Behavioral simulation and synthesis of biological neuron systems using synthesizable VHDL

J. A. Bailey, R. Wilcock, P. R. Wilson, J. E. Chad

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Neurons are complex biological entities which form the basis of nervous systems. Insight can be gained into neuron behavior through the use of computer models and as a result many such models have been developed. However, there exists a trade-off between biological accuracy and simulation time with the most realistic results requiring extensive computation. To address this issue, a novel approach is described in this paper that allows complex models of real biological systems to be simulated at a speed greater than real time and with excellent accuracy. The approach is based on a specially developed neuron model VHDL library which allows complex neuron systems to be implemented on field programmable gate array (FPGA) hardware. The locomotion system of the nematode Caenorhabditis elegans is used as a case study and the measured results show that the real time FPGA based implementation performs 288 times faster than traditional ModelSim simulations for the same accuracy.

Original languageEnglish
Pages (from-to)2392-2406
Number of pages15
JournalNeurocomputing
Volume74
Issue number14-15
DOIs
Publication statusPublished - 1 Jul 2011

Keywords

  • Hardware
  • Network
  • Neuron
  • Simulation
  • VHDL

ASJC Scopus subject areas

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence

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