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Modeling the Nerve Action Potential

  • Suresh R. Devasahayam
Chapter
  • 1.1k Downloads
Part of the Topics in Biomedical Engineering International Book Series book series (TOBE)

Abstract

Excitable tissues like nerves and muscles possess the property that when stimulated beyond some threshold an all-or-none action potential can be observed. This action potential is a local depolarization of the normally polarized cell membrane on the axon. The local depolarization causes the depolarization of adjacent regions of the cell; the continuation of this process results in propagation of the action potential over the axon. This propagating action potential is an important means of information transmission in animals; nerve cells communicate by means of such action potentials propagating along axons. Information between cells is usually conveyed across a synapse in which the action potential from one nerve causes the release of a transmitter chemical which in turn generates excitatory or inhibitory post-synaptic potentials. Sufficient excitatory post-synaptic potential amplitude will in turn evoke another action potential in the receiving cell. Sensory receptors like retinal cells, touch receptors, etc., transduce external physical signals into depolarizations in the receptor ultimately resulting in action potentials which carry the information to the brain. On the other hand activity of neurons in the motor cortex results in action potentials being conveyed to spinal neurons which impinge on muscle fibers and evoke muscle fiber action potentials. The muscle fiber action potential leads to a sequence of activity which ultimately produces muscle contraction, force production and locomotion. The process of generation of action potentials in all these various types of cell is essentially the same.

Keywords

Ionic Conductance Rest Membrane Potential Step Response Voltage Clamp Membrane Voltage 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    R.B. Stein, Nerve and Muscle, Plenum Press, New York, 1980.CrossRefGoogle Scholar
  2. 2.
    A.T. Bahill, Bioengineering: Biomedical, Medical and Clinical Engineering, Prentice Hall, 1981.Google Scholar
  3. 3.
    R. Plonsey and R.C. Barr, Bioelectricity: A Quantitative Approach, Plenum Press, 1988.Google Scholar

Copyright information

© Springer Science+Business Media New York 2000

Authors and Affiliations

  • Suresh R. Devasahayam
    • 1
  1. 1.School of Biomedical EngineeringIndian Institute of TechnologyBombayIndia

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