ModelDB: Current flow during PAP in squid axon at diameter change (Joyner et al 1980)

Current flow during PAP in squid axon at diameter change (Joyner et al 1980)

Accession: 9853

From the paper abstract: An impulse ... sees an increased electrical load at regions of increasing diameter or at branch points with certain morphologies. We present here theoretical and experimental studies on the changes in membrane current and axial current associated with diameter changes. The theoretical studies were done with numerical solutions for cable equations that were generalized to include a varying diameter; the Hodgkin-Huxley equations were used to represent the membrane properties. ... As an action potential approaches a region of increased electrical load, the action potential amplitude and rate of rise decrease, but there is a marked increase in the magnitude of the inward sodium current. ... (See paper for more details.)
Reference: Joyner RW, Westerfield M, Moore JW (1980) Effects of cellular geometry on current flow during a propagated action potential. Biophys J 31:183-94 [PubMed]

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Model Information (Click on a link to find other models with that property)

Model Type:	Axon;
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):	I Na,t; I K;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment:	Neuron;
Model Concept(s):	Influence of Dendritic Geometry; Axonal Action Potentials;
Implementer(s):	Hines, Michael [Michael.Hines at Yale.edu];

Search NeuronDB for information about: I Na,t; I K;

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Joyner, Westerfield, and Moore (1980)
Effects of cellular geometry on current flow during a propagated action potential.
Biophys. J. 31: 183-194

This model qualitatively reproduces figures 2,3,4,5 and,
to a lesser extent, fig 7.
It is entirely possible that I misinterpreted  the meaning of figure 7 as
a plot of separately integrated positive and negative total membrane current.
Such a plot shows much less "charge transfer" in the proximal region of
the wire than is shown in the paper figure.
I attribute other discrepancies to the precise recording locations and the
details of spatial discretization.

The NEURON implementation of this model was prepared by Michael Hines.
Questions about details of this implementation should be addressed to him
at michael.hines@yale.edu.

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