Help with resting state analysis-RSFC

AFNI Message Board
1

Hello AFNI experts,
I have recently started experimenting with afni. Despite the steep learning curve, I am enjoying the process.
We are trying to do resting state analysis with RSFC to calculate ALFF and fALFF values. We have combined the scripts from example 10b and 11 because we wanted to regress out WM and CSF signal and align the data to the MNI 152 template (Also because we are a bunch of masochists who like to make life unnecessarily complicated).

Are the following steps and their order appropriate for extracting ALFF values?

afni_proc.py -subj_id AD001_rest
-blocks despike tshift align tlrc volreg blur mask regress
-copy_anat AD001_SurfVol.nii
-anat_follower_ROI aaseg anat aparc.a2009s+aseg.nii
-anat_follower_ROI aeseg epi aparc.a2009s+aseg.nii
-anat_follower_ROI FSvent epi FT_vent.nii
-anat_follower_ROI FSWe epi FT_white.nii
-anat_follower_erode FSvent FSWe
-dsets AD001_Rest.nii
-tcat_remove_first_trs 2
-tlrc_base MNI_avg152T1+tlrc
-tlrc_NL_warp
-volreg_align_to MIN_OUTLIER
-volreg_align_e2a
-volreg_tlrc_warp
-regress_ROI_PC FSvent 3
-regress_anaticor_fast
-regress_anaticor_label FSWe
-regress_bandpass 0.01 0.1
-regress_apply_mot_types demean deriv
-regress_RSFC
-regress_est_blur_epits
-regress_est_blur_errts
-regress_run_clustsim no

A big shout out to whoever inserts the quirky jokes in the help pages!

  • Anna
2

Hi Anna,

When using non-linear registration, it might be good to use a
template that is not a blurry average, but one that itself was
created by non-linear registration, such as MNI152_T1_2009c+tlrc.

Note that Paul has been pondering some updates to 3dRSFC to
deal with censoring, but that they are still just on the todo list.

Your interest in making life unnecessarily complicated is well
appreciated!

  • rick
3

Thank you Rick for the pointers. I hope Paul’s to-do list becomes shorter in the near future.
I have a related but very basic questions. I wanted to confirm that it is the errts data set that gets passed on to 3dRSFC

Thanks again!
-Anna

4

Hi Anna,

Yes, the errts dataset should be the residual time series
after removing the regressors of no interest.

  • rick
5

Thank you!