Comparison of spiral waves in simplified cardiac tissue models

Cover Page

Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription or Fee Access

Abstract

Spiral waves of electrical activation in cardiac tissue can lead to life-threatening arrhythmias; therefore, understanding the mechanisms underlying the formation and propagation of these spiral waves is of great interest in cardiac dynamics. In this study, we conduct a comparative analysis of spiral waves using two simplified component models for cardiac tissue (a) the Panfilov model and (b) the Aliev-Panfilov model, by varying the parameters that govern excitability and recovery in both models. From our numerical studies, we observe states of (i) a periodic spiral, (ii) a quasi-periodic spiral, and (iii) spiral turbulence in both models, depending on the parameters. Our systematic study reveals that the Panfilov model exhibits conduction velocity restitution behavior and spiral transition sequences that closely resemble those observed in biophysical models; thus, it is better suited for studying wave dynamics in cardiac tissue compared to the Aliev-Panfilov model, providing an alternative to computationally expensive cardiac tissue models.

About the authors

S. Mohanty

International Institute of Information Technology (IIIT) Bhubaneswar

Email: aloknayak@iiit-bh.ac.in
Bhubaneswar, India

D. Prusty

International Institute of Information Technology (IIIT) Bhubaneswar

Author for correspondence.
Email: aloknayak@iiit-bh.ac.in
Bhubaneswar, India

A. R Nayak

International Institute of Information Technology (IIIT) Bhubaneswar

Email: aloknayak@iiit-bh.ac.in
Bhubaneswar, India

References

  1. S. Sawai, P. A. Thomason, and E. C. Cox, Nature 433, 323 (2005).
  2. J. Lechleiter, S. Girard, E. Peralta, and D. Clapham, Science 252, 123 (1991).
  3. Y. Yu, L. M. Santos, L. A. Mattiace, M. L. Costa, L. C. Ferreira, K. Benabou, A. H. Kim, J. Abrahams, M. V. Bennett, and R. Rozental, Proceedings of the National Academy of Sciences 109, 2585 (2012).
  4. X. Huang, W. C. Troy, Q. Yang, H. Ma, C. R. Laing, S. J. Schiff, and J.-Y. Wu, J. Neurosci. 24, 9897 (2004).
  5. S. Alonso, M. B¨ar, and B. Echebarria, Reports on Progress in Physics 79, 096601 (2016).
  6. F. H. Fenton, E. M. Cherry, H. M. Hastings, and S. J. Evans, Chaos: An Interdisciplinary Journal of Nonlinear Science 12, 852 (2002).
  7. A. Panfilov and P. Hogeweg, Phys. Lett. A 176, 295 (1993).
  8. R. R. Aliev and A. V. Panfilov, Chaos, Solitons & Fractals 7, 293 (1996).
  9. A. V. Panfilov, Chaos: An Interdisciplinary Journal of Nonlinear Science 8, 57 (1998).
  10. T. Shajahan, S. Sinha, and R. Pandit, Int. J. Mod. Phys. B 17, 5645 (2003).
  11. A. Panfilov, Phys. Rev. Lett. 88, 118101 (2002).
  12. K. H. ten Tusscher and A. V. Panfilov, Multiscale Modeling & Simulation 3, 265 (2005).
  13. A. Panfilov, S. C. Mu¨ller, V. S. Zykov, and J. P. Keener, Phys. Rev. E 61, 4644 (2000).
  14. Z. Qu, F. Xie, A. Garfinkel, and J. N. Weiss, Annals of Biomedical Engineering 28, 755 (2000).
  15. T. Shajahan, A. R. Nayak, and R. Pandit, PLoS One 4, e4738 (2009).
  16. K. Rajany, A. R. Nayak, R. Majumder, and R. Pandit, Physics Open 13, 100120 (2022).

Supplementary files

Supplementary Files
Action
1. JATS XML

Copyright (c) 2025 Russian Academy of Sciences