Literature DB >> 8509309

Wiener and Volterra analyses applied to the auditory system.

J J Eggermont1.   

Abstract

The application of a particular branch of non-linear system analysis, the functional series expansion or integral method, to the auditory system is reviewed. Both the Volterra and Wiener approach are discussed and an extension of the Wiener method from its traditional white-noise stimulus approach to that of Poisson distributed clicks is presented. This type of analysis has been applied to compound and single-unit responses from the auditory nerve, cochlear nucleus, auditory midbrain and medial geniculate body. Most studies have estimated only first-order Wiener kernels but in recent years second-order Wiener and Volterra kernels have been estimated, particularly with reference to dynamic non-linearities. A particular form of second-order analysis, the Spectro Temporal Receptive Field, offers an alternative to first-order cross-correlation when phase-lock is absent. The correlation method has revealed that neural synchronization is less affected by intensity changes and damage to the hair cells than is neural firing rate. Although the presence of the static cochlear non-linearity could be demonstrated on the basis of the intensity dependence of the first-order Wiener kernel, the identification of the exact form of the nonlinearity of the peripheral auditory system on basis of higher-order Wiener kernels has so far been inconclusive. However, successes of the method can be found in the description of the dynamic non-linearities and non-linear neural interactions.

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Mesh:

Year:  1993        PMID: 8509309     DOI: 10.1016/0378-5955(93)90139-r

Source DB:  PubMed          Journal:  Hear Res        ISSN: 0378-5955            Impact factor:   3.208


  33 in total

1.  Spectral-temporal receptive fields of nonlinear auditory neurons obtained using natural sounds.

Authors:  F E Theunissen; K Sen; A J Doupe
Journal:  J Neurosci       Date:  2000-03-15       Impact factor: 6.167

2.  Assessing the performance of neural encoding models in the presence of noise.

Authors:  J C Roddey; B Girish; J P Miller
Journal:  J Comput Neurosci       Date:  2000 Mar-Apr       Impact factor: 1.621

3.  Robust spectrotemporal reverse correlation for the auditory system: optimizing stimulus design.

Authors:  D J Klein; D A Depireux; J Z Simon; S A Shamma
Journal:  J Comput Neurosci       Date:  2000 Jul-Aug       Impact factor: 1.621

Review 4.  Mechanics of the mammalian cochlea.

Authors:  L Robles; M A Ruggero
Journal:  Physiol Rev       Date:  2001-07       Impact factor: 37.312

5.  Auditory space-time receptive field dynamics revealed by spherical white-noise analysis.

Authors:  R L Jenison; J W Schnupp; R A Reale; J F Brugge
Journal:  J Neurosci       Date:  2001-06-15       Impact factor: 6.167

6.  Nonlinear spectrotemporal sound analysis by neurons in the auditory midbrain.

Authors:  Monty A Escabi; Christoph E Schreiner
Journal:  J Neurosci       Date:  2002-05-15       Impact factor: 6.167

7.  Representation of acoustic communication signals by insect auditory receptor neurons.

Authors:  C K Machens; M B Stemmler; P Prinz; R Krahe; B Ronacher; A V Herz
Journal:  J Neurosci       Date:  2001-05-01       Impact factor: 6.167

8.  Linearity of cortical receptive fields measured with natural sounds.

Authors:  Christian K Machens; Michael S Wehr; Anthony M Zador
Journal:  J Neurosci       Date:  2004-02-04       Impact factor: 6.167

9.  A system identification analysis of neural adaptation dynamics and nonlinear responses in the local reflex control of locust hind limbs.

Authors:  Oliver P Dewhirst; Natalia Angarita-Jaimes; David M Simpson; Robert Allen; Philip L Newland
Journal:  J Comput Neurosci       Date:  2012-06-23       Impact factor: 1.621

10.  Understanding spike-triggered covariance using Wiener theory for receptive field identification.

Authors:  Roman A Sandler; Vasilis Z Marmarelis
Journal:  J Vis       Date:  2015       Impact factor: 2.240

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