Emotions are a critical aspect of the human experience that directly impact how we make decisions, how we form interpersonal relationships, and our broader mental and physical health. Emotions result from making evaluations about the world while considering our future goals, past experiences, and current states. For example, humans have a basic need to connect with others, and emotions such as guilt can provide signals that help guide our behavior to meet these broader social goals by minimizing the negative impact of our actions on others. However, these internal experiences can currently only be subjectively assessed via introspection, which has limited our ability to understand how our brain generates these unique feelings and the overall consistency of these experiences across individuals. Through a series of studies, we will: (a) elicit feelings of guilt in participants tasked with making choices to reduce another person's suffering; (b) develop objective measures of these guilt experiences using computational models of facial expressions and brain activity; and (c) evaluate how these guilt experiences relate to other types of psychological processes such as perceiving guilt in others, remembering past experiences of guilt, and making decisions to harm others. This work has important implications for a number of consequential, emotional, and costly decisions that might impact others in a multitude of domains such as healthcare, politics, and business.
This proposal leverages computational techniques to identify objective measures of guilt experiences using brain patterns and facial expressions. In Aim 1, we will elucidate how guilt-aversion is a central motivation in making decisions to minimize harm to others and can be objectively measured by modelling patterns of brain activity. In Aim 2, we use these objective measures to better understand how guilt experiences relate to other types of psychological processes (perceiving, remembering, and imagining guilt). In Aim 3, we will examine if brain signals are uniquely able to capture signatures of guilt, or if these experiences can also be measured using patterns of facial expressions. This work provides a unique interdisciplinary approach to improve our understanding of guilt. First, we demonstrate our ability to successfully elicit guilt using a naturalistic social interaction and identify a common representation in a pattern of brain activity. This will allow us to perform construct validation on this measure to characterize how the experience of guilt relates to other related psychological experiences such as observing others in pain, recalling a previous guilty experience, or making decisions to harm others. Third, this proposal will evaluate whether guilt is uniquely encoded in brain signals, or if it might be manifested in other downstream signals such as patterns of facial expressions. If successful, this work might have a transformative impact on the field of emotion by overcoming the limitations of self-report in studying emotional experiences. This proposal can also provide important insight into evaluating the utility of alternative low-cost measurements to neuroimaging in capturing psychological experiences via facial expressions. Finally, this work could have implications for decision-making more broadly; our preferences for minimizing guilt may be so strong that they overwhelm the other costs associated with decision outcomes. This proposal also incorporates synergistic educational training and outreach to broaden the work, including a new intensive summer training program; outreach to community service organizations; and new curriculum for undergraduate and medical students.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
