Computational Physiology: Simula Summer School 2022

Computational Physiology: Simula Summer School 2022

This is the 13th volume in the Simula SpringerBriefs series and compiles student reports from the 2022 Simula Summer School, which together describe a number of modern approaches to modeling excitable tissue.

The Simula SpringerBriefs on Computing series aims to provide introductions to select areas of research in computing. Each volume aims to provide an introduction to, and overview of, research fields that can otherwise be inaccessible. This is the 13th volume in this series.

Computational Physiology: Simula Summer School 2022 − Student Reports edited by Kimberly J. McCabe is now available for download. This open access volume compiles student reports from the 2022 Simula Summer School in Computational Physiology. Interested readers will find therein a number of modern approaches to modeling excitable tissue. This should provide an overview of several tools available to model subcellular and tissue-level physiology across scales and scientific questions.

Simula Summer School in Computational Physiology

In June through August of 2022, Simula held the eighth annual Summer School in Computational Physiology in collaboration with the University of Oslo (UiO) and the University of California, San Diego (UCSD). The course focuses on modeling excitable tissues, with a special emphasis on cardiac physiology and neuroscience. The majority of the school consists of group research projects conducted by Masters and PhD students from around the world, and advised by scientists at Simula, UiO and UCSD. At the end of the course, each group produces a report that addresses a specific problem of importance in physiology with a succinct summary of the findings. Reports may not necessarily represent new scientific results; rather, they can reproduce or supplement earlier computational studies or experimental findings.

Reports from seven of the summer projects are included as separate chapters. The fields represented include machine learning for the development of constitutive equations (Chapter 1), electromechanical prediction of drug effects in the heart (Chapter 2), ion channel modeling of sex differences in osteoarthritis (Chapter 3), investigating functional heterogeneity in both cardiac and pancreatic beta cells (Chapter 4), investigation of astrocyte-neuron interactions using the EMI model (Chapter 5), the Reynolds-Orr Method for understanding flow instabilities in aneurysms (Chapter 6), and mechanical remodeling of the cardiac right ventricle (Chapter 7). 

Open access

As with all the Simula SpringerBriefs on Computing, this volume is open access under a CC BY 4.0 license and was published by SpringerOpen.

About the editor

Kimberly J. McCabe is a Research Scientist at Simula Research Laboratory and the program director for SUURPh (the Simula UiO UCSD Research and PhD training program), the program that organises the Simula Summer School. Her current research is focused on subcellular modeling of cardiac mechanics and calcium handling, which she conducts primarily in collaboration with partners at the University of California, San Diego.