Mapping value based planning and extensively trained choice in the human brain
Open accessAbstract
Investigations of the underlying mechanisms of choice in humans have focused on learning from prediction errors, leaving the computational structure of value based planning comparatively underexplored. Using behavioral and neuroimaging analyses of a minimax decision task, we found that the computational processes underlying forward planning are expressed in the anterior caudate nucleus as values of individual branching steps in a decision tree. In contrast, values represented in the putamen pertain solely to values learned during extensive training. During actual choice, both striatal areas showed a functional coupling to ventromedial prefrontal cortex, consistent with this region acting as a value comparator. Our findings point toward an architecture of choice in which segregated value systems operate in parallel in the striatum for planning and extensively trained choices, with medial prefrontal cortex integrating their outputs.
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Ventromedial prefrontal cortex may act as a hub or convergence point for different types of expected value signals, such as experienced-based expected value computed in putamen and model-based value computed in caudate.
“This is consistent with recent findings that the vmPFC may act as a “hub” or “convergence point” for different types of expected value signals, such as experienced-based expected value signals computed in the putamen and model-based value signals computed in the caudate48.”
From Representation of aversive prediction errors in the human periaqueductal gray (2014) · cites this paper as [48]
One human study found evidence in support of the postulated computational dissociation between model-based and model-free RL signals in the DMS and DLS.
“One such study found evidence in support of the postulated computational dissociation [31]”
From Contributions of the striatum to learning, motivation, and performance: an associative account (2012) · cites this paper as [31]
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References 54 · Cited by 310
- Authors
- Wunderlich, K., Dayan, P., & Dolan, R. J.
- Affiliations
- Wellcome Centre for Human Neuroimaging (GB)
- Gatsby Computational Neuroscience Unit (GB)
- Corresponding author
- Wunderlich, Klaus
- Venue
- Nature Neuroscience
- Published
- 2012-03-11
- Volume
- 15
- Issue
- 5
- Pages
- 786-791
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- PMC
- PMC3378641
- OpenAlex
- W1999696971
- Cited by
- 310
- References
- 54
- Citations by year
- 2026: 4 · 2025: 10 · 2024: 8 · 2023: 8 · 2022: 23 · 2021: 23 · 2020: 45 · 2019: 20 · 2018: 16 · 2017: 23 · 2016: 26 · 2015: 41 · 2014: 31 · 2013: 18 · 2012: 14
- FWCI
- 17.02
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Max Planck Digital Library (submittedVersion, other-oa)
- MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Funders
- Wellcome Trust (091593, 078865, 091593/Z/10/Z)
- Gatsby Charitable Foundation
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Keywords
- value-based planning, decision-making, striatum, putamen, decision tree, prediction error learning, ventromedial prefrontal cortex, value comparison, forward planning, computational modeling of choice
- MeSH terms
- Adolescent, Adult, Brain, Brain Mapping, Choice Behavior, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Motivation, Oxygen, Predictive Value of Tests, Probability, Psychomotor Performance, Reward, Time Factors, Maze Learning, Young Adult, Executive Function
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