Neural modelling to relate individual differences in physiological and perceptual responses with sensorineural hearing loss

  • Michael G. Heinz Department of Speech, Language, and Hearing Sciences, Purdue University, West Lafayette, IN, USA Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA

Abstract

A great challenge in diagnosing and treating hearing impairment comes from the fact that people with similar degrees of hearing loss often have different speech-recognition abilities. Many studies of the perceptual consequences of peripheral damage have focused on outer-hair-cell (OHC) effects; however, anatomical and physiological studies suggest that many common forms of sensorineural hearing loss (SNHL) arise from mixed OHC and inner-hair-cell (IHC) dysfunction. Thus, individual differences in perceptual consequences of hearing impairment may be better explained by a more detailed understanding of differential effects of OHC/IHC dysfunction on neural coding of perceptually relevant sounds. Whereas it is difficult experimentally to estimate or control the degree of OHC/IHC dysfunction in individual subjects, computational neural models provide great potential for predicting systematically the complicated physiological effects of combined OHC/IHC dysfunction. Here, important physiological effects in auditory-nerve (AN) responses following different types of SNHL and the ability of current models to capture these effects are reviewed. In addition, a new approach is presented for computing spike-train metrics of speech-in-noise envelope coding to predict how differential physiological effects may contribute to individual differences in speech intelligibility.

References

Axe, D.R. and Heinz, M.G. (2015). “The effects of carboplatin-induced ototoxicity on temporal coding in the auditory nerve,” Assoc. Res. Otolaryngol. Abstr., 38, 76-77.

Biondi, E. and Schmid, R. (1972). “Mathematical models and prostheses for sense organs,” in Theory and Applications of Variable Structure Systems. Eds. R.R. Mohler and A. Ruberti (Academic Press, London), pp. 183-211.

Biondi, E. (1978). “Auditory processing of speech and its implications with respect to prosthetic rehabilitation. The bioengineering viewpoint,” Audiology, 17, 43-50.

Bondy, J., Becker, S., Bruce, I.C., Trainor, L., and Haykin, S. (2004). “A novel signal-processing strategy for hearing-aid design: Neurocompensation,” Signal Process., 84, 1239-1253.

Bruce, I.C., Sachs, M.B., and Young, E.D. (2003). “An auditory-periphery model of the effects of acoustic trauma on auditory nerve responses,” J. Acoust. Soc. Am., 113, 369-388.

Carney, L.H. (1993). “A model for the responses of low-frequency auditory-nerve fibers in cat,” J. Acoust. Soc. Am., 93, 401-417.

Edwards, B. (2004). “Hearing aids and hearing impairment,” in Speech Processing in the Auditory System. Ed. S. Greenberg, W.A. Ainsworth, A.N. Popper, and R.R. Fay (Springer, New York), pp. 339-421.

Elhilali, M., Chi, T., and Shamma, S.A. (2003). “A spectro-temporal modulation index (STMI) for assessment of speech intelligibility,” Speech Commun., 41, 331-348.

Harrison, R.V. (1981). “Rate-versus-intensity functions and related AP responses in normal and pathological guinea pig and human cochleas,” J. Acoust. Soc. Am., 70, 1036-1044.

Heinz, M.G., Colburn, H.S., and Carney, L.H. (2001). “Evaluating auditory performance limits: I One-parameter discrimination using a computational model for the auditory nerve,” Neural Comput., 13, 2273-2316.

Heinz, M.G. and Young, E.D. (2004). “Response growth with sound level in auditory-nerve fibers after noise-induced hearing loss,” J. Neurophysiol., 91, 784-795.

Heinz, M.G., Issa, J.B., and Young, E.D. (2005). “Auditory-nerve rate responses are inconsistent with common hypotheses for the neural correlates of loudness recruitment,” J. Assoc. Res. Otolaryngol., 6, 91-105.

Heinz, M.G. (2010). “Computational Modeling of Sensorineural Hearing Loss,” in Computational Models of the Auditory System, Eds. R. Meddis, E.A. Lopez-Poveda, A.N. Popper, and R.R. Fay (Springer, New York), pp. 177-202.

Hines, A. and Harte, N. (2012). “Speech intelligibility prediction using a Neurogram Similarity Index Measure,” Speech Commun., 54, 306-320.

