The overall goal of our lab is to understand how complex visual scenes are represented in the central nervous system. Our current understanding of the brain suggests that basic features of images are represented in primary visual cortex (Area 17) and that more abstract aspects of the scene like illusory contours or differences in texture are represented in higher cortical areas based on the output of Area 17. For example, neurons in Area 17 would detect the edges of the floral rug and the pattern of the flower weave, but higher cortical areas extract the shape of the toy hidden under the rug. While the classical model of brain organization suggest that the higher cortical areas build their representation from the simple representation in the primary visual cortex, it is possible that many of the abstractions are encoded much earlier in the visual system (in the retina or the lateral geniculate nucleus [LGN]). This possibility has been ignored because it is assumed that abstraction is too complex for anything but cerebral cortex. The proposed experiments challenge this assumption, and ask whether the pro9perties of the neurons before cortex make them able to extract behaviorally important information from a scene. Specifically, the proposed research will use targeted microelectrode recordings to determine if and how neurons in the LGN encode a particular class of abstract image features known as second-order image features.
Naoum Issa, M.D., Ph.D.