Hello!
I was wondering if instead of the options listed for extracting the ROI time series and detrending (from [
afni.nimh.nih.gov]), it would be alright/equivalent to run 3dDeconvolve to remove the trend and account for motion, collect the residuals, then use the residuals for ROI time series extraction and proceed as outlined? Sample script below
Thank you for your time!
Ali
3dDeconvolve \
-input \
pb04.${sub}.r1.scale+tlrc pb04.${sub}.r2.scale+tlrc pb04.${sub}.r3.scale+tlrc \
pb04.${sub}.r4.scale+tlrc pb04.${sub}.r5.scale+tlrc pb04.${sub}.r6.scale+tlrc \
-censor motion_all_censor.1D \
-cbucket MacA_PPI_${sub}_cbucket \
-bucket MacA_PPI_${sub}_bucket \
-rout -tout -fout -xsave \
-x1D MacA_PPI_${sub}_xmat \
-polort A \
-jobs 2 \
-num_stimts 6 \
-stim_file 1 motion_all_demean.1D'[0]' -stim_base 1 -stim_label 1 roll \
-stim_file 2 motion_all_demean.1D'[1]' -stim_base 2 -stim_label 2 pitch \
-stim_file 3 motion_all_demean.1D'[2]' -stim_base 3 -stim_label 3 yaw \
-stim_file 4 motion_all_demean.1D'[3]' -stim_base 4 -stim_label 4 dS \
-stim_file 5 motion_all_demean.1D'[4]' -stim_base 5 -stim_label 5 dL \
-stim_file 6 motion_all_demean.1D'[5]' -stim_base 6 -stim_label 6 dP \
-errts MacA_PPI_${sub}_errts \
-progress 10000
