Greg DeAngelis

Current Institution
University of Rochester
Department of Brain & Cognitive Sciences

Scholar: 2000

Awarded Institution
Washington University


Research Interests

My laboratory studies cortical circuits that mediate visual perception and visually guided behavior. This work involves a creative fusion of the disciplines of neurophysiology and psychology. Monkeys are trained to perform demanding visual discrimination tasks, and we record from single or multiple neurons in visual cortex during performance of these tasks. Thus, we can directly compare the ability of neurons to discriminate between different visual stimuli with the ability of the behaving animal to make the same discrimination. In addition, the techniques of electrical microstimulation and/or reversible inactivation are used to establish causal links between physiology and behavior.

Our research currently has two main foci: 1) Mechanisms of stereoscopic depth perception. The image formed on each retina is a two-dimensional projection of the three-dimensional (3D) world. However, objects at different depths project onto slightly disparate points on the two retinas. The brain is able to extract these binocular disparities from the retinal images and create a vivid sensation of depth, such as when one views a 3D-art poster. My lab studies the mechanisms by which binocular disparity information is encoded, processed, and read out by the brain in order to perceive depth and compute 3D surface structure. We are just beginning to elucidate the brain areas that contribute to stereoscopic depth perception under different conditions, and much remains to be learned about this interesting cognitive process. 2) Mechanisms of visual feature integration. At early stages in the visual system, local visual features (i.e., oriented line segments) are encoded by neurons with very small receptive fields. How are these local features assembled into complex representations of 3D objects? One interesting and controversial hypothesis is that feature integration occurs through temporal coding; two neurons selective for local image features are hypothesized to synchronize their activities when these two units respond to parts of a single object, but not when they respond to parts of different objects. Our work is aimed at conducting rigorous tests of hypotheses such as this. We train monkeys to perform visual discrimination tasks that require feature integration, and we record from multiple neurons in visual cortex during the task.