Hi Eugene,
Thanks for your reply!
I like the idea of using the voxel dependent EV at the higher level analyzes.
The way I understood your suggestion and am currently thinking of going
about this is the following (please let me know if this is indeed along the
lines of what you meant):
step 1) Create a 4D image (where the 4th dimension is subject) by
concatenating the statistical maps (copes or zstats?) associated with the EV
I'd like to control for (say, EV2);
(example: fslmerge -t zstat2_subject1.nii zstat2_subject2.nii ...)
step 2) When running the regression of the behavioral variable on EV1 across
subjects, enter the 4D image created on step 1 as a voxel-dependent EV.
Thanks again for your feedback.
Hope all is well,
Regina
On Tue, 6 Oct 2009 01:04:12 +0100, Eugene Duff <[log in to unmask]> wrote:
>Hey Regina,
>
>In one sentence, the question is: is a *within-subjects* residualization
>> procedure (routinely part of fsl) sufficient to control for individual
>> differences in EV2 statistical maps when running a voxelwise regression
>> *across subjects* on EV1 statistical maps?
>>
>
>If I follow you, no - it is feasible to model uninteresting cross-session
>variation in a contrast of interest by including a regressor reflecting the
>cross-session variation of some control condition performed in the same
>run. It may be feasible to do this using a voxel dependent EV. I've been
>trying something similar myself.
>
>Cheers,
>
>Eugene
>
>
>
>> Thanks much for any clarification or recommendations,
>>
>> Regina
>>
>>
>> On Wed, 29 Apr 2009 09:55:46 +0100, Mark Woolrich <[log in to unmask]
>> >
>> wrote:
>>
>> >Hi Regina,
>> >
>> >It sounds like you want to know how, within a voxelwise GLM containing
>> >2 EVs, you can find only the explanatory power associated with (i.e.
>> >variance explained by) EV1 above and beyond EV2 and vice versa. The
>> >answer is that when you do [1 0] or [0 1] contrasts the GLM will
>> >automatically take care of this for you. For example, if the EVs are
>> >partially correlated then the GLM fitting of the parameter estimate
>> >for EV1is only driven by the component of EV1 that is orthogonal with
>> >(uncorrelated to) EV2 - and the resulting statistics will
>> >automatically reflect this accordingly.
>> >
>> >Cheers, Mark.
>> >
>> >----
>> >Dr Mark Woolrich
>> >EPSRC Advanced Research Fellow University Research Lecturer
>> >
>> >Oxford University Centre for Functional MRI of the Brain (FMRIB),
>> >John Radcliffe Hospital, Headington, Oxford OX3 9DU, UK.
>> >
>> >Tel: (+44)1865-222782 Homepage:
http://www.fmrib.ox.ac.uk/~woolrich<http://www.fmrib.ox.ac.uk/%7Ewoolrich>
>> >
>> >
>> >
>> >
>> >On 29 Apr 2009, at 02:45, Regina Lapate wrote:
>> >
>> >> Dear all,
>> >>
>> >> I have a question that I can imagine two potential ways of answering
>> >> it, and
>> >> while I am comfortable with how to implement it the first way, I
>> >> would like
>> >> to know if there is a practical way to implement it the second way
>> >> (in fsl).
>> >> The question is:
>> >>
>> >> - If one wants to residualize brain activation associated with
>> >> condition A,
>> >> from brain activation associated in condition B...
>> >>
>> >> 1) In a ROI approach, I assume one can extract parameter estimates
>> >> associated with BOLD changes due to condition A (cope1), similarly for
>> >> condition B(cope2), and regress cope1 on cope2 using a statistical
>> >> program
>> >> while saving the residuals of this regression;
>> >>
>> >> 2) But what about in a voxel-wise GLM approach in fsl, where both
>> >> conditions
>> >> A and B are EVs in the model? Is there a practical way where fsl can
>> >> save/output the residuals that remain after accounting for the
>> >> variance
>> >> associated with condition A, so that I could look at the variance B
>> >> accounts for once variance due to A has been removed?
>> >>
>> >> Thanks much for any suggestions!
>> >>
>> >> Regina
>> >>
>>
>
>
>
>--
>Eugene Duff
>
>Centre for Functional MRI of the Brain (FMRIB)
>University of Oxford
>John Radcliffe Hospital, Headington OX3 9DU Oxford UK
>
>Ph: +44 (0) 1865 222 523 Fax: +44 (0) 1865 222 717
>
>--
>
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