Neural representations underlying visual perception of objects and faces

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How are visual objects represented and recognized in the human brain? My research program is targeted to answer this broad question. In the last 40 years, psychophysics, electrophysiology and, more recently, neural imaging studies have deciphered many aspects of the early stages of visual processing. We now know that visual perception starts with a decomposition of images into their most basic properties such as spatial frequency and orientation. A lot less is known about the later stages of visual processing that enable recognition complex visual objects. We propose to use methodological equivalents of approaches that have been instrumental in studies of lower-level vision to examine higher-level processes involving invariant visual object recognition.The ability to recognize an object while ignoring variations that do not pertain to its identity is referred to as invariance. For example, human observers are scale-invariant in recognizing letters. Thus they are able to read text at a wide range of visual sizes, from very large, e.g., on a billboard, to very small, e.g., fine-print. Without invariance, there can be no real recognition. The exquisite ability of the human brain to accomplish invariant recognition stands in stark contrast to the capabilities of state-of-the-art artificial recognition systems. It is therefore one of the most exciting open problems in neuroscience to discover how invariant and robust object recognition is achieved in the human brain. Breakthroughs in this area will have far-reaching implications for collaborative efforts with the medical community to develop rehabilitation programs for diseases that may disrupt face processing such as prosopagnosia (face blindness) and autism, and with the engineering community towards realizing robust automated recognition systems.