| Summary: | We present a novel two-stage probabilistic learning task that examines the participants’ ability to learn and utilize valid cues across several levels of probabilistic feedback. In the first stage, participants sample from one of three cues that gives predictive information about the outcome of the second stage. Participants are rewarded for correct prediction of the outcome in stage two. Only one of the three cues gives valid predictive information and thus participants can maximise their reward by learning to sample from the valid cue. The validity of this predictive information, however, is reinforced across several levels of probabilistic feedback. A second manipulation involved changing the consistency of the predictive information in stage one and the outcome in stage two. The results show that participants, with higher probabilistic feedback, learned to utilise the valid cue. In inconsistent task conditions, however, participants were significantly less successful in utilising higher validity cues. We interpret this result as implying that learning in probabilistic categorization is based on developing a representation of the task that allows for goal-directed action.
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