Open AccessPreserving properties of object shape by computations in primary visual cortex
Author(s) -
Charles F. Stevens
Publication year - 2004
Publication title -
proceedings of the national academy of sciences of the united states of america
Language(s) - English
Resource type - Journals
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.0406664101
Subject(s) - visual cortex , computation , artificial intelligence , computer vision , property (philosophy) , object (grammar) , computer science , wavelet transform , pattern recognition (psychology) , representation (politics) , wavelet , process (computing) , cognitive neuroscience of visual object recognition , image (mathematics) , algorithm , neuroscience , biology , philosophy , epistemology , politics , political science , law , operating system
Although our visual system is extremely good at extracting objects from the visual scene, this process involves complicated computations that are thought to require image processing by many successive cortical areas. Thus, intermediate stages in object extraction should not eliminate essential properties of the objects that are still required by later stages. A particularly important characteristic of an object is its shape, and shape has the property that it is unchanged by translations, rotations, and magnifications of the image. I show that the requirement for this property of shape to be preserved in the image, as represented by the firing of neurons in the primary visual cortex (V1), is equivalent to a particular type of computation, known as a wavelet transform, determining the firing rate of V1 neurons in response to an image on the retina. Experimental data support the conclusion that the neural representation of images in V1 is described by a wavelet transform and, therefore, that the properties of shape are preserved.