Proceedings of the National Academy of Sciences of the United States of America

About the PNAS Member Editor
Name Geisler, Wilson S.
Location The University of Texas at Austin
Primary Field Psychological and Cognitive Sciences
Secondary Field Systems Neuroscience
 Election Citation
Geisler developed mathematical models of visual processing, along with empirical explorations of neural mechanisms. His theories explain phenomena ranging from the complex visual tasks performed by retinal and cortical neurons to how human visual acuity is determined by the distribution of visual receptors and the quantum nature of light.
 Research Interests
I study perception and perceptual neuroscience, with an emphasis on vision in humans and non-human primates. My early years were directed at understanding the relationship between the retinal physiology of light and dark adaptation and the behavioral detection and discrimination performance of humans. This was followed by a series of studies directed at understanding the role of optical and retinal factors in limiting human spatial and color vision. These studies pioneered the application of (Bayesian) ideal observer theory to domains beyond simple photon detection and intensity discrimination. More recently the lab has been focused on spatial and contrast coding in the primate visual cortex, on natural tasks and natural scene statistics, and on the mathematics of how to perform perceptual tasks optimally. For example, we derived the theory for how to move the eyes optimally when searching for targets in natural texture and are using that theory to analyze human performance and eye movement statistics. For another example, we measured the statistical properties of contours in natural scenes, derived the theory of how to optimally use those properties to detect and interpolate contours in natural images and are using the theory to analyze human contour detection and interpolation performance.

 
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