Biomedical subjects

S Abramovich-Sivan

Publications and source records attributed to S Abramovich-Sivan.

9 recordsLinked to original sources

PubMed2000

A simulation of the SA node by a phase response curve-based model of a two-dimensional pacemaker cells array.

This paper presents a simulation of the sino-atrial (SA) node by a two-dimensional pacemaker cells array model, based on phase response curve (PRC) interaction. This simple model of the cardiac pacemaker cells, involves only the most basic functional properties, which play a direct role in the determination of the SA node rhythm. The two most relevant functional properties of the pacemaker cells are: The intrinsic cycle length, an "internal" feature of each pacemaker cell, and the PRC, an "overall collective" function. The PRC contains the "information" about the type of interactions of each pacemaker cell with the outside world (i.e., interaction with neighboring cells, external stimulus, etc.), and "strength" of the interaction (strong, weak, etc.). We studied the spatial interaction among a large number of pacemaker cells (15 x 15), as a function of the regional variation of cells properties, the "electrical" coupling between cells (the PRC), and the appearance of regions with abnormal cycle lengths. We investigated the influence of those parameters on the mutual interaction between the pacemaker cells, on the activation pattern and conduction time of the array, and on a pseudo-electrocardioigram (ECG) signal. This study demonstrates that by representing the pacemaker cells in the SA node by only two fundamental features, and by applying a simple physical-mathematical model, we can create a global picture of the SA node system. This enables us to explore physiological phenomena related to the genesis and maintenance of the SA node activity, and to gain insight into the conditions which predispose the SA node instability, and conduction disturbances.

Body Surface Potential Mapping↗

PubMed1999

Phase response curve based model of the SA node: simulation by two-dimensional array of pacemaker cells with randomly distributed cycle lengths.

A simulation of the SA node is presented, based on a 2D array (15 x 15) model of randomly distributed pacemaker cells, interacting via a phase response curve (PRC). The model involves only the basic properties that play a direct role in the determination of the SA node rhythm: intrinsic cycle length and PRC. The PRC reflects the 'type' of interaction of each pacemaker cell with the outside world (neighbouring cells, external stimulus, etc.). A major outcome of this study is the demonstration that global dynamics and the degree of 'disorder' of the SA node are strongly affected by the cycle length distribution of the model, as well as spatial inhomogeneity in the cell-to-cell 'electrical' coupling (PRC). Those factors also determine the conduction velocity throughout the SA node and may therefore be responsible for anisotropic conduction. For example, lowering the PRC parameters (d and a) by 25% increases the array activation time from 46 to 126 ms. The model also responds appropriately to a perturbation such as a vagal pulse. This pulse produces a shift of the dominant pacemaker to another site in the array and a transient lengthening of the array cycle length, for example from 312 to 355 ms.

Biological Clocks↗

PubMed1999

Simulation of atrial activity by a phase response curve based model of a two-dimensional pacemaker cells array: the transition from a normal activation pattern to atrial fibrillation.

In this paper, we present an original model of the atria, based on our hypothesis that atrial cells have features of pacemaker cells, characterized by their normally longer intrinsic cycle lengths and different type of connection (stronger) than the, sino-atrial (SA) node pacemaker cells. The atrium is simulated by a two-dimensional array of pacemaker cells (25 x 25), composed of a region of SA node pacemaker cells (11 x 11) surrounded by atrial pacemaker cells. All pacemakers cells are characterized by only the most relevant functional properties, those which play the most direct role in the determination of the cardiac rate and in the mechanism of arrhythmias. These properties are: the intrinsic cycle length, tau, an 'internal' feature of each pacemaker cell, and the phase-response curve (PRC), an 'overall collective' function. The PRC embodies the interactions of each pacemaker cell with its neighboring cells, and thus represents the type of connection (strong, weak, etc.) of the pacemaker cell with its surroundings. In our model, the SA node region differs from the atrial region by cycle length distribution and PRCs. We studied the spatial interaction between SA node pacemaker cells and atrial pacemaker cells as a function of the regional variation of cells properties and as a function of the "electrical" coupling between cells (the PRC), in the SA node region, in the atrial region, and in a border zone between them. We investigated the influence of those parameters on the activation pattern, on the conduction time of the array, and on a pseudo-ECG signal. This study demonstrates that by representing the atrial cells as a population of 'pacemaker-like' cells, similar to the SA node pacemaker cells, but differing markedly in their cycle lengths and cell-to-cell interaction (PRC), we can create a global picture of the atrial system by applying a simple physical-mathematical model. This approach enables us to explore physiological phenomena related to the genesis and maintenance of atrial activity. It also reveals the conditions which predispose to atrial arrhythmias and conduction disturbances (e.g. tachycardia, pacemaker shift, re-entry, fibrillation). In particular, it yields insight into the mechanism of transition from normal atrial activity to the disordered state of atrial fibrillation. Therefore, this study suggests a new way of looking at the development of cardiac arrhythmias of atrial origin.

