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This article is part of the series Image Perception.

Open Access Research Article

A Survey of Architecture and Function of the Primary Visual Cortex (V1)

Jeffrey Ng1*, Anil A Bharath1 and Li Zhaoping2

Author Affiliations

1 Department of Bioengineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK

2 Natural Intelligence Laboratory, Department of Psychology, University College London, Gower Street, London WC1E 6BT, UK

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EURASIP Journal on Advances in Signal Processing 2007, 2007:097961  doi:10.1155/2007/97961

The electronic version of this article is the complete one and can be found online at: http://asp.eurasipjournals.com/content/2007/1/097961


Received:1 December 2005
Revisions received:6 September 2006
Accepted:18 September 2006
Published:17 December 2006

© 2007 Ng et al.

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

The largest visual area, known as the primary visual cortex or V1, has greatly contributed to the current understanding of mammalian and human visual pathways and their role in visual perception. The initial discovery of orientation-sensitive neurons in V1, arranged according to a retinotopic mapping, suggested an analogy to its function as a low-level feature analyzer. Subsequent discoveries of phase, spatial frequency, color, ocular origin, and direction-of-motion-sensitive neurons, arranged into overlapping maps, further lent support to the view that it performs a rich decomposition, similar to signal processing transforms, of the retinal output. Like the other cortical areas, V1 has a laminar organization with specialization for input from the relayed retinal afferents, output to the higher visual areas, and the segregation of the magno (motion) and parvo (form) pathways. Spatially lateral connections that exist between neurons of similar and varying properties have also been proposed to give rise to a computation of a bottom-up saliency map in V1. We provide a review of the selectivity of neurons in V1, laminar specialization and analogies to signal processing techniques, a model of V1 saliency computation, and higher-area feedback that may mediate perception.

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