Hi guys,

We have a stochastic problem at our scanner that goes, for example, as follows:

-We intend to get, say, 3 runs each of 128 acquisitions of EPI data and 128 acquisitions-worth of physio data. From time to time, however, we come up one acquisition short of a full 4D series (literally, not in the sense that I'm trying to call someone crazy by saying that they are "one acquisition short of a full 4D series") for one of the runs so that we're left with the situation:
Run 1: 128 TRs; 128 lines of physio data
Run 2: 127 TRs; 128 lines of physio data
Run 3: 128 TRs; 128 lines of physio data

...where Run 2 is missing the first acquisition...

Considering also that we want to drop the first five TRs, I attempt to account for everything via the following:

afni_proc.py -subj_id ${subj_id} \
-dsets ${episcan}_R1+orig'[5..127]' ${episcan}_R2+orig'[4..126]' ${episcan}_R3+orig'[5..127]' \
-copy_anat ${anat}+orig \
-blocks despike ricor tshift align tlrc volreg mask scale regress \
-ricor_regs_nfirst 5 \
-ricor_regs Physio-Reg*.slibase.1D \
-ricor_regress_method per-run \
-tlrc_NL_warp \
-volreg_tlrc_warp \
-volreg_base_ind 1 1 \
-regress_stim_times ./MSQ_times*.1D \
-regress_stim_labels catch_trial nonself_actual_actual nonself_actual_ideal nonself_ideal_ideal self_actual_actual self_actual_ideal self_ideal_ideal \
-regress_opts_3dD \
-jobs 4 \
-regress_basis GAM \
-regress_censor_motion 0.2 \
-regress_censor_outliers 0.1 \
-regress_apply_mot_types demean deriv \
-execute

So, given that we have an unequal number of TRs to remove at the beginning, I'm removing them "manually" with sub-brick notation as opposed to using -tcat_remove_first_trs. Further, I'm telling ricor to ignore the first 5 TRs, as well. However, these two methods are not communicating: ERROR: ricor NT != dset len (123, 128).

How shall I go about reconciling all this? Sorry for my relative newb-ish-ness at afni_proc...

Paul



Edited 1 time(s). Last edit at 03/31/2015 09:26PM by paul.hamilton.