Hi Joe, David, thanks for your thoughts on this:
One important thing - this should not affect the registration because
example_func is generated _before_ all the brain extraction and
thresholding stuff.
Do other people find that the BET settings in FEAT are suboptimal? I
ask just because we've not had any problems with Oxford data. I guess
we could at the very least add a 'hidden' FEAT variable that could be
used to change BET behaviour if people wanted?
Cheers, Steve.
On 8 Mar 2008, at 09:22, Joseph T. Devlin wrote:
> Hi Steve,
>
> Thanks for the extra info.
>
>> Yes - it's just supposed to be a mostly-unimportant, liberal brain
>> masking. It shouldn't matter if it is over-liberal - I've not seen
>> any
>> cases where that was a problem.
>
> Well, in the data I've been working with, it is over-liberal and
> just provides out-of-the-brain false positives. Presumably it has
> at least a small effect on the inferential stats by inflating the
> search space as well. I may try replacing the command with
> something less liberal and see how it affects the results over a
> couple of studies...
>
>> If the 10% intensity thresholding is too high (it isn't normally?)
>> then you can just lower that under the 'misc' tab, even down to 0 if
>> necessary. Hopefully the voxels that you're losing are just down to
>> the thresholding.
>
> Hard to answer this one. When I bump the threshold up to 30%, it
> removes most of the material outside of the brain. But it also
> means more missing voxels within the brain...
>
>> It's to exclude voxels which are dodgy to use for exactly this
>> reason ;-) Do you really want to include such voxels who's motion is
>> taking them in-and-out of being 'valid'? You can always lower the
>> threshold though :)
>
> I understand your point here but it has unfortunate consequences at
> the group level where any single voxel which was potentially dodgy
> in a single volume in any subject ends up being excluded from the
> group. Also, some of the voxels in my data that are being excluded
> are not due to motion -- they are deep grey matter where the signal
> is slightly reduced relative to the surface. Within that set,
> occasionally a voxel has an abnormally low signal value --
> apparently randomly. The same process seems to be occurring in
> surface voxels with occasion outlier values, but the overall higher
> signal intensity in these areas makes this not a problem.
> Basically, the -Tmin option seems overly conservative to me -- I'm
> missing a non-trivial number of voxels in my group analyses and it
> gets worse the more subjects I have.
>
> Obviously this reflects data quality in problematic areas and I'm
> working to track that down, but I'm concerned that given the data I
> have, the procedure may be overly-liberal on the edge of the brain
> and overly conservative inside the brain volume.
>
> Anyway, thanks for all the info -- it's very helpful.
>
> All the best,
> Joe
>
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Stephen M. Smith, Professor of Biomedical Engineering
Associate Director, Oxford University FMRIB Centre
FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK
+44 (0) 1865 222726 (fax 222717)
[log in to unmask] http://www.fmrib.ox.ac.uk/~steve
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