Memory and the Computational Brain spans the fields of cognitive science, linguistics, psychology, neuroscience, and education, to suggest new perspectives on the way we consider learning mechanisms in the brain. Gallistel and King propose that the architecture of the brain is structured precisely for learning and for memory, and that the concept of an addressable read/write memory mechanism should be integrated into the foundations of neuroscience. They argue that the field of neuroscience can and should benefit from the recent advances of cognitive science and the development of information theory over the recent decades. Based on three lectures given by Randy Gallistel in the prestigious Blackwell-Maryland Lectures in Language and Cognition, the text has been significantly revised and expanded with numerous interdisciplinary examples and models and reflects recent research to make it essential reading for both students and those working in the field.

C. R. Gallistel is Co-Director of the Rutgers Center for Cognitive Science. He is one of the foremost psychologists working on the foundations of cognitive neuroscience. His publications include The Symbolic Foundations of Conditional Behavior (2002), and The Organization of Learning (1990). Adam Philip King is Assistant Professor of Mathematics at Fairfield University.

Leseprobe

Preface. 1. Information. 2. Bayesian Updating. 3. Functions. 4. Representations. 5. Symbols. 6. Procedures. 7. Computation. 8. Architectures. 9. Data Structures. 10. Computing with Neurons. 11. The Nature of Learning. 12. Learning Time and Space. 13. The Modularity of Learning. 14. Dead Reckoning in a Neural Network. 15. Neural Models of Interval Timing. 16. The Molecular Basis of Memory. References. Glossary. Index.