Linear models of simple cells: Correspondence to real cell responses and space 
spanning properties

Wallis, GM

doi:10.1163/156856801753253573

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Linear models of simple cells: Correspondence to real cell responses and space spanning properties

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Wallis, GM
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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https://brill.com/view/journals/sv/14/3-4/article-p237_2.xml
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Citation

Wallis, G. (2001). Linear models of simple cells: Correspondence to real cell responses and space spanning properties. Spatial Vision, 14(3-4), 237-260. doi:10.1163/156856801753253573.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-E20A-3

Abstract

Despite their limitations, linear filter models continue to be used to simulate the receptive field properties of cortical simple cells. For theoreticians interested in large scale models of visual cortex, a family of self-similar filters represents a convenient way in which to characterise simple cells in one basic model. This paper reviews research on the suitability of such models, and goes on to advance biologically motivated reasons for adopting a particular group of models in preference to all others. In particular, the paper describes why the Gabor model, so often used in network simulations, should be dropped in favour of a Cauchy model, both on the grounds of frequency response and mutual filter orthogonality.