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Depression: A Decision-Theoretic Analysis
Open accessAbstract
The manifold symptoms of depression are common and often transient features of healthy life that are likely to be adaptive in difficult circumstances. It is when these symptoms enter a seemingly self-propelling spiral that the maladaptive features of a disorder emerge. We examine this malignant transformation from the perspective of the computational neuroscience of decision making, investigating how dysfunction of the brain's mechanisms of evaluation might lie at its heart. We start by considering the behavioral implications of pessimistic evaluations of decision variables. We then provide a selective review of work suggesting how such pessimism might arise via specific failures of the mechanisms of evaluation or state estimation. Finally, we analyze ways that miscalibration between the subject and environment may be self-perpetuating. We employ the formal framework of Bayesian decision theory as a foundation for this study, showing how most of the problems arise from one of its broad algorithmic facets, namely model-based reasoning.
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“From a dynamical systems perspective, this corresponds to a pathological attractor state in neural activity (47, 48).”
From Predictive coding and neurocomputational psychiatry: a mechanistic framework for understanding mental disorders (2026) · cites this paper as [47]
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“Bipolar disorder, marked by oscillations between manic (or hypo-manic) and depressive states, can be conceptualised in predictive coding terms as an instability in how the brain regulates precision across different states (47, 53).”
From Predictive coding and neurocomputational psychiatry: a mechanistic framework for understanding mental disorders (2026) · cites this paper as [47]
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“Efforts in computational psychiatry have sought to characterize changes in decision-making processes in the context of depression and have revealed dysfunction in the processes underlying model-based decision-making (for review see ref. 55).”
From Paying attention to attention in depression (2019) · cites this paper as [55]
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Kaske, E. A., Chen, C. S., Meyer, C., Yang, F., Ebitz, R. B., Grissom, N. M., Kapoor, A., Darrow, D., & Herman, A. B. (2022) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2022.12.004 · Cited by 20
The Similarity Structure of Real-World MemoriesPreprint
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Driven by Pain, Not Gain: Computational Approaches to Aversion-Related Decision Making in Psychiatry
Paulus, M. P. (2019) · Biological Psychiatry · doi:10.1016/j.biopsych.2019.08.025 · Cited by 19
Effects of subclinical depression on prefrontal–striatal model-based and model-free learning
Heo, S., Sung, Y., & Lee, S. W. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009003 · Cited by 16
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Ruffini, G., Castaldo, F., Lopez-Sola, E., Sanchez-Todo, R., & Vohryzek, J. (2024) · Entropy · doi:10.3390/e26110953 · Cited by 20
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Differential Associations of Dopamine and Serotonin With Reward and Punishment Processes in Humans
Mkrtchian, A., Qiu, Z., Abir, Y., Erdmann, T., Dercon, Q., Sedlinská, T., Browning, M. D., Costello, H., & Huys, Q. J. M. (2025) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2025.0839 · Cited by 16
Self-citationPallikaras, V., & Shizgal, P. (2022) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2022.851067 · Cited by 18
Metadata
- Authors
- Huys, Q. J. M., Daw, N. D., & Dayan, P.
- Affiliations
- University of Zurich (CH)
- New York University (US)
- Gatsby Computational Neuroscience Unit (GB)
- Venue
- Annual Review of Neuroscience
- Publisher
- Annual Reviews
- Published
- 2015-07-08
- Volume
- 38
- Issue
- 1
- Pages
- 1-23
- ISSN
- 0147-006X (ISSN-L)
- 1545-4126
- OpenAlex
- W2164531443
- Cited by
- 221
- References
- 165
- Citations by year
- 2026: 18 · 2025: 16 · 2024: 24 · 2023: 35 · 2022: 28 · 2021: 20 · 2020: 22 · 2019: 15 · 2018: 14 · 2017: 14 · 2016: 8 · 2015: 7
- FWCI
- 1.43
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Annual Review of Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion)
- Funders
- Wellcome Trust (091593)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Keywords
- depression, decision-making, Bayesian decision theory, model-based reasoning, pessimism, state estimation, computational psychiatry, adaptive behavior
- MeSH terms
- Bayes Theorem, Decision Making, Decision Theory, Depression, Humans
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