Null hypotheses are simple, precise, and theoretically important. Conventional statistical analysis cannot support them; Bayesian analysis can. The challenge in a Bayesian analysis is to formulate a suitably vague alternative, because the vaguer the alternative is (the more it spreads out the unit mass of prior probability), the more the null is…

A. Redish et al. (2007) proposed a reinforcement learning model of context-dependent learning and extinction in conditioning experiments, using the idea of "state classification" to categorize new observations into states. In the current article, the authors propose an interpretation of this idea in terms of normative statistical inference. They…

The participation of attentional and associative mechanisms in extinction, spontaneous recovery, external disinhibition, renewal, reinstatement, and reacquisition was evaluated through computer simulations with an extant computational model of classical conditioning (N. A. Schmajuk, Y. Lam, & J. A. Gray, 1996; N. A. Schmajuk & J. A. Larrauri,…

Cue competition is one of the most studied phenomena in associative learning. However, a theoretical disagreement has long stood over whether it reflects a learning or performance deficit. The comparator hypothesis, a model of expression of Pavlovian associations, posits that learning is not subject to competition but that performance reflects a…

Early experiments suggesting that classical conditioning depends on the contingency between conditioned stimulus (CS) and the unconditioned stimulus (US) are reconsidered along with later evidence that shows conditioning of the CS and its context in random training. CS-US contingency is neither necessary nor sufficient for conditioning. (SLD)

This article reviews evidence and theories concerning the nature of stimulus representations in Pavlovian conditioning. It focuses on the elemental approach developed in stimulus sampling theory (R. C. Atkinson & W. K. Estes, 1963; R. R. Bush & F. Mosteller, 1951b) and extended by I. P. L. McLaren and N. J. Mackintosh (2000, 2002) and contrasts…

A theory of classical conditioning is presented, which is based on a parallel, rule-based performance system integrated with mechanisms for inductive learning. A major inferential heuristic incorporated into the theory involves "unusualness," which is focused on novel cues. The theory is implemented via computer simulation. (TJH)

The participation of the hippocampus in classical conditioning is described in terms of a multilayer network portraying stimulus configuration. A model of hippocampal function is presented, and computer simulations are used to study neural activity in the various brain areas mapped according to the model. (SLD)

By integrating previous computational models of corticohippocampal function, the authors develop and test a unified theory of the neural substrates of familiarity, recollection, and classical conditioning. This approach integrates models from 2 traditions of hippocampal modeling, those of episodic memory and incremental learning, by drawing on an…

A detailed description of a layered network model is provided, with computer simulations of key associative learning phenomena and predictions generated from the model. The model is compared to more conventional theories of learning to learn and configural learning. (SLD)