Hi,
There are various practical reasons why TBSS samples the data into
1x1x1mm standard space, primarily because having the mean-FA skeleton
at this resolution works much better in practice than at lower
resolutions. We don't generally recommend doing a "VBM-style"
voxelwise analysis (i.e. using the first stage of the TBSS processing
only) for the reasons outlined in the original TBSS paper - however,
you're right, if we _did_, then working at 2x2x2mm would probably be
just as good.
You're right that upsampling the data complicates the multiple
comparison correction - but at any given resolution, and taking into
account intrinsic data smoothness, it is important to get all these
issues taking into account. Hence both Gaussian random field theory
inference explicitly corrects for effective smoothness for you, and
permutation-based inference, with FWE thresholding, implicitly also
takes all these things into account, to give valid multiple comparison
correction. If you take either of these approaches in general when
done correctly you are ok.
Cheers.
On 18 May 2009, at 18:32, John Kuster wrote:
> I apologize if this has already been posted to the list, but I did
> not see
> it come through successfully. Thanks!
>
>
>
> Dear FSLers,
>
> We have a question regarding correction for multiple comparisons in a
> diffusion tensor imaging study:
>
> We have conducted a DTI study in which we have a priori areas of
> interest
> in our voxel-based analysis. We've pulled out the areas of interest
> and
> are only evaluating them initially, so the correction for multiple
> comparisons should be based on the number of voxels considered, with
> smoothing/clustering criteria taken into account.
>
> So far, this is all fine. However, the problem arises when I realize
> that
> the registrations that FSL uses to put DTI data into standardized
> space
> (using an MNI template), takes 2x2x2 data and registers it into a
> 1x1x1
> volume. The voxel-based contrast is done on the registered 1x1x1
> images,
> and thus, eight times the number of comparisons are made than would
> have
> been made on the original data. So the question is: How do we
> correct for
> multiple comparisons? It doesn't make sense to me to "increase"
> resolution and the number of comparisons without actually adding real
> information.
>
> Does anyone have any suggestions how to deal with this situation?
>
> Thank you!
>
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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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