Prokaryotic voltage-gated sodium channels are more effective than endogenous Na1.5 channels in rescuing cardiac action potential conduction: an in silico study.

Methods to augment Na current in cardiomyocytes hold potential for the treatment of various cardiac arrhythmias involving conduction slowing. Because the gene coding cardiac Na channel (Na1.5) is too large to fit in a single adeno-associated virus (AAV) vector, new gene therapies are being developed to enhance endogenous Na1.

Rule-based definition of muscle bundles in patient-specific models of the left atrium.

Atrial fibrillation (AF) is the most common arrhythmia encountered clinically, and as the population ages, its prevalence is increasing. Although the CHADS VASc score is the most used risk-stratification system for stroke risk in AF, it lacks personalization. Patient-specific computer models of the atria can facilitate personalized risk assessment and treatment planning.

Composite Backward Differentiation Formula for the Bidomain Equations.

The bidomain equations have been widely used to model the electrical activity of cardiac tissue. While it is well-known that implicit methods have much better stability than explicit methods, implicit methods usually require the solution of a very large nonlinear system of equations at each timestep which is computationally prohibitive. In this work, we present two fully implicit time integration methods for the bidomain equations: the backward Euler method and a second-order one-step two-stage composite backward differentiation formula (CBDF2) which is an L-stable time integration method.

Excitation properties of computational models of unmyelinated peripheral axons.

Biophysically based computational models of nerve fibers are important tools for designing electrical stimulation therapies, investigating drugs that affect ion channels, and studying diseases that affect neurons. Although peripheral nerves are primarily composed of unmyelinated axons (i.e.

Modeling the effects of sinusoidal stimulation and synaptic plasticity on linked neural oscillators.

The brain exhibits intrinsic oscillatory behavior, which plays a vital role in communication and information processing. Abnormalities in brain rhythms have been linked to numerous disorders, including depression and schizophrenia. Rhythmic electrical stimulation (e.

Rhythmic modulation of thalamic oscillations depends on intrinsic cellular dynamics.

Objective: Rhythmic brain stimulation has emerged as a powerful tool to modulate cognition and to target pathological oscillations related to neurological and psychiatric disorders. However, we lack a systematic understanding of how periodic stimulation interacts with endogenous neural activity as a function of the brain state and target.

Approach: To address this critical issue, we applied periodic stimulation to a unified biophysical thalamic network model that generates multiple distinct oscillations, and examined thoroughly the impact of rhythmic stimulation on different oscillatory states.

Muscle Thickness and Curvature Influence Atrial Conduction Velocities.

Electroanatomical mapping is currently used to provide clinicians with information about the electrophysiological state of the heart and to guide interventions like ablation. These maps can be used to identify ectopic triggers of an arrhythmia such as atrial fibrillation (AF) or changes in the conduction velocity (CV) that have been associated with poor cell to cell coupling or fibrosis. Unfortunately, many factors are known to affect CV, including membrane excitability, pacing rate, wavefront curvature, and bath loading, making interpretation challenging.

Microheterogeneity-induced conduction slowing and wavefront collisions govern macroscopic conduction behavior: A computational and experimental study.

The incidence of cardiac arrhythmias is known to be associated with tissue heterogeneities including fibrosis. However, the impact of microscopic structural heterogeneities on conduction in excitable tissues remains poorly understood. In this study, we investigated how acellular microheterogeneities affect macroscopic conduction under conditions of normal and reduced excitability by utilizing a novel platform of paired in vitro and in silico studies to examine the mechanisms of conduction.

Unified thalamic model generates multiple distinct oscillations with state-dependent entrainment by stimulation.

The thalamus plays a critical role in the genesis of thalamocortical oscillations, yet the underlying mechanisms remain elusive. To understand whether the isolated thalamus can generate multiple distinct oscillations, we developed a biophysical thalamic model to test the hypothesis that generation of and transition between distinct thalamic oscillations can be explained as a function of neuromodulation by acetylcholine (ACh) and norepinephrine (NE) and afferent synaptic excitation. Indeed, the model exhibited four distinct thalamic rhythms (delta, sleep spindle, alpha and gamma oscillations) that span the physiological states corresponding to different arousal levels from deep sleep to focused attention.

