Hello AFNI team,
I am following the instructions here to complete a gPPI analysis:
https://afni.nimh.nih.gov/CD-CorrAna
In Step 3 it recommends plotting the deconvolved seed timeseries to see if it looks reasonable when comparing to the stimulus presentation in the experiment. The data I am analyzing is a fast, event-related design, therefore I am wondering how to validate this step? I have used 1dplot to look at the timeseries before and after deconvolution, although I am not sure how to evaluate these plots.
In addition, for step 6 when running the regression, do I include all of my conditions of interest into one 3dDeconvolve step? For example, my code is pasted below with four conditions of interest (hour, day, week, month). Or should I run 3dDeconvolve four separate times instead, one for each condition?
Thank you,
Catherine
3dDeconvolve -input allruns+orig \
-polort 3 \
-num_stimts 22 \
-mask /usr/local/mridata/Consolidation_2019/atlases/Kirby/dil+orig \
-stim_file 1 /usr/local/mridata/Consolidation_2019/${i}/${i}.results.secondhalf.noblur/motion_short.1D'[0]' -stim_base 1 -stim_label 1 roll \
-stim_file 2 /usr/local/mridata/Consolidation_2019/${i}/${i}.results.secondhalf.noblur/motion_short.1D'[1]' -stim_base 2 -stim_label 2 pitch \
-stim_file 3 /usr/local/mridata/Consolidation_2019/${i}/${i}.results.secondhalf.noblur/motion_short.1D'[2]' -stim_base 3 -stim_label 3 yaw \
-stim_file 4 /usr/local/mridata/Consolidation_2019/${i}/${i}.results.secondhalf.noblur/motion_short.1D'[3]' -stim_base 4 -stim_label 4 dS \
-stim_file 5 /usr/local/mridata/Consolidation_2019/${i}/${i}.results.secondhalf.noblur/motion_short.1D'[4]' -stim_base 5 -stim_label 5 dL \
-stim_file 6 /usr/local/mridata/Consolidation_2019/${i}/${i}.results.secondhalf.noblur/motion_short.1D'[5]' -stim_base 6 -stim_label 6 dP \
-stim_file 7 /usr/local/mridata/Consolidation_2019/${i}/${i}.results.secondhalf.noblur/motion_deriv_short.1D'[0]' -stim_base 7 -stim_label 7 rolldx \
-stim_file 8 /usr/local/mridata/Consolidation_2019/${i}/${i}.results.secondhalf.noblur/motion_deriv_short.1D'[1]' -stim_base 8 -stim_label 8 pitchdx \
-stim_file 9 /usr/local/mridata/Consolidation_2019/${i}/${i}.results.secondhalf.noblur/motion_deriv_short.1D'[2]' -stim_base 9 -stim_label 9 yawdx \
-stim_file 10 /usr/local/mridata/Consolidation_2019/${i}/${i}.results.secondhalf.noblur/motion_deriv_short.1D'[3]' -stim_base 10 -stim_label 10 dSdx \
-stim_file 11 /usr/local/mridata/Consolidation_2019/${i}/${i}.results.secondhalf.noblur/motion_deriv_short.1D'[4]' -stim_base 11 -stim_label 11 dLdx \
-stim_file 12 /usr/local/mridata/Consolidation_2019/${i}/${i}.results.secondhalf.noblur/motion_deriv_short.1D'[5]' -stim_base 12 -stim_label 12 dPdx \
-stim_times 13 ../timing_files/${i}'_all_foils_tf_chop5.txt' 'TENT(0,14,8)' -stim_label 13 all_foils \
-stim_times 14 ../timing_files/${i}'_hour_targets_tf_chop5.txt' 'TENT(0,14,8)' -stim_label 14 hour_targets \
-stim_times 15 ../timing_files/${i}'_day_targets_tf_chop5.txt' 'TENT(0,14,8)' -stim_label 15 day_targets \
-stim_times 16 ../timing_files/${i}'_week_targets_tf_chop5.txt' 'TENT(0,14,8)' -stim_label 16 week_targets \
-stim_times 17 ../timing_files/${i}'_month_targets_tf_chop5.txt' 'TENT(0,14,8)' -stim_label 17 month_targets \
-stim_file 18 AllRuns_HIPP_Seed.1D -stim_label 18 Seed \
-stim_file 19 AllRuns_Interaction_timeseries_hour.1D -stim_label 19 PPIHour \
-stim_file 20 AllRuns_Interaction_timeseries_day.1D -stim_label 20 PPIDay \
-stim_file 21 AllRuns_Interaction_timeseries_week.1D -stim_label 21 PPIWeek \
-stim_file 22 AllRuns_Interaction_timeseries_month.1D -stim_label 22 PPIMonth \
-jobs 16 \
-rout -tout \
-bucket fxnConnOutput
