Hi Gabe,

You can first convert the all_*.1D files to stim_times files
via the make_stim_times.py program. See example #4 from
"make_stim_times.py -help". Assuming your TR is 2.5 seconds,
and you have 7 runs with 120 TRs per run, it might read:

make_stim_times.py -prefix stimes -tr 2.5 -nruns 7 -nt 120 \
-labels auditory visual \
-files all_auditory.1D all_visual.1D

All that would do is make TR-locked timing files from those
0/1 delta files, stimes.01.auditory and stimes.02.visual.1D.

Then you can use TENT basis functions instead of the lags.
The resulting regressors should be identical to what you had
used.

To encode the TENT basis function, it is necessary to know
your TR. Other than that, the 12 lags (0-11) correspond to
12 tent functions.

Let me assume your TR is 2.5 seconds. Then the 12 lags cover
11 TR intervals (keep in mind that lags 0 and 1 would cover
only 1 interval, not 2). And 11 TR intervals spans 27.5
seconds (11*2.5). So a stim_times option might read:

-stim_times 1 stimes.01.auditory.times.1D 'TENT(0,27.5,12)'

- rick