Literature DB >> 19894822

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

Muhammad S A Zilany1, Ian C Bruce, Paul C Nelson, Laurel H Carney.   

Abstract

There is growing evidence that the dynamics of biological systems that appear to be exponential over short time courses are in some cases better described over the long-term by power-law dynamics. A model of rate adaptation at the synapse between inner hair cells and auditory-nerve (AN) fibers that includes both exponential and power-law dynamics is presented here. Exponentially adapting components with rapid and short-term time constants, which are mainly responsible for shaping onset responses, are followed by two parallel paths with power-law adaptation that provide slowly and rapidly adapting responses. The slowly adapting power-law component significantly improves predictions of the recovery of the AN response after stimulus offset. The faster power-law adaptation is necessary to account for the "additivity" of rate in response to stimuli with amplitude increments. The proposed model is capable of accurately predicting several sets of AN data, including amplitude-modulation transfer functions, long-term adaptation, forward masking, and adaptation to increments and decrements in the amplitude of an ongoing stimulus.

Entities:  

Mesh:

Year:  2009        PMID: 19894822      PMCID: PMC2787068          DOI: 10.1121/1.3238250

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


  82 in total

1.  Short-term adaptation and incremental responses of single auditory-nerve fibers.

Authors:  R L Smith; J J Zwislocki
Journal:  Biol Cybern       Date:  1975       Impact factor: 2.086

2.  Short-term adaptation in single auditory nerve fibers: some poststimulatory effects.

Authors:  R L Smith
Journal:  J Neurophysiol       Date:  1977-09       Impact factor: 2.714

3.  Quantal analysis of a decremental response at hair cell-afferent fibre synapses in the goldfish sacculus.

Authors:  T Furukawa; M Kuno; S Matsuura
Journal:  J Physiol       Date:  1982-01       Impact factor: 5.182

4.  Auditory-nerve response from cats raised in a low-noise chamber.

Authors:  M C Liberman
Journal:  J Acoust Soc Am       Date:  1978-02       Impact factor: 1.840

5.  A model of the hair cell-primary fiber complex.

Authors:  S Ross
Journal:  J Acoust Soc Am       Date:  1982-04       Impact factor: 1.840

6.  Effects of stimulus frequency on adaptation in auditory-nerve fibers.

Authors:  P J Abbas
Journal:  J Acoust Soc Am       Date:  1979-01       Impact factor: 1.840

7.  Representation of speech-like sounds in the discharge patterns of auditory-nerve fibers.

Authors:  B Delgutte
Journal:  J Acoust Soc Am       Date:  1980-09       Impact factor: 1.840

8.  The relationship between spike rate and synchrony in responses of auditory-nerve fibers to single tones.

Authors:  D H Johnson
Journal:  J Acoust Soc Am       Date:  1980-10       Impact factor: 1.840

9.  Forward masking of auditory nerve fiber responses.

Authors:  D M Harris; P Dallos
Journal:  J Neurophysiol       Date:  1979-07       Impact factor: 2.714

10.  Adaptive rundown of excitatory post-synaptic potentials at synapses between hair cells and eight nerve fibres in the goldfish.

Authors:  T Furukawa; S Matsuura
Journal:  J Physiol       Date:  1978-03       Impact factor: 5.182

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  112 in total

1.  A point process framework for modeling electrical stimulation of the auditory nerve.

Authors:  Joshua H Goldwyn; Jay T Rubinstein; Eric Shea-Brown
Journal:  J Neurophysiol       Date:  2012-06-06       Impact factor: 2.714

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.  Implications of within-fiber temporal coding for perceptual studies of F0 discrimination and discrimination of harmonic and inharmonic tone complexes.

Authors:  Sushrut Kale; Christophe Micheyl; Michael G Heinz
Journal:  J Assoc Res Otolaryngol       Date:  2014-06

4.  Speech enhancement for listeners with hearing loss based on a model for vowel coding in the auditory midbrain.

Authors:  Akshay Rao; Laurel H Carney
Journal:  IEEE Trans Biomed Eng       Date:  2014-03-25       Impact factor: 4.538

5.  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

6.  Modeling the anti-masking effects of the olivocochlear reflex in auditory nerve responses to tones in sustained noise.

Authors:  Ananthakrishna Chintanpalli; Skyler G Jennings; Michael G Heinz; Elizabeth A Strickland
Journal:  J Assoc Res Otolaryngol       Date:  2012-04

7.  Evidence for a neural source of the precedence effect in sound localization.

Authors:  Andrew D Brown; Heath G Jones; Alan Kan; Tanvi Thakkar; G Christopher Stecker; Matthew J Goupell; Ruth Y Litovsky
Journal:  J Neurophysiol       Date:  2015-09-23       Impact factor: 2.714

8.  Predictions of diotic tone-in-noise detection based on a nonlinear optimal combination of energy, envelope, and fine-structure cues.

Authors:  Junwen Mao; Azadeh Vosoughi; Laurel H Carney
Journal:  J Acoust Soc Am       Date:  2013-07       Impact factor: 1.840

9.  Predicting spike timing in highly synchronous auditory neurons at different sound levels.

Authors:  Bertrand Fontaine; Victor Benichoux; Philip X Joris; Romain Brette
Journal:  J Neurophysiol       Date:  2013-07-17       Impact factor: 2.714

10.  Adaptive temporal encoding leads to a background-insensitive cortical representation of speech.

Authors:  Nai Ding; Jonathan Z Simon
Journal:  J Neurosci       Date:  2013-03-27       Impact factor: 6.167

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