Home > M.R. Bauer Foundation > 1997 Summary Report > Dana H. Ballard, Ph.D.

Dana H. Ballard, Ph.D.


Professor, Department of Computer Science
University of Rochester
Rochester, New York
September 26, 1996

The Role of Working Memory in Behaviors

Biosketch

Dana Ballard obtained his Ph.D. degree from the University of California at Irvine in 1974. During 1974-1975 he had a post-doctoral appointment at the Laboratorio Tecnologie Biomediche in Rome, Italy. Since 1975 he has been at the University of Rochester in the Computer Science Department where he has the rank of professor. He is the co-author with Professor Brown of "Computer Vision", a standard text, and has a new text "An Introduction to Natural Computation" that will be published by MIT Press in 1997.

Ballard's current research focus is in computational theories of the brain that account for its real-time performance. In 1985 with Chris Brown, he led a team that designed and built a high speed binocular camera control system capable of simulating human eye movements. Recently he has extended his interests to the use of Virtual Reality equipment, both for robot modeling and human behavioral studies.

The Role of Working Memory in Behaviors

Computational theories of the brain necessarily must have hierarchies, wherein the brain can be seen as using different instruction sets at different spatio-temporal scales. A central time scale is that of one-third of a second. At this time scale, the brain's neural instructions direct the physical resources of its body. An example of these kinds of instructions are those used to direct discrete eye-movements. Interpreting experimental data from this perspective implies that subjects select eye-movements in a special strategy to avoid loading working memory. Keeping working memory load at a minimum may reflect the structure of natural tasks. Studies of task learning show that the amount of state information needed at any instant is highly variable. This constraint has important implications for the computational theories of high-level behavior.

 


 

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