Causal Unit of Rotors in a Cardiac System

TL;DR

This paper investigates the causal structure of rotors in cardiac systems during atrial fibrillation using a multiscale information-theoretic approach, identifying a scale where causal influence peaks, which may inform targeted therapies.

Contribution

It introduces a novel multiscale analysis of cardiac rotors using causal emergence and renormalization, linking microscopic activity to macroscopic causal power.

Findings

Peak causal information occurs at a specific spatiotemporal scale.

Number of rotors correlates positively with causal emergence.

Identified causal units could serve as therapeutic targets.

Abstract

The heart exhibits complex systems behaviors during atrial fibrillation (AF), where the macroscopic collective behavior of the heart causes the microscopic behavior. However, the relationship between the downward causation and scale is nonlinear. We describe rotors in multiple spatiotemporal scales by generating a renormalization group from a numerical model of cardiac excitation, and evaluate the causal architecture of the system by quantifying causal emergence. Causal emergence is an information-theoretic metric that quantifies emergence or reduction between microscopic and macroscopic behaviors of a system by evaluating effective information at each spatiotemporal scale. We find that there is a spatiotemporal scale at which effective information peaks in the cardiac system with rotors. There is a positive correlation between the number of rotors and causal emergence up to the scale of peak causation. In conclusion, one can coarse-grain the cardiac system with rotors to identify a macroscopic scale at which the causal power reaches the maximum. This scale of peak causation should correspond to that of the AF driver, where networks of cardiomyocytes serve as the causal units. Those causal units, if identified, can be reasonable therapeutic targets of clinical intervention to cure AF.