On the nature of CS and US representations in Pavlovian learning.

A significant problem in the study of Pavlovian conditioning is characterizing the nature of the representations of events that enter into learning. This issue has been explored extensively with regard to the question of what features of the unconditioned stimulus enter into learning, but considerably less work has been directed to the question of characterizing the nature of the conditioned stimulus. This article introduces a multilayered connectionist network approach to understanding how "perceptual" or "conceptual" representations of the conditioned stimulus might emerge from conditioning and participate in various learning phenomena. The model is applied to acquired equivalence/distinctiveness of cue effects, as well as a variety of conditional discrimination learning tasks (patterning, biconditional, ambiguous occasion setting, feature discriminations). In addition, studies that have examined what aspects of the unconditioned stimulus enter into learning are also reviewed. Ultimately, it is concluded that adopting a multilayered connectionist network perspective of Pavlovian learning provides us with a richer way in which to view basic learning processes, but a number of key theoretical problems remain to be solved, particularly as they relate to the integration of what we know about the nature of the representations of conditioned and unconditioned stimuli.