Reward impacts visual statistical learning [article]

Su Hyoun Park, Leeland L. Rogers, Matthew R. Johnson, Timothy J. Vickery
2020 bioRxiv   pre-print
Humans automatically and unintentionally 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 some respects, yet whether and how reward learning impacts VSL is largely unexamined. In two studies, we investigated the impact of reward on VSL and examined the neural basis of this interaction using fMRI. Subjects completed a risky choice task, in which they
more » ... the values (high or low) of fractal images through a trial-and-error binary-choice task. Unbeknownst to subjects, we paired images so that some images always predicted other images on the following trial. This led to four types of pairings (High-High, High-Low, Low-High, and Low-Low). In a subsequent recognition task and reward memory task, we asked them to choose the more familiar of two pairs (a target and a foil) and to recall the value of images (high or low). We found better recognition when the first image of a pair was a high-value image, with High-High pairs showing the highest recognition rate. To investigate the neural basis of this effect, we measured brain responses to visual images that were associated with both varying levels of reward and sequential contingencies with event-related fMRI. Subjects completed the same risky choice task and then passively viewed a stream of the images with pairwise relationships intact. Brain responses to images during the risky choice task were affected by both value and statistical contingencies. When we compared responses between the first image of a pair that was high-value and the first image of a pair that was low-value, we found greater activation in regions that included inferior frontal gyrus, left anterior cingulate gyrus, middle temporal gyrus, superior temporal gyrus, hippocampus, orbitofrontal cortex, caudate, nucleus accumbens, hippocampus, and lateral occipital cortex. These findings are not driven solely by the value difference, but rather the interaction between statistically structured information and reward − the same value contrast yielded no regions for either second-image contrasts or for singletons. Our results suggest that the first images of pairs that were associated with high-value, in comparison to those associated with low-value, were involved in greater attentional engagement, potentially enabling better memory for statistically learned pairs and reward information. Additionally, we found neural evidence that when an image contains both statistical structure and reward information, the reward learning may be predicted by the type of the statistical structure it is associated with. We conclude that reward contingencies affect VSL, with high-value associated with stronger behavioral and neural signatures of such learning.
doi:10.1101/2020.04.04.025668 fatcat:i5jii4tynffqjpcjm7mlax5osy