Modeling dynamics in diseased cardiac tissue: Impact of model choice.

Cardiac arrhythmias have been traditionally simulated using continuous models that assume tissue homogeneity and use a relatively large spatial discretization. However, it is believed that the tissue fibrosis and collagen deposition, which occur on a micron-level, are critical factors in arrhythmogenesis in diseased tissues. Consequently, it remains unclear how well continuous models, which use averaged electrical properties, are able to accurately capture complex conduction behaviors such as re-entry in fibrotic tissues.

Electrical stimulation of gut motility guided by an in silico model.

Objective: Neuromodulation of the central and peripheral nervous systems is becoming increasingly important for treating a diverse set of diseases-ranging from Parkinson's Disease and epilepsy to chronic pain. However, neuromodulation of the gastrointestinal (GI) tract has achieved relatively limited success in treating functional GI disorders, which affect a significant population, because the effects of stimulation on the enteric nervous system (ENS) and gut motility are not well understood. Here we develop an integrated neuromechanical model of the ENS and assess neurostimulation strategies for enhancing gut motility, validated by in vivo experiments.

Modeling an Excitable Biosynthetic Tissue with Inherent Variability for Paired Computational-Experimental Studies.

To understand how excitable tissues give rise to arrhythmias, it is crucially necessary to understand the electrical dynamics of cells in the context of their environment. Multicellular monolayer cultures have proven useful for investigating arrhythmias and other conduction anomalies, and because of their relatively simple structure, these constructs lend themselves to paired computational studies that often help elucidate mechanisms of the observed behavior. However, tissue cultures of cardiomyocyte monolayers currently require the use of neonatal cells with ionic properties that change rapidly during development and have thus been poorly characterized and modeled to date.

Adaptive Mesh Refinement and Adaptive Time Integration for Electrical Wave Propagation on the Purkinje System.

A both space and time adaptive algorithm is presented for simulating electrical wave propagation in the Purkinje system of the heart. The equations governing the distribution of electric potential over the system are solved in time with the method of lines. At each timestep, by an operator splitting technique, the space-dependent but linear diffusion part and the nonlinear but space-independent reactions part in the partial differential equations are integrated separately with implicit schemes, which have better stability and allow larger timesteps than explicit ones.

A brief history of tissue models for cardiac electrophysiology.

The last four decades have produced a number of significant advances in the developments of computer models to simulate and investigate the electrical activity of cardiac tissue. The tissue descriptions that underlie these simulations have been built from a combination of clever insight and careful comparison with measured data at multiple scales. Tissue models have not only led to greater insights into the mechanisms of life-threatening arrhythmias but have been used to engineer new therapies to treat the consequences of cardiac disease.

A microstructural model of reentry arising from focal breakthrough at sites of source-load mismatch in a central region of slow conduction.

Regions of cardiac tissue that have a combination of focal activity and poor, heterogeneous gap junction coupling are often considered to be arrhythmogenic; however, the relationship between the properties of the cardiac microstructure and patterns of abnormal propagation is not well understood. The objective of this study was to investigate the effect of microstructure on the initiation of reentry from focal stimulation inside a poorly coupled region embedded in more well-coupled tissue. Two-dimensional discrete computer models of ventricular monolayers (1 × 1 cm) were randomly generated to represent heterogeneity in the cardiac microstructure.

Electromagnetohydrodynamic modeling of Lorentz effect imaging.

Lorentz Effect Imaging (LEI) is an MRI technique that has been proposed for direct imaging of neuronal activity. While promising results have been obtained in phantoms and in the human median nerve in vivo, its contrast mechanism is still not fully understood. In this paper, computational model simulations were used to investigate how electromagnetohydrodynamics (EMHD) may explain the LEI contrast.

Microscopic variations in interstitial and intracellular structure modulate the distribution of conduction delays and block in cardiac tissue with source-load mismatch.

