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.