Atrial Fibrillation↗

PubMed1998

A phase response curve based model: effect of vagal and sympathetic stimulation and interaction on a pacemaker cell.

This study introduces a simple mathematical model for a pacemaker cell affected by an external parasympathetic and/or sympathetic input. The model presented is based on the two most important functional properties of the cardiac pacemaker cells. The first property is the intrinsic pacemaker cycle length, an "internal" parameter of the cell. The second basic property is the phase response curve (PRC), a function which reflects the various interactions of the pacemaker cell with the outside world (i.e. interaction with surrounding cells, external stimulus). The vagal stimulus is simulated as affecting the pacemaker cycle length via a PRC, while the sympathetic input is expressed in the model as a continuous reduction in the pacemaker cycle length. When combined vagal and sympathetic activation is allowed, our model shows that autonomic systems are also capable of interacting. First, we studied the entrainment phenomena resulting from a repetitively applied vagal stimulus. Various complex patterns of dynamic interaction between the pacemaker cell and the vagal input were simulated. The PRC parameters appear to be an important factor in the prediction of the entrainment phenomena. Specifically, they permit a quantitative description of the limits of a 1:1 synchronization zone. Next, we apply this model to qualitatively investigate the phenomenon of "accentuated antagonism" between parasympathetic and sympathetic autonomic branches. We examined the various options for this interaction in regulating the pacemaker periodicity. Although this model is a simplified reflection of the biological system, we conclude that it can mimic many aspects of the dynamic autonomic control and of the possible interactions between vagal and sympathetic stimulation of a pacemaker cell.

Animals↗

PubMed1998

A PRC based model of a pacemaker cell: effect of vagal activity and investigation of the respiratory sinus arrhythmia.

In this study we present a computer model of a pacemaker cell subjected to vagal stimulation. This model allows us to investigate the entrainment phenomena of the pacemaker cell resulting from its dynamic interaction with a periodic train of vagal bursts. The possibility of entrainment depends mainly on the fact that a vagal stimulation discharge can "correct" the pacemaker rhythm by an amount that depends on its instantaneous relationship to the pacemaker cycle length. This very simple model, is based on the two most important functional properties of the cardiac pacemaker cells. The first property is the intrinsic pacemaker cycle length, which is an "internal" parameter of the cell, describing the most basic feature of a pacemaker cell. The second one is the phase response curve (PRC), which is an "overall collective" function, containing all the "information" about the possible interactions between the pacemaker cell and the outside world (i.e. its interaction with surrounding cells, external stimulus, etc.). A "collective" PRC was reconstructed from the resulting effects of all the pulses composing a burst. It appears that the PRC parameters as well as the vagal burst parameters are important factors in predicting the entrainment phenomena. Specifically, we found that the tendency of the pacemaker cell to become synchronized with bursts of vagal activity is greater, the larger the number of pulses per burst. However, increasing the number of pulses may also increase the tendency of the pacemaker towards instability, which was unveiled as changes in the configuration of the "collective" PRC. We applied the periodic train of vagal bursts so as to simulate the respiratory sinus arrhythmia (RSA) modulation on the pacemaker cell. We included also a modulation of sympathetic origin, represented as periodic changes in the intrinsic pacemaker cycle length. The frequency response of the pacemaker to "autonomic" modulations allowed us to demonstrate that the RSA dynamics can be interpreted in terms of the entrainment of the pacemaker cell by the respiratory modulation of vagal activity.

Autonomic Nervous System↗

PubMed1998

A single pacemaker cell model based on the phase response curve.

A single pacemaker cell model and its response to repetitive external depolarization stimulations is described in this paper. This model is a simple model based on the two most important functional properties of the cardiac pacemaker cells. The first property is the intrinsic pacemaker cycle length, which is an 'internal' parameter of the cell, describing the most important feature of a pacemaker cell. The second functional property is the phase response curve (PRC), which is an 'overall collective' function: it contains all the 'information' about the possible interactions of the pacemaker cell with the outside world (external stimulus, interaction with surrounding cells, etc.). This study demonstrates that by representing the pacemaker cell only by two fundamental features, and by applying a simple physical-mathematical model, a global picture of the system can be achieved, allowing us to explore qualitatively various physiological phenomena related to the pacemaker function. For example, we demonstrated that the PRC is a crucial parameter in the prediction of the entrainment phenomena of a single pacemaker cell in response to a periodic train of depolarization pulses. Specifically, the PRC permits a quantitative determination of the 1:1 synchronization range for a single pacemaker cell and an external depolarization pulse. Moreover, we show that the PRC can be used to represent the type of external stimulus applied to the pacemaker (e.g. depolarization pulse) and its intensity. Therefore, the PRC emerges as an important determinant and a useful 'tool' for the understanding of the dynamic interaction of pacemaker cells with the outside world. As a result of our simulations, we unveil a new important parameter: the 'degree of influence', which determines the range of 1:1 synchronization between an external depolarization pulse and a pacemaker cell. This interaction parameter is a direct function of the PRC parameters. It appears to be a helpful 'tool' for the understanding of synchronization and mutual entrainment mechanisms between the pacemaker cell and an external stimulus, and therefore it supports the basic importance of the PRC in the description and determination of these mechanisms.

