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R C Barr

Publications and source records attributed to R C Barr.

At least 19 recordsLinked to original sources
PubMed1992

Propagation model using the DiFrancesco-Noble equations. Comparison to reported experimental results.

Propagation, re-entry and the effects of stimuli within the conduction system can be studied effectively with computer models when the pertinent membrane properties can be represented accurately in mathematical form. To date, no membrane models have been shown to be accurate representations during repolarisation and recovery of excitability, although for the Purkinje membrane the DiFrancesco-Noble (DN) model has become a possibility. The paper examines the DN model, restates its equations and compares simulated waveforms in a number of propagation contexts to experimental measurements reported in the literature. The objective is to determine whether or not the DN model reproduced phenomena such as supernormality, shortening in action potential duration during pacing rate increases, alternation of duration with changes in rhythm, graded responses and 'all-or-none' repolarisation in a quantitatively realistic way, as each of these come from time and space dependencies not directly a part of the ionic current measurements on which the DN model is based. The results show that the DN equations correctly simulate these situations and support the goal of having a model that is broadly applicable to Purkinje tissue, including refractory period properties and response to electrical stimulation.

Action Potentials↗
PubMed1992

Electrophysiological interaction through the interstitial space between adjacent unmyelinated parallel fibers.

The influence of interstitial or extracellular potentials on propagation usually has been ignored, often through assuming these potentials to be insignificantly different from zero, presumably because both measurements and calculations become much more complex when interstitial interactions are included. This study arose primarily from an interest in cardiac muscle, where it has been well established that substantial interstitial potentials occur in tightly packed structures, e.g., tens of millivolts within the ventricular wall. We analyzed the electrophysiological interaction between two adjacent unmyelinated fibers within a restricted extracellular space. Numerical evaluations made use of two linked core-conductor models and Hodgkin-Huxley membrane properties. Changes in transmembrane potentials induced in the second fiber ranged from nonexistent with large intervening volumes to large enough to initiate excitation when fibers were coupled by interstitial currents through a small interstitial space. With equal interstitial and intracellular longitudinal conductivities and close coupling, the interaction was large enough (induced Vm approximately 20 mV peak-to-peak) that action potentials from one fiber initiated excitation in the other, for the 40-microns radius evaluated. With close coupling but no change in structure, propagation velocity in the first fiber varied from 1.66 mm/ms (when both fibers were simultaneously stimulated) to 2.84 mm/ms (when the second fiber remained passive). Although normal propagation through interstitial interaction is unlikely, the magnitudes of the electrotonic interactions were large and may have a substantial modulating effect on function.

Animals↗
PubMed1992

Reflection after delayed excitation in a computer model of a single fiber.

Reflection (reflected reentry) is a case of reentry in a one-dimensional structure, divided into proximal and distal segments, in which tissue excited by a wave front propagating in a forward direction is reexcited by electrical activity coming backward from the original direction of propagation. Cases of reflection have been demonstrated in Purkinje fibers and in ventricular muscle preparations containing multiple fibers. Several mechanisms possibly responsible for reflected reentry have been proposed. However, the difficulty in the interpretation of the experimental results, as well as the limited number of different conditions in which reflection was obtained, has kept open the question about conditions and mechanisms for reflection. We have developed a computer model in which reflection occurs. The model involves a single fiber and uses the DiFrancesco-Noble equations for the Purkinje fiber to model the ionic currents. The results show that reflection is possible in a single fiber and that diastolic depolarization (automaticity) is not a requirement for reflection. Active membrane responses to a just-above-threshold stimulus were important for achieving the necessary time delay. Systematic simulations showed further that reflection occurred only when the right coupling conditions linked a short or long proximal fiber to a short distal segment.

Action Potentials↗
PubMed1991

One-dimensional model of cardiac defibrillation.

The response of a single strand of cardiac cells to a uniform defibrillatory shock assuming steady-state linear conditions is examined. It is argued that the effect of this current is quantitatively described by the induced transmembrane potential even under passive conditions. The characteristics of the single strand are those that would exist if the heart was a system of equivalent parallel pathways from apex to base. It is shown that essentially every cell is both hyperpolarized and depolarised from the shock by an amount proportional to the stimulus intensity and the intercellular junctional resistance. For physiological values of model parameters the evaluated depolarisations are consistent with levels necessary to affect electrophysiological behaviour.

Electric Countershock↗
PubMed1991

Computer simulations of activation in an anatomically based model of the human ventricular conduction system.