Jørgensen, S. and Dau, T. (2011). “Predicting speech intelligibility based on the signal-to-noise envelope power ratio after modulation-frequency selective processing,” J. Acoust. Soc. Am., 130, 1475-1487.

Kates, J.M. (1991). “A time-domain digital cochlear model,” IEEE Trans. Signal Process., 39, 2573-2592.

Kujawa, S.G. and Liberman, M.C. (2015). “Synaptopathy in the noise-exposed and aging cochlea: Primary neural degeneration in acquired sensorineural hearing loss,” Hear. Res., 330, 191-199.

Liberman, M.C. and Dodds, L.W. (1984). “Single-neuron labeling and chronic cochlear pathology III Stereocilia damage and alterations of threshold tuning curves,” Hear. Res., 16, 55-74.

Liberman, M.C. and Kiang, N.Y.S. (1984). “Single-neuron labeling and chronic cochlear pathology IV Stereocilia damage and alterations in rate- and phase-level functions,” Hear. Res., 16, 75-90.

Louage, D.H., van der Heijden, M., and Joris, P.X. (2004). “Temporal properties of res-ponses to broadband noise in the auditory nerve,” J. Neurophysiol., 91, 2051-2065.

Miller, R.L., Schilling, J.R., Franck, K.R., and Young, E.D. (1997). “Effects of acoustic trauma on the representation of the vowel /ε/ in cat auditory nerve fibers,” J. Acoust. Soc. Am., 101, 3602-3616.

Moore, B.C.J. (1995). Perceptual Consequences of Cochlear Damage (Oxford University Press, New York).
Oxenham, A.J. and Bacon, S.P. (2003). “Cochlear compression: Perceptual measures and implications for normal and impaired hearing,” Ear Hearing, 24, 352-366.

Patuzzi, R. (1996). “Cochlear micromechanics and macromechanics,” in The Cochlea. Eds. P. Dallos, A.N. Popper, and R.R. Fay (Springer, New York), pp. 186-257.

Saremi, A. and Stenfelt, S. (2013). “Effect of metabolic presbyacusis on cochlear responses: A simulation approach using a physiologically-based model,” J. Acoust. Soc. Am., 134, 2833-2851.

Schmiedt, R.A., Lang, H., Okamura, H.O., and Schulte, B.A. (2002). “Effects of furosemide applied chronically to the round window: A model of metabolic presbyacusis,” J. Neurosci., 22, 9643-9650.

Sewell, W.F. (1984). “The effects of furosemide on the endocochlear potential and auditory-nerve fiber tuning curves in cats,” Hear. Res., 14, 305-314.

Swaminathan, J. and Heinz, M.G. (2011). “Predicted effects of sensorineural hearing loss on across-fiber envelope coding in the auditory nerve,” J. Acoust. Soc. Am., 129, 4001-4013.

Wake, M., Takeno, S., Ibrahim, D., and Harrison, R. (1994). “Selective inner hair cell ototoxicity induced by carboplatin,” Laryngoscope, 104, 488-493.

Wang, J., Powers, N., Hofstetter, P., Trautwein, P., Ding, D., and Salvi, R. (1997). “Effects of selective inner hair cell loss on auditory nerve fiber threshold, tuning and spontaneous and driven discharge rate,” Hear. Res., 107, 67-82.

Zilany, M.S.A. and Bruce, I.C. (2006). “Modeling auditory-nerve responses for high sound pressure levels in the normal and impaired auditory periphery,” J. Acoust. Soc. Am., 120, 1446-1466.

Zilany, M.S.A., Bruce, I.C., Nelson, P.C., and Carney, L.H. (2009). “A phenomenological model of the synapse between the inner hair cell and auditory nerve: Long-term adaptation with power-law dynamics,” J. Acoust. Soc. Am., 126, 2390-2412.

Zilany, M.S.A., Bruce, I.C., and Carney, L.H. (2014). “Updated parameters and expanded simulation options for a model of the auditory periphery,” J. Acoust. Soc. Am., 135, 283-286.
Published
2015-12-15
How to Cite
HEINZ, Michael G.. Neural modelling to relate individual differences in physiological and perceptual responses with sensorineural hearing loss. Proceedings of the International Symposium on Auditory and Audiological Research, [S.l.], v. 5, p. 137-148, dec. 2015. Available at: <https://proceedings.isaar.eu/index.php/isaarproc/article/view/2015-16>. Date accessed: 20 nov. 2017.