The DOI matches its Crossref record; 178 of the 178 references it cites were found in a registry or an index.
From prediction error to incentive salience: mesolimbic computation of reward motivation.
Open accessAbstract
Reward contains separable psychological components of learning, incentive motivation and pleasure. Most computational models have focused only on the learning component of reward, but the motivational component is equally important in reward circuitry, and even more directly controls behavior. Modeling the motivational component requires recognition of additional control factors besides learning. Here I discuss how mesocorticolimbic mechanisms generate the motivation component of incentive salience. Incentive salience takes Pavlovian learning and memory as one input and as an equally important input takes neurobiological state factors (e.g. drug states, appetite states, satiety states) that can vary independently of learning. Neurobiological state changes can produce unlearned fluctuations or even reversals in the ability of a previously learned reward cue to trigger motivation. Such fluctuations in cue-triggered motivation can dramatically depart from all previously learned values about the associated reward outcome. Thus, one consequence of the difference between incentive salience and learning can be to decouple cue-triggered motivation of the moment from previously learned values of how good the associated reward has been in the past. Another consequence can be to produce irrationally strong motivation urges that are not justified by any memories of previous reward values (and without distorting associative predictions of future reward value). Such irrationally strong motivation may be especially problematic in addiction. To understand these phenomena, future models of mesocorticolimbic reward function should address the neurobiological state factors that participate to control generation of incentive salience.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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?
In the citing paper
“All these observations indicate that the role of physiological ‘drive states’ is really to amplify the incentive value of their relevant incentive targets, and magnify their reward properties, rather than act as independent drives (Toates, 1986; Berridge, 2012).”
From Evolving Concepts of Emotion and Motivation (2018) · cites this paper as Berridge, 2012
In the citing paper
“By contrast, incentive salience has distinct signature features: often being cue-triggered as a temporary peak of desire to obtain or consume an associated reward (Berridge, 2001, 2012).”
From Evolving Concepts of Emotion and Motivation (2018) · cites this paper as Berridge, 2012
In the citing paper
“Reward cues alone are relatively powerless at producing motivation without an appropriate brain state. It’s the brain’s reaction to a cue that matters for ‘wanting’ motivation via incentive salience (Berridge, 2012; Dayan and Berridge, 2014).”
From Evolving Concepts of Emotion and Motivation (2018) · cites this paper as Berridge, 2012
In the citing paper
“Stress, similar to drugs of abuse, may also induce neurological changes that enhance dopaminergic activity and the attribution of incentive value to rewards and their cues (Berridge, 2012; T. E. Robinson, Angus, & Becker, 1985; Yap et al., 2015).”
From Cued for Risk: Evidence for an Incentive Sensitization Framework to Explain the Interplay between Stress and Anxiety, Substance Abuse, and Reward Uncertainty in Disordered Gambling Behavior (2019) · cites this paper as Berridge, 2012
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A neural substrate of prediction and reward
Schultz, W., Dayan, P., & Montague, P. R. (1997) · Science · doi:10.1126/science.275.5306.1593 · Cited by 9,388
The neural basis of drug craving: An incentive-sensitization theory of addiction
Robinson, T. (1993) · Brain Research Reviews · doi:10.1016/0165-0173(93)90013-p · Cited by 7,346
Koob, G. F., & Volkow, N. D. (2010) · Neuropsychopharmacology · doi:10.1038/npp.2009.110 · Cited by 5,340
The Psychology of Learning and Motivation
(2021) · The Psychology of learning and motivation/The psychology of learning and motivation · doi:10.1016/s0079-7421(21)x0002-3 · Cited by 5,082
Predictive reward signal of dopamine neurons
Schultz, W. (1998) · Journal of Neurophysiology · doi:10.1152/jn.1998.80.1.1 · Cited by 4,564
What is the role of dopamine in reward: hedonic impact, reward learning, or incentive salience?
