Associative and connectionist accounts of biased contingency detection in humans

Associative models, such as the Rescorla-Wagner model (Rescorla & Wagner, 1972), correctly predict how some experimental manipulations give rise to illusory correlations. However, they predict that outcome-density effects (and illusory correlations, in general) are a preasymptotic bias that vanishes as learning proceeds, and only predict positive illusory correlations. Behavioural data showing illusory correlations that persist after extensive training and showing persistent negative illusory correlations exist but have been considered as anomalies. We investigated what the simplest connectionist architecture should comprise in order to encompass these results. Though the phenomenon involves the acquisition of hetero-associative relationships, a simple hetero associator did not suffice. An auto-hetero-associator was needed in order to simulate the behavioural data. This indicates that the structure of the inputs contributes to the outcome-density effect.status: publishe