It has been suggested that causal learning in humans is similar to Pavlovian conditioning in animals. According to this view, judgments of cause reflect the degree to which an association exists between the cause and the effect. Inferential accounts, by contrast, suggest that causal judgments are reasoning based rather than associative in nature. We used a direct measure of associative strength, identification of the outcome with which a cause was paired (cued recall), to see whether associative strength translated directly into causal ratings. Causal compounds AB+ and CD+ were intermixed with A+ and C- training. Cued-recall performance was better for cue B than for cue D; thus, associative strength was inherited by cue B from the strongly associated cue A (augmentation). However, the reverse was observed on the causal judgment measure: Cue B was judged to be less causal than D (cue competition). These results support an inferential over an associative account of causal judgments.
Both human and nonhuman animals need to be sensitive to the causal relationships between events in order to behave adaptively. It is not surprising, therefore, that a common mechanism-associative learning-has been proposed to account for the ability of humans and nonhumans to adapt to changing causal relationships in the environment (Dickinson, Shanks, & Evenden, 1984).
A scenario that has been widely used to investigate the underlying mechanism of causal learning in humans is the allergist task (Larkin, Aitken, & Dickinson, 1998). In this task, participants are informed that Mr. X has eaten (for example) cabbage, and they are then told that Mr. X suffered an allergic reaction. On test, participants commonly attribute the allergic reaction to the consumption of cabbage. The most straightforward account of this process in associative terms is that, because the cue (cabbage) was followed by the outcome (the allergic reaction), an association formed between the mental representations corresponding to these two events. Cabbage was judged to cause the allergic reaction because its presentation produced activation of the allergic reaction representation.
A range of findings support this associative account of causal learning (see De Houwer & Beckers, 2002, for a review), and the most important of these is cue competition (see, e.g., Chapman & Robbins, 1990). In cue competition, Mr. X might consume two different meals, cabbage and bread (compound cue AB) and pizza and beans (compound cue CD), and suffer an allergic reaction ( + ) following both meals (AB+ and CD+). If food cue A is also observed to be allergenic when presented alone (A+), but food C is safe (C-), then the causal rating of D will be higher than that of B on test. In associative learning terminology, the outcome on AB+ and CD+ trials can support only a limited amount of associative strength, for which each cue must compete. Therefore, A+ trials reduce, and C- trials increase, the amount of strength that remains to be made available to the partner cues B and D, respectively.
In general, the associative account makes the strong prediction that patterns of causal ratings will reflect the degree to which the allergic reaction outcome node is activated when a food cue is presented. Thus, outcome activation, or associative strength, could be measured independently to test this prediction. One method that has been used to assess associative strength in past studies is cued recall. Aitken, Larkin, and Dickinson (2001; see also Melchers, Lachnit, & Shanks, 2004) used cued recall to index the strength of an association between two food cues in their causal judgment experiment. Thus, a target food was presented on test, and participants were required to identify from a separate list the food that had appeared with the target during training. Accuracy on this task was taken to indicate the strength of the association between the two foods. Mitchell, Lovibond, Minard, and Lavis (in press) used a similar cued-recall task to measure the strength of association between a food cue and an outcome in the allergist task. …