Literature DB >> 20685981

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

Muhammad S A Zilany1, Laurel H Carney.   

Abstract

Neurons in the auditory system respond to recent stimulus-level history by adapting their response functions according to the statistics of the stimulus, partially alleviating the so-called "dynamic-range problem." However, the mechanism and source of this adaptation along the auditory pathway remain unknown. Inclusion of power-law dynamics in a phenomenological model of the inner hair cell (IHC)-auditory nerve (AN) synapse successfully explained neural adaptation to sound-level statistics, including the time course of adaptation of the mean firing rate and changes in the dynamic range observed in AN responses. A direct comparison between model responses to a dynamic stimulus and to an "inversely gated" static background suggested that AN dynamic-range adaptation largely results from the adaptation produced by the response history. These results support the hypothesis that the potential mechanism underlying the dynamic-range adaptation observed at the level of the auditory nerve is located peripheral to the spike generation mechanism and central to the IHC receptor potential.

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Year:  2010        PMID: 20685981      PMCID: PMC2935089          DOI: 10.1523/JNEUROSCI.0647-10.2010

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  48 in total

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Authors:  T Moser; D Beutner
Journal:  Proc Natl Acad Sci U S A       Date:  2000-01-18       Impact factor: 11.205

2.  A phenomenological model for the responses of auditory-nerve fibers: I. Nonlinear tuning with compression and suppression.

Authors:  X Zhang; M G Heinz; I C Bruce; L H Carney
Journal:  J Acoust Soc Am       Date:  2001-02       Impact factor: 1.840

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Authors:  H Steven Colburn; Laurel H Carney; Michael G Heinz
Journal:  J Assoc Res Otolaryngol       Date:  2003-09

4.  An auditory-periphery model of the effects of acoustic trauma on auditory nerve responses.

Authors:  Ian C Bruce; Murray B Sachs; Eric D Young
Journal:  J Acoust Soc Am       Date:  2003-01       Impact factor: 1.840

5.  The power law of sensory adaptation: simulation by a model of excitability in spider mechanoreceptor neurons.

Authors:  Andrew S French; Päivi H Torkkeli
Journal:  Ann Biomed Eng       Date:  2007-10-19       Impact factor: 3.934

6.  Specialized neuronal adaptation for preserving input sensitivity.

Authors:  Paul V Watkins; Dennis L Barbour
Journal:  Nat Neurosci       Date:  2008-09-28       Impact factor: 24.884

7.  Input normalization by global feedforward inhibition expands cortical dynamic range.

Authors:  Frédéric Pouille; Antonia Marin-Burgin; Hillel Adesnik; Bassam V Atallah; Massimo Scanziani
Journal:  Nat Neurosci       Date:  2009-11-01       Impact factor: 24.884

8.  Dynamic range adaptation to sound level statistics in the auditory nerve.

Authors:  Bo Wen; Grace I Wang; Isabel Dean; Bertrand Delgutte
Journal:  J Neurosci       Date:  2009-11-04       Impact factor: 6.167

9.  Time course and calcium dependence of transmitter release at a single ribbon synapse.

Authors:  Juan D Goutman; Elisabeth Glowatzki
Journal:  Proc Natl Acad Sci U S A       Date:  2007-10-02       Impact factor: 11.205

10.  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

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  27 in total

1.  Time course of dynamic range adaptation in the auditory nerve.

Authors:  Bo Wen; Grace I Wang; Isabel Dean; Bertrand Delgutte
Journal:  J Neurophysiol       Date:  2012-03-28       Impact factor: 2.714

2.  An active loudness model suggesting tinnitus as increased central noise and hyperacusis as increased nonlinear gain.

Authors:  Fan-Gang Zeng
Journal:  Hear Res       Date:  2012-05-26       Impact factor: 3.208

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Journal:  J Assoc Res Otolaryngol       Date:  2012-04

4.  Speed-invariant encoding of looming object distance requires power law spike rate adaptation.

Authors:  Stephen E Clarke; Richard Naud; André Longtin; Leonard Maler
Journal:  Proc Natl Acad Sci U S A       Date:  2013-07-29       Impact factor: 11.205

5.  Independent population coding of speech with sub-millisecond precision.

Authors:  Jose A Garcia-Lazaro; Lucile A C Belliveau; Nicholas A Lesica
Journal:  J Neurosci       Date:  2013-12-04       Impact factor: 6.167

6.  Neuronal adaptation to sound statistics in the inferior colliculus of behaving macaques does not reduce the effectiveness of the masking noise.

Authors:  Francesca Rocchi; Ramnarayan Ramachandran
Journal:  J Neurophysiol       Date:  2018-09-26       Impact factor: 2.714

7.  Updated parameters and expanded simulation options for a model of the auditory periphery.

Authors:  Muhammad S A Zilany; Ian C Bruce; Laurel H Carney
Journal:  J Acoust Soc Am       Date:  2014-01       Impact factor: 1.840

8.  Tone-in-noise detection using envelope cues: comparison of signal-processing-based and physiological models.

Authors:  Junwen Mao; Laurel H Carney
Journal:  J Assoc Res Otolaryngol       Date:  2014-09-30

9.  Ion channel noise can explain firing correlation in auditory nerves.

Authors:  Bahar Moezzi; Nicolangelo Iannella; Mark D McDonnell
Journal:  J Comput Neurosci       Date:  2016-08-02       Impact factor: 1.621

10.  Adaptation in the auditory system of a beluga whale: effect of adapting sound parameters.

Authors:  Vladimir V Popov; Alexander Ya Supin; Dmitri I Nechaev; Evgenia V Sysueva
Journal:  J Comp Physiol A Neuroethol Sens Neural Behav Physiol       Date:  2019-07-06       Impact factor: 1.836

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