Hi experts,

I would like to make use of the local WM regression from ANATICOR like in example 9b from anfi_proc.py in combination with regression the average eroded CSF like in example 10 for resting state preprocessing - please see below.
1) Does anything speak against this combination?
2) In example 11, it is not local but average WM, right?
3) How much better is the "first 3 principal components of lateral ventricles" method in combination with freesurfer segmentation used in example 11 compared to the eroded mean CSF from example 10 or on what factors does it depend how big the difference is? What is your recommendation regarding my data (high motion sample with ASD including children and adolescents, 10min RS)?

Thanks for any input!
Janina



afni_proc.py
-subj_id ...
-dsets ...
-blocks despike tshift align tlrc volreg mask blur regress
-tcat_remove_first_trs 0
-tlrc_base MNI_avg152T1+tlrc
-volreg_align_e2a
-volreg_tlrc_warp
-regress_anaticor
-blur_size 6.0
-mask_segment_anat yes
-mask_segment_erode yes
-regress_censor_motion 0.3
-regress_censor_outliers 0.3
-regress_bandpass 0.01 0.1
-regress_apply_mot_types demean deriv
-regress_ROI CSFe
-regress_run_clustsim no
-regress_est_blur_errts