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Trust is a key component of every social interaction. When meeting unfamiliar others, people make quick decisions on whom to trust that pose serious consequences for financial well-being. Older adults exhibit excessive trust relative to younger adults (e.g., 1, 2). A consequence of their excessive trust is that older adults are more likely to fall victim to financial fraud after initially meeting others (3), which may severely decrease quality of life. One explanation for their excessive trust is that older adults may learn to trust differently than younger adults. However, little is known about how age differences in learning to trust results in excessive trust among older adults. Given the growing US population of senior citizens (6), understanding how people learn to trust is an important societal issue. This project is significant in that it utilizes a unique approach drawing from decision neuroscience and computational modeling to test a novel mechanism underlying age differences in how younger versus older adults learn to trust.