Cited by 219Neural and Behavioral Psychology StudiesNeurotransmitter Receptor Influence on BehaviorDecision-Making and Behavioral Economics

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The Dopaminergic Midbrain Encodes the Expected Certainty about Desired Outcomes

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Abstract

Dopamine plays a key role in learning; however, its exact function in decision making and choice remains unclear. Recently, we proposed a generic model based on active (Bayesian) inference wherein dopamine encodes the precision of beliefs about optimal policies. Put simply, dopamine discharges reflect the confidence that a chosen policy will lead to desired outcomes. We designed a novel task to test this hypothesis, where subjects played a "limited offer" game in a functional magnetic resonance imaging experiment. Subjects had to decide how long to wait for a high offer before accepting a low offer, with the risk of losing everything if they waited too long. Bayesian model comparison showed that behavior strongly supported active inference, based on surprise minimization, over classical utility maximization schemes. Furthermore, midbrain activity, encompassing dopamine projection neurons, was accurately predicted by trial-by-trial variations in model-based estimates of precision. Our findings demonstrate that human subjects infer both optimal policies and the precision of those inferences, and thus support the notion that humans perform hierarchical probabilistic Bayesian inference. In other words, subjects have to infer both what they should do as well as how confident they are in their choices, where confidence may be encoded by dopaminergic firing.

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Crossref · 10.1093/cercor/bhu159

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Figure 1. Experimental Design. (A) Each game comprised a specified number of trials (discrete time steps). On each trial, subjects had to decide whether to accept a current offer or wait for the next trial. If subjects decided to wait, the low offer could be withdrawn with probability r, it could be replaced by a high offer with probability q or could be carried over to the next trial with probability 1 − (r + q). (B) The withdrawal probability increased, whereas a high offer became less likely with each successive trial. (C) Average probabilities of accepting the initial offer at each trial (note that Pwait = 1 − Paccept)., indicating that subjects were prepared to wait for the high offer (except at the last time step). The decrease in acceptance-probability at the seventh trial in long games is not due to an actual decreased propensity to accept but due to very few data points for these trials. (D) Structure of a game in the scanner: Each game started with an orientation screen, specifying the number of trials and the amount of the initial offer. At each trial, subjects had a brief period to make a decision, followed by a response period. Following a short break, the next offer was presented. After the last trial, the break-screen was replaced by a screen indicating the win amount on this game, followed by a jittered interstimulus interval (ISI)—before the next game.
Figure 1. Experimental Design. (A) Each game comprised a specified number of trials (discrete time steps). On each trial, subjects had to decide whether to accept a current offer or wait for the next trial. If subjects decided to wait, the low offer could be withdrawn with probability r, it could be replaced by a high offer with probability q or could be carried over to the next trial with probability 1 − (r + q). (B) The withdrawal probability increased, whereas a high offer became less likely with each successive trial. (C) Average probabilities of accepting the initial offer at each trial (note that Pwait = 1 − Paccept)., indicating that subjects were prepared to wait for the high offer (except at the last time step). The decrease in acceptance-probability at the seventh trial in long games is not due to an actual decreased propensity to accept but due to very few data points for these trials. (D) Structure of a game in the scanner: Each game started with an orientation screen, specifying the number of trials and the amount of the initial offer. At each trial, subjects had a brief period to make a decision, followed by a response period. Following a short break, the next offer was presented. After the last trial, the break-screen was replaced by a screen indicating the win amount on this game, followed by a jittered interstimulus interval (ISI)—before the next game.CC BY · PubMed Central
Figure 2. Simulation of state-dependent changes of expected precision and putative dopaminergic responses. (A) Receiving the high offer (left upper panel) produces a sharp increase in precision (lower left panel) and simulated dopaminergic firing (lower right panel). The high offer induces a change in policy and compels the agent to accept (“switch,” upper right panel). (B) Same format as in (A), but illustrating the withdrawal of an initial offer, leading to a decrease in precision and a consequent dip in dopaminergic firing.
Figure 2. Simulation of state-dependent changes of expected precision and putative dopaminergic responses. (A) Receiving the high offer (left upper panel) produces a sharp increase in precision (lower left panel) and simulated dopaminergic firing (lower right panel). The high offer induces a change in policy and compels the agent to accept (“switch,” upper right panel). (B) Same format as in (A), but illustrating the withdrawal of an initial offer, leading to a decrease in precision and a consequent dip in dopaminergic firing.CC BY · PubMed Central
Figure 3. Observed and estimated acceptance probabilities as predicted by our model (note that Pwait = 1 − Paccept). These estimates are based upon maximum a posteriori values for prior precision, the hazard rate, and sensitivity to differences in monetary cues. Note that the observed acceptance probabilities are identical to the ones shown in Figure 1C.
Figure 3. Observed and estimated acceptance probabilities as predicted by our model (note that Pwait = 1 − Paccept). These estimates are based upon maximum a posteriori values for prior precision, the hazard rate, and sensitivity to differences in monetary cues. Note that the observed acceptance probabilities are identical to the ones shown in Figure 1C.CC BY · PubMed Central
Figure 4. Effects of choice conflict defined as the entropy of the probability distribution over the 2 alternative actions (wait vs. accept). SPM thresholded at P < 0.005 (uncorrected) and masked for the midbrain for display purposes.
Figure 4. Effects of choice conflict defined as the entropy of the probability distribution over the 2 alternative actions (wait vs. accept). SPM thresholded at P < 0.005 (uncorrected) and masked for the midbrain for display purposes.CC BY · PubMed Central
Figure 5. Neuronal correlates of expected precision in the brain. (A) Using a hand-drawn ROI for the SN/VTA, we detected substantial effects for expected precision in both the substantia nigra as well as the ventral tegmental area: SPM thresholded at P < 0.005 (uncorrected) and masked for the midbrain for display purposes. SPM thresholded at P < 0.005 (uncorrected) and masked for the midbrain for display purposes. (B) At the whole-brain level, we found distributed and strong effects of precision in prefrontal, inferotemporal, and parietal regions as well as in the striatum and anterior insular cortex. SPM thresholded at P < 0.005 (uncorrected) and masked for the midbrain for display purposes.
Figure 5. Neuronal correlates of expected precision in the brain. (A) Using a hand-drawn ROI for the SN/VTA, we detected substantial effects for expected precision in both the substantia nigra as well as the ventral tegmental area: SPM thresholded at P < 0.005 (uncorrected) and masked for the midbrain for display purposes. SPM thresholded at P < 0.005 (uncorrected) and masked for the midbrain for display purposes. (B) At the whole-brain level, we found distributed and strong effects of precision in prefrontal, inferotemporal, and parietal regions as well as in the striatum and anterior insular cortex. SPM thresholded at P < 0.005 (uncorrected) and masked for the midbrain for display purposes.CC BY · PubMed Central

