Visual attention modulates the integration of goal-relevant evidence and not value
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Abstract
When choosing between options, such as food items presented in plain view, people tend to choose the option they spend longer looking at. The prevailing interpretation is that visual attention increases value. However, in previous studies, ‘value’ was coupled to a behavioural goal, since subjects had to choose the item they preferred. This makes it impossible to discern if visual attention has an effect on value, or, instead, if attention modulates the information most relevant for the goal of the decision-maker. Here, we present the results of two independent studies—a perceptual and a value-based task—that allow us to decouple value from goal-relevant information using specific task-framing. Combining psychophysics with computational modelling, we show that, contrary to the current interpretation, attention does not boost value, but instead it modulates goal-relevant information. This work provides a novel and more general mechanism by which attention interacts with choice.
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The PEB can be flipped, creating a negative evidence bias, if the decision is reframed as a search for the weaker response option.
“Second, the PEB can be flipped, creating a negative evidence bias, if the decision is reframed as a search for the weaker response option (e.g., fewer dots or a disliked item; Sepulveda et al. 2020).”
From Metacognition and Confidence: A Review and Synthesis (2024) · cites this paper as Sepulveda et al. 2020
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Decomposing Economic Choices with Drift-Diffusion Models
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- Authors
- Sepulveda, P., Usher, M., Davies, N., Benson, A. A., Ortoleva, P., & De Martino, B.
- Affiliations
- Institute of Cognitive Neuroscience, University College London, London, United Kingdom
- Tel Aviv University (IL)
- University College London (GB)
- Princeton University (US)
- Venue
- eLife
- Publisher
- eLife Sciences Publications, Ltd
- Published
- 2020-11-17
- Volume
- 9
- ISSN
- 2050-084X (ISSN-L)
- PMC
- PMC7723413
- OpenAlex
- W3099802890
- Cited by
- 121
- References
- 50
- Citations by year
- 2026: 21 · 2025: 20 · 2024: 16 · 2023: 23 · 2022: 15 · 2021: 20 · 2020: 6
- FWCI
- 8.60
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- eLife (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Chilean National Agency for Research and Development (Graduate student scholarship - DOCTORADO BECAS CHILE/2017 - 72180193)
- Wellcome Trust (Sir Henry Dale Fellowship (102612 /A/13/Z))
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- visual attention, decision-making, value-based choice, perceptual decision making, task framing, food choice
- MeSH terms
- Adult, Attention, Choice Behavior, Decision Making, Eye Movements, Female, Food Preferences, Goals, Humans, Hunger, Male, Middle Aged, Young Adult
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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