Prepace in PSD example

Question

Hi all,

I’m working on the Phase Singularity Distribution experiment from Example 21 (Reentry Induction Protocols). While looking through the induceReentry.py file—specifically the PSD function—I noticed the following parameter settings:

'-prepacing_lats', job.ID + '/LATS.dat', '-prepacing_beats', 100, '-prepacing_bcl', args.PSD_bcl

From my understanding, these parameters seem to control the prepacing phase. Could someone clarify what each of these commands actually does? I wasn’t able to find detailed documentation explaining them.

In particular, does this mean that the tissue will be prepaced for 100 beats at the specified basic cycle length before the PSD protocol runs and the rotor is induced? Or is the intended workflow to run the prepacing protocol separately, save the resulting state, and then use that as the starting point for PSD?

I’m trying to better understand the correct approach for prepacing the tissue, so any clarification would be greatly appreciated. Thank you in advance!

Answer 1

Hey, you can find the documentation of these (and all other parameters) in the manual or on openCARP parameters. If you have read these already, would you mind sharing what was unclear to you and leave some hints on how we can improve the documentation of these parameters to make it more clear? We would appreciate it!

Otherwise, its pretty much what the descriptions says: 

prepacing_lats is the file that contains the activation times used to start the prepacing from on the tissue level.

prepacing_beats defines how many beats are used to prepace the ionic models for a single cell. This state is then saved and applied to the tissue.

prepacing_bcl sets the basic cycle length for the single cell prepacing.

So it's pretty much the same as running single cell experiments in bench using the same number of beats/bcl and then start openCARP tissue simulations using the saved state from bench to initialize the ionic models. Except, that we also use activation times to introduce the phase singularity.

Hope that helps!