Ambiguity Drives Higher-Order Pavlovian Learning

Abstract

In the natural world, stimulus-outcome associations are often noisy and ambiguous. Learning to disambiguate these associations to identify which specific outcomes will occur is critical for survival. Pavlovian occasion setters are stimuli that determine whether other stimuli that are ambiguous will result in a specific outcome. Occasion setting is a well-established field, but very little investigation has been conducted on how occasion setters are disambiguated when they themselves are ambiguous. We investigated the role of higher-order Pavlovian occasion setting in humans. We also developed and tested the first computational model predicting direct associations, traditional occasion setting, and 2nd-order occasion setting. Results showed that occasion setters affected ambiguous but not unambiguous lower-order stimuli and that 2nd-order occasion setting was indeed learned. Our computational model demonstrated excellent fit with the data, advancing our theoretical understanding of learning with ambiguity. These results may ultimately improve treatment of Pavlovian-based mental health disorders (e.g., anxiety).

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