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Introduction

Published online by Cambridge University Press:  10 January 2011

Nestor Schmajuk
Affiliation:
Duke University Medical Center, Durham
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Summary

This book contains the presentations given during the Duke Symposium on Computational Models of Conditioning, which took place between May 15th and May 17th of 2009 at the Duke Campus in Durham, N.C. The meeting was sponsored by the Duke Department of Psychology and Neuroscience, the Duke Office of the Vice Provost for International Affairs, and the Duke Arts and Sciences Research Council. All the participants and I are indebted for their generous support.

The meeting was organized with the assistance of my friend and former Ph.D. advisor Professor John Moore (University of Massachusetts at Amherst). I am particularly thankful to John for helping me in finding a group of participants who contributed both well-established and novel theories of classical conditioning. I am also grateful to Munir Gunes Kutlu for his help in running many aspects of the meeting.

The models

John Kruschke and Rick Hullinger (Indiana University, USA) prepared the chapter on “The evolution of learned attention.” In this chapter, the authors use simulated evolution, with adaptive fitness measured as overall accuracy during a lifetime of learning, and show that evolution converges to architectures that incorporate attentional learning. They also describe the specific training environments that encourage this evolutionary trajectory, and how we assess attentional learning in the evolved learners. Interestingly, the resulting attentional mechanism is similar to that proposed by Mackintosh (1975).

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Chapter
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Publisher: Cambridge University Press
Print publication year: 2010

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References

Grossberg, S. (1975). A neural model of attention, reinforcement, and discrimination learning. International Review of Neurobiology, 18, 263–327.CrossRefGoogle ScholarPubMed
Harris, J. A. (2006). Elemental representations of stimuli in associative learning. Psychological Review, 113, 584–605.CrossRefGoogle ScholarPubMed
Holland, P. C. & Fox, G. D. (2003). Effects of hippocampal lesions in overshadowing and blocking procedures. Behavioral Neuroscience, 117(3), 650–656.CrossRefGoogle ScholarPubMed
Pelley, M. E. (2004). The role of associative history in models of associative learning: a selective review and a hybrid model. The Quarterly Journal of Experimental Psychology, 57B, 193–243.CrossRefGoogle Scholar
Mackintosh, N. J. (1975). A theory of attention: variations in the associability of stimuli with reinforcement. Psychological Review, 82, 276–298.CrossRefGoogle Scholar
Miller, R. R. & Schachtman, T. (1985). Conditioning context as an associative baseline: implications for response generation and the nature of conditioned inhibition. In Miller, R. R. and Spear, N. E., eds., Information Processing in Animals: Conditioned Inhibition. Hillsdale, NJ: Erlbaum, pp. 51–88.Google Scholar
Padfield, G. D. & Lawrence, B. (2003). The birth of flight control: an engineering analysis of the Wright brothers' 1902 glider. The Aeronautical Journal, December, 697–718.Google Scholar
Pearce, J. M. & Hall, G. (1980). A model for Pavlovian conditioning: variations in the effectiveness of conditioned but not unconditioned stimuli. Psychological Review, 87, 332–352.CrossRefGoogle Scholar
Rescorla, R. A. & Wagner, A. (1972). A theory of Pavlovian conditioning: variations in the effectiveness of reinforcement and non-reinforcement. In Black, A. H. and Prokasy, W. F., eds., Classical Conditioning ii: Current Research and Theory. New York: Appleton–Century–Crofts, pp. 64–99.Google Scholar
Romer, A. S. (1970). The Vertebrate Body. Philadelphia: W. B. Saunders.Google Scholar
Schmajuk, N. A. (2010). Mechanisms in Classical Conditioning: A Computational Approach. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Schmajuk, N. A. & Di Carlo, J. J. (1989). A neural network approach to hippocampal function in classical conditioning. Behavioral Neuroscience, 105, 82–110.CrossRefGoogle Scholar
Schmajuk, N. A. & Di Carlo, J. J. (1992). Stimulus configuration, classical conditioning, and the hippocampus. Psychological Review, 99, 268–305.CrossRefGoogle Scholar
Schmajuk, N. A. & Larrauri, J. A. (2006). Experimental challenges to theories of classical conditioning: application of an attentional model of storage and retrieval. Journal of Experimental Psychology: Animal Behavior Processes, 32, 1–20.Google ScholarPubMed
Schmajuk, N. A., Cox, L. & Gray, J. A. (2001). Nucleus accumbens, entorhinal cortex and latent inhibition: a neural network approach. Behavioral Brain Research, 118, 123–141.CrossRefGoogle Scholar
Schmajuk, N. A., Lam, Y. & Gray, J. A. (1996). Latent inhibition: a neural network approach. Journal of Experimental Psychology: Animal Behavior Processes, 22, 321–349.Google ScholarPubMed
Schmajuk, N. A., Lamoureux, J. A. & Holland, P. C. (1998). Occasion setting: a neural network approach. Psychological Review, 105, 3–32.CrossRefGoogle ScholarPubMed
Stout, S. C. & Miller, R. R. (2007). Sometimes-competing retrieval (SOCR): a formalization of the comparator hypothesis. Psychological Review, 114, 759–783.CrossRefGoogle ScholarPubMed
Wagner, A. R. (1976). Priming in STM: an information-processing mechanism for self-generated or retrieval-generated depression in performance. In Tighe, T. J. and Leaton, R. N., eds., Habituation: Perspectives from Child Development, Animal Behavior, and Neurophysiology. Hillsdale, NJ: Erlbaum, pp. 95–128.Google Scholar
Wagner, A. R. (1979). Habituation and memory. In Dickinson, A. and Boakes, R. A., eds., Mechanisms of Learning and Motivation. Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
Wagner, A. R. (1981). SOP: A model of automatic memory processing in animal behavior. In Spear, N. E. and Miller, R. R., eds., Information Processing in Animals: Memory Mechanisms. Hillsdale, NJ: Erlbaum, pp. 5–47.Google Scholar
Wagner, A. R. & Brandon, S. E. (1989). Evolution of a structured connectionist model of Pavlovian conditioning (AESOP). In Klein, S. B. and Mowrer, R. R., eds., Contemporary Learning Theories: Pavlovian Conditioning and the Status of Traditional Learning Theory. Hillsdale, NJ: Erlbaum, pp. 149–189.Google Scholar

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  • Introduction
  • Nestor Schmajuk, Duke University Medical Center, Durham
  • Book: Computational Models of Conditioning
  • Online publication: 10 January 2011
  • Chapter DOI: https://doi.org/10.1017/CBO9780511760402.001
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  • Introduction
  • Nestor Schmajuk, Duke University Medical Center, Durham
  • Book: Computational Models of Conditioning
  • Online publication: 10 January 2011
  • Chapter DOI: https://doi.org/10.1017/CBO9780511760402.001
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Introduction
  • Nestor Schmajuk, Duke University Medical Center, Durham
  • Book: Computational Models of Conditioning
  • Online publication: 10 January 2011
  • Chapter DOI: https://doi.org/10.1017/CBO9780511760402.001
Available formats
×