I'm a beginner in AFNI and trying to evaluate, with 3dDeconvolve "-nodata" mode, the time series generated by RFSgen. According to the "afni_howto" tutorial, under the circumstance of 3 experimental conditions (A, B, and C), 3 GLT's are needed (contrasts of AB, AC, and BC).
Now my problem is that I have 6 conditions (say, A to F). Then how should I do the GLT's? Contrasts between each pair (AB, AC, ..., EF), each triplet (ABC, ABD, ..., DEF), or between each combination with 4 or more conditions? Or all above?
Or, is it so that I don't need the glt option actually? If so, by what do I compare the qualities of different time series?
I know this question may be simple but it's really annoying me and I would appreciate any help. Thanks!
PS. Here is my code without adding the glt option (only showing the 3dDeconvolve part; 10 repetitions for each condition):
3dDeconvolve \
-nodata 150 2.0 \
-nfirst 3 -nlast 149 \
-polort A \
-num_stimts 6 \
-stim_file 1 "RSF.0001.1D[0]" -stim_label 1 S1 \
-stim_file 2 "RSF.0001.1D[1]" -stim_label 2 S2 \
-stim_file 3 "RSF.0001.1D[2]" -stim_label 3 S3 \
-stim_file 4 "RSF.0001.1D[3]" -stim_label 4 S4 \
-stim_file 5 "RSF.0001.1D[4]" -stim_label 5 S5 \
-stim_file 6 "RSF.0001.1D[5]" -stim_label 6 S6 \
> 3dD.nodata.0001
and here's the screen output:
++ using NT=150 time points for -nodata
++ Imaging duration=300.0 s; Automatic polort=3
++ Number of time points: 150 (before censor) ; 147 (after)
+ Number of parameters: 10 [4 baseline ; 6 signal]
++ ----- Signal+Baseline matrix condition [X] (147x10): 1.46989 ++ VERY GOOD ++
++ ----- Signal-only matrix condition [X] (147x6): 1 ++ VERY GOOD ++
++ ----- Baseline-only matrix condition [X] (147x4): 1.08516 ++ VERY GOOD ++
++ ----- polort-only matrix condition [X] (147x4): 1.08516 ++ VERY GOOD ++
++ +++++ Matrix inverse average error = 2.36283e-16 ++ VERY GOOD ++
++ Matrix setup time = 0.00 s
and the file:
Stimulus: S1
h[ 0] norm. std. dev. = 0.3394
Stimulus: S2
h[ 0] norm. std. dev. = 0.3451
Stimulus: S3
h[ 0] norm. std. dev. = 0.3531
Stimulus: S4
h[ 0] norm. std. dev. = 0.3509
Stimulus: S5
h[ 0] norm. std. dev. = 0.3423
Stimulus: S6
h[ 0] norm. std. dev. = 0.3410
