Building Bridges between Perceptual and Economic Decision-Making: Neural and Computational Mechanisms
Open accessAbstract
Investigation into the neural and computational bases of decision-making has proceeded in two parallel but distinct streams. Perceptual decision-making (PDM) is concerned with how observers detect, discriminate, and categorize noisy sensory information. Economic decision-making (EDM) explores how options are selected on the basis of their reinforcement history. Traditionally, the sub-fields of PDM and EDM have employed different paradigms, proposed different mechanistic models, explored different brain regions, disagreed about whether decisions approach optimality. Nevertheless, we argue that there is a common framework for understanding decisions made in both tasks, under which an agent has to combine sensory information (what is the stimulus) with value information (what is it worth). We review computational models of the decision process typically used in PDM, based around the idea that decisions involve a serial integration of evidence, and assess their applicability to decisions between good and gambles. Subsequently, we consider the contribution of three key brain regions - the parietal cortex, the basal ganglia, and the orbitofrontal cortex (OFC) - to perceptual and EDM, with a focus on the mechanisms by which sensory and reward information are integrated during choice. We find that although the parietal cortex is often implicated in the integration of sensory evidence, there is evidence for its role in encoding the expected value of a decision. Similarly, although much research has emphasized the role of the striatum and OFC in value-guided choices, they may play an important role in categorization of perceptual information. In conclusion, we consider how findings from the two fields might be brought together, in order to move toward a general framework for understanding decision-making in humans and other primates.
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The race model captures several features of the relationship between choice, reaction time and confidence in a value-based choice paradigm.
“In keeping with recent research efforts that have incorporated dynamic models into the field of economic decision-making28, we find that this model captures several features of the relationship between choice, reaction time and confidence in a value-based choice paradigm.”
From Confidence in value-based choice (2013) · cites this paper as [28]
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Confidence in value-based choice
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Deconstructing the human algorithms for exploration
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Midbrain dopamine neurons signal belief in choice accuracy during a perceptual decision
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- Authors
- Summerfield, C., & Tsetsos, K.
- Affiliations
- University of Oxford (GB)
- Corresponding author
- Summerfield, Christopher
- Venue
- Frontiers in Neuroscience
- Publisher
- Frontiers Media SA
- Published
- 2012
- Volume
- 6
- Pages
- 70-70
- ISSN
- 1662-453X (ISSN-L)
- 1662-4548
- PMC
- PMC3359443
- OpenAlex
- W2070685206
- Cited by
- 167
- References
- 228
- Citations by year
- 2026: 2 · 2025: 9 · 2024: 6 · 2023: 9 · 2022: 12 · 2021: 10 · 2020: 16 · 2019: 19 · 2018: 10 · 2017: 21 · 2016: 15 · 2015: 17 · 2014: 10 · 2013: 9 · 2012: 2
- FWCI
- 6.22
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by-nc
- Locations
- Frontiers in Neuroscience (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Explore Bristol Research (publishedVersion)
- BIROn (Birkbeck, University of London) (acceptedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- perceptual decision making, economic decision-making, evidence integration, parietal cortex, basal ganglia, striatum, orbitofrontal cortex, reward value, computational models of decision making
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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.
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