Literature DB >> 14749318

Analysis of the optimal channel density of the squid giant axon using a reparameterized Hodgkin-Huxley model.

Thomas D Sangrey1, W Otto Friesen, William B Levy.   

Abstract

A reparameterized Hodgkin-Huxley-type model is developed that improves the 1952 model's fit to the biological action potential. In addition to altering Na(+) inactivation and K(+) activation kinetics, a voltage-dependent gating-current mechanism has been added to the model. The resulting improved model fits the experimental trace nearly exactly over the rising phase, and it has a propagation velocity that is within 3% of the experimentally measured value of 21.2 m/s (at 18.5 degrees C). Having eliminated most inaccuracies associated with the velocity-dependent rising phase of the action potential, the model is used to test Hodgkin's maximum velocity hypothesis, which asserts that channel density has evolved to maximize conduction velocity. In fact the predicted optimal channel density is more than twice as high as the actual squid channel density. When the available capacitance is reduced to approximate more modern serial Na(+)-channel models, the optimal channel density is 4 times the actual value. We suggest that, although Hodgkin's maximum velocity hypothesis is acceptable as a first approximation, the microscopic optimization perspective of natural selection will not explain the channel density of the squid unless other constraints are taken into account, for example, the metabolic costs of velocity.

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Year:  2004        PMID: 14749318     DOI: 10.1152/jn.00646.2003

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


  5 in total

1.  The evolution of vertebrate and invertebrate myelin: a theoretical computational study.

Authors:  Ann M Castelfranco; Daniel K Hartline
Journal:  J Comput Neurosci       Date:  2015-04-02       Impact factor: 1.621

2.  Action potential energy efficiency varies among neuron types in vertebrates and invertebrates.

Authors:  Biswa Sengupta; Martin Stemmler; Simon B Laughlin; Jeremy E Niven
Journal:  PLoS Comput Biol       Date:  2010-07-01       Impact factor: 4.475

3.  Communication consumes 35 times more energy than computation in the human cortex, but both costs are needed to predict synapse number.

Authors:  William B Levy; Victoria G Calvert
Journal:  Proc Natl Acad Sci U S A       Date:  2021-05-04       Impact factor: 11.205

4.  Regulatory evolution and voltage-gated ion channel expression in squid axon: selection-mutation balance and fitness cliffs.

Authors:  Min Kim; Don McKinnon; Thomas MacCarthy; Barbara Rosati; David McKinnon
Journal:  PLoS One       Date:  2015-04-13       Impact factor: 3.240

5.  From Squid to Mammals with the HH Model through the Nav Channels' Half-Activation-Voltage Parameter.

Authors:  Nedialko I Krouchev; Frank Rattay; Mohamad Sawan; Alain Vinet
Journal:  PLoS One       Date:  2015-12-02       Impact factor: 3.240

  5 in total

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