Aims: Reentrant activity in the heart is often correlated with heterogeneity in both the intracellular structure and the interstitial structure surrounding cells; however, the combined effect of cardiac microstructure and interstitial resistivity in regions of source-load mismatch is largely unknown. The aim of this study was to investigate how microstructural variations in cell arrangement and increased interstitial resistivity influence the spatial distribution of conduction delays and block in poorly coupled regions of tissue.

Methods And Results: Two-dimensional 0.

Emergent bursting and synchrony in computer simulations of neuronal cultures.

Experimental studies of neuronal cultures have revealed a wide variety of spiking network activity ranging from sparse, asynchronous firing to distinct, network-wide synchronous bursting. However, the functional mechanisms driving these observed firing patterns are not well understood. In this work, we develop an in silico network of cortical neurons based on known features of similar in vitro networks.

A computer model of engineered cardiac monolayers.

Engineered monolayers created using microabrasion and micropatterning methods have provided a simplified in vitro system to study the effects of anisotropy and fiber direction on electrical propagation. Interpreting the behavior in these culture systems has often been performed using classical computer models with continuous properties. However, such models do not account for the effects of random cell shapes, cell orientations, and cleft spaces inherent in these monolayers on the resulting wavefront conduction.

Collision-based spiral acceleration in cardiac media: roles of wavefront curvature and excitable gap.

We have previously shown in experimental cardiac cell monolayers that rapid point pacing can convert basic functional reentry (single spiral) into a stable multiwave spiral that activates the tissue at an accelerated rate. Here, our goal is to further elucidate the biophysical mechanisms of this rate acceleration without the potential confounding effects of microscopic tissue heterogeneities inherent to experimental preparations. We use computer simulations to show that, similar to experimental observations, single spirals can be converted by point stimuli into stable multiwave spirals.

Increased interstitial loading reduces the effect of microstructural variations in cardiac tissue.

Electrical propagation in diseased and aging hearts is strongly influenced by structural changes that occur in both the intracellular and interstitial spaces of cardiac tissue; however, very few studies have investigated how interactions between the two spaces affect propagation at the microscale. In this study, we used one-dimensional microstructural computer models of interconnected ventricular myocytes to systematically investigate how increasing the effective interstitial resistivity (rho(oeff)) influences action potential propagation in fibers with variations in intracellular properties such as cell coupling and cell length. Changes in rho(oeff) were incorporated into a monodomain model using a correction to the intracellular properties that was based on bidomain simulations.

Thresholds for transverse stimulation: fiber bundles in a uniform field.

Cable theory is used to model fibers (neural or muscular) subjected to an extracellular stimulus or activating function along the fiber (longitudinal stimulation). There are cases however, in which activation from fields across a fiber (transverse stimulation) is dominant and the activating function is insufficient to predict the relative stimulus thresholds for cells in a bundle. This work proposes a general method of quantifying transverse extracellular stimulation using ideal cases of long fibers oriented perpendicular to a uniform field (circular cells in a 2-D extracellular domain).

Unscented Kalman filter for brain-machine interfaces.

Brain machine interfaces (BMIs) are devices that convert neural signals into commands to directly control artificial actuators, such as limb prostheses. Previous real-time methods applied to decoding behavioral commands from the activity of populations of neurons have generally relied upon linear models of neural tuning and were limited in the way they used the abundant statistical information contained in the movement profiles of motor tasks. Here, we propose an n-th order unscented Kalman filter which implements two key features: (1) use of a non-linear (quadratic) model of neural tuning which describes neural activity significantly better than commonly-used linear tuning models, and (2) augmentation of the movement state variables with a history of n-1 recent states, which improves prediction of the desired command even before incorporating neural activity information and allows the tuning model to capture relationships between neural activity and movement at multiple time offsets simultaneously.

Genesis of complex fractionated atrial electrograms in zones of slow conduction: a computer model of microfibrosis.

Background: Complex fractionated atrial electrograms are used as potential targets for catheter ablation therapy of atrial fibrillation. Although fibrosis has been associated with the presence of fractionated electrograms, characterizing the substrate through the inspection of electrograms is challenging.

Objective: This study sought to determine how progression of microfibrosis and slow conduction affect electrogram morphology.