Literature DB >> 16162837

Nonlinear modeling of auditory-nerve rate responses to wideband stimuli.

Eric D Young1, Barbara M Calhoun.   

Abstract

The spectral selectivity of auditory nerve fibers was characterized by a method based on responses to random-spectrum-shape stimuli. The method models the average discharge rate of fibers for steady stimuli and is based on responses to approximately 100 noise-like stimuli with pseudorandom spectral levels in 1/8- or 1/16-octave frequency bins. The model assumes that rate is determined by a linear weighting of the spectrum plus a second-order weighting of all pairs of spectrum values within a certain frequency range of best frequency. The method allows prediction of rate responses to stimuli with arbitrary wideband spectral shapes, thus providing a direct test of the degree of linearity of spectral processing Auditory-nerve fibers are shown to rely mainly on linear weighting of the stimulus spectrum; however, significant second-order terms are present and are important in predicting responses to random-spectrum shape stimuli, although not for predicting responses to noise filtered with cat head-related transfer functions. The second-order terms weight the products of levels at identical frequencies positively and the products of different frequencies negatively. As such, they model both curvature in the rate versus level function and suppressive interactions between different frequency components. The first- and second-order characterizations derived in this method provide a measure of higher-order nonlinearities in neurons, albeit without providing information about temporal characteristics.

Mesh:

Year:  2005        PMID: 16162837     DOI: 10.1152/jn.00261.2005

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  13 in total

1.  Wiener-Volterra characterization of neurons in primary auditory cortex using poisson-distributed impulse train inputs.

Authors:  Martin Pienkowski; Greg Shaw; Jos J Eggermont
Journal:  J Neurophysiol       Date:  2009-03-25       Impact factor: 2.714

2.  Nonlinear temporal receptive fields of neurons in the dorsal cochlear nucleus.

Authors:  Sharba Bandyopadhyay; Eric D Young
Journal:  J Neurophysiol       Date:  2013-08-28       Impact factor: 2.714

3.  Stimulus-frequency-dependent dominance of sound localization cues across the cochleotopic map of the inferior colliculus.

Authors:  Ryan Dorkoski; Kenneth E Hancock; Gareth A Whaley; Timothy R Wohl; Noelle C Stroud; Mitchell L Day
Journal:  J Neurophysiol       Date:  2020-03-18       Impact factor: 2.714

4.  Robust Rate-Place Coding of Resolved Components in Harmonic and Inharmonic Complex Tones in Auditory Midbrain.

Authors:  Yaqing Su; Bertrand Delgutte
Journal:  J Neurosci       Date:  2020-01-29       Impact factor: 6.167

5.  Dorsal Cochlear Nucleus of the Rat: Representation of Complex Sounds in Ears Damaged by Acoustic Trauma.

Authors:  Yang Li; Tessa-Jonne F Ropp; Bradford J May; Eric D Young
Journal:  J Assoc Res Otolaryngol       Date:  2015-05-13

6.  Task Engagement Improves Neural Discriminability in the Auditory Midbrain of the Marmoset Monkey.

Authors:  Luke A Shaheen; Sean J Slee; Stephen V David
Journal:  J Neurosci       Date:  2020-11-18       Impact factor: 6.167

7.  Linear processing of interaural level difference underlies spatial tuning in the nucleus of the brachium of the inferior colliculus.

Authors:  Sean J Slee; Eric D Young
Journal:  J Neurosci       Date:  2013-02-27       Impact factor: 6.167

8.  Nonlinear modeling of causal interrelationships in neuronal ensembles.

Authors:  Theodoros P Zanos; Spiros H Courellis; Theodore W Berger; Robert E Hampson; Sam A Deadwyler; Vasilis Z Marmarelis
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2008-08       Impact factor: 3.802

9.  Understanding auditory spectro-temporal receptive fields and their changes with input statistics by efficient coding principles.

Authors:  Lingyun Zhao; Li Zhaoping
Journal:  PLoS Comput Biol       Date:  2011-08-18       Impact factor: 4.475

10.  Frequency response areas in the inferior colliculus: nonlinearity and binaural interaction.

Authors:  Jane J Yu; Eric D Young
Journal:  Front Neural Circuits       Date:  2013-05-10       Impact factor: 3.492

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