Monthly
288 pp. per issue
6 x 9, illustrated
ISSN
0899-7667
E-ISSN
1530-888X
2014 Impact factor:
2.21

Neural Computation

July 1994, Vol. 6, No. 4, Pages 696-717
(doi: 10.1162/neco.1994.6.4.696)
© 1994 Massachusetts Institute of Technology
Dimension Reduction of Biological Neuron Models by Artificial Neural Networks
Article PDF (1.38 MB)
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.