Development of a Model of the Electrically Stimulated Cochlea

  • Waldo Nogueira
  • Waldemar Würfel
  • Richard T. Penninger
  • Andreas Büchner
Part of the Lecture Notes in Applied and Computational Mechanics book series (LNACM, volume 74)


Cochlear Implants (CIs) are implantable medical devices that can restore the sense of hearing in people with profound sensorineural hearing loss. Clinical trials assessing speech intelligibility in CI users have found large inter subject variability. One possibility to explain the variability are the individual differences in the interface created between electrodes and the auditory nerve. For example, the exact position of the electrodes in each cochlea may differ from one patient to another. Additionally the amount of functional auditory neurons might also vary considerably between CI users. In order to understand the variability, models of the voltage distribution of the electrically stimulated cochlea may be useful. With this purpose we have developed a model that allows to simulate the voltage distribution at different positions on the auditory nerve. Simulations show differences in the extracellular voltage of the spiral ganglions depending on the electrode positions and the cochlear size, which might explain some of the variability. Finally, the model of the electrically stimulated cochlea has been used to simulate the extracellular voltage patterns produced by different instrumental sounds. These patterns have been inserted in an automatic instrument classifier that helps to illustrate the mentioned variability.


Cochlear implant Finite element method Electric field Cochlea Sound coding strategy Instrument identification 


