CRCNS US-German Collaborative Research Proposal: Neural and computational mechanisms of flexible goal-directed decision making

CRCNS 美德合作研究提案：灵活目标导向决策的神经和计算机制

• 批准号: 2309022
• 负责人: Amitai Shenhav
• 金额: $ 81.22万
• 依托单位: Brown University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-02-01 至 2028-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2309022&HistoricalAwards=false
• 关键词: CRCNS; US; German; Collaborative; Research

To behave adaptively, people need to flexibly align their decisions with their immediate and long-term goals. Failures of such goal-directed decision-making can result in an array of maladaptive behaviors, such as financial risk taking, drug abuse, or gambling. While past research has helped identify the drivers of goal-directed decisions, there are still significant gaps in our understanding of how people are able to reorient those decisions as flexibly as they do, as well as when and why they fail to do so. In a series of studies that combine computational modeling with measures of behavior, attentional focus, and brain activity, we are studying the capacities and limits of human decision-makers to flexibly adjust their information search and actions to different goals and task demands. By uncovering the hidden levers and potential failure modes of goal-directed behavior, our work better disentangles sources of real-world decision-making failures, and provide a path towards targeted interventions to better align choices with long-term goals. Our project addresses critical gaps in research on the neural and computational mechanisms that link decision-making and cognitive control. Past work on the computational and neural mechanisms of goal-directed decision-making has been singularly focused on a narrow subset of human goals (how people select the best option from a set). It is therefore unknown how people flexibly reconfigure to their wider array of goals – for instance, selecting under different criteria or accumulating information across options rather than comparing between them – and when and why they fail to do so. Our project develops and tests a computational framework that accommodates the range of flexibility observed in human decision-making, by representing explicit choice goals that define a) how information is translated into evidence and b) how evidence is then integrated to select responses. We are testing our framework in a series of studies that combine behavioral tasks with eye-tracking, EEG and fMRI. This multi-modal approach allows us to uncover the neural circuits and dynamics that enable people to flexibly transform and integrate information about their options to achieve their current goals, and to understand how and why people vary in these capacities. The project further supports outreach activities aimed at training researchers in computational methods for predicting and testing a wide array of decision-making behavior.A companion project is being funded by the Federal Ministry of Education and Research, Germany (BMBF).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.

为了适当的行为，人们需要灵活地将自己的决定与直接和长期目标保持一致。这种指导决策的失败可能会导致一系列不良适应行为，例如财务风险服用，吸毒或赌博。尽管过去的研究有助于确定目标定向决策的驱动力，但我们对人们如何能够像他们一样灵活地重新定向这些决定，以及何时以及为什么不这样做仍然存在很大的差距。在一系列研究中，将计算建模与行为，注意力重点和大脑活动的度量相结合，我们正在研究人类决策者的能力和限制，以灵活地将其信息搜索和行动调整为不同的目标和任务要求。通过揭示隐藏的杠杆和目标指导行为的潜在故障模式，我们的工作可以更好地解开现实世界决策失败的来源，并为有针对性的干预措施提供途径，以更好地与长期目标更好地对齐选择。我们的项目解决了将决策和认知控制联系起来的神经和计算机制研究的关键差距。过去关于目标指导决策的计算和神经机制的工作一直集中在人类目标的狭窄子集上（人们如何从集合中选择最佳选择）。因此，人们如何灵活地重新配置各种目标是未知的 - 例如，在不同的条件下选择或在选项之间累积信息，而不是在它们之间进行比较 - 何时以及为什么不这样做。我们的项目开发和测试了一个计算框架，该计算框架通过代表定义的明确选择目标来适应人类决策中观察到的灵活性范围，a）信息如何转化为证据，b）然后如何将证据整合到选择响应。我们正在一系列研究中测试我们的框架，这些研究将行为任务与眼球，脑电图和fMRI结合在一起。这种多模式方法使我们能够揭示神经回路和动态，使人们能够灵活地转换和集成有关其选择的信息，以实现他们当前的目标，并了解人们在这些能力上的变化以及为什么会变化。 The project further supports outreach activities aimed at training researchers in Computational methods for predicting and testing a wide array of decision-making behavior.A companion project is being funded by the Federal Ministry of Education and Research, Germany (BMBF).This award reflects NSF's statutory mission and has been deemed precious of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.