Literature DB >> 9147482

Comparison of contrast-normalization and threshold models of the responses of simple cells in cat striate cortex.

D J Tolhurst1, D J Heeger.   

Abstract

In almost every study of the linearity of spatiotemporal summation in simple cells of the cat's visual cortex, there have been systematic mismatches between the experimental observations and the predictions of the linear theory. These mismatches have generally been explained by supposing that the initial spatiotemporal summation stage is strictly linear, but that the following output stage of the simple cell is subject to some contrast-dependent nonlinearity. Two main models of the output nonlinearity have been proposed: the threshold model (e.g. Tolhurst & Dean, 1987) and the contrast-normalization model (e.g. Heeger, 1992a,b). In this paper, the two models are fitted rigorously to a variety of previously published neurophysiological data, in order to determine whether one model is a better explanation of the data. We reexamine data on the interaction between two bar stimuli presented in different parts of the receptive field; on the relationship between the receptive-field map and the inverse Fourier transform of the spatial-frequency tuning curve; on the dependence of response amplitude and phase on the spatial phase of stationary gratings; on the relationships between the responses to moving and modulated gratings; and on the suppressive action of gratings moving in a neuron's nonpreferred direction. In many situations, the predictions of the two models are similar, but the contrast-normalization model usually fits the data slightly better than the threshold model, and it is easier to apply the equations of the normalization model. More importantly, the normalization model is naturally able to account very well for the details and subtlety of the results in experiments where the total contrast energy of the stimuli changes; some of these phenomena are completely beyond the scope of the threshold model. Rigorous application of the models' equations has revealed some situations where neither model fits quite well enough, and we must suppose, therefore, that there are some subtle nonlinearities still to be characterized.

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Year:  1997        PMID: 9147482     DOI: 10.1017/s0952523800011433

Source DB:  PubMed          Journal:  Vis Neurosci        ISSN: 0952-5238            Impact factor:   3.241


  33 in total

1.  Parametric population representation of retinal location: neuronal interaction dynamics in cat primary visual cortex.

Authors:  D Jancke; W Erlhagen; H R Dinse; A C Akhavan; M Giese; A Steinhage; G Schöner
Journal:  J Neurosci       Date:  1999-10-15       Impact factor: 6.167

2.  Direction selectivity and spatiotemporal separability in simple cortical cells.

Authors:  M A García-Pérez
Journal:  J Comput Neurosci       Date:  1999 Sep-Oct       Impact factor: 1.621

3.  Motion opponency in visual cortex.

Authors:  D J Heeger; G M Boynton; J B Demb; E Seidemann; W T Newsome
Journal:  J Neurosci       Date:  1999-08-15       Impact factor: 6.167

4.  Contrast gain control in the visual cortex: monocular versus binocular mechanisms.

Authors:  A M Truchard; I Ohzawa; R D Freeman
Journal:  J Neurosci       Date:  2000-04-15       Impact factor: 6.167

5.  A novel mechanism of response selectivity of neurons in cat visual cortex.

Authors:  Maxim Volgushev; Joachim Pernberg; Ulf T Eysel
Journal:  J Physiol       Date:  2002-04-01       Impact factor: 5.182

Review 6.  Mapping receptive fields in primary visual cortex.

Authors:  Dario L Ringach
Journal:  J Physiol       Date:  2004-05-21       Impact factor: 5.182

7.  A nonlinear model of the behavior of simple cells in visual cortex.

Authors:  Miguel A García-Pérez
Journal:  J Comput Neurosci       Date:  2004 Nov-Dec       Impact factor: 1.621

8.  The emergence of contrast-invariant orientation tuning in simple cells of cat visual cortex.

Authors:  Ian M Finn; Nicholas J Priebe; David Ferster
Journal:  Neuron       Date:  2007-04-05       Impact factor: 17.173

9.  Linearity and normalization in simple cells of the macaque primary visual cortex.

Authors:  M Carandini; D J Heeger; J A Movshon
Journal:  J Neurosci       Date:  1997-11-01       Impact factor: 6.167

Review 10.  The normalization model of attention.

Authors:  John H Reynolds; David J Heeger
Journal:  Neuron       Date:  2009-01-29       Impact factor: 17.173

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