Faculty

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Johannes Burge, PhD

Assistant Professor of Psychology

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Department: Psychology

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1f Graduate Group Affiliations 8

Neuroscience

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Suite 312C
17 3401 Walnut St.
39 Philadelphia, PA 19104
Philadelphia, PA 19104

2e Office: 215 573 6528
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Email:
jburge@sas.upenn.edu

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13 Education:
21 7 BA 17 (Psychology) c
2c Stanford University, 2000.
21 8 PhD 1b (Vision Science) c
3d University of California at Berkeley, 2008.
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a6 NGG Home » NGG Faculty » Computational a

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Description of Research Expertise

1bb A fundamental goal of vision research and systems neuroscience is to understand how sensory-perceptual processing operates with natural stimuli. How do we see? What are the computations that optimally transform sensory information into behaviorally relevant representations of the environment? What are the computations that humans and animals actually use? And how is performance supported by the underlying neurophysiology?
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237 Most knowledge of visual processing derives from research with simple artificial stimuli (e.g. bars and blobs). These artificial stimuli are easy to characterize mathematically, but they lack the rich structure of natural stimuli. Often, models that account for performance with artificial stimuli generalize poorly to natural stimuli. Unfortunately, natural stimuli are complex and difficult to study with precision. How, then, can we study sensory-perceptual processing with complex natural stimuli without sacrificing experimental and computational rigor?
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4f1 First, we simplify the problem. Rather than attempting to study natural stimuli in general, we narrow the problem by focusing on the properties of natural stimuli that are most useful for particular tasks. We do this because information relevant for one task may not be relevant for others; for example, the relative activation of the three cone types is a useful signal for estimating object color but it is not useful for estimating object motion. Next, we develop tools to enable rigorous mathematical characterization of task-relevant properties of natural stimuli. These tools help generate principled, quantitative hypotheses about how visual information should be ideally processed. Then, we use these hypotheses to design experiments that test behavioral performance and neural processing. In some cases, we have discovered strong similarities between the performance of ideal and human vision systems. Our work is showing that the variation and uncertainty in natural stimuli can be an asset rather than a hindrance for discovering the processing rules that optimize performance in critical sensory-perceptual tasks. Particular projects focus on the estimation and discrimination of motion, binocular disparity, and defocus blur from natural images.
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Selected Publications

e9 Bonnen K, Burge J, Yates J, Pillow JW, Cormack LK: Continuous psychophysics: Target-tracking to measure visual sensitivity. Journal of Vision 15(3): 1-16, 2015.

ef Sebastian S*, Burge J*, Geisler WS: Defocus discrimination in natural images with natural optics. Journal of Vision 15(5): 1-17, 2015 Notes: * Joint first authorship.

b9 Burge J, Geisler WS: Optimal disparity estimation in natural stereo-images. Journal of Vision 14(2): 1-18, 2014.

144 Geisler WS, Burge J, D'Antona AD, Michel MM: Characterizing the effects of stimulus and neural variability on perceptual performance. The Cognitive Neurosciences, 5th Edition. Gazzinga & Mangun (Eds.) (eds.). Cambridge: MIT Press, Page: 363-374, 2014.

e7 Scholl B, Burge J, Priebe NJ: Binocular integration and disparity selectivity in mouse primary visual cortex. Journal of Neurophysiology 109: 3013-3024, 2013.

e9 Burge J & Geisler WS: Optimal defocus estimates from individual images for autofocusing a digital camera. Proceedings of the SPIE-IS&T 8299(82990E): 1-12, 2012.

fc Burge J, Geisler WS: Optimal image-based defocus estimates from individual natural images. Proceedings of the Optical Society of America: Imaging Systems & Applications July 2011.

e2 Burge J, Geisler WS: Optimal defocus estimation in individual natural images. Proceedings of the National Academy of Sciences 108(40): 16849-16854, 2011.

101 Banks MS, Burge J, & Held R: The statistical relationship between depth, visual cues, and human perception. In: Sensory Cue Integration. Landy M (eds.). Oxford University Press, 2011.

ca Cooper EA, Burge J, Banks MS: The vertical horopter is not adaptable but it may be adaptive. Journal of Vision 11(3): 1-19, 2011.

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