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Mechanisms in Classical Conditioning: A Computational Approach

Mechanisms in Classical Conditioning: A Computational Approach

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Nestor Schmajuk
Cambridge University Press, 1/14/2010
EAN 9780521887809, ISBN10: 0521887801

Hardcover, 504 pages, 24.7 x 17.4 x 2.7 cm
Language: English

What mechanisms are involved in enabling us to generate predictions of what will happen in the near future? Although we use associative mechanisms as the basis to predict future events, such as using cues from our surrounding environment, timing, attentional, and configural mechanisms are also needed to improve this function. Timing mechanisms allow us to determine when those events will take place. Attentional mechanisms ensure that we keep track of cues that are present when unexpected events occur and disregard cues present when everything happens according to our expectations. Configural mechanisms make it possible to combine separate cues into one signal that predicts an event different from that predicted individually by separate cues. Written for graduates and researchers in neuroscience, computer science, biomedical engineering and psychology, the author presents neural network models that incorporate these mechanisms and shows, through computer simulations, how they explain the multiple properties of associative learning.

Part I. Introduction
1. Classical conditioning
data and theories
Part II. Attentional and Associative Mechanisms
2. An attentional-associative model of conditioning
3. Simple and compound conditioning
4. The neurobiology of classical conditioning
5. Latent inhibition
6. The neurobiology of latent inhibition
7. Creativity
8. Blocking and overshadowing
9. Extinction
10. The neurobiology of extinction
Part III. Configural Mechanisms
11. A configural model of conditioning
12. Occasion setting
13. The neurobiology of occasion setting
Part IV. Attentional, Associative, Configural, and Timing Mechanisms
14. Configuration and timing
timing and occasion setting
15. Attention and configuration
extinction cues
16. Attention, association and configuration
causal learning and inferential reasoning
Part V. Conclusion
Mechanisms of classical conditioning.