Berridge, K. C., & Robinson, T. E. (1998) · Brain Research Reviews · doi:10.1016/s0165-0173(98)00019-8 · Cited by 4,127
Self-citationKapur, S. (2003) · American Journal of Psychiatry · doi:10.1176/appi.ajp.160.1.13 · Cited by 2,813
NEURAL MECHANISMS OF ADDICTION: The Role of Reward-Related Learning and Memory
Hyman, S. E., Malenka, R. C., & Nestler, E. J. (2006) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.29.051605.113009 · Cited by 2,647
Back to Bentham? Explorations of Experienced Utility
Kahneman, D. J., Wakker, P. P., & Sarin, R. K. (1997) · The Quarterly Journal of Economics · doi:10.1162/003355397555235 · Cited by 2,537
Drug abuse: hedonic homeostatic dysregulation
Koob, G. F., & Moal, M. L. (1997) · Science · doi:10.1126/science.278.5335.52 · Cited by 2,535
Research works printed but not linked: 8
- Dickinson A., 2002, Stevens’ Handbook of Experimental Psychology: Learning, Motivation, and Emotion, 497
- Dickinson A., 2010, Pleasures of the Brain, 74
- DiFeliceantonio A.G., 2010, Neostriatal Sites of Mu Opioid Stimulation Enhance CS Motivational Magnets
- Heath R.G., 1996, Exploring the Mind‐Brain Relationship
- Kringelbach M.L., 2010, Pleasures of the Brain, 202
- Leyton M., 2010, Pleasures of the Brain, 222
- Robinson M.J.F., 2010, Instant Incentive Salience: dynamic Transformation of An Aversive Salt Cue Into a ‘Wanted’ Motivational Magnet
- Toates F., 1986, Motivational Systems
Cited by
Sorted by citations
Items 601–699 of 699
Pleasure, Displeasure, and Affective Valence
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.010
Terpstra, A. R., & Todd, R. M. (2020) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/zdt36
Psychological Hedonism and Its Problems
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.008
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.027
Reward, Incentive Salience, and Hedonic Motivation
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.013
Editorial for “ Cross‐Scanner Harmonization of Neuromelanin‐Sensitive MRI for Multisite Studies”
Wieland, L., & Schlagenhauf, F. (2021) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.27924
Reformulating Psychological Hedonism
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.009
Understanding the Causes of Behavior
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.004
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.012
Oh, Du meine Psyche, Du mein Herz!
Marter, K. (2021) · Über/Strom: Wegweiser durchs digitale Zeitalter · doi:10.1007/978-3-658-34061-2_2
The Phylogenetic Development of Psychological Hedonism
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.021
Clinical and Research Methods in the Addictions
Sussman, S. Y. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108632591.008
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.018
From Hedonic Motivation to Unhealthy Behavior
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.016
Rauthmann, J. F. (2017) · Springer-Lehrbuch · doi:10.1007/978-3-662-53004-7_9
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.022
Darwinian Hedonism and Political Will
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.029
Darwinian Hedonism and Hedonic Desire for Calorie-Dense Foods
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.024
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.001
Conclusions and Future Directions
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.030
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.002
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.033
The Epidemic of Unhealthy Behavior
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.003
Darwinian Hedonism and Hedonic Desire for Smoking, Drinking, and Drug Use
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.026
Levels of Analysis and Etiology
(2020) · Cambridge University Press eBooks · doi:10.1017/9781108632591.014
Anticipating Criticisms of Darwinian Hedonism
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.032
Ongoing and Future Research Directions
(2020) · Cambridge University Press eBooks · doi:10.1017/9781108632591.030
Darwinian Hedonism and Health-Behavior Policy
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.028
Sussman, S. Y. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108632591.002
Srivastava, A. B., & Gold, M. S. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108632591.033
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.019
Hedonic Motivation and Other Motivation Concepts
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.031 · Cited by 1
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.006
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.014
Darwinian Hedonism and Unhealthy Behavior
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.023
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.011
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.005
Extending the two-component model of delusion to substance use disorder etiology and recovery
Richardson, G. B., & Mcgee, N. D. (2022) · New Ideas in Psychology · doi:10.1016/j.newideapsych.2022.100935
Juego patológico: historia y bases neuroanatómicas y fisiopatológicas
Muñoz, A. Z., Noreña, D. D., Ezpeleta, D., & González, G. L. (2022) · Kranion · doi:10.24875/kranion.m21000014
Faculty Opinions recommendation of Affective valence in the brain: modules or modes?
