Mechanisms underlying cortical activity during value-guided choice
Open accessAbstract
When choosing between two options, correlates of their value are represented in neural activity throughout the brain. Whether these representations reflect activity that is fundamental to the computational process of value comparison, as opposed to other computations covarying with value, is unknown. We investigated activity in a biophysically plausible network model that transforms inputs relating to value into categorical choices. A set of characteristic time-varying signals emerged that reflect value comparison. We tested these model predictions using magnetoencephalography data recorded from human subjects performing value-guided decisions. Parietal and prefrontal signals matched closely with model predictions. These results provide a mechanistic explanation of neural signals recorded during value-guided choice and a means of distinguishing computational roles of different cortical regions whose activity covaries with value.
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Prior work has established that the ventromedial prefrontal cortex (vmPFC) plays a central role in computing the value of potential choice options, with activity in this region reflecting the dynamic evolution of a value comparison.
“Prior work has established that the ventromedial prefrontal cortex (vmPFC) plays a central role in computing the value of potential choice options1-5, with activity in this region reflecting the dynamic evolution of a value comparison6.”
From Confidence in value-based choice (2013) · cites this paper as [6]
Given that both difference in value and confidence had independent effects on vmPFC activity, this result provides convergent support for the idea that vmPFC acts as a dynamic accumulator of choice values.
“Given that both difference in value and confidence had independent effects on vmPFC activity, this result provides convergent support for the idea that vmPFC acts as a dynamic accumulator of choice values6.”
From Confidence in value-based choice (2013) · cites this paper as [6]
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“These approaches are based on previous demonstrations that such analyses can be linked to mutual inhibition processes in attractor models (Chau et al., 2014; Hunt et al., 2012).”
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- Authors
- Hunt, L. T., Kolling, N., Soltani, A., Woolrich, M. W., Rushworth, M. F. S., & Behrens, T. E. J.
- Affiliations
- University of Oxford (GB)
- Howard Hughes Medical Institute (US)
- John Radcliffe Hospital (GB)
- Wellcome Centre for Human Neuroimaging (GB)
- Corresponding author
- Hunt, Laurence T
- Behrens, Timothy E J
- ORCID
- Venue
- Nature Neuroscience
- Published
- 2012-01-08
- Volume
- 15
- Issue
- 3
- Pages
- 470-476
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- PMC
- PMC3378494
- OpenAlex
- W2147479622
- Cited by
- 454
- References
- 50
- Citations by year
- 2026: 22 · 2025: 24 · 2024: 20 · 2023: 24 · 2022: 24 · 2021: 48 · 2020: 43 · 2019: 44 · 2018: 29 · 2017: 23 · 2016: 33 · 2015: 39 · 2014: 41 · 2013: 24 · 2012: 15
- FWCI
- 19.47
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- Wellcome Trust (091593, 080540, 088312)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Keywords
- decision-making, value comparison, reciprocal inhibition, prefrontal cortex, parietal cortex, cortical activity, computational modeling
- MeSH terms
- Biophysics, Brain Mapping, Cerebral Cortex, Choice Behavior, Contingent Negative Variation, Evoked Potentials, Visual, Female, Humans, Image Processing, Computer-Assisted, Judgment, Magnetic Resonance Imaging, Male, Models, Neurological, Neural Pathways, Photic Stimulation, Predictive Value of Tests, Psychomotor Performance, Reaction Time, Magnetoencephalography, Linear Models
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