Joel Zylberberg, Ph.D.

Faculty Member

Professor
Department of Ophthalmology
David Geffen School of Medicine
University of California, Los Angeles

Personal Statement

I am a Canada Research Chair in Computational Neuroscience, and my research is focused on representations of visual information in artificial and biological neural networks, including those in the retina and visual cortex. Through this research, I have extensive experience in creating mechanistic models of retinal ganglion cell responses to visual stimulation and using information theory to understand how the responses of neurons in those models (and in my collaborators’ experiments) encode visual information. I also have substantial expertise in training artificial neural networks (ANNs) to predict the responses of neurons in visual cortex to natural image stimulation, and of training ANNs to infer a person’s sleep stage from LFP signals recorded by implanted electrodes. The proposed work will bring my areas of expertise together with those of my collaborators: my lab will develop and train ANNs to predict responses of retinal ganglion cells to naturalistic stimuli (recorded in the Field and Rieke labs). My research in this area has led to many impactful peer-reviewed publications and has been funded by multiple grants on which I am PI or co-I, including grants from: NIH; Natural Science and Engineering Research Council of Canada (NSERC); New Frontiers in Research Fund; Google; Sloan Foundation; and Canadian Institute For Advanced Research (CIFAR). In my role as PI (since 2015), I have gained substantial experience in recruiting and mentoring trainees, managing research projects, and delivering high quality results to the scientific community. In summary, I have the necessary technical background, and leadership experience, to successfully carry out the proposed work.