Hello Steve,
Thanks for your explanation. Could you please explain how this applies to
probtrack output? We have used randomise to compare probtrack outputs from a
ROI in subjects and controls and are unsure of how to correct in this
case...
Thank you!!
---------------------------- Original Message ----------------------------
> Subject: Re: [FSL] stastical corrections?
> From: "Steve Smith" <[log in to unmask]>
> Date: Tue, May 19, 2009 6:09 am
> To: [log in to unmask]
> --------------------------------------------------------------------------
>
> 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 5/18/09 1:32 PM, "John Kuster" <[log in to unmask]> 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!
>
>
>
>
>
>
>
>
|