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FSL  July 2010

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Subject:

Re: different versions of standard atlases

From:

Joe Devlin <[log in to unmask]>

Reply-To:

FSL - FMRIB's Software Library <[log in to unmask]>

Date:

Wed, 21 Jul 2010 19:09:16 +0100

Content-Type:

text/plain

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text/plain (49 lines)

Hi Jesper,

I'm afraid we may have to agree to disagree on this one.  :)

The problem is not whether the images can be made to look more like  
one another -- they can be.  The issue is whether this is a meaningful  
thing to do.  Consider the case of V1 -- which is a region of the  
occipital lobes that can be  defined  functional based on retinotopy.   
Anatomically, it more or less sits in the calcarine sulcus but its  
extent and specific topography varies from person to person which is  
why if one wants to study it with fMRI in humans, it is necessary to  
do a retinotopy scan.  Any transformation that made subject 1's V1  
match subject 2's V1 by forcing them into a common space isn't helpful  
-- in fact, it is just the opposite because it is explicitly removing  
information that is present in the data (i.e. that the two areas are  
not the same).

And it's worth noting that the issue becomes more pronounced as one  
moves away from primary sensory/motor areas.  So called higher-order  
association areas have greater anatomical and functional variability  
than "earlier" areas.

Two final points that follow on from that:

1. Because the critical information is not present in the images  
themselves, even "expert" manual analyses based on gross anatomical  
features will never suffice to make two different brain the same.  I  
agree with you that loads of groups seem to be actively working along  
these lines, but from my perspective -- as a neuroimager with an  
interest in anatomy -- the endeavor itself is flawed.

2. Despite this variability that doesn't mean one should give up on  
group studies (which is a position that some groups have advocated,  
e.g. Fedorenko & Kanwisher (2009) Language and Linguistics Compass,  
3(4): 839-865).  It just means that if we want to make meaningful  
group comparisons, particularly across studies, then we need to accept  
this intrinsic variability as part of the interesting problem that we  
are trying to solve.  We don't want to either throw it away OR  
artificially inflate it by introducing additional (unnecessary)  
variability as a result of our registration procedures.  Linear  
registration meets both of these criteria; nonlinear registration  
violates both.

Ok, thats it from me.  Thanks again for a stimulating discussion of a  
topic that receives less attention than it should.

All the best,
Joe

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