Overview
- This is a brief text that is accessible for a large audience with a background in computational mathematics
- The text introduces a state-of-the-art approach to simulation of excitable cells
- Software is available for all the models presented in the text
Part of the book series: Simula SpringerBriefs on Computing (SBRIEFSC, volume 7)
Part of the book sub series: Reports on Computational Physiology (RCP)
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About this book
This open access volume presents a novel computational framework for understanding how collections of excitable cells work. The key approach in the text is to model excitable tissue by representing the individual cells constituting the tissue. This is in stark contrast to the common approach where homogenization is used to develop models where the cells are not explicitly present. The approach allows for very detailed analysis of small collections of excitable cells, but computational challenges limit the applicability in the presence of large collections of cells.
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Keywords
Table of contents (7 chapters)
Editors and Affiliations
About the editors
Marie E. Rognes is a research professor at Simula Research Laboratory and a founding member of the Young Academy of Norway. She has over 50 scientific publications and has delivered numerous keynote addresses and invited talks, including a TEDx talk. Her research is primarily focused on mathematical and computational modelling of fluid flow in the brain, and this work has been partially funded by an ERC starting grant.
Bibliographic Information
Book Title: Modeling Excitable Tissue
Book Subtitle: The EMI Framework
Editors: Aslak Tveito, Kent-Andre Mardal, Marie E. Rognes
Series Title: Simula SpringerBriefs on Computing
DOI: https://doi.org/10.1007/978-3-030-61157-6
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s) 2021
Softcover ISBN: 978-3-030-61156-9Published: 31 October 2020
eBook ISBN: 978-3-030-61157-6Published: 30 October 2020
Series ISSN: 2512-1677
Series E-ISSN: 2512-1685
Edition Number: 1
Number of Pages: XVII, 100
Number of Illustrations: 25 illustrations in colour
Topics: Mathematical and Computational Biology, Applications of Mathematics, Mathematical Modeling and Industrial Mathematics