Learned associability and associative change in human causal learning.

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.     

Uncertainty and predictiveness determine attention to cues during human associative learning

Prior research has suggested that attention is determined by exploiting what is known about the most valid predictors of outcomes and exploring those stimuli that are associated with the greatest degree of uncertainty about subsequent events. Previous studies of human contingency learning have revealed evidence for one or other of these processes, but differences in the designs and procedures of these studies make it difficult to pinpoint the crucial determinant of whether attentional exploitation or exploration will dominate. Here we present two studies in which we systematically manipulated both the predictiveness of cues and uncertainty regarding the outcomes with which they were associated. This allowed us to demonstrate, for the first time, evidence of both attentional exploration and exploitation within the same experiment. Moreover, while the effect of predictiveness persisted to influence the rate of novel learning about the same cues in a second stage, the effect of uncertainty did not. This suggests that attentional exploration is more sensitive to a change of context than is exploitation. The pattern of data is simulated with a hybrid attentional model.     

Comparing elemental and configural associative theories in human causal learning: a case for attention

In two causal learning experiments with human participants, the authors compared various associative theories that assumed either elemental (unique cue, modified unique cue, replaced elements model, and Harris' model) or configural processing of stimuli (Pearce's theory and a modification of it). The authors used modified patterning problems initially suggested by Redhead and Pearce (1995). Predictions for all theories were generated by computer simulations. Both configural theories and the unique cue approach failed to account for the observations. The replaced elements model was able to account for part of the data, but only if the replacement parameters could vary across discrimination problems. The Harris model and the modified unique cue approach, assuming that the salience of stimuli decreases with an increasing number of stimuli in a compound, successfully accounted for all of our data. This success implies that attentional factors should be explicitly taken into account in associative learning theory.     

Landmarks as beacons and associative cues: Their role in route learning

Relatively little is known about how people use the landmarks in their environment to learn routes. Landmarks are commonly regarded as associative cues--stimuli that enable recall of directional responses that lead closer to the navigator's goal. We contrast the function of landmark as associative cue with that of a beacon-a landmark near enough to a goal that moving toward it leads the navigator closer to his or her goal. In five experiments, participants learned a route through a simple desktop virtual environment. In the first three experiments, routes were learned better when their landmarks served as beacons than as associative cues. Two additional experiments showed that the acquired route knowledge depends on the function that landmarks serve during learning. Beacon-based route knowledge is less enduring and relatively less likely to involve knowledge of directions in the environment than is the route knowledge formed from landmarks that serve as associative cues.     

Blocking and unblocking in human causal learning

Three experiments sought to develop the suggestion that, under some circumstances, common associative learning mechanisms might underlie animal conditioning and human causal learning, by demonstrating, in humans, an effect analogous to the unblocking by reinforcer omission observed in animal conditioning. Experiment 1 found no such effect. Experiment 2, designed to prevent inhibitory influences that might have masked excitatory unblocking in Experiment 1, demonstrated unblocking, indicating common human-animal associative learning mechanisms in which the associability of a stimulus varies as a function of its predictive history. Experiment 3, using a similar design but with a procedure promoting application of rational inference processes, failed to detect the same unblocking effect, indicating that associative and cognitive mechanisms may influence human causal learning.     

Associative and categorical relations in the associative memory illusion

What kinds of associations underlie the associative memory illusion? In Experiment 1, lists composed of horizontal, or coordinate, free associates elicited false recognition of critical lures much more often than did lists composed of vertical, or subordinate, category instances. Experiment 2 replicated this result, and showed that the difference between free associates and category instances was not an artifact of differential levels of forward or backward associative strength. Associative structure plays an important role in the associative memory illusion: The illusion is strongest when the critical lure lies at the same level of categorization as the studied items.     

Context change as the mechanism of reinstatement in causal learning

Four experiments were conducted to explore the mechanism of reinstatement in human causal learning. After a retroactive interference treatment in which a stimulus was first followed by an outcome (A+) and then followed by a different outcome (A*), simple exposure to the original outcome (+) in the interference-test context produced partial reinstatement of the first-learned information (A+). When exposure to the outcome took place in a context different from the interference-test context, reinstatement was not observed (Experiment 1). Equivalent results appeared when the outcome presented during reinstatement was different from the one originally related to the stimulus affected by interference, independent of whether the interfering outcome (Experiments 2, 3, and 4) or a new outcome (Experiments 3 and 4) was presented before the test. These results suggest an interpretation of reinstatement in terms of a context change between interference and testing.     

Positive and negative patterning in human causal learning

Investigations of patterning discriminations by nonhuman animals have generally found that positive patterning is easier to learn than negative patterning. Studies of patterning discriminations in human causal learning tasks have failed to document any differences between positive and negative patterning. In the present study, human participants predicted an outcome on trials involving either a compound cue or its elements. Positive and negative patterning problems were successfully solved in a within-subjects design; negative patterning problems proved to be more difficult when an additional, 50% contingent cue was included (Experiment 2), but not when it was excluded (Experiment 1). Possible reasons for these results are discussed. The discussion concludes with an analysis of exemplar models (e.g., Pearce, 1994) of human causal learning and considers the conditions under which these models do and do not anticipate our results.     

