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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Vydáno v:	PloS one Ročník 18; číslo 6; s. e0286648
Hlavní autoři:	Kislov, Andrew, Shestakova, Anna, Ushakov, Vadim, Martinez-Saito, Mario, Beliaeva, Valeria, Savelo, Olga, Vasilchuk, Aleksey, Klucharev, Vasily
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States Public Library of Science 02.06.2023 Public Library of Science (PLoS)
Témata:	Analysis Behavior Biology and Life Sciences Brain Brain - diagnostic imaging Brain mapping Brain research Chain restaurants Consumer behavior Diagnostic imaging Evaluation Food Food habits Food Preferences Functional magnetic resonance imaging Human subjects Humans Image processing Magnetic resonance Magnetic resonance imaging Magnetic Resonance Imaging - methods Medical imaging Medicine and Health Sciences Meta-analysis Neostriatum Neuroimaging Physical Sciences Popularity Regression analysis Research and Analysis Methods Restaurants Reward Sales Social networks Social Sciences Success Valuation Russia
ISSN:	1932-6203, 1932-6203
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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 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.
AbstractList	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.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. 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. 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. 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. 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.sup.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.
Audience	Academic
Author	Beliaeva, Valeria Savelo, Olga Vasilchuk, Aleksey Klucharev, Vasily Kislov, Andrew Martinez-Saito, Mario Ushakov, Vadim Shestakova, Anna
AuthorAffiliation	1 International Laboratory of Social Neurobiology, Institute for Cognitive Neuroscience, HSE University, Moscow, Russia Temple University, UNITED STATES 3 Institute for Advanced Brain Studies, Lomonosov Moscow State University, Moscow, Russia 4 Restart Vasilchuk Brothers, Moscow, Russia 2 Decision Neuroscience Lab, Department of Health Sciences and Technology, ETH Zurich, Zürich, Switzerland
AuthorAffiliation_xml	– name: 4 Restart Vasilchuk Brothers, Moscow, Russia – name: Temple University, UNITED STATES – name: 3 Institute for Advanced Brain Studies, Lomonosov Moscow State University, Moscow, Russia – name: 2 Decision Neuroscience Lab, Department of Health Sciences and Technology, ETH Zurich, Zürich, Switzerland – name: 1 International Laboratory of Social Neurobiology, Institute for Cognitive Neuroscience, HSE University, Moscow, Russia
Author_xml	– sequence: 1 givenname: Andrew orcidid: 0000-0001-9722-3347 surname: Kislov fullname: Kislov, Andrew – sequence: 2 givenname: Anna surname: Shestakova fullname: Shestakova, Anna – sequence: 3 givenname: Vadim surname: Ushakov fullname: Ushakov, Vadim – sequence: 4 givenname: Mario orcidid: 0000-0001-6794-336X surname: Martinez-Saito fullname: Martinez-Saito, Mario – sequence: 5 givenname: Valeria orcidid: 0000-0002-3515-7265 surname: Beliaeva fullname: Beliaeva, Valeria – sequence: 6 givenname: Olga surname: Savelo fullname: Savelo, Olga – sequence: 7 givenname: Aleksey surname: Vasilchuk fullname: Vasilchuk, Aleksey – sequence: 8 givenname: Vasily surname: Klucharev fullname: Klucharev, Vasily
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/37267322$$D View this record in MEDLINE/PubMed
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Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Current address: International Laboratory of Social Neurobiology, Institute of Cognitive Neuroscience, Moscow, Russian Federation Competing Interests: The authors have declared that no competing interests exist. OS and AV also contributed equally to this work.
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SubjectTerms	Analysis Behavior Biology and Life Sciences Brain Brain - diagnostic imaging Brain mapping Brain research Chain restaurants Consumer behavior Diagnostic imaging Evaluation Food Food habits Food Preferences Functional magnetic resonance imaging Human subjects Humans Image processing Magnetic resonance Magnetic resonance imaging Magnetic Resonance Imaging - methods Medical imaging Medicine and Health Sciences Meta-analysis Neostriatum Neuroimaging Physical Sciences Popularity Regression analysis Research and Analysis Methods Restaurants Reward Sales Social networks Social Sciences Success Valuation
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Title	The prediction of market-level food choices by the neural valuation signal
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