Inter-scale information flow as a surrogate for downward causation that maintains spiral waves

Area of Science:

• Computational biology
• Cardiac electrophysiology
• Complex systems analysis

Background:

• Rotors are hypothesized to maintain spiral waves, the mechanism behind human atrial fibrillation (AF).
• The causal link between rotors and spiral wave maintenance remains unclear.
• Investigating downward causation from macro-scale spiral wave behavior to micro-scale cardiac components is crucial.

Purpose of the Study:

• To quantify inter-scale information flow as a surrogate for downward causation in cardiac spiral wave systems.
• To determine the relationship between rotors and downward causation in a numerical cardiac model.
• To assess the role of rotors as the causal mechanism maintaining spiral waves in AF.

Main Methods:

• Developed a numerical cardiac model simulating spiral waves.
• Employed renormalization group methods to generate multi-scale system descriptions.
• Utilized transfer entropy to quantify inter-scale information flow (upward and downward).

Main Results:

• Transfer entropy successfully quantified inter-scale information flow.
• No synergistic effects were observed between transfer entropy and intrinsic transfer entropy.
• Inter-scale information flow decreased with increasing macro-scale system description.
• Downward information flow correlated with rotor number, but not monotonically.

Conclusions:

• The study's findings contradict the rotor theory as the sole causal mechanism for spiral wave maintenance in AF.
• Downward causation is not directly proportional to the number of rotors.
• This challenges clinical strategies targeting rotors for AF elimination and may explain conflicting study results.