Thank you for the quick reply!
I've been elaborating with a ROI-based approach for VBM where I first create an unbiased template for each MZ-pair (non-linear registration; ANTS SyN); second, create a group template in MNI-space where ROIs are defined; third, warp each pair template to the group template and use the inverse transformations to get ROIs to pair-space where data are obtained (from the modulated images native->pair). With this approach, deformations are smaller and specific to each paired comparison and I do not have to smooth the data as much. From what I can tell, it outperforms the traditional group analysis when using MZ twins. Would it make sense to try something similar with the cortical thickness analysis in Freesurfer?
Best,
Örjan

From: freesurfer-bounces@nmr.mgh.harvard.edu [freesurfer-bounces@nmr.mgh.harvard.edu] on behalf of Martin Reuter [mreuter@nmr.mgh.harvard.edu]
Sent: Wednesday, November 04, 2015 14:55
To: Freesurfer support list
Subject: Re: [Freesurfer] applying longitudinal processing on twins

Hi Oerjan,

yes, MZ twins are very similar (InfoAd: are you familiar with our BrainPrint NeuroImaging paper where we compare MZ and DZ brain shapes: http://www.sciencedirect.com/science/article/pii/S1053811915000476
http://reuter.mit.edu/blue/papers/wachinger-brainprint15/wachinger-brainprint15.pdf ).

Anyway, I doubt the longitudinal stream is going to work for this, as it is really designed for longitudinal and not across subject situations (even with MZ twins I expect differences to be too large). Even if a few cases work, there will be too many that fail.

Best, Martin

On 11/04/2015 05:13 AM, Örjan de Manzano wrote:

Dear FreeSurfers,

I'm about to analyze cortical thickness in monozygotic twins discordant for certain expertise. The within-pair similarities in brain morphology are striking (e.g. twin1 x twin2 intracranial volume correlation r=.99) and you could easily play a memory game with the images. Nonetheless, there are notable within-pair differences in gyrification etc. I'm trying to figure out if the longitudinal stream, or some version of it, might still be a viable option in this situation. The sample is fairly small and I want to do what I can to maximize sensitivity. Do any of you have experience with a similar data set or ideas/opinions/recommendations?

Best regards,

Örjan
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-- 
Martin Reuter, PhD
Assistant Professor of Radiology, Harvard Medical School
Assistant Professor of Neurology, Harvard Medical School
A.A.Martinos Center for Biomedical Imaging
Massachusetts General Hospital
Research Affiliate, CSAIL, MIT
Phone: +1-617-724-5652
Web  : http://reuter.mit.edu