AUTHOR=Wu Shih-Wei , Delgado Mauricio R., Maloney Laurence T. TITLE=GAMBLING ON VISUAL PERFORMANCE: NEURAL CORRELATES OF METACOGNITIVE CHOICE BETWEEN VISUAL LOTTERIES JOURNAL=Frontiers in Neuroscience VOLUME=9 YEAR=2015 URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2015.00314 DOI=10.3389/fnins.2015.00314 ISSN=1662-453X ABSTRACT=

A lottery is a list of mutually exclusive outcomes together with their associated probabilities of occurrence. Decision making is often modeled as choices between lotteries and—in typical research on decision under risk—the probabilities are given to the subject explicitly in numerical form. In this study, we examined lottery decision task where the probabilities of receiving various rewards are contingent on the subjects' own visual performance in a random-dot-motion (RDM) discrimination task, a metacognitive or second order judgment. While there is a large literature concerning the RDM task and there is also a large literature on decision under risk, little is known about metacognitive decisions when the source of uncertainty is visual. Using fMRI with humans, we found distinct fronto-striatal and fronto-parietal networks representing subjects' estimates of his or her performance, reward value, and the expected value (EV) of the lotteries. The fronto-striatal network includes the dorsomedial prefrontal cortex and the ventral striatum, involved in reward processing and value-based decision-making. The fronto-parietal network includes the intraparietal sulcus and the ventrolateral prefrontal cortex, which was shown to be involved in the accumulation of sensory evidence during visual decision making and in metacognitive judgments on visual performance. These results demonstrate that—while valuation of performance-based lotteries involves a common fronto-striatal valuation network—an additional network unique to the estimation of task-related performance is recruited for the integration of probability and reward information when probability is inferred from visual performance.