
> create a mask from a cluster ID run using a subset of the sample, and 
> then use that mask to extract cortical thickness values from a model 
> run with the full sample.
>
> I am running a pretty basic cortical thickness- behavioural 
> correlation analysis with two groups using fsgd. Because I have a 
> relatively small sample size (just over 40 participants in each group) 
> I wanted to restrict my analysis to only regions that showed a 
> relationship within the HC group. I ran the model using mri_glmfit:
>
> mri_glmfit --y HC.43.rh.10.mgh --fsgd Behav.fsgd --C v1.slope.mtx 
> --surf fsaverage rh --cortex --glmdir MCCB.HC.43.rh
>
> Behav.fsgd setup:
> GroupDescriptorFile 1
> Title MaineffectofGroup
> Class HC
> Variables BehavMC
> Input 128 HC -5
> Input 132 HC 8
> Input 192 HC -10
> Input 193 HC -6
> ...
>
> v1.slope.mtx:
> 0 1
>
> *quick side question - in the past I was curious to see if this could 
> test positive and negative relationships. I tried two different 
> contrasts: 0 1 and 0 -1 to test the positive and negative 
> relationships, respectively, however the results were the direct 
> inverse of each other... it didn't show negative slope relationships. 
> I am curious if its possible to test for negative relationships in 
> freesurfer? How would you set up that contrast?
>
> next, I used mri_surfcluster to generate image and table files:
> mri_surfcluster --in HC.43.rh/v1.slope/sig.mgh --subject fsaverage 
> --hemi rh --surf pial --annot aparc --thmin 2 --ocn 
> HC.43.rh/v1.slope/results.ocn.mgh --sum HC.43.rh/v1.slope/results.sum.txt
>
> my results.sum.txt file shows a number of clusters
> ClusterNo  Max   VtxMax   Size(mm^2)  TalX   TalY   TalZNVtxs Annot
>13.719  163035270.33 57.7  -34.6  -21.5   234 
>  inferiortemporal
>23.499   22608217.35 33.2  -48.2  -15.1   230  fusiform
>33.1702804 93.01 42.1   22.1 23.9   132 
>  rostralmiddlefrontal
>
> Would it be possible to create a mask defined by say "ClusterNo 1"?
>
> Once the mask is created, I want to use it to extract the cortical 
> thickness values for all participants (including those that weren't 
> used to create the mask).. Is this possible? Can that be done using 
> mri_segstats?
>
> Let me know if you require any other details.
> Freesurfer version: freesurfer-Darwin-lion-stable-pub-v5.3.0
>
>
> Thank you in advance,
>
>
> Lindsay
>
>
> ___
> 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
gr...@nmr.mgh.harvard.edu
Phone Number: 617-724-2358
Fax: 617-726-7422

Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting
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[Freesurfer] create mask from cluster number?

2017-04-09 Thread lindsay hanford
Hello Freesurfer Developers,

The main point of my post is to determine whether its possible to create a
mask from a cluster ID run using a subset of the sample, and then use that
mask to extract cortical thickness values from a model run with the full
sample.

I am running a pretty basic cortical thickness- behavioural correlation
analysis with two groups using fsgd. Because I have a relatively small
sample size (just over 40 participants in each group) I wanted to restrict
my analysis to only regions that showed a relationship within the HC group.
I ran the model using mri_glmfit:

mri_glmfit --y HC.43.rh.10.mgh --fsgd Behav.fsgd --C v1.slope.mtx --surf
fsaverage rh --cortex --glmdir MCCB.HC.43.rh

Behav.fsgd setup:
GroupDescriptorFile 1
Title MaineffectofGroup
Class HC
Variables BehavMC
Input 128 HC -5
Input 132 HC 8
Input 192 HC -10
Input 193 HC -6
...

v1.slope.mtx:
0 1

*quick side question - in the past I was curious to see if this could test
positive and negative relationships. I tried two different contrasts: 0 1
and 0 -1 to test the positive and negative relationships, respectively,
however the results were the direct inverse of each other... it didn't show
negative slope relationships. I am curious if its possible to test for
negative relationships in freesurfer? How would you set up that contrast?

next, I used mri_surfcluster to generate image and table files:
mri_surfcluster --in HC.43.rh/v1.slope/sig.mgh --subject fsaverage --hemi
rh --surf pial --annot aparc --thmin 2 --ocn HC.43.rh/v1.slope/results.ocn.mgh
--sum HC.43.rh/v1.slope/results.sum.txt

my results.sum.txt file shows a number of clusters
ClusterNo  Max   VtxMax   Size(mm^2)  TalX   TalY   TalZNVtxs   Annot
   13.719  163035270.33 57.7  -34.6  -21.5   234
 inferiortemporal
   23.499   22608217.35 33.2  -48.2  -15.1   230  fusiform
   33.1702804 93.01 42.1   22.1   23.9   132
 rostralmiddlefrontal

Would it be possible to create a mask defined by say "ClusterNo 1"?

Once the mask is created, I want to use it to extract the cortical
thickness values for all participants (including those that weren't used to
create the mask).. Is this possible? Can that be done using mri_segstats?

Let me know if you require any other details.
Freesurfer version:  freesurfer-Darwin-lion-stable-pub-v5.3.0


Thank you in advance,


Lindsay
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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.