Affordable Access

deepdyve-link deepdyve-link
Publisher Website

Predicting single spikes and spike patterns with the Hindmarsh-Rose model.

Authors
  • de Lange, Enno
  • Hasler, Martin
Type
Published Article
Journal
Biological cybernetics
Publication Date
Nov 01, 2008
Volume
99
Issue
4-5
Pages
349–360
Identifiers
DOI: 10.1007/s00422-008-0260-y
PMID: 19011923
Source
Medline
License
Unknown

Abstract

Most simple neuron models are only able to model traditional spiking behavior. As physiologists discover and classify different electrical phenotypes, computational neuroscientists become interested in using simple phenomenological models that can exhibit these different types of spiking patterns. The Hindmarsh-Rose model is a three-dimensional relaxation oscillator which can show both spiking and bursting patterns and has a chaotic regime. We test the predictive powers of the Hindmarsh-Rose model on two different test databases. We show that the Hindmarsh-Rose model can predict the spiking response of rat layer 5 neocortical pyramidal neurons on a stochastic input signal with a precision comparable to the best known spiking models. We also show that the Hindmarsh-Rose model can capture qualitatively the electrical footprints in a database of different types of neocortical interneurons. When the model parameters are fit from sub-threshold measurements only, the model still captures well the electrical phenotype, which suggests that the sub-threshold signals contain information about the firing patterns of the different neurons.

Report this publication

Statistics

Seen <100 times