Schoenbaum, G. M., & Costa, K. M. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.735001483.793560814
Williams, D. M. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316275047.034
Sussman, S. Y. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108632591.042
Marques, D. B. (2022) · Digital Library of Theses and Dissertations (Universidade de São Paulo) · doi:10.11606/t.17.2022.tde-06052022-163630
Evolution of Learning Processes
(2022) · Cambridge University Press eBooks · doi:10.1017/9781108768450.003
Bonometti, V., Ruiz, M. J., Drachen, A., & Wade, A. R. (2022) · Computational Brain & Behavior · doi:10.1007/s42113-022-00147-0 · Cited by 1
Smirnitskaya, I. A. (2022) · Studies in computational intelligence · doi:10.1007/978-3-031-19032-2_25
Bosulu, J. (2022) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/wpqj7
Dorv�, C. (2022) · MOspace Institutional Repository (University of Missouri) · doi:10.32469/10355/94212 · Cited by 1
Labusga, M. (2023) · eDiss (Georg-August-Universität Göttingen) · doi:10.53846/goediss-9734
Computational Modeling in Various Cognitive Fields
(2023) · Cambridge University Press eBooks · doi:10.1017/9781108755610.027
The Neurobiology of Opioid Use
Khatri, S., Maher, E. E., Bondy, E. O., & Gipson, C. D. (2023) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780197618431.013.6
The Achilles Heel of Artificial Intelligence
Premaratne, U. K., & Halgamuge, S. K. (2023) · Communications in computer and information science · doi:10.1007/978-3-031-42430-4_32
Youdin, R. (2023) · doi:10.1093/oso/9780197575024.003.0006
Youdin, R. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780197575024.003.0005
Youdin, R. (2023) · doi:10.1093/oso/9780197575024.003.0004
Jordan, C. J., & Andersen, S. L. (2024) · Addiction Neuroscience · doi:10.1016/j.addicn.2024.100161
A disinhibitory basal forebrain-to-cortex projection supports sustained attention
Li, S.-J., Hangya, B., Gupta, U., Singh, H., Fischer, K. B., Sturgill, J. F., Callaway, E. M., & Kepecs, Á. (2026) · Cell · doi:10.1016/j.cell.2026.05.046
Proietti, R., Parr, T., Tessari, A., Friston, K. J., & Pezzulo, G. (2024) · doi:10.31234/osf.io/m87wk
Guimpel, B. (2024) · Elsevier eBooks · doi:10.1016/b978-2-294-78127-8.00014-2
Job, V., & Goschke, T. (2024) · Springer eBooks · doi:10.1007/978-3-662-68476-4_10
Mao, M., Cai, Y., Li, Y., Li, Z., Dong, W., Wang, Y., & Zhang, X. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.12.23.630185
The Revised Reward Theory of Desire
Pober, J. (2025) · Erkenntnis · doi:10.1007/s10670-025-00932-w
Schwarze, Y., Stierand, J., Voges, J. F., Zillikens, E., Junghanns, K., Voß, O., Paulus, F. M., Krach, S., Cabanis, M., & Rademacher, L. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.17.665126
Dayan, P. (2025) · Handbook of behavioral neuroscience · doi:10.1016/b978-0-443-29867-7.09992-8
Kognitive und neuronale Grundlagen von Motivation, Belohnung und Selbstkontrolle
Goschke, T. (2025) · Springer eBooks · doi:10.1007/978-3-662-69368-1_10
Reward-associated cues reduce H-current amplitude in midbrain dopamine neurons
Calo‐Guadalupe, C., Bosque-Cordero, K. Y., Capella-Muñiz, J., Consuegra‐García, D., Vázquez‐Torres, R., Vélez‐Acevedo, O., Laboy-Juárez, K. J., Sanabria, P., & Jiménez‐Rivera, C. A. (2025) · Neuropharmacology · doi:10.1016/j.neuropharm.2025.110699
Hernández-Colín, A. E., Canseco-Alba, A., & Rodrı́guez–Manzo, G. (2025) · Psychopharmacology · doi:10.1007/s00213-025-06903-x
Addictive motivational scaffolds and the structure of social media
Manuali, L. (2025) · Synthese · doi:10.1007/s11229-025-05312-z · Cited by 1
Skórzewska, A., Kuchniak, K., Wyszogrodzka, E., & Taracha, E. (2025) · Behavioural Brain Research · doi:10.1016/j.bbr.2025.115906
Serotonin modulates nucleus accumbens circuits to suppress aggressionPreprint
Zhang, Z., Touponse, G. C., Alderman, P. J., Yassine, T., Pomrenze, M. B., Harris, T. W., Shank, A. N., Malenka, R. C., & Eshel, N. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.11.26.690732
