David J. Heeger

Cognitive and Computational Neuroscience, Vision, fMRI

Julius Silver, Roslyn S. Silver, and Enid Silver Winslow Professor
Professor of Psychology and Neural Science

I received my Ph.D. in computer science from the University of Pennsylvania. I was a postdoctoral fellow at MIT, a research scientist at the NASA-Ames Research Center, and an Associate Professor at Stanford before coming NYU. I was awarded the David Marr Prize in computer vision in 1987, an Alfred P. Sloan Research Fellowship in neuroscience in 1994, the Troland Award in psychology from the National Academy of Sciences in 2002, and the Margaret and Herman Sokol Faculty Award in the Sciences from New York University in 2006. I was elected to the National Academy of Sciences in 2013.

The research in my lab spans an interdisciplinary cross-section of engineering, psychology, and neuroscience. We have studied visual perception and visual neuroscience, cognitive neuroscience, computational neuroscience, computer vision, image processing, computer graphics, AI, artificial neural networks, and data science.

Current research is focused on understanding the computations performed by neural circuits in the brain. There is considerable evidence that the brain relies on a set of canonical neural computations, repeating them across brain regions and modalities to apply operations of the same form, but we lack a theoretical framework for how such canonical computations can support a wide variety of cognitive processes, brain functions, and neural systems. The field of neuroscience needs a general theory of brain function, like Maxwell's Equations for the brain. We are developing such a theoretical framework. The theory offers a unified framework for the dynamics of neural activity, and it recapitulates many key neurophysiological and cognitive/perceptual phenomena (including sensory processing and attention in visual cortex, and working memory in prefrontal cortex), measured with a wide range of methodologies (including intracellular recordings of membrane potential fluctuations, firing rates of individual neurons, optogenetic manipulations, local field potentials, neuroimaging, and behavioral performance).