Extinction dynamics of spiral defect chaos

Area of Science:

• Complex Systems
• Statistical Physics
• Computational Biology

Background:

• Spatially extended excitable systems can display spiral defect chaos (SDC), characterized by continuous formation and disappearance of spiral waves.
• Simulating SDC termination in large systems is computationally intensive.
• Cardiac fibrillation involves disorganized electrical activity with fragmenting spiral waves, motivating research into SDC dynamics.

Purpose of the Study:

• To develop a computationally efficient method for predicting the mean episode duration of SDC.
• To investigate the relationship between system size and SDC episode duration.
• To apply techniques from statistical physics to model complex dynamical states in excitable systems.

Main Methods:

• Modeling the number of spiral waves as a stochastic population using a birth-death equation.
• Employing statistical physics techniques to derive the mean episode duration of SDC.
• Utilizing generic models of cardiac electrophysiology.

Main Results:

• The mean episode duration of SDC can be computed in minimal computational time.
• SDC episode duration exhibits an exponential dependence on the domain size.
• The developed approach provides efficient and accurate predictions for SDC mean episode duration.

Conclusions:

• A novel statistical physics approach enables efficient and accurate prediction of SDC termination.
• The findings offer insights into the dynamics of spiral waves in excitable media, relevant to cardiac fibrillation.
• This method can be extended to more complex geometries and biological models for improved understanding of cardiac arrhythmias.