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<p>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.</p>

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A densely sampled fMRI dataset for investigating food valuation

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月27日

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  • Michiyo Sugawara,
  • Yoko Mano,
  • Yuhi Aoki,
  • Koki Nakaya,
  • Yuma Matsuda,
  • Asako Toyama,
  • Shinsuke Suzuki

摘要

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.