Anticipation Effect after Implicit Distributional Learning


Distributional learning research has established that humans can track the frequencies of sequentially presented stimuli in order to infer the probabilities of upcoming events (e.g., Hasher & Zacks, 1984). Here, we set out to explore anticipation of a stimulus after implicit distributional learning. We hypothesize that as people learn the category frequency information implicitly, response times will scale according to the relative frequency of the stimulus category. Twelve adult participants viewed photographs of faces, tools, and buildings while performing a simple classification task. We found that response times significantly decreased with greater frequencies in the distribution of stimulus categories. This result suggested that distributional information about the internal representations of the stimuli could be learned and indicated the possibility that participants anticipated the stimuli proportional to the probability of the category appearing and thereby reduced response times for the more frequent categories.

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