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Research Article
Transitivity, flexibility, conjunctive representations, and the hippocampus. II. A computational analysis
Article first published online: 7 FEB 2003
DOI: 10.1002/hipo.10084
Copyright © 2003 Wiley-Liss, Inc.
1098-1063/asset/cover.gif?v=1&s=006e5eacb07d69754fc016e21b7d8264e80128d3 "Hippocampus")
Additional Information
How to Cite
Frank, M. J., Rudy, J. W. and O'Reilly, R. C. (2003), Transitivity, flexibility, conjunctive representations, and the hippocampus. II. A computational analysis. Hippocampus, 13: 341–354. doi: 10.1002/hipo.10084
Publication History
- Issue published online: 7 FEB 2003
- Article first published online: 7 FEB 2003
- Manuscript Accepted: 22 MAY 2002
Funded by
- National Institute of Mental Health. Grant Number: MH613616
- Abstract
- References
- Cited By
Keywords:
- transitive inference;
- hippocampus;
- conjunctive representations;
- computational models;
- learning
Abstract
A computational neural network model is presented that explains how the hippocampus can contribute to transitive inference performance observed in rats (Dusek and Eichenbaum, 1997. Proc Natl Acad Sci U S A 94:7109–7114; Van Elzakker et al., 2003. Hippocampus 12:this issue). In contrast to existing theories that emphasize the idea that the hippocampus contributes by flexibly relating previously encoded memories, we find that the hippocampus contributes by altering the elemental associative weights of individual stimulus elements during learning. We use this model to account for a range of existing data and to make a number of distinctive predictions that clearly contrast these two views. Hippocampus 2003;13:341–354. © 2003 Wiley-Liss, Inc.