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Hi - the first thing to do is to evaluate/fix the registrations on the basis of the underlying images (like example_func and highres), not on the basis of the stats maps, which will confuse matters probably.   If you believe that the registrations are suboptimal, then you should do all you can to try to improve that before going any further.

Once this is optimised, if you still have some subjects missing from areas you care about, you will need to exclude the problem subjects, as there is currently no straightforward way in FEAT to handle those missing subjects otherwise, sorry!  If their fields-of-view are fine but their registrations poor, then it is best to exclude them anyway.

Cheers.




On 14 Sep 2010, at 00:33, Anna-Maria D'Cruz wrote:

Hi all,

I have searched through the boards for topics about this, and have posted but haven't got a reply. Still struggling with this, so please see below and let me know what your thoughts are with dealing with this problem:

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I am producing group maps but I think registration problems may be affecting the appearance of functional maps.

In posterior visual cortex, I frequently get a sharp cut-off in the map, i.e. activation cuts off in a sharp diagonal line. This makes for a messy figure, and unfortunately affects precisely those slices in which I have other areas of activation that I want to present. Dropping one or another subject whose orientation appears to be tilted (by eyeballing the "registration" results page) improves the situation somewhat but does not remove the problem. Further, this approach has the disadvantage of not allowing all subjects to contribute to the group activation map, changing the presentation of results.

I understand that FSL only includes those voxels in a group analyses which are shared by ALL subjects - how can I loosen this restriction?  

Are there any other ways of remedying the problem of a few subjects' orientation impacting group maps? For instance, how can I identifying the specific subject(s) that are contributing to this problem? What approaches can I take to deal with these subjects w/o removing their data from the group analyses altogether?

Thanks for your help,

Anna-Maria



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