Animals↗

PubMed1998

A pacemaker cell pair model based on the phase response curve.

A pacemaker cell pair model and the dynamic interaction between the two pacemaker cells is described in this paper. It is an extension of our single pacemaker cell model, in which we studied its response to repetitive external depolarization stimulations. This model is a simple model based on the two most important functional properties of the cardiac pacemaker cells: its intrinsic pacemaker cycle length, which is an 'internal' parameter of the cell, and the phase response curve (PRC), which is an 'overall collective' function. The PRC contains all the 'information' about the possible interactions of the pacemaker cell with the outside world (interaction with surrounding cells, external stimulus, etc.). First, we examined the properties and solutions of 1:1 synchronization between two pacemaker cells. We found that in order to achieve synchronization between two pacemaker cells, there should be limitations on the PRC parameters, which depend on the cells intrinsic cycle lengths. Next, we investigated the 2:1 entrainment state between two interacting pacemaker cells. We found that there is not necessarily a unique solution for this state as there was for the 1:1 state. Finally, we ran our computer model to investigate the properties of more complex patterns of entrainment between two pacemaker cells. As a result of our analytical study, we unveil two new important parameters, which are fully defined as a function of the PRC parameters: (1) the 'accelerator factor' which describes the tendency of a pair of interacting pacemaker cells to synchronize at a common cycle length, which is closer to the faster cycle of the pair; (2) the 'degree of coupling', which describes the range of the 1:1 synchronization and the 'strength' of the interaction between a pair of interacting pacemaker cells. Those two interaction parameters arise as helpful 'tools' for the understanding of synchronization and mutual entrainment mechanisms between pacemaker cells. Therefore, this study establishes the PRC as an important determinant and a useful approach for the understanding of the dynamic interaction of pacemaker cells among themselves and with the outside world.

Animals↗

PubMed1996

The effects of lidocaine on cardiac parasympathetic control in normal subjects and in subjects after myocardial infarction.

It has been widely accepted that lidocaine has little or no effect on the autonomic nervous system. However, we have previously shown that in dogs with vagally induced atrial fibrillation, lidocaine has a pronounced parasympatholytic effect. To study the possible effect of lidocaine on autonomic cardiac control in humans, we performed spectral analysis of heart rate fluctuations in 19 healthy volunteers, who received an i.v. bolus of lidocaine (1.4 mg/kg), as well as in 13 patients suffering from acute inferior myocardial infarction (IMI) and 13 patients suffering from acute anterior myocardial infarction (AMI), who received therapeutic doses of i.v. lidocaine infusion (4 mg/min). Heart rate variability and respiratory pattern were monitored according to a predetermined protocol, with and without lidocaine. Computing the heart rate power spectrum and integrating over predetermined frequency bands, we focused mainly on the respiratory frequency band, known to predominantly reflect parasympathetic control. The administration of lidocaine resulted in a significant overall increase in mean heart rate: for the healthy control group an increase of 5.5 +/- 2.2% (mean +/- SE), for the IMI group an increase of 9.4 +/- 3.5%, and for the AMI group an increase of 8.1 +/- 2.9% (p < 0.01 for all). Simultaneously, following the administration of lidocaine, there was a decrease in the power of respiratory fluctuations: for the healthy control group a decrease of 38.4 +/- 12.5%, for the IMI group a decrease of 46.3 +/- 32.9%, and for the AMI group a decrease of 33.9 +/- 16.2% (p < 0.01 for all). These findings indicate that lidocaine has a consistent and significant parasympatholytic effect on the human heart, in healthy volunteers as well as in patients in the acute phase of myocardial infarction.

Adult↗

PubMed1991

A combined heat clearance method for tissue blood flow measurement.

Tissue Blood Flow is measured by applying a combined procedure of two independent approaches based on heat clearance: the Pulse Decay Method and the Continuous Method. The Pulse Method allows absolute assessment of tissue BF with no need for calibration, and can be applied only if the tissue BF is steady during the period of measurement. On the other hand, the Continuous Method enables the observation of rapid changes in tissue BF, and can be applied under non steady-state conditions. Using the combined method, a continuous quantitative measurement of transient changes in tissue BF can be obtained. For this purpose, we have developed two experimental systems consisting of independent electronic units: a Pulse Unit and a Continuous Unit. A micro-computer with dedicated software controls the operation of the electronic units and calculates tissue BF on-line. In vitro measurements are performed and demonstrate the reliability of the methods. In vivo measurements in rat brain tissue are also performed and include physiological and pharmacological changes of local tissue BF. The results of the two heat clearance methods correlate well with tissue BF values measured by a third independent method, the Hydrogen Clearance Method.

Animals↗