HI Afni experts,

I have multiband rs-fMRI data, acquired on a Seimens scanner, with TR=0.681s with 870 time points. This acquisition exactly follows the ADNI3 acquisition protocols.

Here is what I have started with for processing:

afni_proc.py -subj_id $line -dsets /data/data05/Studies/MCSA/RAW/MRI/$line/$RSN -copy_anat /data/data05/Studies/MCSA/RAW/MRI/$line/$T1 -blocks despike align volreg mask regress -tcat_remove_first_trs 10 -volreg_align_e2a -mask_apply epi -mask_segment_anat yes -mask_segment_erode yes -regress_apply_mot_types demean deriv -regress_run_clustsim yes -regress_est_blur_errts

3dresample -master errts.$line.tproject+orig -prefix DKT_resample -input /data/data05/melissa/MCSA_processing/t1_preproc/$line/freesurfer_DKT.nii
@MakeLabelTable -lab_file ../DKT.txt 1 0 -labeltable sub.niml.lt -dset DKT_resample+orig
3dcalc -a DKT_resample+orig -expr 'step(a)' -prefix DKT_mask
3dcalc -a errts.$line.tproject+orig -b DKT_mask+orig -expr 'a*b' -prefix errts_DKT_fs
3dNetCorr -prefix netcorr -mask mask_GM_resam+orig.BRIK -ts_out -fish_z -inset errts_DKT_fs+orig -in_rois DKT_resample+orig -output_mask_nonnull -push_thru_many_zeros -ts_wb_corr -ts_wb_strlabel
fat_mat_sel.py -m netcorr_000.netcc -P "FZ" --A_plotmin=0.27 --B_plotmax=1 --Tight_layout_on --dpi_file=75 -L 2 -d 300 -S 2

Can you please validate, if I am missing an important step in the preprocessing.
I am running the above script on my Alzheimer's dataset.
We have a few followup scans. The resting state connectivity in the old acquisition with TR = 2s and 150 time-points was very low than what I see for the same patient in the new scans described above. For the comparison purpose, I preprocessed both the scans with the exact same pipeline.
I see very high correlations across the entire brain in the multiband acquisition but following the same connectivity pattern as in the old acquisition.
Any suggestions from experience?"

Naveed



Edited 3 time(s). Last edit at 02/11/2019 07:53PM by Naveed.