Decision Neuroscience

许多人每天都在努力做出与他们的目标一致的选择。他们吃不健康的食物，尽管知道健康的后果，看电视而不是去健身房，花几个小时在社交媒体上而不是工作。在压力、分心或时间紧迫的情况下，难以做出好的决策会变得特别严重，导致人们在做出好的决策最关键的时候做出次优的选择。尽管经过了几十年的研究，我们仍然不能完全理解其中的原因。为了了解人们面临的困难，并帮助他们做出更符合目标的选择，拟议的研究有三个目标。首先，它寻求开发更好的计算模型，以了解人们如何在相互竞争的优先事项之间进行艰难的权衡（例如，享受一顿饭与减肥）;当面临身体或精神限制（如疲劳、压力或时间限制）时，决策如何以及为什么会改变;以及这些变化如何导致选择偏见。其次，它试图理解这些计算的大脑基础或神经基础，并将神经功能的差异与计算过程的差异联系起来。最后，它试图将来自计算和神经过程的见解与现实世界的结果联系起来，无论是在日常目标实现的规模上，还是在数周至数月的时间段内。为了实现这些目标，拟议的研究计划将使用计算建模和脑成像的创新组合，沿着通过移动的技术（即，Apple Watch、定制的移动的手机应用程序的组合）。通过将计算预测和神经数据与基于实验室和现实世界的行为联系起来，该项目将阐明人们如何调整他们的决策策略，以适应他们每天面临的各种复杂的多因素选择。这项突破性的研究将为人们无法实现目标的原因提供新的见解，并使我们能够开发新的技术和策略来帮助他们取得成功。

Many people struggle on a daily basis to make choices that are consistent with their goals. They eat unhealthy foods despite knowing the health consequences, watch TV instead of going to the gym, and spend hours on social media instead of working. Difficulty making good decisions can become especially acute when stressed, distracted, or under a time crunch, leading people to suboptimal choices at precisely those moments where good decision making can be most crucial. Despite decades of research, we don't fully understand why. In order to understand the difficulties people face and to help them make more goal-consistent choices, the proposed research has three objectives. First, it seeks to develop better computational models for understanding how people navigate difficult trade-offs between competing priorities (e.g., enjoying a meal vs. losing weight); how and why decisions change when faced with physical or mental constraints like fatigue, stress, or time limits; and how those changes might lead to biases in choice. Second, it seeks to understand the brain-based, or neural, underpinnings of these computations, and to link differences in neural function to differences in computational processes. Finally, it seeks to link insights from computational and neural processes to real-world outcomes, both on the scale of day-to-day goal achievement and over time periods of weeks to months. In service of these objectives, the proposed research program will use innovative combinations of computational modeling and brain imaging, along with passive and active monitoring of daily goal achievement through mobile technology (i.e., a combination of Apple Watches, custom-built mobile phone apps). By linking computational predictions and neural data to both lab-based and real-world behaviour, this project will illuminate how people adapt their decision-making strategies to the kinds of complex, multi-factorial choices that they face on a daily basis. This ground-breaking research will yield novel insights into why people fail to achieve their goals, and allow us to develop new technologies and strategies to help them succeed.