Abstract
Economic choice options contain multiple components and constitute vectorial bundles. The question arises how they are represented by single-dimensional, scalar neuronal signals that are suitable for economic decision-making. Revealed Preference Theory provides formalisms for establishing preference relations between such bundles, including convenient graphic indifference curves. During stochastic choice between bundles with the same two juice components, we identified neuronal signals for vectorial, multi-component bundles in the orbitofrontal cortex of monkeys. A scalar signal integrated the values from all bundle components in the structured manner of the Theory; it followed the behavioral indifference curves within their confidence limits, was indistinguishable between differently composed but equally revealed preferred bundles, predicted bundle choice and complied with an optimality axiom. Further, distinct signals in other neurons coded the option components separately but followed indifference curves as a population. These data demonstrate how scalar signals represent vectorial, multi-component choice options.
Highlights
Economic choice options contain multiple components and constitute vectorial bundles
With exhaustive choice sets composed of finite numbers of mutually exclusive multi-component options, revealed preferences do not depend on one bundle component alone but their combination into a bundle
The preferences are revealed by measurable choice: bundles that are chosen with equal probability are considered to be revealed preferred and to have same utility; a bundle that is chosen with higher probability than any other bundle in that option set is considered to be revealed preferred to that bundle and inferred to have higher utility than that bundle
Summary
Economic choice options contain multiple components and constitute vectorial bundles. 30 of 56 tested neurons (54%) showed significantly stronger chosen value responses to bundle x compared with bundle y in both {x, y, z} and {x, y} nonzero bundle sets (90 responses) (P < 0.002 for bundle factor x vs y and z in two-factor ANOVA; P < 0.0001 in Spearman rank-correlation), with convex ICs and concave ICs, even when one reward in the alternative bundle y (or z) was larger than in the revealed preferred bundle x (Fig. 5b, c; Supplementary Fig. 24b, c).
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