Literature DB >> 16709635

'Simplification' of responses of complex cells in cat striate cortex: suppressive surrounds and 'feedback' inactivation.

Cedric Bardy1, Jin Yu Huang, Chun Wang, Thomas FitzGibbon, Bogdan Dreher.   

Abstract

In mammalian striate cortex (V1), two distinct functional classes of neurones, the so-called simple and complex cells, are routinely distinguished. They can be quantitatively differentiated from each other on the basis of the ratio between the phase-variant (F1) component and the mean firing rate (F0) of spike responses to luminance-modulated sinusoidal gratings (simple, F1/F0 > 1; complex, F1/F0 < 1). We investigated how recurrent cortico-cortical connections affect the spatial phase-variance of responses of V1 cells in the cat. F1/F0 ratios of the responses to optimally oriented drifting sine-wave gratings covering the classical receptive field (CRF) of single V1 cells were compared to those of: (1) responses to gratings covering the CRFs combined with gratings of different orientations presented to the 'silent' surrounds; and (2) responses to CRF stimulation during reversible inactivation of postero-temporal visual (PTV) cortex. For complex cells, the relative strength of the silent surround suppression on CRF-driven responses was positively correlated with the extent of increases in F1/F0 ratios. Inactivation of PTV cortex increased F1/F0 ratios of CRF-driven responses of complex cells only. Overall, activation of suppressive surrounds or inactivation of PTV 'converted' substantial proportions (50 and 30%, respectively) of complex cells into simple-like cells (F1/F0 > 1). Thus, the simple-complex distinction depends, at least partly, on information coming from the silent surrounds and/or feedback from 'higher-order' cortices. These results support the idea that simple and complex cells belong to the same basic cortical circuit and the spatial phase-variance of their responses depends on the relative strength of different synaptic inputs.

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Year:  2006        PMID: 16709635      PMCID: PMC1817736          DOI: 10.1113/jphysiol.2006.110320

Source DB:  PubMed          Journal:  J Physiol        ISSN: 0022-3751            Impact factor:   5.182


  77 in total

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

2.  Orientation specificity of cells in cat striate cortex.

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Journal:  J Neurophysiol       Date:  1974-11       Impact factor: 2.714

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Authors:  R W Rodieck; J D Pettigrew; P O Bishop; T Nikara
Journal:  Vision Res       Date:  1967-01       Impact factor: 1.886

4.  The visual cortex as a spatial frequency analyser.

Authors:  L Maffei; A Fiorentini
Journal:  Vision Res       Date:  1973-07       Impact factor: 1.886

5.  Effects of bicuculline on functions of inhibition in visual cortex.

Authors:  D Rose; C Blakemore
Journal:  Nature       Date:  1974-05-24       Impact factor: 49.962

6.  Projection of X- and Y-cells of the cat's lateral geniculate nucleus to areas 17 and 18 of visual cortex.

Authors:  J Stone; B Dreher
Journal:  J Neurophysiol       Date:  1973-05       Impact factor: 2.714

7.  An analysis of neuronal circuitry for two types of visual cortical neurones classified on the basis of their responses to photic stimuli.

Authors:  K Toyama; K Maekawa; T Takeda
Journal:  Brain Res       Date:  1973-10-26       Impact factor: 3.252

8.  Conduction velocity of afferents to cat visual cortex: a correlation with cortical receptive field properties.

Authors:  K P Hoffman; J Stone
Journal:  Brain Res       Date:  1971-09-24       Impact factor: 3.252

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Authors:  K J Sanderson; S M Sherman
Journal:  J Neurophysiol       Date:  1971-05       Impact factor: 2.714

10.  The neural mechanism of binocular depth discrimination.

Authors:  H B Barlow; C Blakemore; J D Pettigrew
Journal:  J Physiol       Date:  1967-11       Impact factor: 5.182

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  18 in total

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2.  Feedback signals from cat's area 21a enhance orientation selectivity of area 17 neurons.

Authors:  C Wang; W J Waleszczyk; W Burke; B Dreher
Journal:  Exp Brain Res       Date:  2007-07-14       Impact factor: 1.972

3.  A neurochemical signature of visual recovery after extrastriate cortical damage in the adult cat.

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4.  A neuronal network model of primary visual cortex explains spatial frequency selectivity.

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Journal:  J Comput Neurosci       Date:  2008-07-31       Impact factor: 1.621

5.  Adaptation changes the spatial frequency tuning of adult cat visual cortex neurons.

Authors:  M Bouchard; P-C Gillet; S Shumikhina; S Molotchnikoff
Journal:  Exp Brain Res       Date:  2008-05-22       Impact factor: 1.972

6.  Adaptation of the simple or complex nature of V1 receptive fields to visual statistics.

Authors:  Julien Fournier; Cyril Monier; Marc Pananceau; Yves Frégnac
Journal:  Nat Neurosci       Date:  2011-07-17       Impact factor: 24.884

7.  Stability of simple/complex classification with contrast and extraclassical receptive field modulation in macaque V1.

Authors:  Christopher A Henry; Michael J Hawken
Journal:  J Neurophysiol       Date:  2013-01-09       Impact factor: 2.714

Review 8.  The divisive normalization model of V1 neurons: a comprehensive comparison of physiological data and model predictions.

Authors:  Tadamasa Sawada; Alexander A Petrov
Journal:  J Neurophysiol       Date:  2017-08-23       Impact factor: 2.714

9.  A computational theory of visual receptive fields.

Authors:  Tony Lindeberg
Journal:  Biol Cybern       Date:  2013-11-07       Impact factor: 2.086

10.  Adaptive behavior of neighboring neurons during adaptation-induced plasticity of orientation tuning in VI.

Authors:  Abdellatif Nemri; Narcis Ghisovan; Svetlana Shumikhina; Stéphane Molotchnikoff
Journal:  BMC Neurosci       Date:  2009-12-14       Impact factor: 3.288

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