Evidence map›Paper›PMID 42045250›Full record

ArticleScientific data2026

A densely sampled fMRI dataset for investigating food valuation.

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

Abstract readDataset
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Michiyo SugawaraGraduate School of Social Data Science, Hitotsubashi University, Kunitachi, Japan.
Yoko ManoHitotsubashi Institute for Advanced Study, Hitotsubashi University, Kunitachi, Japan.
Yuhi AokiGraduate School of Social Data Science, Hitotsubashi University, Kunitachi, Japan.
Koki NakayaGraduate School of Social Data Science, Hitotsubashi University, Kunitachi, Japan.
Yuma MatsudaGraduate School of Social Data Science, Hitotsubashi University, Kunitachi, Japan.
Asako ToyamaHitotsubashi Institute for Advanced Study, Hitotsubashi University, Kunitachi, Japan.
Shinsuke SuzukiGraduate School of Social Data Science, Hitotsubashi University, Kunitachi, Japan. shinsuke.szk@gmail.com.

Funding

Japan Society for the Promotion of Science JP22K21357
6 · The paper itself

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.

Indexed as

FoodMagnetic Resonance ImagingPrefrontal CortexRewardBrainHumansVentral Striatum

Identifiers

PMID42045250
PMCPMC13323986

What OpenQuestion holds

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Registered trials

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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.