Literature DB >> 17652422

Internal spatial organization of receptive fields of complex cells in the early visual cortex.

Kota S Sasaki1, Izumi Ohzawa.   

Abstract

The receptive fields of complex cells in the early visual cortex are economically modeled by combining outputs of a quadrature pair of linear filters. For actual complex cells, such a minimal model may be insufficient because many more simple cells are thought to make up a complex cell receptive field. To examine the minimalist model physiologically, we analyzed spatial relationships between the internal structure (subunits) and the overall receptive fields of individual complex cells by a two-stimulus interaction technique. The receptive fields of complex cells are more circular and only slightly larger than their subunits in size. In addition, complex cell subunits occupy spatial extents similar to those of simple cell receptive fields. Therefore in these respects, the minimalist schema is a fair approximation to actual complex cells. However, there are violations against the minimal model. Simple cell receptive fields have significantly fewer subregions than complex cell subunits and, in general, simple cell receptive fields are elongated more horizontally than vertically. This bias is absent in complex cell subunits and receptive fields. Thus simple cells cannot be equated to individual complex cell subunits and spatial pooling of simple cells may occur anisotropically to constitute a complex cell subunit. Moreover, when linear filters for complex cell subunits are examined separately for bright and dark responses, there are significant imbalances and position displacements between them. This suggests that actual complex cell receptive fields are constructed by a richer combination of linear filters than proposed by the minimalist model.

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Year:  2007        PMID: 17652422     DOI: 10.1152/jn.00429.2007

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  11 in total

1.  Complex cells in the cat striate cortex have multiple disparity detectors in the three-dimensional binocular receptive fields.

Authors:  Kota S Sasaki; Yuka Tabuchi; Izumi Ohzawa
Journal:  J Neurosci       Date:  2010-10-13       Impact factor: 6.167

2.  Spatial and temporal features of synaptic to discharge receptive field transformation in cat area 17.

Authors:  Lionel G Nowak; Maria V Sanchez-Vives; David A McCormick
Journal:  J Neurophysiol       Date:  2009-11-11       Impact factor: 2.714

3.  Orientation selectivity in cat primary visual cortex: local and global measurement.

Authors:  Tao Xu; Hong-Mei Yan; Xue-Mei Song; Ming Li
Journal:  Neurosci Bull       Date:  2015-06-18       Impact factor: 5.203

4.  Effects of generalized pooling on binocular disparity selectivity of neurons in the early visual cortex.

Authors:  Daisuke Kato; Mika Baba; Kota S Sasaki; Izumi Ohzawa
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2016-06-19       Impact factor: 6.237

Review 5.  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

6.  A reaction-diffusion model to capture disparity selectivity in primary visual cortex.

Authors:  Mohammed Sultan Mohiuddin Siddiqui; Basabi Bhaumik
Journal:  PLoS One       Date:  2011-10-13       Impact factor: 3.240

7.  Subpopulations of neurons in visual area v2 perform differentiation and integration operations in space and time.

Authors:  Anita M Schmid; Keith P Purpura; Ifije E Ohiorhenuan; Ferenc Mechler; Jonathan D Victor
Journal:  Front Syst Neurosci       Date:  2009-11-04

8.  A Convolutional Subunit Model for Neuronal Responses in Macaque V1.

Authors:  Brett Vintch; J Anthony Movshon; Eero P Simoncelli
Journal:  J Neurosci       Date:  2015-11-04       Impact factor: 6.167

9.  Integration of Multiple Spatial Frequency Channels in Disparity-Sensitive Neurons in the Primary Visual Cortex.

Authors:  Mika Baba; Kota S Sasaki; Izumi Ohzawa
Journal:  J Neurosci       Date:  2015-07-08       Impact factor: 6.167

10.  Slow feature analysis on retinal waves leads to V1 complex cells.

Authors:  Sven Dähne; Niko Wilbert; Laurenz Wiskott
Journal:  PLoS Comput Biol       Date:  2014-05-08       Impact factor: 4.475

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