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Biological Cybernetics

, Volume 64, Issue 1, pp 69–76 | Cite as

Effects of paranodal potassium permeability on repetitive activity of mammalian myelinated nerve fiber models

  • F. Awiszus
Article

Abstract

Almost all potassium channels within mammalian myelinated nerve fibers are covered by the myelin sheath and their majority is concentrated in a small paranodal region. In order to investigate effects of this paranodal potassium permeability on nerve fiber behavior via a simulation approach, a myelinated fiber model is required that treats myelin sheath and internodal axolemma as separate entities. Such a fiber description was developed by Blight (1985) and his model was used to investigate the effects paranodal potassium channels have on the ability of maintaining repetitive firing in response to a constant current injected into the fiber. It was found that increasing the potassium channel density at the paranode from low to moderate values widened the range of injected currents with a repetitive response. This promotion of repetitive activity by the introduction of additional potassium channels occurred up to an “optimal” value beyond which a further increase in paranodal potassium permeability narrowed the range of currents with a repetitive response. Finally, if a certain limit in paranodal potassium channel density was exceeded, repetitive activity was abolished completely. These results were obtained regardless of the assumptions about the electrical resistance of the myelin sheath. On the other hand, in the absence of potassium channels repetitive firing could be observed only when a high resistance myelin sheath was assumed, whereas a nerve fiber model with electrical properties inferred from intracellular recordings needed at least some potassium channels within the paranodal region for repetitive firing in response to an injected current.

Keywords

Electrical Property Nerve Fiber Potassium Channel Myelin Sheath Simulation Approach 
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. Awiszus F (1990) Effects of a slow potassium permeability on repetitive activity of the frog node of Ranvier. Biol Cybern 63:155–159CrossRefPubMedGoogle Scholar
  2. Baker M, Bostock H, Grafe P, Martius P (1987) Function and distribution of three types of rectifying channels in rat spinal root myelinated axons. J Physiol 383:45–67PubMedGoogle Scholar
  3. Barrett EF, Barrett JN (1982) Intracellular recording from vertebrate myelinated axons: Mechanisms of the depolarizing afterpotential. J Physiol 323:117–144PubMedGoogle Scholar
  4. Blight AR (1985) Computer simulation of action potentials and afterpotentials in mammalian myelinated axons: the case for a lower resistance myelin sheath. Neuroscience 15:13–31CrossRefPubMedGoogle Scholar
  5. Blight AR, Someya S (1985) Depolarizing afterpotentials in myelinated axons of mammalian spinal cord. Neuroscience 15:1–12CrossRefPubMedGoogle Scholar
  6. Brismar T, Schwarz JR (1985) Potassium permeability in rat myelinated nerve fibre. Acta Physiol Scand 124:141–148PubMedGoogle Scholar
  7. Bromm B, Frankenhaeuser B (1972) Repetitive discharge of the excitable membrane computed on the basis of voltage clamp data for the node of Ranvier. Pflügers Arch 332:21–27CrossRefGoogle Scholar
  8. Carver MB, Hinds HV (1978) The method of lines and the advektive equation. Simulation 31:59–69Google Scholar
  9. Chiu SY, Ritchie JM (1981) Evidence for the presence of potassium channels in the paranodal region of acutely demyelinated mammalian single nerve fibres. J Physiol 313:415–437PubMedGoogle Scholar
  10. Corrette BJ, Dreyer F, Repp H, Schwarz JR (1990) Dendrotoxin blocks one type of paranodal fast K+ channel in rat myelinated nerve. Pflügers Arch [Suppl] to 415:311Google Scholar
  11. Dubois JM (1981) Evidence for the existence of three types of potassium channels in the frog Ranvier node membrane. J Physiol 318:297–316PubMedGoogle Scholar
  12. Dubois JM (1983) Potassium currents in the frog node of Ranvier. Prog Biophys Mol Biol 42:1–20CrossRefPubMedGoogle Scholar
  13. Frankenhaeuser B, Huxley AF (1964) The action potential in the myelinated nerve fibre of Xenopus Laevis as computed on the basis of voltage clamp data. J Physiol 171:302–315PubMedGoogle Scholar
  14. Holden AV, Yoda M (1981) Ionic channel density of excitable membranes can act as a bifurcation parameter. Biol Cybern 42:29–38CrossRefPubMedGoogle Scholar
  15. Jonas P, Bräu ME, Hermsteiner M, Vogel W (1989) Single-channel recording in myelinated nerve fibers reveals one type of Na channel but different K channels. Proc Natl Acad Sci USA 86:7238–7242PubMedGoogle Scholar
  16. Moore JW, Joyner RW, Brill MH, Waxman SD, Najar-Joa M (1978) Simulations of conduction in uniform myelinated fibers. Relative sensitivity to change in nodal and internodal parameters. Biophys J 21:147–160PubMedGoogle Scholar
  17. Neumcke B, Stämpfli R (1982) Sodium currents and sodium-current fluctuations in rat myelinated nerve fibres. J Physiol 329:163–184PubMedGoogle Scholar
  18. Neumcke B, Schwarz JR, Stämpfli R (1987) A comparison of sodium currents in rat and frog myelinated nerve: normal and modified sodium inactivation. J Physiol 382:175–191PubMedGoogle Scholar
  19. Röper J, Schwarz JR (1989) Heterogeneous distribution of fast and slow potassium channels in myelinated rat nerve fibres. J Physiol 416:93–110PubMedGoogle Scholar
  20. Schwarz JR, Eikhof G (1987) Na currents and action potentials in rat myelinated nerve fibres at 20 and 37°C. Pflügers Arch 409:569–577CrossRefGoogle Scholar
  21. Waxman SG, Ritchie JM (1985) Organization of ion channels in the myelinated nerve fiber. Science 228:1502–1507PubMedGoogle Scholar

Copyright information

© Springer-Verlag 1990

Authors and Affiliations

  • F. Awiszus
    • 1
  1. 1.Medizinische Hochschule Hannover, Abteilung Neurophysiologie (OE 4230)Hannover 61Federal Republic of Germany

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