Dear all,

I used a shell script (see below) to first use make_random_stimuli and then 3dDeconcolve to check out the effectivity of each design.
I chose 50000 iterations and calculated an average effectivity index per iteration by calculating the mean effectivity of all conditions and entered contrasts in order to be able to compare iterations.

I know that the effectivity value is not really comparable between different designs, so I just wanted to ask whether someone could help me fining out if I need more iterations...

Using 50000 the best average eff was 0.1961 and the worst was 0.1994.

At first glance the 0.003 difference does not seem very much...
Do I need more iterations or does the effectivity 'just doesn't get better'....
(btw, my computer needed 3.5 days to calculate 50000..so if I don't need to run that much iterations to get 'the best' effectivity, that would be good in terms of processing time)..

Does anyone has some experience with that?

Thanks in advance and Best,
Dorit



******************

#!/bin/csh


########## set execution parameters
set iterations = 1000
set seed = 248390
set outdir = /Users/dziobek/Apps/abin/Results
set show = 10
set LCfile = $outdir/LC


############# create random timing sets per condition

set iter = 0

while ( $iter < $iterations )

@ iter = $iter + 1

@ seed = $seed + 1

python make_random_timing.py \
-num_stim 12 \
-num_runs 4 \
-run_time 300 \
-stim_dur 2.15 4 2.15 4 2.15 4 2.15 4 2.15 4 2.15 4 \
-stim_labels a1 b1 a2 b2 a3 b3 a4 b4 a5 b5 a6 b6 \
-ordered_stimuli 1 2 \
-ordered_stimuli 3 4 \
-ordered_stimuli 5 6 \
-ordered_stimuli 7 8 \
-ordered_stimuli 9 10 \
-ordered_stimuli 11 12 \
-show_timing_stats \
-seed @seed \
-t_gran 0.05 \
-prefix stim${iter} \
-num_reps 5 \
-pre_stim_rest 10 \
-post_stim_rest 10



./3dDeconvolve\
-nodata 720 2\
-polort A\
-num_stimts 12\
-stim_times 1 "stim${iter}_01_a1.1D" 'GAM'\
-stim_label 1 'stimA1'\
-stim_times 2 "stim${iter}_02_b1.1D" 'BLOCK(2)'\
-stim_label 2 'stimB1'\
-stim_times 3 "stim${iter}_03_a2.1D" 'GAM'\
-stim_label 3 'stimA2'\
-stim_times 4 "stim${iter}_04_b2.1D" 'BLOCK(2)'\
-stim_label 4 'stimB2'\
-stim_times 5 "stim${iter}_05_a3.1D" 'GAM'\
-stim_label 5 'stimA3'\
-stim_times 6 "stim${iter}_06_b3.1D" 'BLOCK(2)'\
-stim_label 6 'stimB3'\
-stim_times 7 "stim${iter}_07_a4.1D" 'GAM'\
-stim_label 7 'stimA4'\
-stim_times 8 "stim${iter}_08_b4.1D" 'BLOCK(2)'\
-stim_label 8 'stimB4'\
-stim_times 9 "stim${iter}_09_a5.1D" 'GAM'\
-stim_label 9 'stimA5'\
-stim_times 10 "stim${iter}_10_b5.1D" 'BLOCK(2)'\
-stim_label 10 'stimB5'\
-stim_times 11 "stim${iter}_11_a6.1D" 'GAM'\
-stim_label 11 'stimA6'\
-stim_times 12 "stim${iter}_12_b6.1D" 'BLOCK(2)'\
-stim_label 12 'stimB6'\
-xjpeg /Users/dziobek/Apps/testXmat.png\
-local_times\
-concat '1D: 0 180 360 540'\
-gltsym 'SYM: stimA1 -stimA2'\
-gltsym 'SYM: stimA3 -stimA4'\
-gltsym 'SYM: stimA5 -stimA6'\
-gltsym 'SYM: stimA1 +stimA3 +stimA5 -stimA2 -stimA4 -stimA6'\
>& Eff${iter}




echo -n "$iter $seed" >> $LCfile

set nums = ( `awk -F= '/h/ {print $2}' Eff${iter}` )
echo -n " $nums" >> $LCfile


set nums = ( `awk -F= '/LC/ {print $2}' Eff${iter}` )
echo -n " $nums" >> $LCfile

echo "" >> $LCfile


end