Literature DB >> 9425519

Predictions of a recurrent model of orientation selectivity.

M Carandini1, D L Ringach.   

Abstract

Recurrent models of orientation selectivity in the visual cortex postulate that an initially broad tuning given by the pattern of geniculate afferents is substantially sharpened by intracortical feedback. We show that these models can be tested on the basis of their predicted responses to certain visual stimuli, without the need for pharmacological or physiological manipulations. First, we consider a detailed recurrent model proposed by Somers, Nelson and Sur [(1995) Journal of Neuroscience, 15, 5448-5465] and show that it can be simplified to a single equation: a center-surround feedback filter in the orientation domain. Then, we explore the responses of the simplified model to stimuli containing two or more orientations. We find that the model exhibits peculiar responses to stimuli containing two orientations, such as plaids or crosses: if the component orientations differ by less than 45 deg the model cannot distinguish between them; if the orientations differ by more than 45 deg the model overestimates their angle by as much as 30 deg. Moreover, the model cannot signal the presence of three orientations separated by 60 deg (it responds as if there were only two orientations), and the addition of two-dimensional visual noise to an oriented stimulus results in strong spurious responses at the orthogonal orientation. We argue that the effects of attraction and repulsion between orientations and the emergence of responses at off-optimal orientations are common to a wide class of feedback models of orientation selectivity. These models could thus be tested by measuring the visual responses of cortical neurons to stimuli containing multiple orientations.

Entities:  

Mesh:

Year:  1997        PMID: 9425519     DOI: 10.1016/s0042-6989(97)00100-4

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


  35 in total

1.  A population density approach that facilitates large-scale modeling of neural networks: analysis and an application to orientation tuning.

Authors:  D Q Nykamp; D Tranchina
Journal:  J Comput Neurosci       Date:  2000 Jan-Feb       Impact factor: 1.621

2.  Computational modeling of orientation tuning dynamics in monkey primary visual cortex.

Authors:  M C Pugh; D L Ringach; R Shapley; M J Shelley
Journal:  J Comput Neurosci       Date:  2000 Mar-Apr       Impact factor: 1.621

3.  Membrane potential and firing rate in cat primary visual cortex.

Authors:  M Carandini; D Ferster
Journal:  J Neurosci       Date:  2000-01-01       Impact factor: 6.167

4.  Dynamics of spatial frequency tuning in macaque V1.

Authors:  C E Bredfeldt; D L Ringach
Journal:  J Neurosci       Date:  2002-03-01       Impact factor: 6.167

Review 5.  A spherical model for orientation and spatial-frequency tuning in a cortical hypercolumn.

Authors:  Paul C Bressloff; Jack D Cowan
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2003-10-29       Impact factor: 6.237

6.  Orientation selectivity in macaque V1: diversity and laminar dependence.

Authors:  Dario L Ringach; Robert M Shapley; Michael J Hawken
Journal:  J Neurosci       Date:  2002-07-01       Impact factor: 6.167

7.  Separation of spatio-temporal receptive fields into sums of gaussian components.

Authors:  Thomas Wennekers
Journal:  J Comput Neurosci       Date:  2004 Jan-Feb       Impact factor: 1.621

Review 8.  Complex receptive fields in primary visual cortex.

Authors:  Luis M Martinez; Jose-Manuel Alonso
Journal:  Neuroscientist       Date:  2003-10       Impact factor: 7.519

9.  Intracortical mechanism of stimulus-timing-dependent plasticity in visual cortical orientation tuning.

Authors:  Haishan Yao; Yaosong Shen; Yang Dan
Journal:  Proc Natl Acad Sci U S A       Date:  2004-03-24       Impact factor: 11.205

10.  Local sensitivity to stimulus orientation and spatial frequency within the receptive fields of neurons in visual area 2 of macaque monkeys.

Authors:  X Tao; B Zhang; E L Smith; S Nishimoto; I Ohzawa; Y M Chino
Journal:  J Neurophysiol       Date:  2011-11-23       Impact factor: 2.714

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