Alternatively, you can run mris_preproc for both time point 1 and 2 to
create separate files with all your subjects in them, then use mris_calc
like below to create a difference file, then follow the standard
command-line stream as is described on the wiki.

doug

Martin Reuter wrote:
> Hi Sandra,
> (and the list, I think this might be interesting for others)
>
> 1.
> the longitudinal ?h.thickness files are in registration (within subject)
> so in order to compute the difference or the rate you can simply use:
> mris_calc -o lh.outdiff sdir2/surf/lh.thickness sdir1/surf/lh.thickness
> and for the rate, you can divide by time 1 thickness or by the average
> thickness. If the time points are not equally spaced across subjects,
> you can also divide by difference in time.
> It is best to smooth the thickness files before you do all this (i.e.
> within time point smooth the ?h.thickness files with mri_surf2surf).
>
> 2.
> then map everything to your template (e.g. fsaverage) with mri_surf2surf
>
> 3. there you can stack the thick-differences or thick-rates with
> mri_concat
>
> 4. do the glm
>
> Beste Gruesse, Martin
>
>
> On Tue, 2010-06-29 at 21:50 +0200, Sandra Duezel wrote:
>
>> Hi Martin
>>
>> I just have got your answer to the longitudinal processing question
>> from Michele and have some other questions regarding the output data
>> from the longitudinal stream.
>> Our study contains MRI scans of 45 elderly subjects from 2 timepoints.
>> I have done all steps from the longitudinal stream and it worked
>> without any problems.
>>
>> Now I would like calculate the thickness difference maps between the
>> prae and post scans, which are already longitudinally processed.
>>
>> I have tried the thickdiffmap-script using the <tp1>.long and
>> <tp2>.long data. It creates a .mgz file in each subject but also a new
>> folder "groupstudy"
>> with the prae/post data resampled to  fsaverage (its an .mgh file)
>>
>> Is this the right way to calculate the difference for longitudinal data?
>>
>> Do I also need to proceed with GLM analysis as suggestet in http://surfer.nmr.mgh.harvard.edu/fswiki/FsTutorial/GroupAnalysis
>>   or do I need to handle the longitudial data in a different way?
>>
>> Thank you very much for your help and answers!
>>
>> Best regards
>>
>> Sandra
>>
>>
>>
>>
>>
>>
>>
>>
>> Am 29.06.2010 um 17:24 schrieb Martin Reuter:
>>
>>
>>> There is a step by step description on the longitudinal stream.
>>> It basically means:
>>> 1. to process your two time points individually through freesurfer
>>> (standard processing).
>>> 2. to create a template for each subjects from these processed time
>>> points
>>> 3. to run the two time points again (passing it the template) to
>>> compute
>>> better longitudinal results (less variability, more accuracy).
>>>
>>
>
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>
>

--
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
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