Computational and electrophysiological study of visual perception, perceptual organization, neural plasticity and neural coding; computer vision.
My research involves the application of computational, modeling and electrophysiological techniques to study the neural basis of visual perception and recognition. The current effort of my laboratory is focused on understanding how the brain actively constructs an internal representation of the perceptual world and how behaviors and experience transform the neural circuitry underlying visual processing. Specific issues include feedback and hierarchical computation, dynamic and attentive vision, plasticity and learning, neural coding and decoding. We also seek to integrate representations and algorithms underlying biological computation into development of new robotic vision system. My laboratory offers training opportunities in primate electrophysiology, computational modeling, statistical data analysis and computer vision.
Lee, T.S., Yang, C., Romero, R. and Mumford, D. Neural activity in early visual cortex reflects experience and higher order perceptual saliency. Nature Neuroscience, 5(6), 589-597, 2002.
Lee, T.S., Mumford, D. Hierarchical Bayesian inference in the visual cortex. Journal of Optical Society of America, A. 20 (7): 1434-1448, 2003.