Single-dimensional human brain signals for two-dimensional economic choice options

Abstract

41Rewarding choice options typically contain multiple components, but neural signals vary in one 42 dimension (up or down). We used rigorous concepts of Revealed Preference Theory to investigate 43 how scalar neural responses represent vectorial rewards. Each reward constituted a bundle 44 containing the same two milkshakes with independently set amounts. Using psychophysics, we 45 estimated stochastic choice indifference curves (IC) that reflected the orderly integration of the 46 bundle components. All bundles on same ICs were equally revealed preferred (choice indifference); 47 bundles on higher ICs were preferred to bundles on lower ICs. Functional magnetic resonance 48 imaging (fMRI) demonstrated brain responses in reward-related brain structures, including striatum, 49 midbrain and medial orbitofrontal cortex. These responses followed the characteristic revealed 50 preference pattern: similar responses along ICs, but monotonic change across ICs. Thus, the 51 striatum, midbrain and medial orbitofrontal cortex integrate multiple reward components into a 52 scalar reward signal beyond known subjective value coding. 53 54 3 55 Introduction 56 57In daily life, we choose between rewards that have multiple components. In a restaurant, we can get, 58 for the same price, a small but tasty steak or a larger but less tasty steak. In that case, we trade taste 59 against meat. The trade-off shows that our preference for a good is based on more than one 60 component (taste and size in this case). To understand such choices, we need to know how the 61 different components of choice options are reflected in scalar measures of utility and preferences, 62 and their defining neuronal processes. 63