External Email - Use Caution        

Hi,

I tried that and it seemed to work. My averages between the 2 groups look 
different now instead of almost identical. Thanks!

I have another similar question. I have a cluster that shows a significant 
difference between the groups when looking at volume. When I look at the 
y.ocn.dat file, the values are in the 0.74188 - 2.16321 range, which are pretty 
low for volume. I found a post where it says that you can multiply those values 
with the cluster size(mm^2) from the summary file to convert them to volume. 
Then, I tried using the formula you provided below (beta, res, yhat), but then 
I get some negative values. Negative volumetric values do not make sense, so I 
was thinking if using the absolute value would correct for that.

Any thoughts?

Thanks for all the help so far.

>If you say y = ocn.dat, then
>beta = (X'*X)*X'*y;
>res = y - X*beta;
>yhat = X(:,1:2)*beta(1:2) + res;
>yhat will be a score for each subject with the nuisance variables removed.
>
>On 9/11/19 2:40 PM, Maximo, Jose Omar wrote:
>
>        External Email - Use Caution
>

>Hi,

>

>I plotted the data from the *.y.ocn.dat file and the graph still shows no 
>apparent significant difference between the groups (see attached pic). Then I 
>>found a post with the following:

>

the ocn.dat files have data that is uncorrected in that sense and might need to 
nuisance factors removed before plotting.

There is a design matrix in there (Xg.dat). You can load that into matlab along 
with the ocn.dat, compute beta = inv(X'*X)*(X'*ocn)

to get the betas. You can then compute yhat = X2*beta2 where X2 has nuisance 
columns removed and beta2 has the same nuisance coefficients removed, then 
treat yhat as your data to be plotted.

>

>I tried that since I have 2 nuisance factors (age and TICV) and want to plot 
>my significant cluster w/o any nuisance effects. This is what I get

>

       1.8973

       1.8973

       1.8973

       …

       3.4728

       3.4728

       3.4728

       …

>Are these the mean averages for each group (cortical thickness). If so, is 
>there a way to get a score for each subject?

>

>Best,

>Omar

      >

>Look  in the *.y.ocn.dat file.

>

> From mri_glmfit-sim --help

>

>csdbase.y.ocn.dat - this is a summary of the input (y) over each

>cluster. It has a column for each cluster. Each row is a subject. The

>value is the average of the input (y) in each cluster. This is a

>simple text file.

>

>

>

>On 9/3/2019 5:16 PM, Maximo, Jose Omar wrote:

>          External Email - Use Caution

>

> Hi,

>

> Which specific file should I load? I see cluster.mgh, cluster.summary, 
> sign.ocn.annot, sig.ocn.mgh, sig.vertex.mgh, and pdf.dat.

>

> How can I extract the values from fsaverage space?

>

> Basically, what is the correct way to extract values from these significant 
> clusters?

>

> Many thanks,

> Omar

>

>      Date: Tue, 3 Sep 2019 15:15:02 +0000

>      From: "Greve, Douglas N.,Ph.D." <DGREVE at 
> mgh.harvard.edu<https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer>>

>      Subject: Re: [Freesurfer] qdec contrast and data extraction

>      To: "freesurfer at 
> nmr.mgh.harvard.edu<https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer>"
>  <freesurfer at 
> nmr.mgh.harvard.edu<https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer>>

>      Message-ID: <2286f9bf-37a4-1be9-2252-0bccc833a218 at 
> mgh.harvard.edu<https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer>>

>      Content-Type: text/plain; charset="utf-8"

>

>      You might have done something wrong along the way. When you run the 
> montecarlo correction, it will create a file with the thickness values in it 
> for each cluster. the first thing to do is to load that and see if you see 
> the expected differences. The other thing is to not go back into native space 
> to extract the numbers. There are several operations that happen as it moves 
> into fsaverage space and in preparation for group analysis (interpolation, 
> and smoothing); sometimes these make a big difference. if the ROI is small, 
> it may not map accurately back into the native space (and you should not need 
> to draw it in the first place)

>

>      On 8/30/2019 11:36 AM, Maximo, Jose Omar wrote:

>

>              External Email - Use Caution

>      Hi,

>

>      I have a question:

>

>      My design is 2 groups (HC and Patients in that respective order) and 2 
> nuisance factors (age and eTIV). When I look at the average volume difference 
> between the 2 groups, I get blue and red clusters. I presume the color coding 
> is where each group is greater than the other (Blue = Patients > HC and Red = 
> HC > Patients).

>

>      Then, I processed to extract individual values from each cluster in 
> order to plot them. When I extract data from the blue clusters and plot them, 
> the two groups show no difference in thickness at all, whereas when I look at 
> volume, HC show more than patients in blue clusters (see attached figure). I 
> would assume that both figures would show patients > HC based on the negative 
> statistic.

>

>      Am I interpreting the colors wrong? Or am I doing something wrong?

>

>      These are my steps 1) After applying montecarlo correction, I drew my 
> ROIs to extract the data from; 2) map it onto every single subject; and then 
> 3) used mris_anatomical_stats to extract the data from each subject.

>

>      Any suggestions are welcome.

>

>      Best,

>      Omar

>

>      Jose O. Maximo, Ph.D. | Postdoctoral Fellow

>      Department of Psychiatry & Behavioral Neurobiology

>      UAB School of Medicine

>      University of Alabama at Birmingham

>      Cell Phone: (619) 252-3492

>      Email: jomaximo at 
> uabmc.edu<https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer><mailto:jomaximo
>  at uabmc.edu<https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer>>
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