@article{38906,
  keywords = {Noise, reduction, neuronal networks, equation, dynamical-systems, Binocular rivalry, competition, Data-mining, Diffusion map, diffusion   maps, Macroscopic, neural model, perceptual bistability, vision},
  author = {Carlo Laing and Thomas Frewen and Ioannis Kevrekidis},
  title = {Reduced models for binocular rivalry},
  abstract = { <p>Binocular rivalry occurs when two very different images are presented to the two eyes, but a subject perceives only one image at a given time. A number of computational models for binocular rivalry have been proposed; most can be categorised as either "rate" models, containing a small number of variables, or as more biophysically-realistic "spiking neuron" models. However, a principled derivation of a reduced model from a spiking model is lacking. We present two such derivations, one heuristic and a second using recently-developed data-mining techniques to extract a small number of "macroscopic" variables from the results of a spiking neuron model simulation. We also consider bifurcations that can occur as parameters are varied, and the role of noise in such systems. Our methods are applicable to a number of other models of interest.</p> },
  year = {2010},
  journal = {Journal of Computational Neuroscience},
  volume = {28},
  pages = {459-476},
  month = {06/2010},
  isbn = {0929-5313},
  language = {English},
}