Literature DB >> 19774412

A model of incomplete adaptation to a severely shifted frequency-to-electrode mapping by cochlear implant users.

Elad Sagi1, Qian-Jie Fu, John J Galvin, Mario A Svirsky.   

Abstract

In the present study, a computational model of phoneme identification was applied to data from a previous study, wherein cochlear implant (CI) users' adaption to a severely shifted frequency allocation map was assessed regularly over 3 months of continual use. This map provided more input filters below 1 kHz, but at the expense of introducing a downwards frequency shift of up to one octave in relation to the CI subjects' clinical maps. At the end of the 3-month study period, it was unclear whether subjects' asymptotic speech recognition performance represented a complete or partial adaptation. To clarify the matter, the computational model was applied to the CI subjects' vowel identification data in order to estimate the degree of adaptation, and to predict performance levels with complete adaptation to the frequency shift. Two model parameters were used to quantify this adaptation; one representing the listener's ability to shift their internal representation of how vowels should sound, and the other representing the listener's uncertainty in consistently recalling these representations. Two of the three CI users could shift their internal representations towards the new stimulation pattern within 1 week, whereas one could not do so completely even after 3 months. Subjects' uncertainty for recalling these representations increased substantially with the frequency-shifted map. Although this uncertainty decreased after 3 months, it remained much larger than subjects' uncertainty with their clinically assigned maps. This result suggests that subjects could not completely remap their phoneme labels, stored in long-term memory, towards the frequency-shifted vowels. The model also predicted that even with complete adaptation, the frequency-shifted map would not have resulted in improved speech understanding. Hence, the model presented here can be used to assess adaptation, and the anticipated gains in speech perception expected from changing a given CI device parameter.

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Year:  2009        PMID: 19774412      PMCID: PMC2820204          DOI: 10.1007/s10162-009-0187-6

Source DB:  PubMed          Journal:  J Assoc Res Otolaryngol        ISSN: 1438-7573


  16 in total

1.  Effects of electrode configuration and frequency allocation on vowel recognition with the Nucleus-22 cochlear implant.

Authors:  Q J Fu; R V Shannon
Journal:  Ear Hear       Date:  1999-08       Impact factor: 3.570

2.  Recognition of spectrally degraded and frequency-shifted vowels in acoustic and electric hearing.

Authors:  Q J Fu; R V Shannon
Journal:  J Acoust Soc Am       Date:  1999-03       Impact factor: 1.840

3.  Frequency-place compression and expansion in cochlear implant listeners.

Authors:  Deniz Başkent; Robert V Shannon
Journal:  J Acoust Soc Am       Date:  2004-11       Impact factor: 1.840

4.  Interactions between cochlear implant electrode insertion depth and frequency-place mapping.

Authors:  Deniz Başkent; Robert V Shannon
Journal:  J Acoust Soc Am       Date:  2005-03       Impact factor: 1.840

5.  Dual-electrode pitch discrimination with sequential interleaved stimulation by cochlear implant users.

Authors:  Bom Jun Kwon; Chris van den Honert
Journal:  J Acoust Soc Am       Date:  2006-07       Impact factor: 1.840

6.  Perceptual adaptation to spectrally shifted vowels: training with nonlexical labels.

Authors:  Tianhao Li; Qian-Jie Fu
Journal:  J Assoc Res Otolaryngol       Date:  2006-11-28

7.  Intensity perception. I. Preliminary theory of intensity resolution.

Authors:  N I Durlach; L D Braida
Journal:  J Acoust Soc Am       Date:  1969-08       Impact factor: 1.840

8.  Relearning sound localization with new ears.

Authors:  P M Hofman; J G Van Riswick; A J Van Opstal
Journal:  Nat Neurosci       Date:  1998-09       Impact factor: 24.884

9.  Acoustic characteristics of American English vowels.

Authors:  J Hillenbrand; L A Getty; M J Clark; K Wheeler
Journal:  J Acoust Soc Am       Date:  1995-05       Impact factor: 1.840

10.  The right information may matter more than frequency-place alignment: simulations of frequency-aligned and upward shifting cochlear implant processors for a shallow electrode array insertion.

Authors:  Andrew Faulkner; Stuart Rosen; Clare Norman
Journal:  Ear Hear       Date:  2006-04       Impact factor: 3.570

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  22 in total

1.  Current and planned cochlear implant research at New York University Laboratory for Translational Auditory Research.

Authors:  Mario A Svirsky; Matthew B Fitzgerald; Arlene Neuman; Elad Sagi; Chin-Tuan Tan; Darlene Ketten; Brett Martin
Journal:  J Am Acad Audiol       Date:  2012-06       Impact factor: 1.664

2.  Improving melody recognition in cochlear implant recipients through individualized frequency map fitting.

Authors:  Walter Di Nardo; Alessandro Scorpecci; Sara Giannantonio; Francesca Cianfrone; Gaetano Paludetti
Journal:  Eur Arch Otorhinolaryngol       Date:  2010-07-16       Impact factor: 2.503

3.  A new software tool to optimize frequency table selection for cochlear implants.

Authors:  Daniel Jethanamest; Chin-Tuan Tan; Matthew B Fitzgerald; Mario A Svirsky
Journal:  Otol Neurotol       Date:  2010-10       Impact factor: 2.311

4.  The neural encoding of formant frequencies contributing to vowel identification in normal-hearing listeners.

Authors:  Jong Ho Won; Kelly Tremblay; Christopher G Clinard; Richard A Wright; Elad Sagi; Mario Svirsky
Journal:  J Acoust Soc Am       Date:  2016-01       Impact factor: 1.840

5.  Deactivating cochlear implant electrodes to improve speech perception: A computational approach.

Authors:  Elad Sagi; Mario A Svirsky
Journal:  Hear Res       Date:  2018-10-19       Impact factor: 3.208

6.  A mathematical model of medial consonant identification by cochlear implant users.

Authors:  Mario A Svirsky; Elad Sagi; Ted A Meyer; Adam R Kaiser; Su Wooi Teoh
Journal:  J Acoust Soc Am       Date:  2011-04       Impact factor: 1.840

7.  A mathematical model of vowel identification by users of cochlear implants.

Authors:  Elad Sagi; Ted A Meyer; Adam R Kaiser; Su Wooi Teoh; Mario A Svirsky
Journal:  J Acoust Soc Am       Date:  2010-02       Impact factor: 1.840

8.  A Smartphone Application for Customized Frequency Table Selection in Cochlear Implants.

Authors:  Daniel Jethanamest; Mahan Azadpour; Annette M Zeman; Elad Sagi; Mario A Svirsky
Journal:  Otol Neurotol       Date:  2017-09       Impact factor: 2.311

9.  Contribution of formant frequency information to vowel perception in steady-state noise by cochlear implant users.

Authors:  Elad Sagi; Mario A Svirsky
Journal:  J Acoust Soc Am       Date:  2017-02       Impact factor: 1.840

10.  Initial Operative Experience and Short-term Hearing Preservation Results With a Mid-scala Cochlear Implant Electrode Array.

Authors:  Maja Svrakic; J Thomas Roland; Sean O McMenomey; Mario A Svirsky
Journal:  Otol Neurotol       Date:  2016-12       Impact factor: 2.311

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