System identification based on point processes and correlation densities. II. The refractory neuron model
type: Item
instance of: scholarly article
title: System identification based on point processes and correlation densities. II. The refractory neuron model
zbMATH Open document ID: 0658.92006
DOI: 10.1016/0025-5564(88)90023-5
published in: Mathematical Biosciences
publication date: 1988-01-01T00:00:00Z
review text: The results presented by the author, \textit{G. Hesselmans} and \textit{P. Johannesma} in part I of this paper, ibid. 80, 143-171 (1986; Zbl 0613.92013), are further developed. The studied neuronal model is composed of three parts: two of them the same as in the previous paper and additionally a linear filter that forms a feedback of the output point process. The feedback causes the output point process to be a self- exciting one. An example of the feedback aiming to describe a dead time after neuronal firing and exponential recovery is considered. The auto- and cross-correlation densities for the model neuron are mainly derived in the case given by the special example. The simulations of the model illustrate the results achieved.
Mathematics Subject Classification ID: 92Cxx
zbMATH DE Number: 4077012
zbMATH Keywords: self-exciting output process
zbMATH Keywords: characteristic functionals
zbMATH Keywords: approximations
zbMATH Keywords: auto-correlation densities
zbMATH Keywords: nonlinear relations
zbMATH Keywords: action potentials
zbMATH Keywords: neuronal model
zbMATH Keywords: linear filter
zbMATH Keywords: feedback
zbMATH Keywords: output point process
zbMATH Keywords: neuronal firing
zbMATH Keywords: exponential recovery
zbMATH Keywords: cross-correlation densities
zbMATH Keywords: simulations
author: Henk F. P. van den Boogaard
reviewed by: Petr Lansky
MaRDI profile type: Publication
full work available at URL: 0025-5564(88)90023-5
OpenAlex ID: W4248884537
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description: scientific article; zbMATH DE number 4077012