Literature DB >> 12621339

Coding of sounds in the auditory system and its relevance to signal processing and coding in cochlear implants.

Brian C J Moore1.   

Abstract

OBJECTIVE: To review how the properties of sounds are "coded" in the normal auditory system and to discuss the extent to which cochlear implants can and do represent these codes. DATA SOURCES: Data are taken from published studies of the response of the cochlea and auditory nerve to simple and complex stimuli, in both the normal and the electrically stimulated ear. REVIEW CONTENT: The review describes: 1) the coding in the normal auditory system of overall level (which partly determines perceived loudness), spectral shape (which partly determines perceived timbre and the identity of speech sounds), periodicity (which partly determines pitch), and sound location; 2) the role of the active mechanism in the cochlea, and particularly the fast-acting compression associated with that mechanism; 3) the neural response patterns evoked by cochlear implants; and 4) how the response patterns evoked by implants differ from those observed in the normal auditory system in response to sound. A series of specific issues is then discussed, including: 1) how to compensate for the loss of cochlear compression; 2) the effective number of independent channels in a normal ear and in cochlear implantees; 3) the importance of independence of responses across neurons; 4) the stochastic nature of normal neural responses; 5) the possible role of across-channel coincidence detection; and 6) potential benefits of binaural implantation.
CONCLUSIONS: Current cochlear implants do not adequately reproduce several aspects of the neural coding of sound in the normal auditory system. Improved electrode arrays and coding systems may lead to improved coding and, it is hoped, to better performance.

Mesh:

Year:  2003        PMID: 12621339     DOI: 10.1097/00129492-200303000-00019

Source DB:  PubMed          Journal:  Otol Neurotol        ISSN: 1531-7129            Impact factor:   2.311


  34 in total

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Authors:  Kate Helms Tillery; Christopher A Brown; Sid P Bacon
Journal:  J Acoust Soc Am       Date:  2012-01       Impact factor: 1.840

2.  Development and evaluation of methods for assessing tone production skills in Mandarin-speaking children with cochlear implants.

Authors:  Ning Zhou; Li Xu
Journal:  J Acoust Soc Am       Date:  2008-03       Impact factor: 1.840

3.  Lexical tone recognition with an artificial neural network.

Authors:  Ning Zhou; Wenle Zhang; Chao-Yang Lee; Li Xu
Journal:  Ear Hear       Date:  2008-06       Impact factor: 3.570

4.  Vocal singing by prelingually-deafened children with cochlear implants.

Authors:  Li Xu; Ning Zhou; Xiuwu Chen; Yongxin Li; Heather M Schultz; Xiaoyan Zhao; Demin Han
Journal:  Hear Res       Date:  2009-06-26       Impact factor: 3.208

5.  Selective Neuronal Activation by Cochlear Implant Stimulation in Auditory Cortex of Awake Primate.

Authors:  Luke A Johnson; Charles C Della Santina; Xiaoqin Wang
Journal:  J Neurosci       Date:  2016-12-07       Impact factor: 6.167

6.  Spatial hearing benefits demonstrated with presentation of acoustic temporal fine structure cues in bilateral cochlear implant listeners.

Authors:  Tyler H Churchill; Alan Kan; Matthew J Goupell; Ruth Y Litovsky
Journal:  J Acoust Soc Am       Date:  2014-09       Impact factor: 1.840

7.  Effects of age on melody and timbre perception in simulations of electro-acoustic and cochlear-implant hearing.

Authors:  Kathryn H Arehart; Naomi B H Croghan; Ramesh Kumar Muralimanohar
Journal:  Ear Hear       Date:  2014 Mar-Apr       Impact factor: 3.570

8.  MUSIC APPRECIATION AND TRAINING FOR COCHLEAR IMPLANT RECIPIENTS: A REVIEW.

Authors:  Valerie Looi; Kate Gfeller; Virginia Driscoll
Journal:  Semin Hear       Date:  2012-11-19

9.  Relationship between tone perception and production in prelingually deafened children with cochlear implants.

Authors:  Ning Zhou; Juan Huang; Xiuwu Chen; Li Xu
Journal:  Otol Neurotol       Date:  2013-04       Impact factor: 2.311

10.  Recognition of lexical tone production of children with an artificial neural network.

Authors:  Li Xu; Xiuwu Chen; Ning Zhou; Yongxin Li; Xiaoyan Zhao; Demin Han
Journal:  Acta Otolaryngol       Date:  2007-04       Impact factor: 1.494

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