Hi Rick,
thanks much ! I am attaching the stim_analyze_modern script at the bottom, with my edits for clarity. from the 3dDeconvolve cmd --

3dDeconvolve \
-nodata 1680 2.000 \
-polort 2 \
-concat '1D: 0 168 336 504 672 840 1008 1176 1344 1512' \
-num_stimts 1 \
-stim_times 1 movemouth.0004_01_mouth.1D GAM \
-stim_label 1 mouth \
-x1D X.movemouth.0004.xmat.1D

from the 3dDecon help, I see that MION(d) could be used instead of GAM (although you mentioned the default was BLOCK?) -- In our experiment, these events are motor outputs of the participant, that last for <1 second. My questions are, 1) is it still appropriate to use the MION(d) if d is so short, or would it be more appropriate to convolve the MION response with the event-times only? 2) our lab's "preferred" mion fxn is piped through fsfast, which takes additional input parameters (ie., mion response is a modified gamma fxn with delta=0, tau=8, exponent=0.3) -- I'm wondering if these are specified as default values somewhere in AFNI, or how it is handled.

thanks much.
best,
Geena

**********
#!/bin/tcsh

# try to find reasonable random event related timing given the experimental
# parameters

# ---------------------------------------------------------------------------
# some experiment parameters (most can be inserted directly into the
# make_random_timing.py command)

# ---------------------------------------------------------------------------
# execution parameters
set iterations = 10000 # number of iterations to compare
set seed = 1234567 # initial random seed
set outdir = stim_results # directory that all results are under
set LCfile = NSD_sums # file to store norm. std. dev. sums in

# set pattern = LC # search pattern for LC[0], say
set pattern = 'norm. std.' # search pattern for normalized stdev vals


# ===========================================================================
# start the work
# ===========================================================================

# ------------------------------------------------------------
# recreate $outdir each time

if ( -d $outdir ) then
echo "** removing output directory, $outdir ..."
\rm -fr $outdir
endif

echo "++ creating output directory, $outdir ..."
mkdir $outdir
if ( $status ) then
echo "failure, cannot create output directory, $outdir"
exit
endif

# move into the output directory and begin work
cd $outdir

# create empty LC file
echo -n "" > $LCfile

echo -n "iteration (of $iterations): 0000"

# ------------------------------------------------------------
# run the test many times

foreach iter (`count -digits 4 1 $iterations`)

# make some other random seed

@ seed = $seed + 1


# create randomly ordered stimulus timing files
# (consider: -tr_locked -save_3dd_cmd tempfile)

make_random_timing.py -num_runs 10 -run_time 336 \
-tr 2 \
-pre_stim_rest 10 -post_stim_rest 40 \
-rand_post_stim_rest no \
-add_timing_class stim 1 \
-add_timing_class rest 2 -1 45 dist=decay_fixed \
-add_stim_class mouth 20 stim rest \
-prefix threat_app.$iter \
-write_event_list events.$iter.txt \
-show_timing_stats \
-seed $seed \
-save_3dd_cmd cmd.3dd.$iter.txt >& out.mrt.$iter


# consider: sed 's/GAM/"TENT(0,15,7)"/' tempfile > cmd.3dd.$iter
# rm -f tempfile

# now evaluate the stimulus timings

tcsh cmd.3dd.$iter.txt >& out.3dD.$iter

# save the sum of the 3 LC values
set nums = ( `awk -F= '/'"$pattern"'/ {print $2}' out.3dD.${iter}` )

# make a quick ccalc command
set sstr = $nums[1]
foreach num ( $nums[2-] )
set sstr = "$sstr + $num"
end
set num_sum = `ccalc -expr "$sstr"`

echo -n "$num_sum = $sstr : " >> $LCfile
echo "iteration $iter, seed $seed" >> $LCfile

echo -n "\b\b\b\b$iter"
end

echo ""
echo "done, results are in '$outdir', LC sums are in '$LCfile'"
echo consider the command: "sort -n $outdir/$LCfile | head -1"