This project is focused on developing a """"""""bottom-up"""""""" view of scalability across levels of biological organization from cells to tissue. For this we focus on how myocytes interact with one another to give rise to the electrical activities observed in heart muscle, particularly the pathological activities known as arrhythmias. The mechanical function of the heart is controlled by interactions between electrical and chemical signaling systems. In the simplest representation, electrical excitation in each heart cell leads to an increase in intracellular calcium concentration ([Ca2+]i), and contraction results from Ca2+ ions binding to myofilaments. However, changes in [Ca2+]i can influence the ionic currents responsible for excitation and thereby alter the electrical signal. Moreover, an optimal sequence of contraction at the organ level requires not only signaling within cells but also the effective transmission of signals between cells. Thus, the beating of the heart depends crucially on regulatory interactions and feedback loops, the common themes of the NYCSB. Because pathologies such as ischemia and heart failure are associated with disruptions in the coupling between electrical and Ca2+ signals, a better characterization of these loops at the cellular and tissue levels will improve our understanding of heart disease and suggest novel targets for therapies. Computational modeling has long served as a valuable tool for understanding cardiac physiology at various spatial scales. Generally, however, models built to simulate physically larger domains have contained less biophysical detail than those that have examined local phenomena, primarily because limited computational power makes detailed simulations at large spatial scales impossible. However, decisions about which mechanistic details to sacrifice when moving to a larger spatial scale have largely been made on an ad hoc, case-by-case basis. In this project we will develop and refine methods for simplifying computational models to provide for better synthesis of quantitative physiology from the cellular to the tissue level.
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