Title :
Attention: Bits Versus Wows
Author_Institution :
Professor, Ph. D., University of California, Irvine, USA., Director of the Institute for Genomics and Bioinformatics, School of Information and Computer Science and Department of Biological Chemistry at the University of California, Irvine
Abstract :
The concept of surprise is central to sensory processing, adaptation and learning, attention, and decision making. Yet, no widely-accepted mathematical theory currently exists to quantitatively characterize surprise elicited by a stimulus or event, for observers that range from single neurons to complex natural or engineered systems. We describe a formal Bayesian definition of surprise that is the only consistent formulation under minimal axiomatic assumptions. Surprise quantifies how data affects a natural or artificial observer, by measuring the difference between posterior and prior beliefs of the observer. Using this framework we measure the extent to which humans direct their gaze towards surprising items while watching television and video games. Humans are strongly attracted to locations of high Bayesian surprise, with 72% of all human gaze shifts directed towards locations more surprising than the average, a figure which rises to 84% when considering only gaze targets simultaneously selected by all subjects. The resulting theory of surprise is applicable across different spatio-temporal scales, modalities, and levels of abstraction.
Keywords :
Bayesian methods; Bioinformatics; Biology; Chemistry; Computer science; Decision making; Genomics; Humans; Neurons; Systems engineering and theory;
Conference_Titel :
Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
Print_ISBN :
0-7803-9422-4
DOI :
10.1109/ICNNB.2005.1614699