A discrete time neural network model with spiking neurons. Rigorous results on the spontaneous dynamics

J Math Biol. 2008 Mar;56(3):311-45. doi: 10.1007/s00285-007-0117-3. Epub 2007 Sep 14.

Abstract

We derive rigorous results describing the asymptotic dynamics of a discrete time model of spiking neurons introduced in Soula et al. (Neural Comput. 18, 1, 2006). Using symbolic dynamic techniques we show how the dynamics of membrane potential has a one to one correspondence with sequences of spikes patterns ("raster plots"). Moreover, though the dynamics is generically periodic, it has a weak form of initial conditions sensitivity due to the presence of a sharp threshold in the model definition. As a consequence, the model exhibits a dynamical regime indistinguishable from chaos in numerical experiments.

MeSH terms

  • Action Potentials / physiology*
  • Algorithms
  • Long-Term Potentiation / physiology
  • Long-Term Synaptic Depression / physiology
  • Markov Chains
  • Membrane Potentials / physiology
  • Models, Biological*
  • Nerve Net / physiology*
  • Neuronal Plasticity / physiology
  • Neurons / physiology*
  • Synapses / physiology
  • Synaptic Transmission / physiology