The Redundancy Effect in Human Causal Learning: Attention, Uncertainty, And Inhibition
Using an allergist task, Uengoer, Lotz and Pearce (2013) found that in a design A+/AX+/BY+/CY-, the blocked cue X was indicated to cause the outcome to a greater extent than the uncorrelated cue Y. This finding has been termed “the redundancy effect” by Pearce and Jones (2015). According to Vogel and Wagner (2017), the redundancy effect “presents a serious challenge for those theories of conditioning that compute learning through a global error-term” (p. 119). One such theory is the Rescorla-Wagner (1972) model, which predicts the opposite result, that Y will have a stronger association with the outcome than X. This thesis explored the basis of the redundancy effect in human causal learning. Evidence from Chapter 2 suggested that the redundancy effect was unlikely to have been due to differences in attention between X and Y. Chapter 3 explored whether differences in participants’ certainty about the causal status of X and of Y contributed to the redundancy effect. Manipulations aimed at disambiguating the effects that X had on the outcome, including outcome-additivity training and low outcome rate, resulted in lower ratings for this cue and a smaller redundancy effect. However, the redundancy effect was still significant with both manipulations, suggesting that while participants’ uncertainty about the causal status of X contributed to it, there may have been other factors. Chapter 4 investigated whether another factor was a lack of inhibition for cue C. In a scenario where inhibition was more plausible than in an allergist task, a negative correlation between causal ratings for C and for Y, and a positive correlation between ratings for C and the magnitude of the redundancy effect, were found. In addition, establishing C as inhibitory resulted in a smaller redundancy effect than establishing C as neutral. Overall, findings of this thesis suggest that the redundancy effect in human causal learning is the result of participants’ uncertainty about the causal status of X, and a lack of inhibition for C. Further work is recommended to explore whether combining manipulations targeting X and Y would reverse the redundancy effect, whether effects of outcome additivity and outcome rate on X are the result of participants’ uncertainty about this cue, and the extent to which participants rely on single versus summed error.
Causal learning, Redundancy effect, Blocked cue, Uncorrelated cue, Attention, Uncertainty, Inhibition, Associative learning
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