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B Victorri

Publications and source records attributed to B Victorri.

3 recordsLinked to original sources

Reconstruction of propagated electrical activity with a two-dimensional model of anisotropic heart muscle.

The propagated electrical activity in normal anisotropic cardiac muscle is characterized by directionally dependent variations in the rising phase of the action potential. An important question concerns the relation between such variations and the propagation velocity and extracellular potentials. This problem was studied here in a sheet of cells, under conditions of uniform intracellular anisotropic resistivity and constant electrical membrane properties, through a numerical solution of the two-dimensional propagation equation. The numerical solution implies a lumping of the cytoplasmic and intercellular resistances into an equivalent junctional resistance to form a distributed resistive network representing the intracellular domain. The interstitial space is assumed isotropic and unbounded, with a resistivity of 100 omega X cm. The electrical properties of the cell membrane are represented by a Beeler-Reuter model. The stimulus current is applied to a small area of the sheet, and attention is focussed on the stable propagated events occurring some 5 or 6 length constants away from the stimulation site. The numerical solution is a good approximation of a continuous uniform structure when the cell size is less than 10% of the length constant along both major axes. Conditions of non-uniform propagation, with directionally dependent variations in the maximum rate of rise and time constant of the foot of the action potential were simulated by increasing the cell size to 30% of the length constant in the transverse direction of the sheet. Our results indicate that the directional changes in the maximum rate of rise correspond to small modifications of the extracellular potentials, while the directional changes in time constant of the foot are associated with the propagation velocity. The maximum effects are observed along the transverse direction as follows: a 19% increase in maximum rate of rise corresponds to a decrease of about 6% in the peak-to-peak amplitude of the extracellular potential, and a 24% increase in time constant of the foot is associated with a decrease of about 7% in the propagation velocity. Under the conditions of the present study, however, the simulated directional changes in maximum rate of rise are smaller than those experimentally observed so the corresponding changes in the extracellular potentials are probably underestimated.

Action Potentials↗

Numerical integration in the reconstruction of cardiac action potentials using Hodgkin-Huxley-type models.

A comparison between traditional numerical integration methods and a new hybrid integration method for the reconstruction of action potential activity is presented, using a mathematical model of the cardiac Purkinje fiber (MNT model). It is shown that the hybrid integration method reduces importantly the overall computation time required for solving the Hodgkin-Huxley differential equations describing membrane electrical events. To accomplish this, the particular form of the gating variable equations is exploited to reformulate the step-by-step computation. In this way, the time increment can be made much larger compared with traditional methods when the membrane potential changes slowly. A mathematical analysis of the hybrid integration method is presented also, together with a numerical verification of its performance both for the propagated and nonpropagated membrane action potential. It is shown that the local error, that is the error arising at each integration step, and the cumulative integration error are strictly controlled by the membrane potential offset. Using the MNT model, the nonpropagated cardiac Purkinje action potential can be reconstructed in real time with an accuracy of 1% for the potential and 5% for the time of occurrence of its main features. In reconstructing propagated events, the hybrid integration method allows computation time savings by a factor of 10 or more compared to accurate Runge-Kutta schemes.

Action Potentials↗

Mathematical model of visual perception.

A mathematical model of visual perception is presented with the intention of throwing some light on the problem of perceptual invariance. Two types of differential manifolds (receptive and effector) are associated with the repertoire which is the fundamental concept in the model. The elements of the repertoire carry weights which control the input-output relation in the repertoire and which can be modified by a learning process. It is shown that, under reasonable conditions, these repertoires possess good stability properties and can adjust to the various environments to which they may be subjected. In particular cases, it is shown that the stochastic learning process can be considered as deterministic to a first approximation.

Animals↗