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

为了做出适应性的行为，人们需要灵活地使他们的决定与他们的近期和长期目标保持一致。这种以目标为导向的决策失败可能会导致一系列不适应行为，如金融冒险、吸毒或赌博。尽管过去的研究帮助确定了目标导向决策的驱动因素，但对于人们如何能够像他们那样灵活地调整决策方向，以及他们何时未能做到这一点，以及他们未能做到这一点的原因，我们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的测量相结合的研究中，我们正在研究人类决策者根据不同的目标和任务要求灵活调整他们的信息搜索和行动的能力和限制。通过揭示目标导向行为的隐藏杠杆和潜在失败模式，我们的工作更好地理清了现实世界决策失败的根源，并提供了一条通向有针对性的干预的道路，以更好地使选择与长期目标保持一致。我们的项目解决了将决策和认知控制联系在一起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集中在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)上。因此，人们如何灵活地重新配置自己的更广泛的目标--例如，在不同的标准下进行选择，或者在不同的选项之间积累信息，而不是在它们之间进行比较--以及他们何时以及为什么未能做到这一点，都是未知的。我们的项目开发和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)如何整合证据以选择回应，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球跟踪、脑电和功能磁共振相结合。这种多模式方法使我们能够发现神经回路和动力学，使人们能够灵活地转换和整合有关实现当前目标的选择的信息，并了解人们如何以及为什么在这些能力上存在差异。该项目还支持外展活动，旨在培训研究人员使用计算方法预测和测试广泛的决策行为。德国联邦教育和研究部(BMBF)正在资助一个配套项目。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.