  1. 1.
    Berenstein, C.K., Mens, L.H., Mulder, J.J., Vanpoucke, F.J.: Current steering and current focusing in cochlear implants: Comparison of monopolar, tripolar, and virtual channel electrode configurations. Ear Hear. 29, 250–260 (2008)CrossRefGoogle Scholar
  2. 2.
    Berenstein, C.K., Vanpoucke, F.J., Mulder, J.J., Mens, L.H.: Electric field imaging as a means to predict the loudness of monopolar and tripolar stimuli in cochlear implant recipients. Hear. Res. 270, 28–38 (2010)CrossRefGoogle Scholar
  3. 3.
    Briaire, J.J.: Cochlear implants from model to patients, Thesis, ISBN 978-90-9023555-4, Universiteit Leiden (2008)Google Scholar
  4. 4.
    Colletti, L., Mandal, M., Colletti, V.: Cochlear implants in children younger than 6 months. Otolaryngol. Head Neck Surg. Off J. Am. Acad. Otolaryngol. Head Neck Surg. 147(1), 139–146 (2012)CrossRefGoogle Scholar
  5. 5.
    Escudé, B., James, C., Deguine, O., Cochard, N., Eter, E., Fraysse, B.: The size of the cochlea and predictions of insertion depth angles for cochlear implant electrodes. Audiol. Neurotology 11(suppl 1), 27–33 (2006)CrossRefGoogle Scholar
  6. 6.
    Finley, C., Wilson, B., White, M.: Models of neural responsiveness to electrical stimulation. In: Miller, J., Spelman, F. (eds.) Cochlear Implants, pp. 55–96. Springer New York (1990)Google Scholar
  7. 7.
    Frijns, J.H.M., de Snoo, S.L., ten Kate, J.H.: Spatial selectivity in a rotationally symmetric model of the electrically stimulated cochlea. Hear. Res. 95, 33–48 (1996)CrossRefGoogle Scholar
  8. 8.
    Frijns, J.H.M., de Snoo, S.L., Schoonhoven, R.: Potential distributions and neural excitation pattervs in a rotationally symmetric model of the electrically stimulated cochlea. Hear. Res. 87, 170–186 (1995)CrossRefGoogle Scholar
  9. 9.
    Greenwood, D.D.: A cochlear frequency-position function for several species- 29 years later. J. Acoust. Soc. Am. 87, 2592–2605 (1990)CrossRefGoogle Scholar
  10. 10.
    Hanekom, T.: Thesis—cochlea modelling. In: Faculty of Engineering, built Environment and Information Technology. University of Pretoria, Pretoria (2001)Google Scholar
  11. 11.
    Hughes, M.L., Vander Werff, K.R., Brown, C.J., Abbas, P.J., Kelsay, D.M., Teagle, H.F., Lowder, M.W.: A longitudinal study of electrode impedance, the electrically evoked compound action potential, and behavioral measures in nucleus 24 cochlear implant users. Ear Hear. 22, 471–486 (2001)CrossRefGoogle Scholar
  12. 12.
    Mens, L.H., Boyle, P.J., Mulder, J.J.: The Clarion electrode positioner: Approximation to the medial wall and current focussing. Audiol. Neurotol. 8, 166–175 (2003)CrossRefGoogle Scholar
  13. 13.
    Nogueira, W., Bchner, A., Lenarz, Th, Edler, B.: A psychoacoustic, “NofM”-type speech coding strategy for cochlear implants. EURASIP J. Adv. Sig. Process. 2005, 101–672 (2005)Google Scholar
  14. 14.
    Nogueira, W., Litvak, L., Edler, B., Ostermann, J., Bchner, A.: Signal processing strategies for cochlear implants using current steering. EURASIP J. Advan. Sig. Process. 2009, 213–531 (2009)Google Scholar
  15. 15.
    De Raeve, L.A.: Longitudinal study on auditory perception and speech intelligibility in deaf children implanted younger than 18 months in comparison to those implanted at later ages. Otol Neurotol 31(8), 1261–1267 (2010)CrossRefGoogle Scholar
  16. 16.
    Rattay, F., Leao, R.N., Felix, H.: A model of the electrically excited human cochlear neuron. II. Influence of the three-dimensional cochlear structure on neural excitability. Hear. Res. 153, 64–79 (2001)CrossRefGoogle Scholar
  17. 17.
    Saba, R.: “Cohlear implant modelling: Stimulation and power consumption”, Thesis, university of Southampton. Faculty of Engineering and Environment, Institute of Sound and Vibration (2012)Google Scholar
  18. 18.
    Sakoe, H., Chiba, S.: Dynamic programming algorithm optimization for spoken work recognition. IEEE Trans. Acoust. Speech Signal Process. 26(1), 43–49 (1993)CrossRefGoogle Scholar
  19. 19.
    Shannon, R.V., Fu, Q.J., Galvin III, J.: The number of spectral channels required for speech recognition depends on the difficulty of the listening situation Acta Otolaryngol. Suppl. 552, 50–54 (2004)Google Scholar
  20. 20.
    Smit, J.E., Hanekom, T., Hanekom, J.J.: Predicting action potential characteristics of human auditory nerve fibers through modifications of the Hudgkin-Huxley equations. S. Afr. J. Sci. 104, 284–292 (2008)Google Scholar
  21. 21.
    Wilson, B.S., Finley, C.C., Lawson, D.T., Wolford, R.D., Eddington, D.K., Rabinowitz, W.M.: Better speech recognition with cochlear I plants. Nature 352, 236–238 (1991)CrossRefGoogle Scholar
  22. 22.
    Wilson, B.S., Dorman, M.F.: “Cochlear implants: A remarkable past and a brilliant future”. In: Proceedings of the 9th International Conference on Cochlear Implants and Related Sciences, pp. 3–21. Elsevier Science Bv, Vienna, AUSTRIA (1996)Google Scholar
  23. 23.
    Würfel, W., Lanfermann, H., Lenarz, T., Majdani, O.: “Cochlear length determination using Cone Beam Computed Tomography in a clincal setting”, Hear. Res. 316, 65–72 (2014)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Waldo Nogueira
    • 1
  • Waldemar Würfel
    • 1
  • Richard T. Penninger
    • 1
  • Andreas Büchner
    • 1
  1. 1.Department of OtolaryngologyMedical School Hannover, Cluster of Excellence “Hearing4all”HannoverGermany

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