Literature DB >> 15836861

A distributed parameter identification problem in neuronal cable theory models.

Jonathan Bell1, Gheorghe Craciun.   

Abstract

Dendritic and axonal processes of nerve cells, along with the soma itself, have membranes with spatially distributed densities of ionic channels of various kinds. These ionic channels play a major role in characterizing the types of excitable responses expected of the cell type. These densities are usually represented as constant parameters in neural models because of the difficulty in experimentally estimating them. However, through microelectrode measurements and selective ion staining techniques, it is known that ion channels are non-uniformly spatially distributed. This paper presents a non-optimization approach to recovering a single spatially non-uniform ion density through use of temporal data that can be gotten from recording microelectrode measurements at the ends of a neural fiber segment of interest. The numerical approach is first applied to a linear cable model and a transformed version of the linear model that has closed-form solutions. Then the numerical method is shown to be applicable to non-linear nerve models by showing it can recover the potassium conductance in the Morris-Lecar model for barnacle muscle, and recover the spine density in a continuous dendritic spine model by Baer and Rinzel.

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Year:  2005        PMID: 15836861     DOI: 10.1016/j.mbs.2004.07.001

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  4 in total

1.  Determining a distributed parameter in a neural cable model via a boundary control method.

Authors:  Sergei Avdonin; Jonathan Bell
Journal:  J Math Biol       Date:  2012-04-24       Impact factor: 2.259

2.  Fast Kalman filtering on quasilinear dendritic trees.

Authors:  Liam Paninski
Journal:  J Comput Neurosci       Date:  2009-11-27       Impact factor: 1.621

3.  Optimal experimental design for sampling voltage on dendritic trees in the low-SNR regime.

Authors:  Jonathan Hunter Huggins; Liam Paninski
Journal:  J Comput Neurosci       Date:  2011-08-23       Impact factor: 1.621

4.  Numerical Approximation of Solutions of a Nonlinear Inverse Problem Arising in Olfaction Experimentation.

Authors:  Donald A French; Richard J Flannery; Charles W Groetsch; Willam B Krantz; Steven J Kleene
Journal:  Math Comput Model       Date:  2006-04
  4 in total

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