Rob de Ruyter van Steveninck
Indiana University, Bloomington
As animals navigate the world their sense organs measure a continuous stream of complex and noisy physical signals. This is particularly true for vision, which is ultimately based on the capture of randomly arriving photons. The brain then uses these sensory measurements to make inferences about events in the animal's environment, and Bayes' rule in statistics is the basis of a general theory of how to make such inferences. In this talk I will explore Biological information processing in terms of this general approach. To implement Bayes' rule one needs a statistical description of the relevant signals. I will present a strategy for sampling the joint statistics of visual signals and motion necessary for building an optimal estimator of motion based on visual input data. This approach leads to specific predictions about the structure of the optimal motion estimator. Those predictions will be compared to the real biological example of sensory measurement and motion estimation in the visual system of the blowfly.
Friday, May 15, 2008 at 4:00 PM
Room L211, Technological Institute
Refreshments are served at 3:30 PM
