Meta-analysis of human prediction error for incentives, perception, cognition, and action
Open accessAbstract
Prediction errors (PEs) are a keystone for computational neuroscience. Their association with midbrain neural firing has been confirmed across species and has inspired the construction of artificial intelligence that can outperform humans. However, there is still much to learn. Here, we leverage the wealth of human PE data acquired in the functional neuroimaging setting in service of a deeper understanding, using an MKDA (multi-level kernel-based density) meta-analysis. Studies were identified with Google Scholar, and we included studies with healthy adult participants that reported activation coordinates corresponding to PEs published between 1999-2018. Across 264 PE studies that have focused on reward, punishment, action, cognition, and perception, consistent with domain-general theoretical models of prediction error we found midbrain PE signals during cognitive and reward learning tasks, and an insula PE signal for perceptual, social, cognitive, and reward prediction errors. There was evidence for domain-specific error signals--in the visual hierarchy during visual perception, and the dorsomedial prefrontal cortex during social inference. We assessed bias following prior neuroimaging meta-analyses and used family-wise error correction for multiple comparisons. This organization of computation by region will be invaluable in building and testing mechanistic models of cognitive function and dysfunction in machines, humans, and other animals. Limitations include small sample sizes and ROI masking in some included studies, which we addressed by weighting each study by sample size, and directly comparing whole brain vs. ROI-based results.
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A recent meta-analysis revealed evidence for domain specificity of prediction error signals, with midbrain prediction error signals associated with cognitive and reward learning tasks and insula prediction error signals associated with a wide range including perceptual, cognitive, and social prediction errors.
“A recent meta-analysis revealed evidence for domain specificity of these error signals with midbrain prediction error signals being associated with cognitive and reward learning tasks, while insula prediction error signals were associated with a wide range including perceptual, cognitive, and social prediction errors”
From Are prediction error modifications domain specific in autism but domain general in ADHD? (2025) · cites this paper as Corlett et al., 2022
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Experimental — accuracy not yet measuredA recent meta-analysis highlights a consistent correspondence between specific brain areas and the domain-specificity of tasks.
“a recent meta-analysis highlights a consistent corre spondence between specific brain areas and the domain-specificity of the tasks (Corlett et al., 2022).”
From Predictive coding in neuropsychiatric disorders: a systematic transdiagnostic review. (2025) · cites this paper as Corlett et al., 2022
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Are prediction error modifications domain specific in autism but domain general in ADHD?
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“…domain specificity of these error signals with midbrain prediction error signals being associated with cognitive and reward learning tasks, while insula prediction error signals were associated with a wide range including perceptual, cognitive, and social prediction errors ( Corlett et al., 2022).”
- Authors
- Corlett, P. R., Mollick, J. A., & Kober, H.
- Affiliations
- Yale University (US)
- Corresponding author
- Corlett, Philip R.
- Venue
- Neuropsychopharmacology
- Published
- 2022-01-11
- Volume
- 47
- Issue
- 7
- Pages
- 1339-1349
- ISSN
- 0893-133X (ISSN-L)
- 1740-634X
- PMC
- PMC9117315
- OpenAlex
- W4206618816
- Cited by
- 135
- References
- 71
- Citations by year
- 2026: 29 · 2025: 37 · 2024: 31 · 2023: 24 · 2022: 13 · 2021: 1
- FWCI
- 3.66
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Neuropsychopharmacology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (R21MH116258, R01MH12887)
- U.S. Department of Health & Human Services | NIH | National Institute on Drug Abuse (R01 DA043690)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Embodied and Extended Cognition
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Keywords
- prediction error, midbrain, insula, reward learning, punishment, visual perception, visual hierarchy, social inference, dorsomedial prefrontal cortex, cognitive control, functional neuroimaging, computational neuroscience
- MeSH terms
- Artificial Intelligence, Cognition, Humans, Magnetic Resonance Imaging, Motivation, Perception, Reward
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