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An Object-Oriented Paradigm for the Design of Realistic Neural Simulators

  • David C. Tam
  • R. Kent Hutson

Abstract

An object-oriented programming approach is used to implement a generic neural simulator to simulate the electrophysiological properties of neurons and interconnected neuronal networks. The neural simulator is designed with a generalizable principle to encourage users to make additions and modifications to the existing neurophysiological models. The object-oriented programming paradigm is used extensively to encapsulate the similarities and differences between different neurons and their components by various “objects”. A neuron is constructed by a compartmental model where electrical properties of the membrane of a neuron are compartmentalized and then linked together to form a whole neuron. Similarly, an equivalent of a biological neural network can constructed by connecting model neurons together to form a network. The object-oriented approach is used not only in constructing the neuronal structural hierarchy but also in the methods for solving mathematical equations governing the electrical properties of the neurons. Using these principles, a truly generic and generalizable model for simulating neuronal properties is accomplished.

Keywords

Neural Element Neuronal Element Biological Neural Network Neural Simulator Neurophysiological Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1993

Authors and Affiliations

  • David C. Tam
    • 1
  • R. Kent Hutson
    • 2
  1. 1.Center for Network NeuroscienceUniversity of North TexasDentonUSA
  2. 2.Keck Center for Computational BiologyRice UniversityHoustonUSA

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