Reward impacts visual statistical learning
Humans automatically detect and remember regularities in the visual environment--a type of learning termed visual statistical learning (VSL). Many aspects of learning from reward resemble statistical learning in respects, yet whether and how reward learning impacts VSL is largely unexamined. In two studies, we found that reward contingencies affect VSL, with high-value associated with stronger behavioral and neural signatures of such learning than low-value images. In Experiment 1, participants learned values (high or low) of images through a trial-and-error risky choice task. Unbeknownst to them, images were paired as four types--High-High, High-Low, Low-High, and Low-Low. In subsequent recognition and reward memory tests, participants chose the more familiar of two pairs (a target and a foil) and recalled the value of images. We found better recognition when the first images of pairs have high-values, with High-High pairs showing the highest recognition rate. In Experiment 2, we provided evidence that brain responses were affected by both value and statistical contingencies. When we compared responses between the high-value first image and the low-value first image, greater activation in regions that included inferior frontal gyrus, anterior cingulate gyrus, hippocampus, among other regions were found. These findings were driven by the interaction between statistically structured information and reward--the same value contrast yielded no regions for second-image contrasts and for singletons. Our results suggested that the powerful allocation of attention in response to the high-value first image potentially enables better memory for statistically learned pairs and reward information than low-value first image.