Hello,
I want to use fsl_regfilt to remove volumes generated from the confound matrix file from the fsl_motion_outliers (which I find to be the most robust method identifying outlier volumes).
I understand that I can add the file Feat if analysing in FSL, but due to consistency with previous data analysis I need to analyse in SPM, with 6 sessions for each subject, within a 2x2x2 design (each session represents a factorial level in a
phfMRI experiment). As you might understand the design matrix becomes quite complicated in SPM if I include regressors for the motion parameters and outlier scans in the SPM design matrix.
I thought it would be simpler and neater to regress out motion and outlier scans using fsl_regfilt and then run those filtered images in SPM first/second level with no need to add the motion and outlier regressors. Would that be possible?
For the motion parameters I assume it is simple as instead of the .par file I can input the rp_ file from SPM. e.g.
fsl_regfilt -i 4D -d rp_file.txt -f "1,2,3,4,5,6" -o 4D_movcor
I am a bit confused what would be the best way to regress out the outlier scans from fls_motion_outliers. the option -f can either be component number or filter threshold. So if i set -f 1 for the confound matrix would it work (as all other values
are zeros?
eg
fsl_regfilt -i 4D_movcor -d counfound_matrix.txt -f 1 -o 4D_filtered
or do I add each column of the matrix as a component e.g.:
fsl_regfilt -i 4D_movcor -d counfound_matrix.txt -f "1,2,3,4.... (number of columns for each matrix)" -o 4D_filtered
would it be preferred or maybe also filter our the metric values for each volume that fsl_motion_outliers generates?
I hope this makes sense and many thanks in advance,
Elias