Selective attention in human associative learning and recognition memory

Four experiments examined the role of selective attention in a new causal judgment task that allowed measurement of both causal strength and cue recognition. In Experiments 1 and 2, blocking was observed; pretraining with 1 cue (A) resulted in reduced learning about a 2nd cue (B) when those 2 cues were trained in compound (AB+). Participants also demonstrated decreased recognition performance for the causally redundant Cue B, suggesting that less attention had been paid to it in training. This is consistent with the idea that attention is preferentially allocated toward the more predictive Cue A, and away from the less predictive Cue B (e.g., N. J. Mackintosh, 1975). Contrary to this hypothesis, in Experiments 3 and 4, participants demonstrated poorer recognition for the most predictive cues, relative to control cues. A new model, which is based on N. J. Mackintosh's (1975) model, is proposed to account for the observed relationship between the extent to which each cue is attended to, learned about, and later recognized     

Human agency and associative learning: Pavlovian principles govern social process in causal relationship detection

Estimates of a worker's causal relationship (CR) to production obeyed associative principles, despite the participants' a priori beliefs that workers are responsible or "at cause" for production. In three experiments, social analogues of conditioned stimuli (workers) and unconditioned stimuli (company production information) were manipulated in familiar Pavlovian paradigms. The findings included (1) CR acquisition, (2) unconditioned stimulus-intensity effects, and (3) CR blocking. The research plan employed an approach that Neal Miller (1959) termed "extension of liberalized S-R theory" and drew on the Rescorla-Wagner model to integrate the experimental results, to illuminate the empirical data of social attribution research, and to guide the study of causal relationship detection using social stimuli.     

Generality of the summation effect in human causal learning

Considerable research has examined the contrasting predictions of the elemental and configural association theories proposed by Rescorla and Wagner (1972) and Pearce (1987), respectively. One simple method to distinguish between these approaches is the summation test, in which the associative strength attributed to a novel compound of two separately trained cues is examined. Under common assumptions, the configural view predicts that the strength of the compound will approximate to the average strength of its components, whereas the elemental approach predicts that the strength of the compound will be greater than the strength of either component. Different studies have produced mixed outcomes. In studies of human causal learning, Collins and Shanks (2006) suggested that the observation of summation is encouraged by training, in which different stimuli are associated with different submaximal outcomes, and by testing, in which the alternative outcomes can be scaled. The reported experiments further pursued this reasoning. In Experiment 1, summation was more substantial when the participants were trained with outcomes identified as submaximal than when trained with simple categorical (presence/absence) outcomes. Experiments 2 and 3 demonstrated that summation can also be obtained with categorical outcomes during training, if the participants are encouraged by instruction or the character of training to rate the separately trained components with submaximal ratings. The results are interpreted in terms of apparent performance constraints in evaluations of the contrasting theoretical predictions concerning summation.     

The role of associative history in models of associative learning: A selective review and a hybrid model

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.     

Second-order backward blocking and unovershadowing in human causal learning

De Houwer and Beckers (in press, Experiment 1) recently demonstrated that ratings about the relation between a target cue T2 and an outcome are higher when training involves CT1+ and T1T2+ followed by C+ trials than when training involves CT1+ and T1T2+ followed by C- trials. We replicated this study but now explicitly asked participants to rate the causal status of the cues both before and after the C+ or C- trials. Results showed that causal ratings for T2 were significantly higher after C+ trials than before C+ trials and that T2 received significantly lower ratings after C- trials than before C- trials. The results thus provide the first evidence for higher-order unovershadowing and higher-order backward blocking. In addition, the ratings for T1 revealed that first-order backward blocking (i.e., decrease in ratings for T1 as the result of C+ trials) was stronger than first-order unovershadowing (i.e., increase in ratings for T1 as the result of C- trials).     

Outcome maximality and additivity training also influence cue competition in causal learning when learning involves many cues and events

Recent evidence shows that outcome maximality (e.g., De Houwer, Beckers, & Glautier, 2002) and additivity training (e.g., Lovibond, Been, Mitchell, Bouton, & Frohard, 2003) have an influence on cue competition in human causal learning. This evidence supports the idea that cue competition is based on controlled reasoning processes rather than on automatic associative processes. Until now, however, all the evidence for controlled reasoning processes comes from studies with rather simple designs that involved only few cues and events. We conducted two experiments with a complex design involving 24 different cues. The results showed that outcome maximality and additivity training had an influence on cue competition but that this influence was more pronounced for forward cue competition than for retrospective cue competition.     

Predictions and causal estimations are not supported by the same associative structure

Studies performed by different researchers have shown that judgements about cue-outcome relationships are systematically influenced by the type of question used to request those judgements. It is now recognized that judgements about the strength of the causal link between a cue and an outcome are mostly determined by the cue-outcome contingency, whereas predictions of the outcome are more influenced by the probability of the outcome given the cue. Although these results make clear that those different types of judgement are mediated by some knowledge of the normative differences between causal estimations and outcome predictions, they do not speak to the underlying processes of these effects. The experiment presented here reveals an interaction between the type of question and the order of trials that challenges standard models of causal and predictive learning that are framed exclusively in associative terms or exclusively in higher order reasoning terms. However, this evidence could be easily explained by assuming the combined intervention of both types of process.     

