Towards Reversing Retinitis Pigmentosa: Re-engineering Photoreceptor Mosaics

Biomedical Engineering Distinguished Lecturer Series sponsored by Stradling Yocca Carlson & Rauth

Speaker: Professor and Dwight C. and Hildagarde E. Baum Chair Norberto M. Grzywacz, Ph.D.

University of Southern California

Host: Assistant Professor Zoran Nenadic, D.Sc.


Abstract: Retinitis pigmentosa is the leading cause of inherited blindness worldwide. This retinal disease initially kills rod photoreceptors and then reorganizes the mosaics of cone photoreceptors, before causing their death. Our studies reveal that the reorganization is due to complex, nonlinear interactions between rods, cones, Müller glial cells, and the retinal pigment epithelium and extra-cellular matrix. We have been building a large-scale computational, biophysically realistic model for these interactions. With the aid of the model, we have been developing cellular-molecular tools to re-engineer the mosaic of cones. Electrophysiological studies demonstrate the effectiveness of these tools.


Bio: Norberto M. Grzywacz received his Bachelor’s 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. Norberto has served as chair of the BME department since 2010.

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).