To date, scientific investigation of order-disorder phase transitions has focused on discovering early warning signs to predict when the transition occurs. However, little attention has been paid to where in the networked dynamical system the phase transition begins. The imminent phase transition may be mitigated or prevented by identifying and modifying the specific components of the system responsible for the initiation of the transition. Here we present an information-theoretic approach to predicting the locations of an order-disorder phase transition from a regular heart rhythm to fibrillation in a cardiac system. We demonstrate the effectiveness of our approach by applying it to numerical simulations of a two-dimensional cardiac system. We show that, by analyzing communication between the components of the system, information-theoretic metrics such as channel capacity, mutual information, and transfer entropy can predict geometrical borders beyond which an order-disorder phase transition from a regular heart rhythm to fibrillation occurs. Importantly, we find that channel capacity and mutual information progressively decline and reach zero at the border of phase transition. This indicates that those information-theoretic metrics can serve as order parameters to describe the macroscopic behavior of the system. Our approach is computationally efficient and is applicable to many complex systems of interest in distinct physical, chemical, and biological disciplines. Our approach could ultimately contribute to an improved therapy of clinical conditions such as sudden cardiac death by identifying potential targets of interventional therapies.
|Original language||English (US)|
|State||Published - Aug 13 2017|
- Cardiac dynamics
- Complex systems
- Information theory
- Phase transition
ASJC Scopus subject areas