High-Frequency Stimulation of Excitable Cells and Networks

High-frequency (HF) stimulation has been shown to block conduction in excitable cells including neurons and cardiac myocytes. However, the precise mechanisms underlying conduction block are unclear. Using a multi-scale method, the influence of HF stimulation is investigated in the simplified FitzhHugh-Nagumo and biophysically-detailed Hodgkin-Huxley models. In both models, HF stimulation alters the amplitude and frequency of repetitive firing in response to a constant applied current and increases the threshold to evoke a single action potential in response to a brief applied current pulse. Further, the excitable cells cannot evoke a single action potential or fire repetitively above critical values for the HF stimulation amplitude. Analytical expressions for the critical values and thresholds are determined in the FitzHugh-Nagumo model. In the Hodgkin-Huxley model, it is shown that HF stimulation alters the dynamics of ionic current gating, shifting the steady-state activation, inactivation, and time constant curves, suggesting several possible mechanisms for conduction block. Finally, we demonstrate that HF stimulation of a network of neurons reduces the electrical activity firing rate, increases network synchronization, and for a sufficiently large HF stimulation, leads to complete electrical quiescence. In this study, we demonstrate a novel approach to investigate HF stimulation in biophysically-detailed ionic models of excitable cells, demonstrate possible mechanisms for HF stimulation conduction block in neurons, and provide insight into the influence of HF stimulation on neural networks

Analysis of Heterogeneous Cardiac Pacemaker Tissue Models and Traveling Wave Dynamics

The sinoatrial-node (SAN) is a complex heterogeneous tissue that generates a stable rhythm in healthy hearts, yet a general mechanistic explanation for when and how this tissue remains stable is lacking. Although computational and theoretical analyses could elucidate these phenomena, such methods have rarely been used in realistic (large-dimensional) gap-junction coupled heterogeneous pacemaker tissue models. In this study, we adapt a recent model of pacemaker cells (Severi et al. 2012), incorporating biophysical representations of ion channel and intracellular calcium dynamics, to capture physiological features of a heterogeneous population of pacemaker cells, in particular "center" and "peripheral" cells with distinct intrinsic frequencies and action potential morphology. Large-scale simulations of the SAN tissue, represented by a heterogeneous tissue structure of pacemaker cells, exhibit a rich repertoire of behaviors, including complete synchrony, traveling waves of activity originating from periphery to center, and transient traveling waves originating from the center. We use phase reduction methods that do not require fully simulating the large-scale model to capture these observations. Moreover, the phase reduced models accurately predict key properties of the tissue electrical dynamics, including wave frequencies when synchronization occurs, and wave propagation direction in a variety of tissue models. With the reduced phase models, we analyze the relationship between cell distributions and coupling strengths and the resulting transient dynamics. Further, the reduced phase model predicts parameter regimes of irregular electrical dynamics. Thus, we demonstrate that phase reduced oscillator models applied to realistic pacemaker tissue is a useful tool for investigating the spatial-temporal dynamics of cardiac pacemaker activity.Comment: 34 pages, 11 figure

The Influence of Ca2+ Buffers on Free [Ca2+] Fluctuations and the Effective Volume of Ca2+ Microdomains

Intracellular calcium (Ca2+) plays a significant role in many cell signaling pathways, some of which are localized to spatially restricted microdomains. Ca2+ binding proteins (Ca2+ buffers) play an important role in regulating Ca2+ concentration ([Ca2+]). Buffers typically slow [Ca2+] temporal dynamics and increase the effective volume of Ca2+ domains. Because fluctuations in [Oa(2+)] decrease in proportion to the square-root of a domain\u27s physical volume, one might conjecture that buffers decrease [Ca2+] fluctuations and, consequently, mitigate the significance of small domain volume concerning Ca2+ signaling. We test this hypothesis through mathematical and computational analysis of idealized buffer-containing domains and their stochastic dynamics during free Ca2+ influx with passive exchange of both Ca2+ and buffer with bulk concentrations. We derive Langevin equations for the fluctuating dynamics of Ca2+ and buffer and use these stochastic differential equations to determine the magnitude of [Ca2+] fluctuations for different buffer parameters (e.g., dissociation constant and concentration). In marked contrast to expectations based on a naive application of the principle of effective volume as employed in deterministic models of Ca2+ signaling, we find that mobile and rapid buffers typically increase the magnitude of domain [Ca2+] fluctuations during periods of Ca2+ influx, whereas stationary (immobile) Ca2+ buffers do not. Also contrary to expectations, we find that in the absence of Ca2+ influx, buffers influence the temporal characteristics, but not the magnitude, of [Ca2+] fluctuations. We derive an analytical formula describing the influence of rapid Ca2+ buffers on [Ca2+] fluctuations and, importantly, identify the stochastic analog of (deterministic) effective domain volume. Our results demonstrate that Ca2+ buffers alter the dynamics of [Ca2+] fluctuations in a nonintuitive manner. The finding that Ca2+ buffers do not suppress intrinsic domain [Ca2+] fluctuations raises the intriguing question of whether or not [Ca2+] fluctuations are a physiologically significant aspect of local Ca2+ signaling