Auditory Midbrain Implant: A Review
Author(s) -
Hubert H. Lim,
Minoo Lenarz,
Thomas Lenarz
Publication year - 2009
Publication title -
trends in amplification
Language(s) - English
Resource type - Journals
eISSN - 1940-5588
pISSN - 1084-7138
DOI - 10.1177/1084713809348372
Subject(s) - inferior colliculus , cochlear implant , speech perception , implant , neural prosthesis , set (abstract data type) , perception , audiology , medicine , computer science , psychology , neuroscience , surgery , nucleus , programming language
The auditory midbrain implant (AMI) is a new hearing prosthesis designed for stimulation of the inferior colliculus in deaf patients who cannot sufficiently benefit from cochlear implants. The authors have begun clinical trials in which five patients have been implanted with a single shank AMI array (20 electrodes). The goal of this review is to summarize the development and research that has led to the translation of the AMI from a concept into the first patients. This study presents the rationale and design concept for the AMI as well a summary of the animal safety and feasibility studies that were required for clinical approval. The authors also present the initial surgical, psychophysical, and speech results from the first three implanted patients. Overall, the results have been encouraging in terms of the safety and functionality of the implant. All patients obtain improvements in hearing capabilities on a daily basis. However, performance varies dramatically across patients depending on the implant location within the midbrain with the best performer still not able to achieve open set speech perception without lip-reading cues. Stimulation of the auditory midbrain provides a wide range of level, spectral, and temporal cues, all of which are important for speech understanding, but they do not appear to sufficiently fuse together to enable open set speech perception with the currently used stimulation strategies. Finally, several issues and hypotheses for why current patients obtain limited speech perception along with several feasible solutions for improving AMI implementation are presented.
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