The role of injection cues in the associative control of the US pre-exposure effect in flavour aversion learning

Two experiments, using rats as subjects, examined the role of contextual cues in producing the unconditioned stimulus (US) pre-exposure effect in conditioned taste aversion. Experiment 1 showed a significant US pre-exposure effect, when the pre-exposure was conducted in a familiar context, and that a change of context between the pre-exposure and conditioning phases did not attenuate this effect. Experiment 2 demonstrated that extinction of injection-related cues after the pre-exposure stage attenuated the US pre-exposure effect, when the pre-exposure was conducted in either a familiar or a novel context. Taken together, these results support the associative explanation of the US pre-exposure effect in terms of blocking, incorporating a role for injection-related cues in the context blocking analysis of the US pre-exposure effect.     

Age differences in associative and strategic processes in human conditional learning

Research indicates associative and strategic deficits mediate age related deficits in memory, whereas simple associative processes are independent of strategic processing and strategic processes mediate resistance to interference. The present study showed age-related deficits in a contingency learning task, although older participants' resistance to interference was not disproportionately affected. Recognition memory predicted discrimination, whereas general cognitive ability predicted resistance to interference, suggesting differentiation between associative and strategic processes in learning and memory, and age declines in associative processes. Older participants' generalisation of associative strength from existing to novel stimulus–response associations was consistent with elemental learning theories, whereas configural models predicted younger participants' responses. This is consistent with associative deficits and reliance on item-level representations in memory during later life.     

Determining whether causal order affects cue selection in human contingency learning: Comments on Shanks and Lopez (1996)

Shanks and Lopez (1996) reported three experiments in which they attempted to test whether causal order affects cue selection, and concluded that it does not. Their study provides an opportunity to highlight some basic methodological criteria that must be met in order to test whether and how causal order influences learning. In particular, it is necessary to (1) ensure that participants consistently interpret the learning situation in terms of directed cause-effect relations; (2) measure the causal knowledge they acquire; (3) manipulate causal order; and (4) control the statistical relations between cause and effect. With respect to these criteria, each experiment reported by Shanks and Lopez fails on multiple counts. Moreover, several aspects of the results reported by Shanks and Lopez are explained by causal-model theory, but not by associative accounts. Their study thus adds to a growing body of evidence from different laboratories indicating that human contingency learning can be guided by causal interpretation.     

Structural awareness mitigates the effect of delay in human causal learning

Many studies have demonstrated that reinforcement delays exert a detrimental influence on human judgments of causality. In a free-operant procedure, the trial structure is usually only implicit, and delays are typically manipulated via trial duration, with longer trials tending to produce both longer experienced delays and also lower objective contingencies. If, however, a learner can become aware of this trial structure, this may mitigate the effects of delay on causal judgments. Here we tested this “structural-awareness” hypothesis by manipulating whether response–outcome contingencies were clearly identifiable as such, providing structural information in real time using an auditory tone to delineate consecutive trials. A first experiment demonstrated that providing cues to indicate trial structure, but without an explicit indication of their meaning, significantly increased the accuracy of causal judgments in the presence of delays. This effect was not mediated by changes in response frequency or timing, and a second experiment demonstrated that it cannot be attributed to the alternative explanation of enhanced outcome salience. In a third experiment, making trial structure explicit and unambiguous, by telling participants that the tones indicated trial structure, completely abolished the effect of delays. We concluded that, with sufficient information, a continuous stream of causes and effects can be perceived as a series of discrete trials, the contingency nature of the input may be exploited, and the effects of delay may be eliminated. These results have important implications for human contingency learning and in the characterization of temporal influences on causal inference.     

Sensory information and associative cues used in food detection by wild vervet monkeys

Understanding animals’ spatial perception is a critical step toward discerning their cognitive processes. The spatial sense is multimodal and based on both the external world and mental representations of that world. Navigation in each species depends upon its evolutionary history, physiology, and ecological niche. We carried out foraging experiments on wild vervet monkeys (Chlorocebus pygerythrus) at Lake Nabugabo, Uganda, to determine the types of cues used to detect food and whether associative cues could be used to find hidden food. Our first and second set of experiments differentiated between vervets’ use of global spatial cues (including the arrangement of feeding platforms within the surrounding vegetation) and/or local layout cues (the position of platforms relative to one another), relative to the use of goal-object cues on each platform. Our third experiment provided an associative cue to the presence of food with global spatial, local layout, and goal-object cues disguised. Vervets located food above chance levels when goal-object cues and associative cues were present, and visual signals were the predominant goal-object cues that they attended to. With similar sample sizes and methods as previous studies on New World monkeys, vervets were not able to locate food using only global spatial cues and local layout cues, unlike all five species of platyrrhines thus far tested. Relative to these platyrrhines, the spatial location of food may need to stay the same for a longer time period before vervets encode this information, and goal-object cues may be more salient for them in small-scale space.