Since first described, multiple properties of classical conditioning have been discovered, establishing the need for mathematical models to help explain the defining features. The mathematical complexity of the models puts our understanding of their workings beyond the ability of our intuitive thinking and makes computer simulations irreplaceable. The complexity of the models frequently results in function redundancy, a natural property of biologically evolved systems that is much desired in technologically designed products. Experts provide the latest advancements in the field and present detailed descriptions of how the models simulate conditioned behaviour and its physiological bases. It offers advanced students and researchers examples of how the models are used to analyse existing experimental results and design future experiments. This volume is of great interest to psychologists and neuroscientists, as well as computer scientists and engineers searching for ideas applicable to the design of robots that mimic animal behaviour.

Presents the latest advancements in the field of computational models of conditioning and some of their physiological bases.

About the Author
Dr Schmajuk is a Professor of Psychology and Neuroscience at Duke University. He has developed and tested several neural network models of classical conditioning, operant conditioning, animal communication, creativity, spatial learning, cognitive mapping and prepulse inhibition. His previous books include Animal Learning and Cognition: A Neural Network Approach (Cambridge University Press, 1997), Latent Inhibition and its Neural Substrates (Kluwer Academic, 2002), and Mechanisms in Classical Conditioning: A Computational Approach (Cambridge University Press, 2010).


Book Information
ISBN 9780521113649
Author Nestor Schmajuk
Format Hardback
Page Count 284
Imprint Cambridge University Press
Publisher Cambridge University Press
Weight(grams) 710g
Dimensions(mm) 253mm * 178mm * 13mm