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3D Hybrid Cellular Automata for Cardiac Electrophysiology: A Concept Study

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Computational Methods in Systems Biology (CMSB 2023)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 14137))

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Abstract

A heartbeat is the emerging collective behavior of billions of cells. However, if this synchronization fails, lethal arrhythmias can appear. Mathematical and computational models offer an ethical alternative to in-vivo analyses of cardiac electrophysiological properties. However, the inherent multiscale complexity of the underlying nonlinear dynamics still limits model applicability and predictability. In previous contributions, we implemented a unidirectional Hybrid Cellular Automata (HCA) model reproducing cardiac cell cables and introducing the concept of a statistically distributed cell-cell resistance. Here, we generalize the theoretical framework by considering a bidirectional coupling and simulate physiological and pathological conditions in three-dimensional domains. The work compares two HCA approaches reproducing critical spatiotemporal phenomena and contrasts them with well-established model formulations. We discuss the limits and applicability of discrete vs. continuum approaches in view of improved numerical performances.

This work has been supported by the Doctoral College Resilient Embedded Systems, which is run jointly by the TU Wien’s Faculty of Informatics and the UAS Technikum Wien.

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Authors and Affiliations

  1. Department Life Science Engineering, UAS Technikum Wien, Vienna, Austria

    Lilly Maria Treml

  2. Institute of Computer Engineering, TU Wien, Vienna, Austria

    Lilly Maria Treml

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  1. Lilly Maria Treml
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Correspondence to Lilly Maria Treml .

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Editors and Affiliations

  1. University of Luxembourg, Esch-sur-Alzette, Luxembourg

    Jun Pang

  2. Inria Lille, Villeneuve d’Ascq, France

    Joachim Niehren

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Treml, L.M. (2023). 3D Hybrid Cellular Automata for Cardiac Electrophysiology: A Concept Study. In: Pang, J., Niehren, J. (eds) Computational Methods in Systems Biology. CMSB 2023. Lecture Notes in Computer Science(), vol 14137. Springer, Cham. https://doi.org/10.1007/978-3-031-42697-1_15

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  • DOI: https://doi.org/10.1007/978-3-031-42697-1_15

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