Modelling analysis of human optic nerve fibre excitation based on experimental data

  • S. Parrini
  • J. Delbeke
  • V. Legat
  • C. Veraart


The aim of the study is to determine which of the existing myelinated mammalian nerve fibre models better fits experimental data resulting from electrical stimulation of the human optic nerve and from propagation velocity measured on primates. The macroscopic electric potential is computed in a 3D, inhomogeneous and anisotropic nerve model. The Chiu-Sweeney (CS) and the Schwarz-Wesselink (SW) membrane descriptions are then considered. Variations in parameters that are not well established (encapsulation-tissue thickness, nerve-fascicle conductivity, geometric and electrochemical fibre cable parameters) are taken into account. Results demonstrate that the SW model predictions are in better agreement with the experimental data than those of the CS model, although thresholds are still too high. When channel densities are varied, the SW model turns out to be more robust than the CS model. For a suitable leakage channel density value (about 8% of the original one), the SW model predicts a conduction velocity of 11.4ms−1 and an excitation threshold of 0.055 mA (for 0.1 ms pulse duration), which is in very good agreement with experimental values (11 ms−1 and 0.055 mA). Potassium current in the SW model is necessary for stability. Introduction of a potassium-like current can restore stability in the CS system.


Optic nerve Human Self-sizing spiral cuff electrode Finite elements method Fibre model 


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  1. Behse, F. (1990): «Morphometric studies on the human sural nerve»,Acta Neurol. Scand.,82, (Suppl. 132), pp. 1–38Google Scholar
  2. Brindley, G., andLevin, W. (1968): «The sensations produced by electrical stimulation of the visual cortex»,J. Physiol.,196, pp. 479–493Google Scholar
  3. Butt, A., andJenkins, H. (1994): «Morphological changes in oligodendrocytes in the intact mouse optic nerve following intravitreal injection of tumour necrosis factor»,J. Neuroimmunol.,51, pp. 27–33Google Scholar
  4. Chintalacharuvu, R., Ksienski, D., andMortimer, J. (1991): «A numerical analysis of the electric field generated by a nerve cuff electrode». Proc. IEEE Eng. Med. Biol. Soc. 13th Ann. Conf.,13, (2), pp. 912–913Google Scholar
  5. Chiu, S., Ritchie, J., Rogart, R., andStagg, D. (1979): «A quantitative description of membrane currents in rabbit myelinated nerve»,J. Physiol.,292, pp. 149–166Google Scholar
  6. Delbeke, J., Parrini, S., Glineur, O., Vanlierde, A., andVeraart, C. (1999): «Phosphene perception thresholds to direct stimulation of a human optic nerve shows spatial and temporal summation»,Soc. Neurosci. Abstr.,25, p. 1042Google Scholar
  7. Deurloo, K., Holsheimer, J., andBoom, H. (1998): «Transverse tripolar stimulation of peripheral nerve: a modelling study of spatial selectivity»,Med. Biol. Eng. Comput.,36, pp. 66–74Google Scholar
  8. Fohlmeister, J., Coleman, P., andMiller, R. (1990): «Modeling the repetitive firing of retinal ganglion cell»,Brain Res.,510, pp. 343–345CrossRefGoogle Scholar
  9. Geddes, L., andBaker, L. (1967): «The specific resistance of biological material—a compendium of data for the biological engineer and physiologist»,Med. Biol. Eng.,5, pp. 271–293Google Scholar
  10. Goodall, E., Ksterman, L., andStruijk, J. (1995): «Modeling study of activation and propagation delays during stimulation of peripheral nerve fibers with a tripolar cuff electrode»,IEEE Trans. Rehab. Eng.,3, pp. 272–282CrossRefGoogle Scholar
  11. Griffin, A., andBurke, W. (1974): «The distribution and nerve fibre groups in the optic tract and lateral geniculate nucleus of macaca irus»,Proc. Aust. Physiol. Pharmacol. Soc.,5, pp. 74PGoogle Scholar
  12. Grill, W., andMortimer, J. (1994): «Electrical properties of implant encapsulation tissue»,Ann. Biomed. Eng.,22, pp. 23–33Google Scholar
  13. Grill, W., andMortimer, J. (1994): «Stimulus waveforms for selective neural stimulation»,IEEE Eng. Med. Biol. Soc. Mag., pp. 375–385Google Scholar
  14. Guckenheimer, J., andHolmes, P. (1983): «Nonlinear oscillations, dynamical systems and bifurcations of vector fields« (Springer-Verlag, New York)Google Scholar
  15. Jonas, J., Muller-Bergh, J., Schlotzer-Schrehardt, U., andNaumann, G. (1990): «Histomorphometry of the human optic nerve»,Invest. Ophthalmol. Vis. Sci.,31, pp. 736–744Google Scholar
  16. Lapique, L. (1907): «Recherches quantitatives sur l'excitation lectrique des nerfs, traite comme une polarisation»,J. Physiol. (Paris) 9, pp. 622–635Google Scholar
  17. McNeal, D. (1976): «Analysis of a model for excitation of myelinated nerve»,IEEE Trans.,BME-23, pp. 329–337Google Scholar
  18. Miller, N. (1988): «Walsh and Hoyt's clinical neuroophthalmology, 4th edn» (Williams and Wilkins, Baltimore)Google Scholar
  19. Parrini, S., Romero, E., Delbeke, J., Legat, V., andVeraart, C. (1999): «A hybrid finite elements-spectral method for computation of the electric potential generated by a nerve cuff electrode»,Med. Biol. Eng. Comput.,37, pp. 733–736.Google Scholar
  20. Rijkhoff, N., Holsheimer, J., Koldewijn, E., Struijk, J., Kerrebroek, P. V., Debruyne, F., andWijkstra, H. (1994): «Selective stimulation of sacral roots for bladder control: a study by computer modeling»,IEEE Trans.,BME-41, pp. 413–424Google Scholar
  21. Schwarz, J., Reid, G., andBostock, H. (1995): «Action potentials and membrane currents in the human node of ranvier»,Pflugers Arch. Eur. J. Physiol.,430, pp. 283–292CrossRefGoogle Scholar
  22. Stone, J. (1993): «Parallel processing in the visual system» (Plenum Press, New York)Google Scholar
  23. Sweeney, J., Mortimer, J., andDurand, D. (1987): «Modeling of mammalian myelinated nerve for functional neuromuscular stimulation». Proc. IEEE-EMBS 9th Ann. Conf., pp. 1577–1578Google Scholar
  24. Veraart, C., Raftopoulos, C., Mortimer, J., Delbeke, J., Pins, D., Michaux, G., Vanlierde, A., Parrini, S., andWanet-Defalque, M.-C. (1998): «Visual sensations produced by optic nerve stimulation using an implanted self-sizing spiral cuff electrode»,Brain Res.,813, pp. 181–186CrossRefGoogle Scholar
  25. Warman, E., Grill, W., andDurand, D. (1992): «Modeling the effects of electric fields on nerve fibers: determination of excitation thresholds»IEEE Trans.,BME-39, pp. 1244–1254Google Scholar
  26. Wesselink, W., Holsheimer, J., andBoom, H. (1999): «A model of the electrical behaviour of myelinated sensory nerve fibres based on human data»,Med. Biol. Eng. Comput.,37, pp. 228–235Google Scholar

Copyright information

© IFMBE 2000

Authors and Affiliations

  1. 1.Neural Rehabilitation Engineering LaboratoryUniversité Catholique de LouvainBrusselsBelgium
  2. 2.CESAME Applied MechanicsUniversité Catholique de LouvainBrusselsBelgium

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