The current focus of the research in our lab is to use functional magnetic resonance imaging (fMRI) to quantitatively investigate the relationship between brain and behavior. The vast majority of neuroimaging experiments from other labs around the world have focused on which parts of the brain are involved in a particular cognitive or perceptual task. Although this has been an important first step, perception and cognition depend not only on which brain areas are active, but also on how neuronal activity within each of those areas varies over space and time. We are using fMRI to measure the timing and amplitude of brain activity, for testing computational theories of the neural processing underlying cognition and perception. Part of my own excitement about this work is that it brings together my engineering training with my interest in neuroscience, as we routinely develop new image processing and computer vision algorithms for analyzing our functional and structural MRI data. We are using fMRI to study visual awareness, visual pattern detection/discrimination, visual motion perception, stereo depth perception, attention, working memory, the control of eye and hand movements, and neural processing of complex audio-visual and emotional experiences (movies, music, narrative).

My research spans an interdisciplinary cross-section of engineering, psychology, and neuroscience. In the fields of image processing, computer vision, and computer graphics, I have worked on motion estimation and image registration, wavelet image representations, anisotropic diffusion (edge-preserving noise reduction), image fidelity metrics (for evaluating image data compression algorithms), texture analysis/synthesis and scientific visualization. In the fields of perceptual psychology and systems/cognitive neuroscience, I have worked on computational models of neuronal processing in the visual system, psychophysical (perceptual psychology) measurements of human vision, and neuroimaging.

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.

E-mail: david.heeger@nyu.edu

Representative Publications (Reprints available online):

Heeger DJ, Normalization of cell responses in cat striate cortex, Visual Neuroscience, 9:181-198, 1992.

Carandini M & Heeger DJ, Summation and Division by Neurons in Visual Cortex, Science, 264:1333-1336, 1994.

Boynton GM, Engel SA, Glover GH, & Heeger DJ, Linear systems analysis of fMRI in human V1, Journal of Neuroscience, 16:4207-4221, 1996.

Demb JB, Boynton GM, & Heeger DJ, Functional magnetic resonance imaging of early visual pathways in dyslexia, Journal of Neuroscience, 18:6939-6951, 1998.

Ress D, Backus BT, & Heeger DJ, Activity in primary visual cortex predicts performance in a visual detection task, Nature Neuroscience, 3:940-945, 2000.

Heeger DJ & Ress D, What does fMRI tell us about neuronal activity?, Nature Reviews Neuroscience, 3:142-151, 2002.

Lee SH, Blake R, & Heeger DJ, Hierarchy of responses underlying binocular rivalry, Nature Neuroscience, 10:1048-1054, 2007.

Hasson U, et al., A hierarchy of temporal receptive windows in human cortex, Journal of Neuroscience, 28:2539-2550, 2008.