2014/10/31 by Hiroshi Ashikaga, José Aguilar-Rodríguez, Shai Gorsky +6 · 13 citations
Biochemistry, Genetics and Molecular Biology · Mathematics · Medicine · Neuroscience · Physics and Astronomy · #Artificial intelligence #Cardiac electrophysiology and arrhythmias #Cardiology #Computer network #Computer science #Electrocardiography #Entropy (arrow of time) #Heartbeat #Information theory #Mathematics #Medicine #Mutual information #Neural dynamics and brain function #Physics #Reentry #Statistics #q-bio.QM #q-bio.TO #stochastic dynamics and bifurcation
paper · pdf · doi:10.1098/rsif.2014.1201
published in Journal of The Royal Society Interface 12(105), 20141201 (Royal Society) · 26 pages (including Appendix), 6 figures, 8 videos (not uploaded due to size limitation)
arxiv created 2014/10/31 · openalex publication_date 2015/03/04 · arxiv updated 2015/03/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Electrical communication between cardiomyocytes can be perturbed during arrhythmia, but these perturbations are not captured by conventional electrocardiographic metrics. We developed a theoretical framework to quantify electrical communication using information theory metrics in two-dimensional cell lattice models of cardiac excitation propagation. The time series generated by each cell was coarse-grained to 1 when excited or 0 when resting. The Shannon entropy for each cell was calculated from the time series during four clinically important heart rhythms: normal heartbeat, anatomical reentry, spiral reentry and multiple reentry. We also used mutual information to perform spatial profiling of communication during these cardiac arrhythmias. We found that information sharing between cells was spatially heterogeneous. In addition, cardiac arrhythmia significantly impacted information sharing within the heart. Entropy localized the path of the drifting core of spiral reentry, which could be an optimal target of therapeutic ablation. We conclude that information theory metrics can quantitatively assess electrical communication among cardiomyocytes. The traditional concept of the heart as a functional syncytium sharing electrical information cannot predict altered entropy and information sharing during complex arrhythmia. Information theory metrics may find clinical application in the identification of rhythm-specific treatments which are currently unmet by traditional electrocardiographic techniques.