Hi Adam,
Whether/how to include confound parameters in an ongoing area of
research with no general consensus regarding a possible optimal
approach that should always be used. For example, on the question of
whether to include motion parameters as confound covariates, some
people do, some don't, and some look at the data before deciding. We
quite often do, and they can indeed help cleanup the data;
alternatively ICA-based cleanup can also help remove structured noise
(including many motion artefacts). FEAT makes it very easy to include
the motion parameters; for details on this see
http://fsl.fmrib.ox.ac.uk/fsl/feat5/detail.html#stats
Cheers, Steve.
On 5 Dec 2008, at 06:37, Adam Jacks wrote:
> Dear FSL users,
>
> I am currently performing analysis on some speech data collected
> using a block fMRI
> design, and wanted to get some feedback on current best practices on
> removing stimulus-
> correlated motion. We limited motion to the extent possible using
> closed-mouth speech,
> however understandably some artefact remained. I understand from
> reading the list that
> some users have employed code by Jesper Andersson in SPM to remove
> artefact and then
> complete analysis in FSL. Is this procedure still in use, or does
> anybody have better
> recommendations?
>
> I appreciate any suggestions that you all may have.
>
> Thanks in advance!
>
> Adam Jacks
>
> Assistant Professor
> Department of Communication Disorders
> Texas State University- San Marcos
>
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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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