Hi Cornelius, dear all,
Thank you a lot for your help.
I have some follow-up questions:
1) Regarding the post
https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=ind1106&L=FSL&P=R36085&1=FSL&
9=A&I=-3&J=on&X=1D83CC50C377547D52&Y=burzynska%40mpib-berlin.mpg.de&d=No+Mat
ch%3BMatch%3BMatches&z=4
Do I need to make the same change in the feat_gm_prepare script?
I use the path with FSLv.4.1.8.
2) My fmri data contains 3 runs/subject. Does it mean that for the 1st level
analyses for feat_gm_prepare I can use only 1 run per subject?
3) I see that feat_gm_prepare uses fast to segment the anatomical images
(with the same parameters as vbm), then smooth, and register to a standard
anatomical image.
I have my anatomical images completely pre-processed for vbm, so they are
modulated by the non-linear component of the transformation to the
study-specific template, concatenated, and smoothed.
Both the VBM template and our fMRI data (on the group level) are at 2x2x2mm3
resolution in standard space.
Can I use the 4D file, such as GM_mod_merg_s3, as an input instead of using
feat_gm_prepare? What is exactly the difference (and advantage) of using the
file generated with feat_gm_prepare? I think both Oakes et al. 2007 and
Filippini et al., 2009 used feat_gm_prepare and did not take the files
generated by VBM.
4) In the last step, feat_gm_prepare de-means the GM images. If I have 2
groups, should I make this step separately for each group, and then fuse the
two 4D images?
Cheers,
Aga
On 6/21/11 6:59 PM, "Cornelius Werner" <[log in to unmask]> wrote:
> Hi,
>
> yes this is available for some time now. For FEAT consult the online
> help under http://www.fmrib.ox.ac.uk/fsl/feat5/detail.html and search
> for the term fsl_gm_prepare. Randomise has the beta option to include
> VBM data as well (type randomise to get the usage) - not sure what the
> beta stage means, however.
>
> Cheers,
> Cornelius
>
> On Tue, Jun 21, 2011 at 5:58 PM, Aga Burzynska
> <[log in to unmask]> wrote:
>> Hi,
>> I would like to follow up on the older post (see message below), as maybe
>> this option is now available.
>>
>> Is there a way to integrate structural VBM data with results from FEAT in
>> FSL, voxel-wise?
>>
>> I mean something similar to
>> http://afni.nimh.nih.gov/pub/dist/doc/program_help/3dTcorrelate.html
>> or the BPM tool in SPM.
>>
>> I could not find an option in randomise to include a separate 3D matrix as a
>> covariate or a way to correlate two multimodal volumes/subject, across the
>> sample.
>>
>> I will be very grateful for your advice!
>>
>> Best,
>> Aga
>>
>> ------
>> Previous post on a similar topic:
>>
>> I'm not sure about FSL, but SPM has.a toolbox -- Biological Parametric
>> Mapping -- from Wake Forest University that dies exactly what you want
>> to do. I believevthe reference is Casanova 2007, but I could have the
>> wrong year.
>>
>> On Tuesday, September 8, 2009, Andrej Schoeke <[log in to unmask]> wrote:
>>> Hello,
>>>
>>> I recently read a paper titled "Integrating VBM into the General Linear
>>> Model with voxelwise anatomical covariates" by T. Oakes et al[1]. I am
>>> interested in applying this analysis technique to our data. I know about the
>>> VBM tools in FSL, but is there a way to integrate the results into the
>>> analysis as described in the paper?
>>> Any hints are welcome.
>>>
>>> Best,
>>> Andrej
>>>
>>> [1] Oakes, T. R., Fox, A. S., Johnstone, T., Chung, M. K., Kalin, N., &
>>> Davidson, R. J. (2007). Integrating VBM into the General Linear Model with
>>> voxelwise anatomical covariates. NeuroImage, 34(2), 500-508. doi:
>>> 10.1016/j.neuroimage.2006.10.007.
>>>
>>
>
>
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