Neural correlates, computation and behavioural impact of decision confidence
Open accessAbstract
Humans and other animals must often make decisions on the basis of imperfect evidence. Statisticians use measures such as P values to assign degrees of confidence to propositions, but little is known about how the brain computes confidence estimates about decisions. We explored this issue using behavioural analysis and neural recordings in rats in combination with computational modelling. Subjects were trained to perform an odour categorization task that allowed decision confidence to be manipulated by varying the distance of the test stimulus to the category boundary. To understand how confidence could be computed along with the choice itself, using standard models of decision-making, we defined a simple measure that quantified the quality of the evidence contributing to a particular decision. Here we show that the firing rates of many single neurons in the orbitofrontal cortex match closely to the predictions of confidence models and cannot be readily explained by alternative mechanisms, such as learning stimulus-outcome associations. Moreover, when tested using a delayed reward version of the task, we found that rats' willingness to wait for rewards increased with confidence, as predicted by the theoretical model. These results indicate that confidence estimates, previously suggested to require 'metacognition' and conscious awareness are available even in the rodent brain, can be computed with relatively simple operations, and can drive adaptive behaviour. We suggest that confidence estimation may be a fundamental and ubiquitous component of decision-making.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
A prominent proposal is that confidence is based on the distance between the measurement and the decision boundary, without any role for sensory uncertainty.
“a prominent proposal is that confidence is based on the distance between the measurement and the decision boundary, without any role for sensory uncertainty [10, 11, 39].”
From Comparing Bayesian and non-Bayesian accounts of human confidence reports (2018) · cites this paper as [11]
Neurons in rodent OFC show statistical signatures of confidence in an odor discrimination task.
“In a seminal study, Kepecs and colleagues found that neurons in rodent OFC showed statistical signatures of confidence in an odor discrimination task (Kepecs et al. 2008).”
From Metacognition and Confidence: A Review and Synthesis (2024) · cites this paper as Kepecs et al. 2008
Postdecisional firing rates of neurons in prefrontal cortex and dopaminergic midbrain covary with choice correctness before explicit feedback is given.
“In animal models, postdecisional firing rates of neurons in prefrontal cortex and dopaminergic midbrain have also been shown to covary with choice correctness before explicit feedback is given (Kepecs et al. 2008, Middlebrooks & Sommer 2012, Tsujimoto et al. 2010).”
From Metacognition and Confidence: A Review and Synthesis (2024) · cites this paper as Kepecs et al. 2008
Rats are preferred for behavioral, memory, and cognitive research due to their physiological similarities to humans and their high learning capacity.
“Rats are preferred for behavioral, memory, and cognitive research due to their physiological similarities to humans and their high learning capacity [17–20].”
In contrast to the TPJ, the vmPFC and ventral striatum are routinely found to be involved in nonsocial types of decision making such as reward-seeking behavior, intertemporal decision making, risk taking, and purchasing behavior.
“However, in contrast to the TPJ, these latter areas are routinely found to be involved in nonsocial types of decision making such as reward-seeking behavior, intertemporal decision making, risk taking, and purchasing behavior (Kable and Glimcher, 2007;Kepecs et al., 2008;Knutson et al., 2007;Kuhnen and Knutson, 2005;Padoa-Schioppa and Assad, 2006;Plassmann et al., 2007;Rangel and Hare, 2010;Samej”
From Linking Brain Structure and Activation in Temporoparietal Junction to Explain the Neurobiology of Human Altruism (2012) · cites this paper as Kepecs et al., 2008
Previous studies have reported neural correlates of decision confidence in brain regions associated with a value representation, for example firing rates in rat orbitofrontal cortex and fMRI signal in human vmPFC show graded changes as perceptual decisions become more difficult.
“Previous studies have reported neural correlates of decision confidence in brain regions associated with a value representation. For example, firing rates in rat orbitofrontal cortex7 and fMRI signal in human vmPFC8 show graded changes as perceptual decisions become more difficult.”
From Confidence in value-based choice (2013) · cites this paper as [7]
Choice confidence emerges from the dynamics of noisy accumulators in the race model, leading to dual effects of difference in value and reaction time on confidence.
“Choice confidence can be seen to emerge from the dynamics of noisy accumulators in the race model7,21, leading to dual effects of difference in value and reaction time on confidence27.”
From Confidence in value-based choice (2013) · cites this paper as [7]
Neural responses to uncertainty or surprise have been reported in multiple structures and linked with variables such as arousal, anxiety, risk preference, or global learning rates.
“Neural responses to uncertainty or surprise have been reported in multiple structures (den Ouden et al., 2010; Fiorillo et al., 2003; Kepecs et al., 2008; McCoy and Platt, 2005; O'Neill and Schultz, 2010; Preuschoff et al., 2006; Preuschoff et al., 2008; Schultz et al., 2008; So and Stuphorn, 2012; Tobler et al., 2009) and have been linked with variables such as arousal, anxiety, risk preference,”
From Attention, learning, and the value of information (2012) · cites this paper as Kepecs et al., 2008
Previous studies have relied on an object-level framework where confidence is equated with the information that governs the choice process.
“Previous studies have relied on an object-level framework, where confidence is equated with the information that governs the choice process [ 30 – 32 ].”
From Metacognition: computation, biology and function (2012) · cites this paper as [30]
The citation lists haven’t been fetched yet
References 53 · Cited by 809
- Authors
- Kepecs, A., Uchida, N., Zariwala, H. A., & Mainen, Z. F.
- Affiliations
- Harvard University (US)
- Allen Institute for Brain Science (US)
- Cold Spring Harbor Laboratory (US)
- Corresponding author
- Mainen, Zachary F.
- Venue
- Nature
- Published
- 2008-08-10
- Volume
- 455
- Issue
- 7210
- Pages
- 227-231
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2043608504
- Cited by
- 809
- References
- 53
- Citations by year
- 2026: 32 · 2025: 49 · 2024: 36 · 2023: 44 · 2022: 34 · 2021: 60 · 2020: 58 · 2019: 49 · 2018: 52 · 2017: 62 · 2016: 58 · 2015: 52 · 2014: 63 · 2013: 33 · 2012: 49
- FWCI
- 13.46
- Type
- journal article
- Language
- en
- Open access
- green
- nrs.harvard.edu
- Licence
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Cold Spring Harbor Laboratory Institutional Repository (Cold Spring Harbor Laboratory) (acceptedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- decision confidence, metacognition, orbitofrontal cortex, perceptual decision making, task difficulty, confidence estimation, single-unit activity, delayed rewards, computational models of decision making, quality of evidence
- MeSH terms
- Animals, Behavior, Animal, Decision Making, Frontal Lobe, Male, Models, Neurological, Neurons, Odorants, Reward, Smell, Confidence Intervals, Linear Models, Rats, Long-Evans, Uncertainty, Rats
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review