Hi,
You might want to look into the unconfound tool:
unconfound <in4d> <out4d> <confound.mat>
However, you should be aware, that it is not the same, if you fit your
full modell and remove confounds based on this fit, or if you remove the
noise irrespective of the regressors of interest. See the explanation by
Christian Beckmann:
https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=FSL;722a5c62.0807
I would rather recommend to script the creation of your fsf-files, so
that a complete model is created for each subject, and use fsl_regfilt.
If it is just a problem, that the same 10 variable have different names
it shoul dbe no problem, to create a loop over all subjects and replace
the specific strings of the file names. It will be more tricky though
possible, if each subject has got a different number of confound
regressors that you want to filter.
I hope this helps,
wolf
On 22/09/11 22:48, Paul Geha wrote:
> Dear FSL users,
> is there a quick way to regress out of the filtered_func_data the
> confounders (confoundersev.txt) and obtain the residual 4D data
> without having to run the whole analysis in feat. I need to use the
> 4D after correction for motion and other noise outside of feat.
> Fslreg_filt seems like an option but I will need to enter 10 variables
> for each subject manually in Glm to obtain a design.
> thanks
> Paul
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