David J. Heeger

New York University

Election Year: 2013
Primary Section: 52, Psychological and Cognitive Sciences
Secondary Section: 28, Systems Neuroscience
Membership Type: Member

Research Interests

Heeger's research spans an interdisciplinary cross-section of engineering, psychology, and neuroscience. His contributions to computational neuroscience include theories for how the brain can sense optic flow and egomotion, and a theory of the neural processing called the normalization model. His empirical research has used a combination of psychophysics (perceptual psychology) and neuroimaging (functional magnetic resonance imaging) to contribute to our understanding of the topographic organization of visual cortex (retinotopy), visual awareness, visual pattern detection/discrimination, visual motion perception, stereopsis (depth perception), attention, working memory, the control of eye and hand movements, neural processing of complex audio-visual and emotional experiences (movies, music, narrative), abnormal visual processing in dyslexia, and neurophysiological characteristics of autism. In the fields of image processing, computer vision, and computer graphics, Heeger 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), and texture analysis/synthesis

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