The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity.
Abstract
The authors present a unified account of 2 neural systems concerned with the development and expression of adaptive behaviors: a mesencephalic dopamine system for reinforcement learning and a "generic" error-processing system associated with the anterior cingulate cortex. The existence of the error-processing system has been inferred from the error-related negativity (ERN), a component of the event-related brain potential elicited when human participants commit errors in reaction-time tasks. The authors propose that the ERN is generated when a negative reinforcement learning signal is conveyed to the anterior cingulate cortex via the mesencephalic dopamine system and that this signal is used by the anterior cingulate cortex to modify performance on the task at hand. They provide support for this proposal using both computational modeling and psychophysiological experimentation.
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The ACC is a site of computation of prediction errors encoding the difference between expected and obtained outcomes of responding.
“Moreover, studies using fMRI and electrophysiological (error-related negativity) methods in humans, as well as single-unit electrophysiology in experimental animals, have identified the ACC to be a site of computation of prediction errors encoding the difference between expected and obtained outcomes of responding [115–117].”
From The role of prefrontal cortex in cognitive control and executive function (2022) · cites this paper as [116]
The functional meaning of FRN has shifted from a purely negative feedback detector toward a broader index of reinforcement-learning signals, reward prediction error, action-outcome evaluation, and reward positivity modulation.
“its functional meaning has shifted from a purely “negative feedback detector” toward a broader index of reinforcement-learning signals, reward prediction error, action–outcome evaluation, and reward positivity modulation [117,118,126,127,128,129].”
Classical reinforcement-learning models propose that unexpected unfavourable outcomes produce negative prediction-error signals that are conveyed through dopaminergic and medial-frontal systems and used to update future behaviour.
“Classical reinforcement-learning models propose that unexpected unfavourable outcomes produce negative prediction-error signals that are conveyed through dopaminergic and medial-frontal systems and used to update future behaviour [117,118].”
In the broader ERP literature, response-locked performance monitoring is usually described as a sequence in which early medial-frontal activity detects conflict, error likelihood, or worse-than-expected outcomes, whereas later positive components support more conscious, evaluative, and metacognitive appraisal of the action that has just been executed.
“In the broader ERP literature, response-locked performance monitoring is usually described as a sequence in which early medial-frontal activity detects conflict, error likelihood, or worse-than-expected outcomes, whereas later positive components support more conscious, evaluative, and metacognitive appraisal of the action that has just been executed [113,116,117,185,186,187].”
Earlier components such as ERN are often interpreted in terms of rapid conflict detection, reinforcement-learning signals, or medial-frontal alarm mechanisms, whereas later positive components appear more closely related to conscious appraisal, confidence, and adaptive updating.
“Earlier components such as ERN are often interpreted in terms of rapid conflict detection, reinforcement-learning signals, or medial-frontal alarm mechanisms, whereas later positive components appear more closely related to conscious appraisal, confidence, and adaptive updating [113,116,117,187].”
Neural signals marking gross violations of expectations respond to incorrect prediction of affectively neutral stimuli, unlike dopamine-related prediction error signals which are largely reward-focused and associated with model-free RL.
“Unlike the prediction error signals associated with dopamine activity, which are largely reward-focused and associated with model-free RL (Holroyd and Coles, 2002), these respond to incorrect prediction of affectively neutral stimuli.”
From States versus Rewards: Dissociable Neural Prediction Error Signals Underlying Model-Based and Model-Free Reinforcement Learning (2010) · cites this paper as Holroyd and Coles, 2002
Anterior cingulate cortex was implicated in monitoring conflict between incompatible response processes or detecting performance errors.
“While anterior cingulate cortex was implicated in monitoring conflict between incompatible response processes35 or detecting performance errors36”
From A reservoir of time constants for memory traces in cortical neurons (2011) · cites this paper as [36]
The P3 is more closely related to reward-seeking behaviors ('wanting') and the FRN to reward consumption ('liking' or 'disliking').
“However, research and theory suggests that the P3 is more closely related to reward-seeking behaviors (‘wanting’) and the FRN to reward consumption (‘liking’ or ’disliking’) [88,89].”
From Social “wanting” dysfunction in autism: neurobiological underpinnings and treatment implications (2012) · cites this paper as [88]
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- Authors
- Holroyd, C. B., & Coles, M. G. H.
- Affiliations
- University of Illinois Urbana-Champaign (US)
- ORCID
- Holroyd, Clay B.
- Venue
- Psychological Review
- Published
- 2002-10
- Volume
- 109
- Issue
- 4
- Pages
- 679-709
- ISSN
- 0033-295X (ISSN-L)
- 1939-1471
- OpenAlex
- W2135572147
- Semantic Scholar
- a497b6f27fa708805f5dab7b7470509e72deb8b2
- Cited by
- 4,027
- References
- 280
- Citations by year
- 2026: 125 · 2025: 172 · 2024: 145 · 2023: 138 · 2022: 152 · 2021: 193 · 2020: 188 · 2019: 188 · 2018: 220 · 2017: 219 · 2016: 218 · 2015: 246 · 2014: 244 · 2013: 219 · 2012: 204
- FWCI
- 30.66
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Psychological Review (publishedVersion)
- PubMed (publishedVersion)
- Ghent University Academic Bibliography (Ghent University) (submittedVersion)
- Funders
- National Institutes of Health (5r01mh041445-13, 5f31mh011530-04)
- National Institute of Mental Health (MH41445, MH11530)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Life Sciences › Neuroscience › Cognitive Neuroscience › Free Will and Agency
- Keywords
- error processing, error-related negativity, reinforcement learning, dopamine, anterior cingulate cortex, negative reinforcement, adaptive behavior, event-related potentials, reaction time task, computational modeling
- MeSH terms
- Analysis of Variance, Brain Mapping, Dopamine, Humans, Models, Neurological, Motor Cortex, Probability Learning, Reinforcement, Psychology
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