particular stimulus should not be interpreted as indicating that the neuron is somehow specialized for that stimulus, since there is an unlimited equivalence class of stimuli capable of producing similar firing rates.) The spatial-frequency theory of vision is based on two physical principles: Any visual stimulus can be represented by plotting the intensity of the light along lines running through it. Any curve can be broken down into constituent sine waves by Fourier analysis. The theory (for which empirical support has yet to be developed) states that in each functional module of the visual cortex, Fourier analysis is performed on the receptive field and the neurons in each module are thought to respond selectively to various orientations and frequencies of sine wave gratings. When all of the visual cortex neurons that are influenced by a specific scene respond together, the perception of the scene is created by the summation of the various sine-wave gratings. (This procedure, however, does not address the problem of the organization of the products of the summation into figures, grounds, and so on. It effectively recovers the original (pre-Fourier analysis) distribution of photon intensity and wavelengths across the retinal projection, but does not add information to this original distribution. So the functional value of such a hypothesized procedure is unclear. Some other objections to the "Fourier theory" are discussed by Westheimer (2001) ). One is generally not aware of the individual spatial frequency components since all of the elements are essentially blended together into one smooth representation. However, computer-based filtering procedures can be used to deconstruct an image into its individual spatial frequency components. Research on spatial frequency detection by visual neurons complements and extends previous research using straight edges rather than refuting it. Further research shows that different spatial frequencies convey different information about the appearance of a stimulus. High spatial frequencies represent abrupt spatial changes in the image, such as edges, and generally correspond to featural information and fine detail. M. Bar (2004) has proposed that low spatial frequencies represent global information about the shape, such as general orientation and proportions. Rapid and specialised perception of faces is known to rely more on low spatial frequency information. In the general population of adults, the threshold for spatial frequency discrimination is about 7%. It is often poorer in dyslexic individuals. Spatial frequency in MRI When spatial frequency is used as a variable in a mathematical