Abstract
In recent years, several studies of human predictive learning demonstrated better learning about outcomes that have previously been experienced as consistently predictable compared to outcomes previously experienced as less predictable, namely the outcome predictability effect. As this effect may have wide-reaching implications for current theories of associative learning, the present study aimed to examine the generality of the effect with a human goal-tracking paradigm, employing three different designs to manipulate the predictability of outcomes in an initial training phase. In contrast to the previous studies, learning in a subsequent phase, when every outcome was equally predictable by novel cues, was not reliably affected by the outcomes’ predictability in the first phase. This lack of an outcome predictability effect provides insights into the parameters of the effect and its underlying mechanisms.
Highlights
Learning about the relationship between stimuli and events is a fundamental ability of humans and other animals that enables organisms to prepare for future events and adapt to their environment
The question has been raised as to whether the associative history of outcomes plays a role in subsequent learning about novel cue-outcome associations, beyond its influence in calculations of prediction error [16 for a review, see 49]
We manipulated outcome predictability using three different designs, and investigated whether this manipulation would bias subsequent learning about the outcomes, when each of them became fully predictable by novel cues
Summary
Learning about the relationship between stimuli and events is a fundamental ability of humans and other animals that enables organisms to prepare for future events and adapt to their environment. A classic example of this ability is Pavlovian conditioning [1]. Many contemporary theories assume that the CR reflects the organism’s prediction of the outcome based on the accumulation of knowledge about the sequential structure of its environment during Pavlovian conditioning [2 for a review]. Associative learning models assume that this knowledge takes the form of associations between mental representations of events, and that learning results in changes to the association between the cue and the outcome (ΔV) [3]. According to the Rescorla-Wagner model, learning is determined by the discrepancy between the outcome experienced, and the outcome predicted by the associations between cues and outcomes (i.e., the prediction error is minimized during learning)
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