Association of neural and emotional impacts of reward prediction errors with major depression
Open accessAbstract
Importance: Major depressive disorder (MDD) is associated with deficits in representing reward prediction errors (RPEs), which are the difference between experienced and predicted reward. Reward prediction errors underlie learning of values in reinforcement learning models, are represented by phasic dopamine release, and are known to affect momentary mood. Objective: To combine functional neuroimaging, computational modeling, and smartphone-based large-scale data collection to test, in the absence of learning-related concerns, the hypothesis that depression attenuates the impact of RPEs. Design, Setting, and Participants: Functional magnetic resonance imaging (fMRI) data were collected on 32 individuals with moderate MDD and 20 control participants who performed a probabilistic reward task. A risky decision task with repeated happiness ratings as a measure of momentary mood was also tested in the laboratory in 74 participants and with a smartphone-based platform in 1833 participants. The study was conducted from November 20, 2012, to February 17, 2015. Main Outcomes and Measures: Blood oxygen level-dependent activity was measured in ventral striatum, a dopamine target area known to represent RPEs. Momentary mood was measured during risky decision making. Results: Of the 52 fMRI participants (mean [SD] age, 34.0 [9.1] years), 30 (58%) were women and 32 had MDD. Of the 74 participants in the laboratory risky decision task (mean age, 34.2 [10.3] years), 44 (59%) were women and 54 had MDD. Of the smartphone group, 543 (30%) had a depression history and 1290 (70%) had no depression history; 918 (50%) were women, and 593 (32%) were younger than 30 years. Contrary to previous results in reinforcement learning tasks, individuals with moderate depression showed intact RPE signals in ventral striatum (z = 3.16; P = .002) that did not differ significantly from controls (z = 0.91; P = .36). Symptom severity correlated with baseline mood parameters in laboratory (ρ = -0.54; P < 1 × 10-6) and smartphone (ρ = -0.30; P < 1 × 10-39) data. However, participants with depression showed an intact association between RPEs and happiness in a computational model of momentary mood dynamics (z = 4.55; P < .001) that was not attenuated compared with controls (z = -0.42; P = .67). Conclusions and Relevance: The neural and emotional impact of RPEs is intact in major depression. These results suggest that depression does not affect the expression of dopaminergic RPEs and that attenuated RPEs in previous reports may reflect downstream effects more closely related to aberrant behavior. The correlation between symptom severity and baseline mood parameters supports an association between depression and momentary mood fluctuations during cognitive tasks. These results demonstrate a potential for smartphones in large-scale computational phenotyping, which is a goal for computational psychiatry.
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Depressed individuals show blunted neural responses to unexpected rewards, a kind of reduced reward prediction error signalling.
“depressed individuals show blunted neural responses to unexpected rewards (a kind of reduced reward prediction error signalling) (52).”
From Predictive coding and neurocomputational psychiatry: a mechanistic framework for understanding mental disorders (2026) · cites this paper as [52]
The Results (Probabilistic Reward Task) report intact reward prediction error signals in depressed participants, with no significant difference from controls. The Discussion likewise says the study found no evidence of impaired reward-related neural processes in its nonlearning task. Although the Introduction notes earlier reports of reduced responses to rewards, this paper's own findings contradict the attributed claim about reduced prediction error signalling. (LLM, conf=0.93)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredRutledge et al. found that prediction error was unchanged in the ventral striatum.
“Rutledge et al. (2017) found that prediction error was unchanged in the ventral striatum.”
From The orbitofrontal cortex: reward, emotion and depression (2020) · cites this paper as Rutledge et al., 2017
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- Authors
- Rutledge, R. B., Moutoussis, M., Smittenaar, P., Zeidman, P., Taylor, T., Hrynkiewicz, L., Lam, J., Skandali, N., Siegel, J. Z., Ousdal, O. T., Prabhu, G., Dayan, P., Fonagy, P., & Dolan, R. J.
- Affiliations
- Wellcome Centre for Human Neuroimaging (GB)
- Gatsby Computational Neuroscience Unit (GB)
- Anna Freud Centre (GB)
- Corresponding author
- Rutledge, Robb B.
- ORCID
- Venue
- JAMA Psychiatry
- Publisher
- American Medical Association (AMA)
- Published
- 2017-08-01
- Volume
- 74
- Issue
- 8
- Pages
- 790
- ISSN
- 2168-622X (ISSN-L)
- PMC
- PMC5710549
- OpenAlex
- W2732023139
- Cited by
- 209
- References
- 42
- Citations by year
- 2026: 21 · 2025: 11 · 2024: 27 · 2023: 21 · 2022: 25 · 2021: 41 · 2020: 22 · 2019: 16 · 2018: 20 · 2017: 5
- FWCI
- 9.88
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- JAMA Psychiatry (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Funders
- Wellcome Trust (095844/Z/11/Z, 098362/Z/12/Z, 091593/Z/10/Z)
- National Institute for Health and Care Research (NF-SI-0514-10157)
- Medical Research Council (MR/N02401X/1)
- 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 › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Keywords
- reward prediction error, major depressive disorder, ventral striatum, dopamine, reinforcement learning, momentary mood, risky decision making, probabilistic reward task, computational modeling, symptom severity, neural correlates of depression
- MeSH terms
- Adult, Affect, Decision Making, Depressive Disorder, Major, Major Depressive Disorder, Female, Humans, Magnetic Resonance Imaging, Male, Models, Psychological, Reward, Risk-Taking, Case-Control Studies, Young Adult, Functional Neuroimaging, Ventral Striatum
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