Literature DB >> 9205714

Modeling the apparent frequency-specific suppression in simple cell responses.

O Nestares1, D J Heeger.   

Abstract

Simple cells in cat striate cortex are selective for spatial frequency. It is widely believed that this selectivity arises simply because of the way in which the neurons sum inputs from the lateral geniculate nucleus. Alternate models, however, advocate the need for frequency-specific inhibitory mechanisms to refine the spatial frequency selectivity. Indeed, simple cell responses are often suppressed by superimposing stimuli with spatial frequencies that flank the neuron's preferred spatial frequency. In this article, we compare two models of simple cell responses head-to-head. One of these models, the flanking-suppression model, includes an inhibitory mechanism that is specific to frequencies that flank the neuron's preferred spatial frequency. The other model, the nonspecific-suppression model, includes a suppressive mechanism that is very broadly tuned for spatial frequency. Both models also include a rectification nonlinearity and both may include an additional accelerating (e.g., squaring) output nonlinearity. We demonstrate that both models can be consistent with the apparent flanking suppression. However, based on other experimental results, we argue that the nonspecific-suppression model is more plausible. We conclude that the suppression is probably broadly tuned for spatial frequency and that the apparent flanking suppression is actually due to distortions introduced by an accelerating output nonlinearity.

Mesh:

Year:  1997        PMID: 9205714     DOI: 10.1016/s0042-6989(96)00268-4

Source DB:  PubMed          Journal:  Vision Res        ISSN: 0042-6989            Impact factor:   1.886


  8 in total

1.  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

2.  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

3.  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

4.  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

5.  Responses to second-order texture modulations undergo surround suppression.

Authors:  Helena X Wang; David J Heeger; Michael S Landy
Journal:  Vision Res       Date:  2012-06-01       Impact factor: 1.886

6.  Human primary visual cortex (V1) is selective for second-order spatial frequency.

Authors:  Luke E Hallum; Michael S Landy; David J Heeger
Journal:  J Neurophysiol       Date:  2011-02-23       Impact factor: 2.714

Review 7.  The normalization model of attention.

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

8.  Inter-ocular contrast normalization in human visual cortex.

Authors:  Farshad Moradi; David J Heeger
Journal:  J Vis       Date:  2009-03-20       Impact factor: 2.240

  8 in total

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