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Marvin H White

Publications and source records attributed to Marvin H White.

2 recordsLinked to original sources

Simulation of biological ion channels with technology computer-aided design.

Computer simulations of realistic ion channel structures have always been challenging and a subject of rigorous study. Simulations based on continuum electrostatics have proven to be computationally cheap and reasonably accurate in predicting a channel's behavior. In this paper we discuss the use of a device simulator, SILVACO, to build a solid-state model for KcsA channel and study its steady-state response. SILVACO is a well-established program, typically used by electrical engineers to simulate the process flow and electrical characteristics of solid-state devices. By employing this simulation program, we have presented an alternative computing platform for performing ion channel simulations, besides the known methods of writing codes in programming languages. With the ease of varying the different parameters in the channel's vestibule and the ability of incorporating surface charges, we have shown the wide-ranging possibilities of using a device simulator for ion channel simulations. Our simulated results closely agree with the experimental data, validating our model.

Computer-Aided Design↗

Parameter-extraction of a two-compartment model for whole-cell data analysis.

Neuronal modeling of patch-clamp data is based on approximations which are valid under specific assumptions regarding cell properties and morphology. Certain cells, which show a biexponential capacitance transient decay, can be modeled with a two-compartment model. However, for parameter-extraction in such a model, approximations are required regarding the relative sizes of the various model parameters. These approximations apply to certain cell types or experimental conditions and are not valid in the general case. In this paper, we present a general method for the extraction of the parameters in a two-compartment model without assumptions regarding the relative size of the parameters. All the passive electrical parameters of the two-compartment model are derived in terms of the available experimental data. The experimental data is obtained from a DC measurement (where the command potential is a hyperpolarizing DC voltage) and an AC measurement (where the command potential is a sinusoidal stimulus on a hyperpolarized DC potential) performed on the cell under test. Computer simulations are performed with a circuit simulator, XSPICE, to observe the effects of varying the two-compartment model parameters on the capacitive transients of the current response. Our general solution for the parameter-estimation of a two-compartment model may be used to model any neuron, which has a biexponential capacitive current decay. In addition, our model avoids the need for simplifying and perhaps erroneous approximations. Our equations may be easily implemented in hardware/software compensation schemes to correct the recorded currents for any series resistance or capacitive transient errors. Our general solution reduces to the results of previous researchers under their approximations.

Algorithms↗