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      Neuronal Development of Hearing and Language: Cochlear Implants and Critical Periods

      1 , 2 , 3 , 4 , 2 , 5

      Annual Review of Neuroscience

      Annual Reviews

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          Abstract

          The modern cochlear implant (CI) is the most successful neural prosthesis developed to date. CIs provide hearing to the profoundly hearing impaired and allow the acquisition of spoken language in children born deaf. Results from studies enabled by the CI have provided new insights into (a) minimal representations at the periphery for speech reception, (b) brain mechanisms for decoding speech presented in quiet and in acoustically adverse conditions, (c) the developmental neuroscience of language and hearing, and (d) the mechanisms and time courses of intramodal and cross-modal plasticity. Additionally, the results have underscored the interconnectedness of brain functions and the importance of top-down processes in perception and learning. The findings are described in this review with emphasis on the developing brain and the acquisition of hearing and spoken language.

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          Most cited references 121

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          Cortical connectivity and sensory coding.

          The sensory cortex contains a wide array of neuronal types, which are connected together into complex but partially stereotyped circuits. Sensory stimuli trigger cascades of electrical activity through these circuits, causing specific features of sensory scenes to be encoded in the firing patterns of cortical populations. Recent research is beginning to reveal how the connectivity of individual neurons relates to the sensory features they encode, how differences in the connectivity patterns of different cortical cell classes enable them to encode information using different strategies, and how feedback connections from higher-order cortex allow sensory information to be integrated with behavioural context.
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            Speech recognition in noise as a function of the number of spectral channels: comparison of acoustic hearing and cochlear implants.

            Speech recognition was measured as a function of spectral resolution (number of spectral channels) and speech-to-noise ratio in normal-hearing (NH) and cochlear-implant (CI) listeners. Vowel, consonant, word, and sentence recognition were measured in five normal-hearing listeners, ten listeners with the Nucleus-22 cochlear implant, and nine listeners with the Advanced Bionics Clarion cochlear implant. Recognition was measured as a function of the number of spectral channels (noise bands or electrodes) at signal-to-noise ratios of + 15, + 10, +5, 0 dB, and in quiet. Performance with three different speech processing strategies (SPEAK, CIS, and SAS) was similar across all conditions, and improved as the number of electrodes increased (up to seven or eight) for all conditions. For all noise levels, vowel and consonant recognition with the SPEAK speech processor did not improve with more than seven electrodes, while for normal-hearing listeners, performance continued to increase up to at least 20 channels. Speech recognition on more difficult speech materials (word and sentence recognition) showed a marginally significant increase in Nucleus-22 listeners from seven to ten electrodes. The average implant score on all processing strategies was poorer than scores of NH listeners with similar processing. However, the best CI scores were similar to the normal-hearing scores for that condition (up to seven channels). CI listeners with the highest performance level increased in performance as the number of electrodes increased up to seven, while CI listeners with low levels of speech recognition did not increase in performance as the number of electrodes was increased beyond four. These results quantify the effect of number of spectral channels on speech recognition in noise and demonstrate that most CI subjects are not able to fully utilize the spectral information provided by the number of electrodes used in their implant.
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              Better speech recognition with cochlear implants.

              HIGH levels of speech recognition have been achieved with a new sound processing strategy for multielectrode cochlear implants. A cochlear implant system consists of one or more implanted electrodes for direct electrical activation of the auditory nerve, an external speech processor that transforms a microphone input into stimuli for each electrode, and a transcutaneous (rf-link) or percutaneous (direct) connection between the processor and the electrodes. We report here the comparison of the new strategy and a standard clinical processor. The standard compressed analogue (CA) processor presented analogue waveforms simultaneously to all electrodes, whereas the new continuous interleaved sampling (CIS) strategy presented brief pulses to each electrode in a nonoverlapping sequence. Seven experienced implant users, selected for their excellent performance with the CA processor, participated as subjects. The new strategy produced large improvements in the scores of speech reception tests for all subjects. These results have important implications for the treatment of deafness and for minimal representations of speech at the auditory periphery.
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                Author and article information

                Journal
                Annual Review of Neuroscience
                Annu. Rev. Neurosci.
                Annual Reviews
                0147-006X
                1545-4126
                July 08 2019
                July 08 2019
                : 42
                : 1
                : 47-65
                Affiliations
                [1 ]Institute of AudioNeuroTechnology and Department of Experimental Otology, ENT Clinics, Hannover Medical University, 30625 Hannover, Germany;
                [2 ]School of Behavioral and Brain Sciences, The University of Texas at Dallas, Dallas, Texas 75080, USA
                [3 ]School of Medicine and Health Sciences, Macquarie University, Sydney, New South Wales 2109, Australia
                [4 ]Department of Speech and Hearing Science, Arizona State University, Tempe, Arizona 85287, USA
                [5 ]School of Medicine and Pratt School of Engineering, Duke University, Durham, North Carolina 27708, USA
                Article
                10.1146/annurev-neuro-080317-061513
                © 2019

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