Literature DB >> 16240815

Analysis of models for the synapse between the inner hair cell and the auditory nerve.

Xuedong Zhang1, Laurel H Carney.   

Abstract

A general mathematical approach was proposed to study phenomenological models of the inner-hair-cell and auditory-nerve (AN) synapse complex. Two models (Meddis, 1986; Westerman and Smith, 1988) were studied using this unified approach. The responses of both models to a constant-intensity stimulus were described mathematically, and the relationship between model parameters and response characteristics was investigated. The mathematical descriptions of the two models were essentially equivalent despite their structural differences. This analytical approach was used to study the effects of adaptation characteristics on model parameters and of model parameters on adaptation characteristics. The results provided insights into these models and the underlying biophysical processing. This analytical method was also used to study offset adaptation, and it was found that the offset adaptation of both models was limited by the models' structures. A modified version of the synapse model, which has the same onset adaptation but improved offset adaptation, is proposed here. This modified synapse model produces more physiologically realistic offset adaptation and also enhances the modulation gain of model AN fiber responses, consistent with AN physiology.

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Year:  2005        PMID: 16240815     DOI: 10.1121/1.1993148

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  10 in total

1.  Auditory information coding by modeled cochlear nucleus neurons.

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Journal:  J Comput Neurosci       Date:  2010-09-23       Impact factor: 1.621

2.  Functional modeling of the human auditory brainstem response to broadband stimulation.

Authors:  Sarah Verhulst; Hari M Bharadwaj; Golbarg Mehraei; Christopher A Shera; Barbara G Shinn-Cunningham
Journal:  J Acoust Soc Am       Date:  2015-09       Impact factor: 1.840

3.  Changes across time in spike rate and spike amplitude of auditory nerve fibers stimulated by electric pulse trains.

Authors:  Fawen Zhang; Charles A Miller; Barbara K Robinson; Paul J Abbas; Ning Hu
Journal:  J Assoc Res Otolaryngol       Date:  2007-06-12

4.  Quantifying envelope and fine-structure coding in auditory nerve responses to chimaeric speech.

Authors:  Michael G Heinz; Jayaganesh Swaminathan
Journal:  J Assoc Res Otolaryngol       Date:  2009-04-14

5.  Investigating the auditory enhancement phenomenon using behavioral temporal masking patterns.

Authors:  Yi Shen; Virginia M Richards
Journal:  J Acoust Soc Am       Date:  2012-11       Impact factor: 1.840

6.  Power-law dynamics in an auditory-nerve model can account for neural adaptation to sound-level statistics.

Authors:  Muhammad S A Zilany; Laurel H Carney
Journal:  J Neurosci       Date:  2010-08-04       Impact factor: 6.167

7.  Mismatch negativity and adaptation measures of the late auditory evoked potential in cochlear implant users.

Authors:  Fawen Zhang; Theresa Hammer; Holly-Lolan Banks; Chelsea Benson; Jing Xiang; Qian-Jie Fu
Journal:  Hear Res       Date:  2010-12-01       Impact factor: 3.208

8.  A phenomenological model of the synapse between the inner hair cell and auditory nerve: long-term adaptation with power-law dynamics.

Authors:  Muhammad S A Zilany; Ian C Bruce; Paul C Nelson; Laurel H Carney
Journal:  J Acoust Soc Am       Date:  2009-11       Impact factor: 1.840

Review 9.  Modeling auditory coding: from sound to spikes.

Authors:  Marek Rudnicki; Oliver Schoppe; Michael Isik; Florian Völk; Werner Hemmert
Journal:  Cell Tissue Res       Date:  2015-06-07       Impact factor: 5.249

10.  A hardware model of the auditory periphery to transduce acoustic signals into neural activity.

Authors:  Takashi Tateno; Jun Nishikawa; Nobuyoshi Tsuchioka; Hirofumi Shintaku; Satoyuki Kawano
Journal:  Front Neuroeng       Date:  2013-11-26
  10 in total

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