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

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 (f...

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Autores principales: Kislov, Andrew, Shestakova, Anna, Ushakov, Vadim, Martinez-Saito, Mario, Beliaeva, Valeria, Savelo, Olga, Vasilchuk, Aleksey, Klucharev, Vasily
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10237376/
https://www.ncbi.nlm.nih.gov/pubmed/37267322
http://dx.doi.org/10.1371/journal.pone.0286648
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author Kislov, Andrew
Shestakova, Anna
Ushakov, Vadim
Martinez-Saito, Mario
Beliaeva, Valeria
Savelo, Olga
Vasilchuk, Aleksey
Klucharev, Vasily
author_facet Kislov, Andrew
Shestakova, Anna
Ushakov, Vadim
Martinez-Saito, Mario
Beliaeva, Valeria
Savelo, Olga
Vasilchuk, Aleksey
Klucharev, Vasily
author_sort Kislov, Andrew
collection PubMed
description 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 R(2) 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.
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spelling pubmed-102373762023-06-03 The prediction of market-level food choices by the neural valuation signal Kislov, Andrew Shestakova, Anna Ushakov, Vadim Martinez-Saito, Mario Beliaeva, Valeria Savelo, Olga Vasilchuk, Aleksey Klucharev, Vasily PLoS One Research Article 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 R(2) 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. Public Library of Science 2023-06-02 /pmc/articles/PMC10237376/ /pubmed/37267322 http://dx.doi.org/10.1371/journal.pone.0286648 Text en © 2023 Kislov et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Kislov, Andrew
Shestakova, Anna
Ushakov, Vadim
Martinez-Saito, Mario
Beliaeva, Valeria
Savelo, Olga
Vasilchuk, Aleksey
Klucharev, Vasily
The prediction of market-level food choices by the neural valuation signal
title The prediction of market-level food choices by the neural valuation signal
title_full The prediction of market-level food choices by the neural valuation signal
title_fullStr The prediction of market-level food choices by the neural valuation signal
title_full_unstemmed The prediction of market-level food choices by the neural valuation signal
title_short The prediction of market-level food choices by the neural valuation signal
title_sort prediction of market-level food choices by the neural valuation signal
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10237376/
https://www.ncbi.nlm.nih.gov/pubmed/37267322
http://dx.doi.org/10.1371/journal.pone.0286648
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