Associative learning theories strive to capture the processes underlying and driving the change in strength of the associations between representations of stimuli that develop as a result of experience of the predictive relationships between those stimuli. Historically, formal models of associative learning have focused on two potential factors underlying associative change, namely processing of the conditioned stimulus (in terms of changes in associability) and processing of the unconditioned stimulus (in terms of changes in error). This review constitutes an analysis of the proper role of these two factors, specifically with regard to the way in which they are influenced by associative history (the prior training undergone by cues). A novel "hybrid" model of associative learning is proposed and is shown to provide a more satisfactory account of the effects of associative history on subsequent learning than any previous single-process theory.

Attention provides the gateway to cognition, by selecting certain stimuli for further analysis. Recent research demonstrates that whether a stimulus captures attention is not determined solely by its physical properties, but is malleable, being influenced by our previous experience of rewards obtained by attending to that stimulus. Here we show that this influence of reward learning on attention extends to task-irrelevant stimuli. In a visual search task, certain stimuli signaled the magnitude of available reward, but reward delivery was not contingent on responding to those stimuli. Indeed, any attentional capture by these critical distractor stimuli led to a reduction in the reward obtained. Nevertheless, distractors signaling large reward produced greater attentional and oculomotor capture than those signaling small reward. This counterproductive capture by task-irrelevant stimuli is important because it demonstrates how external reward structures can produce patterns of behavior that conflict with task demands, and similar processes may underlie problematic behavior directed toward real-world rewards.

This article presents a comprehensive survey of research concerning interactions between associative learning and attention in humans. Four main findings are described. First, attention is biased toward stimuli that predict their consequences reliably (). This finding is consistent with the approach taken by Mackintosh (1975) in his attentional model of associative learning in nonhuman animals. Second, the strength of this attentional bias is modulated by the value of the outcome (). That is, predictors of high-value outcomes receive especially high levels of attention. Third, the related but opposing idea that may result in increased attention to stimuli (Pearce & Hall, 1980), receives less support. This suggests that hybrid models of associative learning, incorporating the mechanisms of both the Mackintosh and Pearce-Hall theories, may not be required to explain data from human participants. Rather, a simpler model, in which attention to stimuli is determined by how strongly they are associated with significant outcomes, goes a long way to account for the data on human attentional learning. The last main finding, and an exciting area for future research and theorizing, is that and modulate both deliberate attentional focus, and more automatic attentional capture. The automatic influence of learning on attention does not appear to fit the traditional view of attention as being either or. Rather, it suggests a new kind of “derived” attention.

The Mackintosh (1975) model of associative learning specifies that processing of both the cues presented on a trial and the outcome of that trial will interact to determine the amount of associative change undergone by a given cue. Experiments looking at the distribution of associative change among the elements of a reinforced compound in animal conditioning studies indicate that processing of the outcome of a trial does indeed influence associative change. The work reported here investigates the distribution of associative change among the elements of a reinforced compound in a human causal judgement paradigm, and it indicates that processing of the cues presented on a trial also plays a role in determining associative change (in terms of changes in the associability of cues as a result of experience). Taken in combination, these results provide good support for Mackintosh (1975) and the characterizations of both cue and outcome processing that it offers.

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Monkeys will selectively and adaptively learn to avoid the most difficult trials of a perceptual discrimination learning task. Couchman, Coutinho, Beran, and Smith (2010) have recently demonstrated that this pattern of responding does not depend on animals receiving trial-by-trial feedback for their responses; it also obtains if experience of the most difficult trials occurs only under conditions of deferred feedback. Couchman et al. argued that this ruled out accounts based on low-level processes of associative learning and instead required explanation in terms of metacognitive processes of decision monitoring. Contrary to this argument, a simple associative model of reinforcement learning is shown to account for the key findings of Couchman et al.'s empirical study, along with several other findings that have previously been claimed to challenge associative models.

Attentional theories of associative learning and categorization propose that learning about the predictiveness of a stimulus influences the amount of attention that is paid to that stimulus. Three experiments tested this idea by looking at the extent to which stimuli that had previously been experienced as predictive or nonpredictive in a categorization task were able to capture attention in a dot probe task. Consistent with certain attentional theories of learning, responses to the dot probe were faster when it appeared in a location cued by a predictive stimulus compared to a location cued by a nonpredictive stimulus. This result was obtained only with short (250-ms or 350-ms) but not long (1,000-ms) delays between onset of the stimuli and the dot probe, suggesting that the observed spatial cuing effect reflects the operation of a relatively rapid, automatic process. These findings are consistent with the approach to the relationship between attention and learning taken by the class of models exemplified by Mackintosh's (1975) theory.

Two experiments used eye-tracking procedures to investigate the relationship between attention and associative learning in human participants. These experiments found greater overt attention to cues experienced as predictive of the outcomes with which they were paired, than to cues experienced as nonpredictive. Moreover, this attentional bias persisted into a second training phase when all cues were equally predictive of the outcomes with which they were paired, and it was accompanied by a related bias in the rate of learning about these cues. These findings are consistent with the attentional model of associative learning proposed by Mackintosh (1975), but not with that proposed by Pearce and Hall (1980).