An Information-Theoretic Framework for Understanding Saccadic Behaviors

Tai Sing Lee and Stella Yu
Advance in Neural Information Processing Systems, 2000.


Download
  • Adobe portable document format (pdf) (373KB)
Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract
In this paper, we propose that information maximization can provide a unified framework for understanding saccadic eye movements. In this framework, the mutual information among the cortical representations of the retinal image, the priors constructed from our long term visual experience, and a dynamic short?erm internal representation constructed from recent saccades provides a map for guiding eye navigation. By directing the eyes to locations of maximum complexity in neuronal ensemble responses at each step, the automatic saccadic eye movement system greedily collects information about the external world, while modifying the neural representations in the process. This framework attempts to connect several psychological phenomena, such as pop?ut and inhibition of return, to long term visual experience and short term working memory. It also provides an interesting perspective on contextual computation and formation of neural representation in the visual system.

Notes

Text Reference
Tai Sing Lee and Stella Yu, "An Information-Theoretic Framework for Understanding Saccadic Behaviors," Advance in Neural Information Processing Systems, 2000.

BibTeX Reference
@inproceedings{Yu_2000_3318,
   author = "Tai Sing Lee and Stella Yu",
   editor = "S.A. Solla, T.K. Leen, K-R. Muller",
   title = "An Information-Theoretic Framework for Understanding Saccadic Behaviors",
   booktitle = "Advance in Neural Information Processing Systems",
   publisher = "MIT Press",
   year = "2000",
   volume = "12",
}