Try unconfound or fsl_glm -- both are easily scriptable (see example for unconfound below).
Cheers,
David
preMAT=${OUTPUTREAL}/for_confound.txt #contains motion parameters and outlier time points identified with fsl_motion_outliers
postMAT=${OUTPUTREAL}/for_unconfound.mat
sed -e 's@OUTPUT@'$OUTPUT'@g' \
-e 's@DATA@'$INDATA'@g' \
-e 's@NVOLUMES@'$NVOLUMES'@g' \
-e 's@UNCONFOUNDFILE@'$preMAT'@g' \
<make_confoundmat.fsf> ${OUTPUTREAL}/for_unconfound.fsf
feat_model ${OUTPUTREAL}/for_unconfound ${preMAT}
unconfound ${INDATA} ${OUTDATA} ${postMAT}
On Sep 22, 2011, at 4:48 PM, 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
|