Hi Rick,
Thanks for replying me!
I thought the longer ISIs the better the deconvolved results. And I thought we needed a slow event design to get better signal change curve of each stimulus. So the long rests were expected. But I am not sure about this. I thought the distribution of events should look evener but some ISIs are too small and the others are too big.
I also tried to reduce run_lengths to 180 includes pre_rest and post_rest:

set num_stim    = 3
set num_runs    = 4
set pre_rest    = 0 #pre_rest will be added manually later in the formal experiment
set post_rest   = 10 
set min_rest    = 10
set tr          = 2.0 
set stim_durs   = 2
set stim_reps   = 8 # This specifies the number of repetitions of each stimulus type, per run
@ run_lengths   = 180 * `printf '%.f' "$tr"`

The optimal sequence looks evener. But the post_rest is still too long to take for me:

timing_tool.py -multi_timing stimes.${iter}_0*                  \
                 -run_len $run_lengths -multi_stim_dur $stim_durs \
                -multi_show_isi_stats

ISI statistics (3 elements) :
                        total      per run
                       ------      ------------------------------
    total time         1440.0       360.0    360.0    360.0    360.0  
    total time: stim    192.0        48.0     48.0     48.0     48.0  
    total time: rest   1248.0       312.0    312.0    312.0    312.0  
    rest: total isi    1142.0       290.0    280.0    280.0    292.0  
    rest: pre stim       18.0         0.0     12.0      6.0      0.0  
    rest: post stim      88.0        22.0     20.0     26.0     20.0  
    num stimuli          96          24       24       24       24  

                         min      mean     max     stdev
                       -------  -------  -------  -------
    rest: pre-stim       0.000    4.500   12.000    5.745
    rest: post-stim     20.000   22.000   26.000    2.828
    rest: run #0 ISI    10.000   12.609   36.000    5.606
    rest: run #1 ISI    10.000   12.174   20.000    2.480
    rest: run #2 ISI    10.000   12.174   16.000    2.329
    rest: run #3 ISI    10.000   12.696   22.000    3.548
    all runs: ISI       10.000   12.413   36.000    3.674

And the NSD of optimal sequence becomes bigger (from 0.332600 to 0.354300).
Do you have suggestions for me to improve?
Yu Zhang



Edited 4 time(s). Last edit at 05/07/2018 05:32AM by Zhang Yu.