The research program of this faculty early career development (CAREER) project is to develop a comprehensive computation and analysis framework for system-level understanding of nonlinear dynamics of heart rhythm disorders that lead to fatal cardiac diseases such as ventricular fibrillation and atrial fibrillation. The specific research objectives of this project include: 1) developing simplified models to accurately describe the dynamics of cardiac myocytes; 2) developing multiscale computational methods to study dynamics of extended cardiac tissue; and 3) developing system-level understanding of cardiac arrhythmias using theoretical analysis and numerical simulation. This research aims to impact the diagnosis and treatment of cardiac arrhythmias. Ventricular fibrillation induces sudden cardiac death, a leading cause of death in the industrialized world. Sudden cardiac death kills more than 350,000 people each year in the United States. Atrial fibrillation is the leading cause of stroke, which will affect one-fifth of Americans over 65. Improved understanding of cardiac dynamics gained from this research may eventually have a broader social impact through its medical implications.
The proposed research activities will also support new cross-disciplinary collaborations in the areas of biomedical engineering, life science, and mathematics. Oscillatory and rhythmic phenomena are common in many biological processes, such as circadian cycle, metabolism, and brain activity. Because of their nonlinear, multiscale complexities, these systems defy understanding based on the conventional reductionist's approach, in which one attempts to understand a system's behavior by putting together all the constituent pieces that have been examined separately. The computational and analytical methods developed in this project provide useful tools to advance system-level understanding of these nonlinear processes. The education plan of this project aspires to train the next generation of scientists who bring nonlinear thinking into biomedical research. College students and graduates are not familiar with nonlinear phenomena and their mathematical representations. The lack of knowledge in nonlinear analysis leaves the students unprepared for real-world problems and nonlinear thinking inherent in biomedical research. Various aspects of the proposed work will be used to enhance graduate and undergraduate education in nonlinear dynamics in biological systems. An outreach program will be developed to expose K-12 students to the excitement and importance of mathematical modeling for biomedical research. In addition, the research will be used to promote higher retention rates among engineering freshmen and underrepresented groups.
