Cardiac electrophysiology is the study of electrical signaling in the heart. We use a variety of computational modeling approaches to study how electrical signaling in cardiac cells becomes irregular and triggers arrhythmias. Using detailed physiological models, we simulate activity of action potentials, calcium transients, ion channels, and intracellular signaling molecules to study their responses in irregular rhythms, such as cardiac alternans, and in cells with mutations associated with disease, such as long QT (LQT) syndrome. We are interested in many different aspects of cardiac electrophysiology regulation, including intercellular nanodomain signaling, ephaptic coupling, intracellular calcium handling, and stochastic calcium release.
Mechanotransduction and extracellular matrix signaling
Mechanical interactions between cells and with their surrounding environment play a key role in regulating cell signaling in development, in healthy tissue and in diseases, such as cancer. We use computational models to study how cells sense and respond to these mechanical cues. In particular, we are interested in how cells assemble, interact with, and are regulated by the extracellular matrix (ECM), a web of proteins that provide structural support for cells in tissues. Using detailed biophysical models, we simulate the dynamics of ECM integrin binding, mechanical stretching, and transduction of acto-myosin generated forces to the surrounding substrate. We are interested in how these mechanical interactions regulate inter- and intracellular signaling, including fibrotic signaling pathways.
Multi-time scale dynamics and fractional-order models
Physiological systems evolve over a wide range of time scales - from sub-millisecond molecular interactions to hours- and days-long protein remodeling. Computational models typically use first-order differential equation models to represent processes with well-defined characteristic time scales, which makes it difficult to simulate multi-time scale behavior. Fractional-order differential equation models are a new tool that can be used to simulate power law responses, without a single time scale. We use fractional-order models to simulate electrical activity in cardiac cells and neurons to understand how multiple time scales introduce short-term memory effects. We study how fractional-order models can influence signaling within individual cells and multicellular coupling, e.g., in cardiac tissue or neural networks, and how these memory effects regulate electrical dynamics in healthy and pathological conditions.