Efficient Data Compression in Perception, Memory, and Attention

Thursday 2 March 2023 – 13:00 GMT

Robert A. Jacobs, Professor of Brain & Cognitive Sciences, of Computer Science, and of the Center for Visual Science
Department of Brain and Cognitive Sciences, University of Rochester, Rochester, NY (USA)

Efficient data compression is essential for capacity-limited systems, such as biological perception, memory, and attention. We hypothesize that the need for efficient compression shapes biological systems in many of the same ways it shapes engineered systems. If true, then the tools engineers use to analyze and design systems, namely rate-distortion theory (RDT), can profitably be used to understand human behaviour. In this talk, we’ll start by discussing three general principles for efficient data compression, and provide experimental data evaluating the implications of these principles for human performance. Next, we’ll note that exact RDT methods are often computationally intractable, and explore a deep neural network architecture that implements RDT in an approximate manner. Lastly, we’ll hypothesize that perception, sensory memory, short-term memory, and long-term memory lie along a continuum, differing primarily in terms of their capacity limitations.

Short Bio: Professor Robert Jacobs attended the University of Pennsylvania for his undergraduate studies where he majored in Psychology.  He spent the next two years working as a Research Assistant in a biomedical research laboratory at Rockefeller University.  He earned a Ph.D. degree in Computer and Information Science (graduate advisor: Andrew Barto) from the University of Massachusetts at Amherst.  He then served in two postdoc positions, one in the Department of Brain & Cognitive Sciences at the Massachusetts Institute of Technology (postdoc advisor: Michael Jordan), and the other in the Department of Psychology at Harvard University (postdoc advisor: Stephen Kosslyn).  Robert Jacobs is currently a Professor of Brain & Cognitive Sciences, of Computer Science, and of the Center for Visual Science and a faculty member at the University of Rochester.  He is also a member of the Center for Computation and the Brain.