Abstract
How can we see? One answer lies in the receptive fields of visual cells in our eyes and brain. A 'receptive field' in the simplest terms is a map of the regions in space where light can affect a cell's electrical output. Millions of such fields analyze and filter the patterns of light that impinge on the retina. I will illustrate the major anatomical structures and physiological processes underlying such fields, in the primary visual pathway from the eye to the brain. An understanding of such fields is critically important, since their output provides the basis upon which conscious visual perception can eventually be constructed by higher brain processes. That is, perception itself is derived from the information as filtered and analyzed by such fields. Complete spatio-temporal receptive fields of simple cells in the visual cortex of monkeys were recently recorded using white-noise analysis techniques by Dan Pollen and colleagues. I discuss various models of the shapes of these fields (Gaussian derivative, Gabor, edge-and-line- detector, and difference-of-offset-Gaussian) in the context of these new data. The Gaussian derivative model provided the simplest and most concise description of the receptive fields to the models tested. Gaussian derivative machine vision spatio-temporal filters, based upon the biological data, produced robust estimates of the spatial and temporal derivatives of the image. These should prove suitable for form, motion, color, and stereo analysis, using only linear, separable filters or their linear combinations. So a partial answer to 'How can we see?' may be that receptive fields in the early visual system may serve as robust derivative analyzers in space and time.
