Using Unobserved Causes to Explain Unexpected Outcomes: The Effect of Existing Causal Knowledge on Protection From Extinction by a Hidden Cause

People often rely on the covariation between events to infer causality. However, covariation between cues and outcomes may change over time. In the associative learning literature, extinction provides a model to study updating of causal beliefs when a previously established relationship no longer holds. Prediction error theories can explain both extinction and protection from extinction when an inhibitory (preventive) cue is present during extinction. In three experiments using the allergist causal learning task, we found that protection could also be achieved by a hidden cause that was inferred but not physically present, so long as that cause was a plausible preventer of the outcome. We additionally showed complete protection by a physically presented cue that was neutral rather than inhibitory at the outset of extinction. Both findings are difficult to reconcile with dominant prediction error theories. However, they are compatible with the idea of theory protection, where the learner attributes the absence of the outcome to the added cue (when present) or to a hidden cause, and therefore does not need to revise causal beliefs about A. Our results suggest that prediction error encourages changes in causal beliefs, but the nature of the change is determined by reasoning processes that incorporate existing knowledge of causal mechanisms and may be biased toward preservation of existing beliefs.