Collaborative Research: Invariants of Decision Making

科学、技术、经济、卫生和其他人类活动领域的创新从根本上取决于发现和利用不变性——即系统在不同环境下保持稳定的那些方面。在这个研究项目中，pi将识别反映在个人决策中的不变性属性——跨个人、跨选择上下文和跨选择任务的不变性。对决策行为的不变量（及其边界）的理解在工业、国家安全、消费者金融决策、健康决策和其他方面具有广泛的影响，特别是在设计决策支持系统、理解消费者行为和加强公民对金融和网络掠夺者的保护方面。该项目有三个组成部分：1)指定关于决策不变量的科学问题的精确数学公式；2)对这些不变量进行实验室研究；3)开发先进的统计和计算技术，用于分析获得的数据。该团队将研究一系列定制的数学模型，这些模型可能为理解决策中的不变性开辟新的途径。在多学科的长期研究传统的基础上，该团队将在实验室研究决策者如何在奖励与风险、奖励与时间延迟之间权衡，并检查指导决策的原则。这项研究的新颖之处在于它的数学工具和对不变性的关注：跨个体（个体差异）、跨选择背景（不同的选择选项）和跨选择任务（例如，风险选择与跨时间选择）。该项目的另一个新颖重点是发现决策不变性的生物标记，通过神经解剖学、神经生理学和脑功能的MRI测量进行检查，并通过调查健康和营养的营养生物标记。

Innovation in science, technology, economics, health, and other areas of human activity fundamentally hinges on discovering and leveraging invariances - those aspects of a system that remain stable across different contexts. In this research project, the PIs will identify the invariance properties reflected in individual decision making -- invariances across individuals, across choice contexts, and across choice tasks. Understanding of invariants of decision making behavior (and their boundaries) has broad implications in industry, national security, consumer financial decision making, health decision making and others, particularly in designing decision support systems, in understanding consumer behavior, and in enhancing citizen protection against financial and cyber-predators.The project has three components: 1) to specify mathematically precise formulations of scientific questions about invariants of decision making, 2) to conduct laboratory studies of such invariants, 3) to develop advanced statistical and computational techniques for the analysis of the obtained data. The team will study a range of customized mathematical models that may open up new avenues to understanding invariance in decision making. Building on a long research tradition in multiple disciplines, the team will study in the laboratory how decision makers trade-off between rewards and risk, rewards and time delays, and examine the principles that guide decision making. The novelty of the research resides in its mathematical tools and in its focus on invariance: across individuals (individual differences), across choice contexts (different choice options), and across choice tasks (say, risky choice vs. inter-temporal choice). An additional novel emphasis of the project is to discover biological markers of invariants in decision making, examined with respect to MRI measures of neuroanatomy, neurophysiology, and brain function, and by investigating nutrient biomarkers of health and nutrition.