ML Anthology

Dimension Reduction of Biological Neuron Models by Artificial Neural Networks

Kenji Doya, Allen I. Selverston
NeCo 1994 pp. 696-717
doi:10.1162/NECO.1994.6.4.696 /neco/1994/doya1994neco-dimension/

Abstract

An artificial neural network approach to dimension reduction of dynamical systems is proposed and applied to conductance-based neuron models. Networks with bottleneck layers of continuous-time dynamical units could make a two-dimensional model from the trajectories of the Hodgkin-Huxley model and a three-dimensional model from the trajectories of a six-dimensional bursting neuron model. Nullcline analysis of these reduced models revealed the bifurcations of the dynamical system underlying firing and bursting behaviors.

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Cite

Text

Doya and Selverston. "Dimension Reduction of Biological Neuron Models by Artificial Neural Networks." Neural Computation, 1994. doi:10.1162/NECO.1994.6.4.696

Markdown

[Doya and Selverston. "Dimension Reduction of Biological Neuron Models by Artificial Neural Networks." Neural Computation, 1994.](https://mlanthology.org/neco/1994/doya1994neco-dimension/) doi:10.1162/NECO.1994.6.4.696

BibTeX

@article{doya1994neco-dimension,
  title     = {{Dimension Reduction of Biological Neuron Models by Artificial Neural Networks}},
  author    = {Doya, Kenji and Selverston, Allen I.},
  journal   = {Neural Computation},
  year      = {1994},
  pages     = {696-717},
  doi       = {10.1162/NECO.1994.6.4.696},
  volume    = {6},
  url       = {https://mlanthology.org/neco/1994/doya1994neco-dimension/}
}