Hi Doug,
Now I am able to convert .dfs files to freesurfer readable files (although I am not sure what is the format of the file, but now I can view it in Freeview). The command I used was write_surf.
Basically I want to get a significance thickness map to see the regions that make contribution to the GLM model. My dependent variable is the learning outcome of a second language. My independent variable include the thickness and one test score (word reading efficiency). In the meanwhile we have to exclude IQ score and age in the model.

To achieve this goal, the followings should be done:
1. Convert all my .dfs files and get each subject's thickness and get average subject thickness using "make_average_subject"
2. convert this average to mgh file format (how to do this)?
3. and run my own monte carlo using "mri_mcsim " to the average subject.
4. after 3 run "mri_glmfit-sim"
5. using qdec to build my GLM model : y= training outcome, x=thickness and cognitive scores, excluding age and IQ as covariates.


Could you please give me some suggestions on whether this looks like the right procedure? Thanks.
Miao


On Tue, Jun 24, 2014 at 3:44 PM, Miao Wei <weimiao@usc.edu> wrote:
Thank you. Hopefully I can do this since my data won't survive fdr correction in matlab. And there are no other options available for the correction.

Miao


On Tue, Jun 24, 2014 at 1:19 PM, Douglas N Greve <greve@nmr.mgh.harvard.edu> wrote:

Hi Mio, sorry, I have no clue, I've never used Brainsuite. If you have
each subject's thickness in a common space, you could convert it to mgh
format and then run mri_glmfit and mri_glmfit-sim
doug



On 06/24/2014 01:16 PM, Miao Wei wrote:
> Dear Freesurfer experts,
> My dataset was processed by Brainsuite, so that after registration
> they are in .dfs format.
> Now I wanted to do multiple comparison correction. How do I import the
> data to freesurfer and do the corrections?
> Thanks.
> Miao
>
>
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