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Simulating Neurons in Reaction-Diffusion Chemistry

  • James Stovold
  • Simon O’Keefe
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7223)

Abstract

Diffusive Computation is a method of using diffusing particles as a representation of data. The work presented attempts to show that through simulating spiking neurons, diffusive computation has at least the same computational power as spiking neural networks. We demonstrate (by simulation) that wavefronts in a Reaction-Diffusion system have a cumulative effect on concentration of reaction components when they arrive at the same point in the reactor, and that a catalyst-free region acts as a threshold on the initiation of an outgoing wave. Spiking neuron models can be mapped onto this system, and therefore RD systems can be used for computation using the same models as are applied to spiking neurons.

Keywords

Spike Train Synaptic Cleft Multiple Wave Chemical Synapse Delay Loop 
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-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • James Stovold
    • 1
  • Simon O’Keefe
    • 1
  1. 1.Department of Computer ScienceUniversity of YorkUK

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