Courses I teach or taught

Please note this list is not complete.

Mathematical Modeling and Simulation

Contents

The role of mathematical modeling in science; genesis of the cardiac action potential; propagation of activation in tissue; simulation of measurable signals: electrograms, monophasic action potentials, the electrocardiogram; simulation of arrhythmia; electromechanical coupling and mechano-electric feedback (briefly).

The philosophy of modeling life science

Contents

What is modeling and how do numerical models compare to other types of models? What role does numerical modeling play in science, in engineering, in diagnosis and treatment of patients, and in health policy? Can it replace animal models or experimentation on patients? Who makes models and who uses them? Forward versus inverse models. Is imaging the same as inverse modeling? Models and Big Data.

Computational Medicine

Objectives

Biological systems are typically very complex. To understand such systems, sophisticated computer modeling techniques and high-performance computing resources are often necessary. To apply such techniques, researchers in medicine and biology rely on collaboration with computational scientists. The purpose of this course is to provide students of computational science with an overview of numerical applications in medicine and biology. The course offers an overview of the vast biomedical field and treats many of the important application domains of numerical science in biomedicine. Three topics will be highlighted and studied with numerical simulations. Special attention is given to topics on which the ICS is at the forefront of scientific progress.

Contents

Biology of the living cell. Electrically active cells in the brain and in the heart. Ion channels. The Hodgkin-Huxley model and its offspring. The electrocardiogram, electro-encefalogram, electro-retinogram, and other applications of electrical fields in the body. Propagating electrical activation in the heart, nerves, and in other organs. Neural networks and neuronal networks. Activation-contraction coupling in muscle. Cardiac contraction. Fluid dynamics of the blood. Computed Tomography. Magnetic Resonance Imaging. Image segmentation and organ reconstruction for computational models. Bone mechanics. Modeling of growth. Branching structures. Molecular dynamics. Inverse problems. Radiotherapy. Population dynamics.

Computational Medicine Project

Numerical simulation plays an important role in the development of biological and medical knowledge as well as in the analysis of medical images and signals. An overview of research in these areas has been given in the second-semester course Computational Medicine. This course follows up and consists of a research project that is carried out individually and supervised by a TA. A choice of projects will be offered within the research areas that have been treated in the Computational Medicine course. Students will prepare a final report and give a presentation of their work at the end of the semester.

Computational Electrophysiology of the Heart

This was a single 2-hour lecture given in an introductory course for bachelor students.

Objectives

Electrically active cells are involved in all rapid actions in biological systems. They are responsible for thinking in the brain, signal transport in nerves, contraction of muscle, vision, hearing, and many other functions. The heart combines aspects of nerve and muscle: its electrically active cells transport electrical impulses, regulate them, and act on them by contracting. This intricate mechanism is responsible for the coordinated contraction of the heart muscle which allows it to pump blood efficiently. Cardiac electrophysiology is the scientific discipline that studies these complex phenomena. It is one of the areas within the life sciences that have most clearly benefited from computational approaches. Computational studies in the 1950s have proven that the dynamics of ion channels in the cell membrane allow cells to generate periodic electrical pulses. Over and over, improved models of the dynamics of the cell membrane have hinted at the existence of additional types of ion chanels, which have subsequently been identified and isolated, and have allowed us to understand how the channels interact. Using high-performance computing systems we can now use numerical techniques to predict how a change in a single ion channel will affect the behaviour of the heart and measurable signals such as the electrocardiogram. In this lecture I will outline the basic mechanisms and the contribution of numerical science to this intrigueing field.

Courses at Maastricht University...

Courses at Université de Montréal...