Literature DB >> 660228

Electrotonic properties of neurons: steady-state compartmental model.

D H Perkel, B Mulloney.   

Abstract

1. If a neuron is represented by a network of resistively coupled isopotential regions, the passive flow of current in its dendritic structure and soma is described by a matrix differential equation. The matrix elements are defined in terms of membrane resistances and capacitances and of coupling resistances between adjoining regions. 2. A uniform cylidrical dendrite can be represented by a chain of identical regions. In this case, a closed-form mathematical expression is derived for the voltage attenuation factor of the dendrite at steady state in terms of the ratio of membrane resistance to coupling resistance. A numerical method is given to determine the coupling resistances, which in turn yield a specified attenuation factor. Related expressions are given for a dendrite coupled to a soma. Formulas are also derived for the input resistance in these configurations. 3. For more complicated neuronal structures, matrix manipulations are described which yield values for input resistances in all regions, attenuation factors between all pairs of regions, and values of applied voltages necessary to attain specified steady-state potentials. 4. Dynamic solutions to the differential equation provide voltage transients (PSPs). Comparison of the shape paramenters of these transients with those of experimental or cable-theoretical PSPs establishes the number of regions necessary to achieve a given degree of approximation to the transients predicted by cable theory.

Mesh:

Year:  1978        PMID: 660228     DOI: 10.1152/jn.1978.41.3.621

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  13 in total

1.  Computational model of the on-alpha ganglion cell receptive field based on bipolar cell circuitry.

Authors:  M A Freed; R G Smith; P Sterling
Journal:  Proc Natl Acad Sci U S A       Date:  1992-01-01       Impact factor: 11.205

2.  Analysis of impulse adaptation in motoneurons.

Authors:  Jianghong Tian; Tetsuya Iwasaki; Wolfgang Otto Friesen
Journal:  J Comp Physiol A Neuroethol Sens Neural Behav Physiol       Date:  2009-12-24       Impact factor: 1.836

3.  Intersegmental coordination of limb movements during locomotion: mathematical models predict circuits that drive swimmeret beating.

Authors:  F K Skinner; B Mulloney
Journal:  J Neurosci       Date:  1998-05-15       Impact factor: 6.167

4.  A continuous cable method for determining the transient potential in passive dendritic trees of known geometry.

Authors:  W R Holmes
Journal:  Biol Cybern       Date:  1986       Impact factor: 2.086

5.  The functional organization of the crayfish lamina ganglionaris. I. Nonspiking monopolar cells.

Authors:  L T Wang-Bennett; R M Glantz
Journal:  J Comp Physiol A       Date:  1987-06       Impact factor: 1.836

6.  Modeling the electrical behavior of anatomically complex neurons using a network analysis program: passive membrane.

Authors:  I Segev; J W Fleshman; J P Miller; B Bunow
Journal:  Biol Cybern       Date:  1985       Impact factor: 2.086

7.  Compartmental models of electrotonic structure and synaptic integration in an identified neurone.

Authors:  D H Edwards; B Mulloney
Journal:  J Physiol       Date:  1984-03       Impact factor: 5.182

8.  Characteristics of M spikes in cat motoneurons and their significance for the measurement of small composite Ia EPSPs.

Authors:  T M Hamm; B R Botterman; R M Reinking; D G Stuart
Journal:  Exp Brain Res       Date:  1983       Impact factor: 1.972

9.  Unequal diameters and their effects on time-varying voltages in branched neurons.

Authors:  B Horwitz
Journal:  Biophys J       Date:  1983-01       Impact factor: 4.033

10.  Passive cable properties of hippocampal CA3 pyramidal neurons.

Authors:  D Johnston
Journal:  Cell Mol Neurobiol       Date:  1981-03       Impact factor: 5.046

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