title: The parameter identification problem for the somatic shunt model.
abstract: The somatic shunt model, a generalized version of the Rall equivalent cylinder model, is used commonly to describe the passive electrotonic properties of neurons. Procedures for determining the parameters of the somatic shunt model that best describe a given neuron typically rely on the response of the cell to a small step of hyperpolarizing current injected by an intrasomatic recording electrode. In this study it is shown that the problem of estimating model parameters for the somatic shunt model using physiological data is ill-posed, in that very small errors in measured data can lead to large and unpredictable errors in parameter estimates. If the somatic shunt is assumed to be a real property of the intact neuron, the effects of these errors are not severe when predicting EPSP waveshapes resulting from synaptic input at a given location. However, if the somatic shunt is assumed to be a consequence of a leakage pathway around the recording electrode, and a correction for the shunt is applied, then the instability of the inverse problem can introduce large errors in estimates of EPSP waveshape as a function of synaptic location in the intact cell. Morphological constraints can be used to improve the accuracy of the inversion procedure in terms of both parameter estimates and predicted EPSP responses.
authors.affiliation: Department of Biomedical Engineering and Otolaryngology-Head and Neck Surgery, Johns Hopkins University School of Medicine, Baltimore, MD 21205.
authors.forename: J A
authors.initials: JA
authors.lastname: White
authors.forename: P B
authors.initials: PB
authors.lastname: Manis
authors.forename: E D
authors.initials: ED
authors.lastname: Young
mesh_terms: D008433:Mathematics; D008564:Membrane Potentials / Q000502:physiology; D008959:Models, Neurological; D015233:Models, Statistical; D009431:Neural Conduction / Q000502:physiology*; D009474:Neurons / Q000502:physiology*; D009435:Synaptic Transmission / Q000502:physiology