Hello Rick,

Thank you very much again for your help.

(1) I guess you're right with the format of motion parameter output. The file reads as follows.

0 0.1978 0.2719 -0.5186 -0.5286 0.7214 0.3009 191.6 169.6
1 -0.5120 0.6810 -0.4259 -0.7477 0.0853 0.2378 206.1 182.3
2 -0.6188 0.8460 -0.3386 -0.8819 -0.1242 0.1928 210 177.3
3 -0.8224 -0.0941 -0.0910 0.0002 -0.6721 0.0781 167.9 148.6
4 -1.1417 0.2466 -0.1846 0.0209 -0.9311 0.1941 194.9 159.1
....

(2) Here is the output of the 1d_tool.py

1d_tool.py -infile Xmat.x1D -show_cormat_warnings

Warnings regarding Correlation Matrix: Xmat.x1D

severity correlation cosine regressor pair
-------- ----------- ------ ----------------------------------------
high: -1.000 0.000 ( 0 vs. 6) Run#1Pol#0 vs. Run#2Pol#0
medium: -0.418 0.021 (12 vs. 16) pleasant#0 vs. unpleasant#0


(3) If I run the script now, it is fine and gives the following comments (see below). But is it right that I now have 18 baseline parameters?

++ '-stim_times_AM2 1 onsettimes_pleasant_S1.txt' has 1 auxiliary values per time point
++ '-stim_times_AM2 1 onsettimes_pleasant_S1.txt' will have 2 regressors
++ '-stim_times_AM2 2 onsettimes_neutral_S1.txt' has 1 auxiliary values per time point
++ '-stim_times_AM2 2 onsettimes_neutral_S1.txt' will have 2 regressors
++ '-stim_times_AM2 3 onsettimes_unpleasant_S1.txt' has 1 auxiliary values per time point
++ '-stim_times_AM2 3 onsettimes_unpleasant_S1.txt' will have 2 regressors
++ 3dDeconvolve: AFNI version=AFNI_2010_10_19_1028 (Jan 3 2011) [64-bit]
++ Authored by: B. Douglas Ward, et al.
++ current memory malloc-ated = 113,501 bytes (about 114 thousand)
++ loading dataset psc.ssm.tsm.cl.dsp.hpf.reg.ts.1+orig psc.ssm.tsm.cl.dsp.hpf.reg.ts.2+orig
++ current memory malloc-ated = 275,373,813 bytes (about 275 million)
++ Auto-catenated datasets start at: 0 210
++ Input polort=5; Longest run=630.0 s; Recommended minimum polort=5 ++ OK ++
++ -stim_times using TR=3 s for stimulus timing conversion
++ -stim_times using TR=3 s for any -iresp output datasets
++ [you can alter the -iresp TR via the -TR_times option]
++ -stim_times_AM2 1 using GLOBAL times
++ '-stim_times_AM2 1' average amplitude#1=-0.157895
++ -stim_times_AM2 2 using GLOBAL times
++ '-stim_times_AM2 2' average amplitude#1=-0.588235
++ -stim_times_AM2 3 using GLOBAL times
++ '-stim_times_AM2 3' average amplitude#1=-0.15
++ -stim_times 4 using GLOBAL times
------------------------------------------------------------
GLT matrix from 'SYM: +pleasant[0] -neutral[0]':
0 0 0 0 0 0 0 0 0 0 0 0 1 0 -1 0 0 0 0 0 0 0 0 0 0

------------------------------------------------------------
GLT matrix from 'SYM: +pleasant[0] -unpleasant[0]':
0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 -1 0 0 0 0 0 0 0 0

------------------------------------------------------------
GLT matrix from 'SYM: +neutral[0] -unpleasant[0]':
0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 -1 0 0 0 0 0 0 0 0

------------------------------------------------------------
GLT matrix from 'SYM: +pleasant[1] -neutral[1]':
0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 -1 0 0 0 0 0 0 0 0 0

------------------------------------------------------------
GLT matrix from 'SYM: +pleasant[1] -unpleasant[1]':
0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 -1 0 0 0 0 0 0 0

------------------------------------------------------------
GLT matrix from 'SYM: +neutral[1] -unpleasant[1]':
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 -1 0 0 0 0 0 0 0

++ Number of time points: 420 (no censoring)
+ Number of parameters: 25 [18 baseline ; 7 signal]
++ Memory required for output bricks = 306,708,480 bytes (about 307 million)
++ Wrote matrix values to file Xmat.x1D
++ ========= Things you can do with the matrix file =========
++ (a) Linear regression with ARMA(1,1) modeling of serial correlation:

3dREMLfit -matrix Xmat.x1D \
-input "psc.ssm.tsm.cl.dsp.hpf.reg.ts.1+orig psc.ssm.tsm.cl.dsp.hpf.reg.ts.2+orig" \
-fout -tout -rout -Rbuck decon_modulation_S1_REML -Rvar decon_modulation_S1_REMLvar \
-Rfitts fitts_modulation_S1_REML -verb

++ N.B.: 3dREMLfit command above written to file decon_modulation_S1.REML_cmd
++ (b) Visualization/analysis of the matrix via ExamineXmat.R
++ (c) Synthesis of sub-model datasets using 3dSynthesize
++ ==========================================================
++ ----- Signal+Baseline matrix condition [X] (420x25): 11.7555 ++ VERY GOOD ++
++ ----- Signal-only matrix condition [X] (420x7): 1.04909 ++ VERY GOOD ++
++ ----- Baseline-only matrix condition [X] (420x18): 10.406 ++ VERY GOOD ++
++ ----- stim_base-only matrix condition [X] (420x6): 6.80116 ++ VERY GOOD ++
++ ----- polort-only matrix condition [X] (420x12): 1.05251 ++ VERY GOOD ++
++ +++++ Matrix inverse average error = 7.91203e-16 ++ VERY GOOD ++
++ Matrix setup time = 2.39 s
++ current memory malloc-ated = 584,259,172 bytes (about 584 million)
++ Calculations starting; elapsed time=13.838
++ voxel loop:0123456789.0123456789.0123456789.0123456789.0123456789.
++ Calculations finished; elapsed time=80.130
++ Wrote bucket dataset into ./decon_modulation_S1+orig.BRIK
+ created 35 FDR curves in bucket header

Best,
Jana