The prediction of market-level food choices by the neural valuation signal

Andrew Kislov, Anna Shestakova, Vadim Ushakov, Mario Martinez-Saito, Valeria Beliaeva, Olga Savelo, Aleksey Vasilchuk and Vasily Klucharev

PLOS ONE, 2023, vol. 18, issue 6, 1-18

Abstract: Neuroimaging studies have demonstrated the ability to use the brain activity of a group of individuals to forecast the behavior of an independent group. In the current study, we attempted to forecast aggregate choices in a popular restaurant chain. During our functional magnetic resonance imaging (fMRI) study, 22 participants were exposed to 78 photos of dishes from a new menu of a popular restaurant chain. In addition to self-reported preferences, fMRI data was extracted from an a priori domain-general and task-specific region of interest—the ventral striatum. We investigated the relationship between the neural activity and real one-year sales provided by the restaurant chain. Activity in the ventral striatum, which was defined using the task-specific region of interest, significantly correlated (r = 0.28, p = 0.01) with one-year sales. A regression analysis, which included ventral striatum activity together with the objective characteristics of the products (price and weight), behavioral, and survey data, showed R2 values of 0.33. Overall, our results confirm prior studies, which have suggested, that brain activity in the reward system of a relatively small number of individuals can forecast the aggregate choice of a larger independent group of people.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0286648

DOI: 10.1371/journal.pone.0286648

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