title: Modelling in vivo action potential propagation along a giant axon.
abstract: A partial differential equation model for the three-dimensional current flow in an excitable, unmyelinated axon is considered. Where the axon radius is significantly below a critical value R(crit) (that depends upon intra- and extra-cellular conductivity and ion channel conductance) the resistance of the intracellular space is significantly higher than that of the extracellular space, such that the potential outside the axon is uniformly small whilst the intracellular potential is approximated by the transmembrane potential. In turn, since the current flow is predominantly axial, it can be shown that the transmembrane potential is approximated by a solution to the one-dimensional cable equation. It is noted that the radius of the squid giant axon, investigated by (Hodgkin and Huxley 1952e), lies close to R(crit). This motivates us to apply the three-dimensional model to the squid giant axon and compare the results thus found to those obtained using the cable equation. In the context of the in vitro experiments conducted in (Hodgkin and Huxley 1952e) we find only a small difference between the wave profiles determined using these two different approaches and little difference between the speeds of action potential propagation predicted. This suggests that the cable equation approximation is accurate in this scenario. However when applied to the it in vivo setting, in which the conductivity of the surrounding tissue is considerably lower than that of the axoplasm, there are marked differences in both wave profile and speed of action potential propagation calculated using the two approaches. In particular, the cable equation significantly over predicts the increase in the velocity of propagation as axon radius increases. The consequences of these results are discussed in terms of the evolutionary costs associated with increasing the speed of action potential propagation by increasing axon radius.
authors.affiliation: School of Mathematics, University of Southampton, Southampton, SO17 1BJ, UK, S.George@soton.ac.uk.
authors.forename: Stuart
authors.initials: S
authors.lastname: George
authors.forename: Jamie M
authors.initials: JM
authors.lastname: Foster
authors.forename: Giles
authors.initials: G
authors.lastname: Richardson
mesh_terms: D000200:Action Potentials; D000465:Algorithms; D000818:Animals; D001369:Axons / Q000502:physiology*; D049832:Decapodiformes; D055641:Mathematical Concepts; D008959:Models, Neurological; D009431:Neural Conduction / Q000502:physiology; D017711:Nonlinear Dynamics; D015221:Potassium Channels / Q000378:metabolism; D015222:Sodium Channels / Q000378:metabolism
chemical_list: D015221:Potassium Channels; D015222:Sodium Channels