On the capabilities and computational costs of neuron models

Michael J. Skocik, Lyle N. Long

Research output: Contribution to journalArticle

18 Scopus citations

Abstract

We review the Hodgkin-Huxley, Izhikevich, and leaky integrate-and-fire neuron models in regular spiking modes solved with the forward Euler, fourth-order Runge-Kutta, and exponential Euler methods and determine the necessary time steps and corresponding computational costs required to make the solutions accurate. We conclude that the leaky integrate-and-fire needs the least number of computations, and that the Hodgkin-Huxley and Izhikevich models are comparable in computational cost.

Original languageEnglish (US)
Article number6687241
Pages (from-to)1474-1483
Number of pages10
JournalIEEE Transactions on Neural Networks and Learning Systems
Volume25
Issue number8
DOIs
StatePublished - Aug 2014

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence

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