Simulations of the electrical activity during excitation were performed in an anatomically based model of the human ventricular conduction system. Each of the 33,000 elements of this model represented a unit bundle of Purkinje or atrioventricular nodal tissue. The Ebihara-Johnson model for sodium defined the active membrane characteristics. Using a combination of new and existing modeling techniques, simulations of excitation were completed in approximately 5 min CPU time on an IBM 3090 at the Cornell National Supercomputer Facility. Activation times at sites in the model were compared to experimental measurements for the excitation of the ventricular myocardium on the endocardial surface. These "literature-based" times were estimated from a number of reported human heart mapping studies. Initially, the times fit poorly. The major factor for the discrepancy was the conduction velocities of the elements, which were a result of the physical and electrical parameters derived from a review of histologic and electrical properties studies. In addition, there was a latency between activation of the system in the left ventricle of the model and that in the right ventricle when compared to the experimental work. When the times were scaled to adjust for the conduction velocity and ventricular latency effects, the match between the simulation and literature-based times was much improved. Quantitative comparison between normalized times resulted in correlation coefficients CCF = 0.76 for the right ventricle and CCF = 0.64 for the left ventricle.

Atrial Function↗
PubMed1990

The construction of an anatomically based model of the human ventricular conduction system.

The ventricular conduction system is a complicated network of specialized muscle cells responsible for the transmission of electrical activity between the atria and the ventricles of the human heart. It has been the focus of numerous electrical and anatomical studies at both the microscopic and macroscopic levels. An understanding of its behavior at both levels is considered important, because it is primarily responsible for the spread of excitation in the ventricles. Previous computer models have been very simple ones that have been primarily adjuncts to models of the ventricles. This paper describes a strategy for the construction of conduction system models which is based on real microscopic and macroscopic features, although the model still is much simpler than reality. The model contains almost 35,000 individual cylindrical elements, each of whose physical dimensions approximate unit bundles of Purkinje and atrioventricular nodal cells. The model, whose physical appearance closely resembles that of the conduction system, was generated from limited anatomical data in less than 2 min CPU time on an IBM 3090 at the Cornell National Supercomputer Facility.

Atrioventricular Node↗
PubMed1988

Adaptive sampling of cardiac waveforms.

In recent years cardiac electrocardiograms and electrograms often have been measured using automated sampling systems that record samples periodically, with a fixed sample-to-sample interval. In contrast, adaptive sampling systems envision variable sample-to-sample intervals, and new information about such systems has emerged in the last few years. The author summarizes these reports. On the whole, they show that the fan algorithm is an effective basis for adaptive sampling of cardiac waveforms, that it works well on electrocardiograms, electrograms, and action potentials, and that prototype sampling systems based on the fan can be constructed to run in real time.

Algorithms↗
PubMed1987

Interstitial potentials and their change with depth into cardiac tissue.

The electrical source strength for an isolated, active, excitable fiber can be taken to be its transmembrane current as an excellent approximation. The transmembrane current can be determined from intracellular potentials only. But for multicellular preparations, particularly cardiac ventricular muscle, the electrical source strength may be changed significantly by the presence of the interstitial potential field. This report examines the size of the interstitial potential field as a function of depth into a semi-infinite tissue structure of cardiac muscle regarded as syncytial. A uniform propagating plane wave of excitation is assumed and the interstitial potential field is found based on consideration of the medium as a continuum (bidomain model). As a whole, the results are inconsistent with any of the limiting cases normally used to represent the volume conductor, and suggest that in only the thinnest of tissue (less than 200 micron) can the interstitial potentials be ignored.

Action Potentials↗
PubMed1987

Mathematical modeling of electrical activity of the heart.

This paper reviews the literature on mathematical models of cardiac activation and evaluates these approaches against an analytical approach that includes both structure and membrane properties. The advantages and disadvantages of each methodology are described and directions for future research suggested.

Animals↗
PubMed1986

A critique of impedance measurements in cardiac tissue.

The specific impedance of cardiac tissue cannot be measured directly. Instead, the investigator obtains voltage and current measurements and places them into a model of the tissue's structure to infer the impedances of elements of the model. If the model fails to describe major aspects of the real tissue, the results may be worthless, although possibly self-consistent. In the literature of impedance measurement in cardiac tissue, only rarely is the model explicitly described; more commonly, the tissue model is adopted implicitly when equations giving the impedance in terms of voltage and current measurements are adopted. This paper examines the series of models that have been used in specific impedance measurements of cardiac tissue and shows how the same or similar measurements can accurately describe tissue impedivity or can lead to significant errors when inadequate models such as isotropic and anisotropic monodomains (although a part of work of historical merit) are used.

Animals↗
PubMed1985

Effect of junctional resistance on source-strength in a linear cable.

This paper studies the relative strength of sources associated with the cell and the junction between cells of an equivalent single cardiac fiber. It is shown that the junctional source is negligible compared to the cellular source. On the other hand, the junctional resistance affects the magnitude of the cellular source reducing it by possibly an order of magnitude. The significance of these results to cardiac electrophysiology is that the effect of the junctional resistance may have to be considered separate from that of the cellular resistance.

Animals↗