Literature DB >> 9916763

Wideband inhibition of dorsal cochlear nucleus type IV units in cat: a computational model.

K E Hancock1, H F Voigt.   

Abstract

A computational model of a portion of dorsal cochlear nucleus neural circuitry was used to investigate relationships between connectivity and response properties of type IV units. The model in this study consists of four neural populations. The pattern of convergence from one population to another and the strengths of those connections are the most important model parameters. Lumped parameter electrical circuit models represent individual cells. Interconnections are achieved by activating variable conductances in post-synaptic cells according to spike activity in pre-synaptic cells. Auditory nerve fibers are incorporated as a bank of logarithmically spaced gammatone filters that drive compartmental models of inner hair cell function. While it might be possible to configure the model without wideband inhibition to simulate type IV unit notch noise responses, the resulting parameters would likely be physiologically implausible. The model with wideband inhibition, however, shows the appropriate notch noise behavior. A wide variety of simulated rate versus cutoff-frequency plots are achieved varying three model parameters. The model was fit to physiological data by finding values of these three parameters that minimize the sum of squared errors. The results show that wideband inhibition can quantitatively account for the responses of type IV units to notch noise.

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Year:  1999        PMID: 9916763     DOI: 10.1114/1.150

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  6 in total

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Journal:  J Acoust Soc Am       Date:  2010-05       Impact factor: 1.840

2.  A modeling study of notch noise responses of type III units in the gerbil dorsal cochlear nucleus.

Authors:  Xiaohan Zheng; Herbert F Voigt
Journal:  Ann Biomed Eng       Date:  2006-12       Impact factor: 3.934

3.  On the role of the wideband inhibitor in the dorsal cochlear nucleus: a computational modeling study.

Authors:  Oleg Lomakin; Kevin A Davis
Journal:  J Assoc Res Otolaryngol       Date:  2008-08-14

4.  Fitting of dynamic recurrent neural network models to sensory stimulus-response data.

Authors:  R Ozgur Doruk; Kechen Zhang
Journal:  J Biol Phys       Date:  2018-06-02       Impact factor: 1.365

5.  A biophysical modelling platform of the cochlear nucleus and other auditory circuits: From channels to networks.

Authors:  Paul B Manis; Luke Campagnola
Journal:  Hear Res       Date:  2017-12-28       Impact factor: 3.208

6.  Adaptive Stimulus Design for Dynamic Recurrent Neural Network Models.

Authors:  R Ozgur Doruk; Kechen Zhang
Journal:  Front Neural Circuits       Date:  2019-01-22       Impact factor: 3.492

  6 in total

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