[PS-1.15] Prediction and statistical learning in infants and adults: A pupillometry study

Zhang, F. 1 , Jaffe-Dax, S. 1 , Wilson, R. . 2 & Emberson, L. 1

1 Princeton University
2 University of Arizona

Infants and adults are able to detect regularities in the environment and use this information to generate predictions about future sensory inputs, an ability known as statistical learning. However, it is unknown whether this represents an ability that is continuous or whether an infant?s ability to learn and predict is different from an adult?s. The goal of this study is to provide the first direct comparison of prediction and prediction error across infants and adults. We used pupillometry because it is one of the few methods that allows for the recording of the same physiological response in an identical behavioral paradigm across these disparate age groups. Furthermore, pupil diameter has been shown to be a marker of uncertainty and surprise in adults, both of which reflect learning and prediction. We measured infants? and adults? pupil dilation response (PDR) as they completed an implicit learning task. We found significantly larger PDR for omission trials (i.e. trials that violated participants? predictions) compared to present trials (i.e. trials that confirmed participants? predictions) in both infants and adults. Furthermore, a learning model demonstrated similar time-course and magnitude of this response across age groups suggesting a life-span continuity of mechanism in prediction and statistical learning.