Professor of Biomedical Engineering
Small networks of retinal neurons, emergence of retinal function during development, retina as an optimal computational device, measurement of visual motion in the brain, perceptual learning, analysis of medical images.
Office: DRB 168
Phone: (213) 821-1150
Fax: (213) 821-2368
Email:
nmg@bmsr.usc.edu
Dr. Grzywacz the director of the USC Neuroscience Graduate Program, and has associations with the
Biomimetic Microelectronic Systems (BMES) and
Visual Processing Laboratory (VPL) labs. You can view a video of Dr. Grzywacz discussing his research
here.
Background
Norberto M. Grzywacz received his Bachelors degrees in Physics and Mathematics from the Hebrew University of Jerusalem in 1980. In 1984, he received his Ph.D. in Neurobiology from the same institution. From 1984 to 1991, he was first a postdoctoral fellow and then a Research Scientist at the Center for Biological Information Processing of the Massachusetts Institute of Technology. That year, he moved to the Smith-Kettlewell Eye Research Institute in San Francisco, where he became a Senior Scientist in 1994. In September of 2001, he joined the Department of Biomedical Engineering as a Professor.
Research
He heads the Visual Processing Laboratory, which is a research facility focused on computational and experimental aspects of vision research.
Dr. Grzywacz combines a host of experimental techniques with computational modeling to study neural processing in the retina, to study visual perception, and to analyze medical images. In particular, he has been applying such a combination to adult retinal circuits, to the development of retinal receptive fields, to sensory adaptation, to the human perception of visual motion, and to perceptual learning. More recently, he also began applying biomimetic tools to the analysis of medical images, specially the early detection of retinal diseases. The experimental techniques used in his perceptual and retinal studies include psychophysics, electrophysiology, immunohistochemistry, light and electron microscopy, calcium imaging, and western blotting. In turn, his modeling encompasses detailed biophysics (when addressing retinal circuits) and higher-level computational models (such as Bayesian models of vision).
