CAREER: Neural and Computational Basis of Guilt in Decision-Making

情绪是人类经验的一个重要方面，它直接影响我们如何做出决定，我们如何形成人际关系，以及我们更广泛的身心健康。情绪来自于对世界的评价，同时考虑我们的未来目标，过去的经历和当前状态。例如，人类有与他人联系的基本需求，而内疚等情绪可以提供信号，帮助指导我们的行为，通过最大限度地减少我们的行为对他人的负面影响来实现这些更广泛的社会目标。然而，这些内部体验目前只能通过内省进行主观评估，这限制了我们理解大脑如何产生这些独特感受以及这些体验在个体之间的整体一致性的能力。通过一系列的研究，我们将：（a）在被要求做出选择以减少他人痛苦的参与者中引发内疚感;（B）使用面部表情和大脑活动的计算模型来开发这些内疚体验的客观衡量标准;以及（c）评估这些内疚体验如何与其他类型的心理过程相关联，例如感知他人的内疚，回忆过去的内疚体验，做出伤害他人的决定这项工作具有重要意义的一些后果，情感，和昂贵的决定，可能会影响他人在众多领域，如医疗保健，政治和business.This建议利用计算技术，以确定使用大脑模式和面部表情的内疚体验的客观措施。在目标1中，我们将阐明内疚厌恶是如何在决策中将对他人的伤害降到最低的核心动机，并且可以通过模拟大脑活动模式来客观地测量。在目标2中，我们使用这些客观测量来更好地理解内疚体验与其他类型的心理过程（感知，记忆和想象内疚）的关系。在目标3中，我们将研究大脑信号是否能够独特地捕捉内疚的信号，或者这些体验是否也可以用面部表情的模式来衡量。这项工作提供了一个独特的跨学科的方法，以提高我们对内疚的理解。首先，我们展示了我们的能力，成功地引发内疚使用自然的社会互动，并确定一个共同的代表性模式的大脑活动。这将使我们能够对这一测量进行结构验证，以描述内疚体验与其他相关心理体验的关系，例如观察他人的痛苦，回忆以前的内疚体验，或做出伤害他人的决定。第三，这项提议将评估内疚是否在大脑信号中被独特编码，或者它是否可能在其他下游信号中表现出来，如面部表情的模式。如果成功的话，这项工作可能会通过克服自我报告在研究情绪体验方面的局限性，对情绪领域产生变革性的影响。这一建议也可以提供重要的洞察力，以评估替代低成本的测量神经成像在捕捉心理经验，通过面部表情的效用。最后，这项工作可能对更广泛的决策产生影响;我们对最小化内疚的偏好可能如此强烈，以至于它们压倒了与决策结果相关的其他成本。 这项建议还包括协同教育培训和推广，以扩大工作，包括一个新的密集的夏季培训计划;社区服务组织的推广;和本科生和医科学生的新课程。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

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.