Literature DB >> 19110048

Practical model description of peripheral neural excitation in cochlear implant recipients: 5. refractory recovery and facilitation.

Lawrence T Cohen1.   

Abstract

In this paper the neural response to electrical stimulation with short inter-pulse intervals was examined. The refractory recovery of the electrically-evoked compound action potential (ECAP) was recorded using masker pulses with a wide range of currents relative to the probe pulse. The ECAP was recorded in subjects implanted with the Nucleus 24 cochlear implant system (three with straight and two with Contour electrode arrays), using the Neural Response Telemetry (NRT) system. Employing the non-refractory parameters previously obtained in the fourth paper of the series and a two-parameter neural refractory recovery function, the model was fitted to ECAP recovery data for a case where the masker current was high relative to that of the probe and masking assumed to be almost complete. A single pair of refractory parameters, fitted at one probe current, allowed the model to describe quite well the ECAP recovery functions for different probe currents. Facilitatory contributions to the recovery functions, for differing current of masker relative to probe, were quantified by comparing experimental recovery functions with modeled functions that included only refractory behavior. The model should provide the means to improve speech processing algorithms for cochlear implants, by allowing the systematic incorporation of additional information concerning the neural response to electrical stimulation.

Mesh:

Year:  2008        PMID: 19110048     DOI: 10.1016/j.heares.2008.11.007

Source DB:  PubMed          Journal:  Hear Res        ISSN: 0378-5955            Impact factor:   3.208


  12 in total

Review 1.  Temporal Considerations for Stimulating Spiral Ganglion Neurons with Cochlear Implants.

Authors:  Jason Boulet; Mark White; Ian C Bruce
Journal:  J Assoc Res Otolaryngol       Date:  2016-02

2.  Effect of stimulus level on the temporal response properties of the auditory nerve in cochlear implants.

Authors:  Michelle L Hughes; Sarah A Laurello
Journal:  Hear Res       Date:  2017-06-13       Impact factor: 3.208

3.  Encoding and decoding amplitude-modulated cochlear implant stimuli--a point process analysis.

Authors:  Joshua H Goldwyn; Eric Shea-Brown; Jay T Rubinstein
Journal:  J Comput Neurosci       Date:  2010-02-23       Impact factor: 1.621

4.  Temporal Response Properties of the Auditory Nerve in Implanted Children with Auditory Neuropathy Spectrum Disorder and Implanted Children with Sensorineural Hearing Loss.

Authors:  Shuman He; Paul J Abbas; Danielle V Doyle; Tyler C McFayden; Stephen Mulherin
Journal:  Ear Hear       Date:  2016 Jul-Aug       Impact factor: 3.570

5.  The polarity sensitivity of the electrically stimulated human auditory nerve measured at the level of the brainstem.

Authors:  Jaime A Undurraga; Robert P Carlyon; Jan Wouters; Astrid van Wieringen
Journal:  J Assoc Res Otolaryngol       Date:  2013-03-12

6.  Predictions of the Contribution of HCN Half-Maximal Activation Potential Heterogeneity to Variability in Intrinsic Adaptation of Spiral Ganglion Neurons.

Authors:  Jason Boulet; Ian C Bruce
Journal:  J Assoc Res Otolaryngol       Date:  2016-12-09

7.  Characteristics of the Adaptation Recovery Function of the Auditory Nerve and Its Association With Advanced Age in Postlingually Deafened Adult Cochlear Implant Users.

Authors:  Shuman He; Jeffrey Skidmore; Brittney L Carter
Journal:  Ear Hear       Date:  2022-01-27       Impact factor: 3.562

8.  A Phenomenological Model of the Electrically Stimulated Auditory Nerve Fiber: Temporal and Biphasic Response Properties.

Authors:  Colin D F Horne; Christian J Sumner; Bernhard U Seeber
Journal:  Front Comput Neurosci       Date:  2016-02-08       Impact factor: 2.380

9.  Monopolar Detection Thresholds Predict Spatial Selectivity of Neural Excitation in Cochlear Implants: Implications for Speech Recognition.

Authors:  Ning Zhou
Journal:  PLoS One       Date:  2016-10-31       Impact factor: 3.240

10.  Learning Pitch with STDP: A Computational Model of Place and Temporal Pitch Perception Using Spiking Neural Networks.

Authors:  Nafise Erfanian Saeedi; Peter J Blamey; Anthony N Burkitt; David B Grayden
Journal:  PLoS Comput Biol       Date:  2016-04-06       Impact factor: 4.475

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.