Simulations of real systems make it possible to test “what if” questions, and compare the results with what did happen. For example, I am working on a study in which a stimulus pulse turns on and off while a spiral wave rotates about an obstacle. We can ask, “What happened to the spiral wave following application of a stimulus pulse?” The answer depends on many factors. The image below shows the results of an experiment that tests this question:
It’s hard to say what happened to the wave. We see recovery, and then eventually activation. We might expect that the additional current supplied by the pulse (green, units not shown) would lead to an earlier activation. How can we say? What if we re-run the same simulation, but do not apply a stimulus pulse?
On inspection, pulse application postponed activation (in the red trace) by extending the duration of the wave and thus, the refractory period. Without the “what-if” data (black) for comparison, the effect of the stimulus pulse seemed less clear.
I give here only one example, but this concept applies to simulations in general. Deterministic simulations have the advantage of perfect repeatability, something much sought after but difficult to achieve in experimental studies.
