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

为了适应行为，人们需要灵活地将他们的决定与他们的近期和长期目标结合起来。这种目标导向决策的失败会导致一系列适应不良行为，如金融冒险、滥用药物或赌博。虽然过去的研究有助于确定目标导向决策的驱动因素，但我们对人们如何能够灵活地重新调整这些决策，以及他们何时以及为什么不能这样做的理解仍然存在重大差距。在一系列将计算建模与行为、注意力集中和大脑活动测量相结合的研究中，我们正在研究人类决策者灵活调整其信息搜索和行动以适应不同目标和任务需求的能力和局限性。通过揭示目标导向行为的隐藏杠杆和潜在失败模式，我们的工作更好地解开了现实世界决策失败的根源，并为有针对性的干预提供了一条途径，使选择更好地与长期目标保持一致。我们的项目解决了连接决策和认知控制的神经和计算机制研究中的关键空白。过去关于目标导向决策的计算和神经机制的研究一直专注于人类目标的一个狭窄子集（人们如何从一组目标中选择最佳选项）。因此，我们不知道人们是如何灵活地重新配置以适应更广泛的目标——例如，根据不同的标准进行选择，或者在不同的选项中积累信息，而不是在它们之间进行比较——以及他们什么时候和为什么不能这样做。我们的项目开发并测试了一个计算框架，该框架通过表示明确的选择目标来定义a)如何将信息转化为证据以及b)如何将证据整合到选择响应中，从而适应人类决策中观察到的灵活性范围。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动追踪、脑电图和功能磁共振成像相结合。这种多模态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整合有关他们的选择的信息，以实现他们当前的目标，并了解人们如何以及为什么在这些能力上有所不同。该项目还支持旨在培训研究人员使用预测和测试各种决策行为的计算方法的外联活动。德国联邦教育和研究部（BMBF）正在资助一个伙伴项目。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.