Literature DB >> 2877464

The structure and symmetry of simple-cell receptive-field profiles in the cat's visual cortex.

D J Field, D J Tolhurst.   

Abstract

Receptive fields of simple cells in the cat visual cortex have recently been discussed in relation to the 'theory of communication' proposed by Gabor (1946). A number of investigators have suggested that the line-weighting functions, as measured orthogonal to the preferred orientation, may be best described as the product of a Gaussian envelope and a sinusoid (i.e. a Gabor function). Following Gabor's theory of 'basis' functions, it has also been suggested that simple cells can be categorized into even- and odd-symmetric categories. Based on the receptive field profiles of 46 simple cells recorded from cat visual cortex, our analysis provides a quantitative description of both the receptive-field envelope and the receptive-field 'symmetry' of each of the 46 cells. The results support the notion that, to a first approximation, Gabor functions with three free parameters (envelope width, carrier frequency and carrier phase) provide a good description of the receptive-field profiles. However, our analysis does not support the notion that simple cells generally fit into even- and odd-symmetric categories.

Mesh:

Year:  1986        PMID: 2877464     DOI: 10.1098/rspb.1986.0060

Source DB:  PubMed          Journal:  Proc R Soc Lond B Biol Sci        ISSN: 0950-1193


  26 in total

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

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8.  Independent component filters of natural images compared with simple cells in primary visual cortex.

Authors:  J H van Hateren; A van der Schaaf
Journal:  Proc Biol Sci       Date:  1998-03-07       Impact factor: 5.349

9.  Recurrent inhibition and clustered connectivity as a basis for Gabor-like receptive fields in the visual cortex.

Authors:  S P Sabatini
Journal:  Biol Cybern       Date:  1996-03       Impact factor: 2.086

10.  Discriminating natural image statistics from neuronal population codes.

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