Hi Laura,

A basic question: assuming you start each run with
the fixation cross, would it be fair to say those
fixations come AFTER each stimulus (as an ISI),
rather than before? make_random_timing.py is set
up to have rest events attached to stimulus events,
where the rest comes after the stimulus.

It should not really matter, but that is the design
of the timing.

With the old form of make_random_timing.py (which
is used in the @stim_analyze example), you can set a
min and max limits on the ISIs, but the distribution
of such events is not fantastic. The newer usage does
well with that (perhaps making it more complicated to
use). See make_random_timing.py -help_advanced .


Getting to your questions:

1) It is difficult to disentangle the video event
from the 2s response, since there is no jitter
between them. You can model them separately, but
the response betas will be noisy, as they fight
with the video events.

In areas of the brain that respond to only the video
or only the response, it might work out okay. But
especially if the response is not really a 2s event,
but the subject is given 2s to do something, that may
or may not really take that long, then modeling them
separately might not work well.


2) Yes, though the distribution of ISI in the older
version isn't as smooth as that from the newer one
(advanced).

3) The 6 extra regressors per run are polort drift
terms. Since each run is 690s, 5th polynomials are
used to model the drift, which include 6 terms.

The x-axis is time points. 690s/2s(TR) = 345, +1
gives 346 time points per run.

4) Random numbers on a computer are never quite
random, as they are generated from some algorithm,
usually based on very large numbers (for example,
they might use 1024 bits (probably old now) or
about 300 digits), which are then reduced to the
range a user wants.

The seed is an initial number in the algorithm.
After that, the same sequence of pseudo-random
numbers should come out. This helps us to test
such software.

Anyway, the seeds are not so necessary here, but
with the seed and the MRT.py command, you can
reproduce the same output. It is more useful in
regression testing.

- rick



Edited 1 time(s). Last edit at 05/14/2018 10:13AM by rick reynolds.