ArticleScientific data2026
A densely sampled fMRI dataset for investigating food valuation.
Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- A densely sampled fMRI dataset for investigating food valuation.Scientific data · 2026Article
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7 authors.
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Abstract
Subjective valuation of food rewards guides our dietary choices and is fundamental to human health and well-being. Extensive literature in human functional magnetic resonance imaging (fMRI) studies has consistently shown that a network of reward-processing brain regions, including the ventromedial prefrontal cortex (vmPFC) and ventral striatum, encodes the subjective values of food rewards. However, the representational geometry of value signals and the mechanisms by which they are constructed in the brain remain poorly understood. This is partly because most fMRI studies on food valuation rely on small stimulus sets, yielding datasets too shallow for advanced analyses such as multi-voxel pattern analysis, and deep neural network modeling. Here, we present a densely sampled fMRI dataset wherein 31 participants provided subjective value ratings for over 500 food images across three separate days. We validate the dataset by replicating the well-established findings regarding the neural encoding of subjective value in the vmPFC and ventral striatum. We anticipate this resource will facilitate diverse studies on neural food valuation using advanced analytical methods.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.