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Metadata

Authors
Schwartenbeck, P., FitzGerald, T. H. B., Mathys, C., Dolan, R., & Friston, K.
Affiliations
Wellcome Centre for Human Neuroimaging (GB)
Corresponding author
Schwartenbeck, Philipp
Venue
Cerebral Cortex
Published
2014-07-23
Volume
25
Issue
10
Pages
3434-3445
ISSN
  • 1047-3211 (ISSN-L)
  • 1460-2199
OpenAlex
W2128918015
Cited by
219
References
80
Citations by year
2026: 20 · 2025: 19 · 2024: 13 · 2023: 19 · 2022: 26 · 2021: 19 · 2020: 26 · 2019: 15 · 2018: 20 · 2017: 12 · 2016: 17 · 2015: 10 · 2014: 3
FWCI
7.81
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Cerebral Cortex (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • SDL (submittedVersion, cc-by)
  • UEA Digital Repository (University of East Anglia) (submittedVersion, other-oa)
  • UCL Discovery (University College London) (submittedVersion)
  • MPG.PuRe (Max Planck Society) (submittedVersion)
Funders
  • Wellcome Trust (091593, 091593/Z/10/, 098362, 098362/Z/12/Z, 091593/Z/10/Z, 088130, 098362/Z/12/)
  • University College London (098362/Z/12/Z)
  • Max-Planck-Gesellschaft (098362/Z/12/Z)
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
dopamine, midbrain, Bayesian inference, active inference, decision-making, surprise minimization, utility maximization, hierarchical Bayesian inference
MeSH terms
Adult, Bayes Theorem, Brain Mapping, Cerebral Cortex, Choice Behavior, Conflict, Psychological, Dopamine, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Risk, Substantia Nigra, Ventral Tegmental Area, Young Adult

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