Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Chaotic behavior in excitable systems.

A V Holden1, M J Lab

  • 1Centre for Nonlinear Studies, University of Leeds, England.

Annals of the New York Academy of Sciences
|January 1, 1990
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A simple adaptation of a handheld ECG recorder to obtain chest lead equivalents.

Journal of electrocardiology·2020
Same author

Effects of shear flows on nonlinear waves in excitable media.

Journal of biological physics·2013
Same author

Towards a computational reconstruction of the electrodynamics of premature and full term human labour.

Progress in biophysics and molecular biology·2011
Same author

Stochastic vagal modulation of cardiac pacemaking may lead to erroneous identification of cardiac "chaos".

Chaos (Woodbury, N.Y.)·2009
Same author

Velocity and stability of solitary planar travelling wave solutions of intracellular [Ca]2+.

Bulletin of mathematical biology·2007
Same author

Computational evaluation of the roles of Na+ current, iNa, and cell death in cardiac pacemaking and driving.

American journal of physiology. Heart and circulatory physiology·2006
Same journal

Multiomics Profiling During Autoimmune Demyelination Highlights a Complex Regulatory Role for Ataxin-1 in B Cells.

Annals of the New York Academy of Sciences·2026
Same journal

Global Trends in Light Pollution and Their Relationship With Socioeconomic Factors.

Annals of the New York Academy of Sciences·2026
Same journal

Wired for Corruption: Inter-Brain Synchrony Encodes Bribery-Related Value Information and Predicts Bribery Agreement.

Annals of the New York Academy of Sciences·2026
Same journal

LM-YOLO: A Lightweight Multi-Scale Enhanced Model for Forest Smoke Detection Using Unmanned Aerial Vehicles.

Annals of the New York Academy of Sciences·2026
Same journal

Polyrhythm Perception and Production: A Scoping Review.

Annals of the New York Academy of Sciences·2026
Same journal

DARTS-CNN-BiLSTM: Intelligent Fault Diagnosis for Computer Numerical Control Machine Tool Feed System.

Annals of the New York Academy of Sciences·2026
See all related articles

This study focuses on biophysically accurate cardiac excitation systems, emphasizing the need for quantitative answers in complex models. Combining experimental data with advanced computational analysis offers a promising path for understanding cardiac tissue dynamics.

Area of Science:

  • Computational biology
  • Biophysics
  • Cardiac electrophysiology

Background:

  • Cardiac excitation systems require biophysically accurate models derived from experimental data.
  • These models are often complex, high-order, and subject to ongoing updates from new experimental findings.
  • Accurate quantitative answers are crucial for understanding biophysically relevant problems in cardiac tissue.

Purpose of the Study:

  • To explore advanced computational methods for analyzing complex dynamics in cardiac tissue models.
  • To integrate experimental data with theoretical analysis for a more comprehensive understanding.
  • To propose an expert system approach for investigating cardiac excitation dynamics.

Main Methods:

  • Utilizing experimentally derived, high-order excitation equations for cardiac tissue.

Related Experiment Videos

  • Employing numerical methods and computer algorithms for model analysis.
  • Leveraging path tracking procedures (e.g., AUTO, PATH) for dynamical systems analysis.

    • Main Results:

    • Highlighting the importance of quantitative analysis in biophysical modeling.
    • Demonstrating the trend towards computer-algorithmic representations of models and analysis methods.
    • Identifying the potential of combining voltage clamp data with bifurcation and singularity theory.

    Conclusions:

    • Suggests combining model formulation from voltage clamp data with dynamical systems analysis.
    • Proposes the development of an expert system for investigating complex dynamics in cardiac models.
    • Emphasizes the integration of experimental data and theoretical analysis for advancing cardiac electrophysiology research.