Integrated Workspace with Subjective Modeling (IWSM) Theory of ConsciousnessPreprint
Muhlert, M. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5681532
Cortical astrocytes flexibly encode reward contingencies and shape conditioned behaviorPreprint
Paniccia, J. E., Grant, R. I., Westphal, A. M., Clarke, R. E., Doncheck, E. M., Pagoota, B. E., Carroll-Deaton, J., Bordieanu, B., Buchmaier, S., Klumb, L. G., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.08.693010
Peng, M. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-29139-5.00051-3
Noninvasive transcranial brain stimulation to treat cognitive aspects of other psychiatric diseases
Downar, J. (2025) · Handbook of behavioral neuroscience · doi:10.1016/b978-0-443-26602-7.00031-2
Gamode, A. A., Malik, R. B., Butler, J., & Kubis, H. (2026) · Nutrients · doi:10.3390/nu18010177
Habit learning is associated with efficiently controlled network dynamics in naive macaque monkeys
Brynildsen, J. K., Fotiadis, P., Szymula, K. P., Kim, J. Z., Pasqualetti, F., Graybiel, A. M., Desrochers, T. M., & Bassett, D. S. (2026) · npj Complexity · doi:10.1038/s44260-025-00066-8 · Cited by 1
The Value of Perceived Control
Yang, Y.-Y., Kwon, S.-J., Derrell, A., & Delgado, M. R. (2026) · Springer eBooks · doi:10.1007/978-3-032-02925-6_19
Polese, D., Mazzetta, A., Costanzi, F., Cozza, G., Niolu, C., Causi, F. S. L., Nardo, G. D., Caserta, D., Parisi, P., Siracusano, A., et al. (2026) · Journal of Affective Disorders · doi:10.1016/j.jad.2026.121416
Versace, F., Green, C., Cui, Y., Robinson, J. D., Deweese, M. M., Minnix, J. A., Kypriotakis, G., Kim, S., Karam‐Hage, M., & Cinciripini, P. M. (2026) · Addiction · doi:10.1111/add.70354
The role of β4-containing nicotinic acetylcholine receptors in nicotine addiction
Harrington, L. (2015) · theses.fr (ABES) · doi:10.70675/835afebdzb53ez461ez920cz1f4b0acd17a6
Étude moléculaire et comportementale de la variabilité de réponse à la cocaïne
Martinez, L. A. A. (2021) · theses.fr (ABES) · doi:10.70675/c394f299z9930z4d9fzb9ecz074185fe9fee
Goutaudier, R. (2022) · theses.fr (ABES) · doi:10.70675/6619b466z54bfz41e3z8a90zf0967825d579
Djorovic, D. J., Aranđelović, J., Ivanović, J., Jezdić, K., Batinić, B., Sharmin, D., Mondal, P., Cook, J. M., & Savić, M. M. (2026) · Pharmacology Research & Perspectives · doi:10.1002/prp2.70245
Costa, K. M., Hammer, N., Knowlton, C. J., Schwenk, J., Müller, T., Schulte, D., Fakler, B., Canavier, C. C., & Roeper, J. (2026) · Journal of Neuroscience · doi:10.1523/jneurosci.1956-25.2026 · Cited by 4
Modulating satiety with neuro-music: a frequency-specific acoustic approach to appetite control
Chang, M., Ibaraki, T., Oaku, Y., Hirate, M., Tanaka, K., Yokota, Y., Koike, S., Naruse, Y., Imamura, Y., Nishimoto, S., et al. (2026) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2026.1796514
Valence, Mirror Self-Recognition, and the Gradualist Evolution of Consciousness
Veit, W. (2026) · Philosophia · doi:10.1007/s11406-026-00994-2
The interpretation of behavior-model correlations in unidentified cognitive modelsPreprint
Miletić, S., & van Maanen, L. (2022) · OSF Preprints (OSF Preprints)
What’s next for interoception and addiction?
Peart, D. R., & Murray, J. E. (2026) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2026.106875
Interval timing and animal communication
Rodríguez‐Saltos, C. A., & Scott, J. (2026) · Journal of Experimental Biology · doi:10.1242/jeb.251731
Crandall, A. K., Dennis, C. V., Gearhardt, A. N., Miller, A. L., Kaciroti, N., & Lumeng, J. C. (2026) · Appetite · doi:10.1016/j.appet.2026.108753
Carbone, E. A., Aloi, M., Rotella, L., Garofalo, S. M., Vizza, G. F., Quirino, D., & Segura‐Garcìa, C. (2026) · Eating and Weight Disorders - Studies on Anorexia Bulimia and Obesity · doi:10.1007/s40519-026-01898-6
Research progress on the role of claustrum in substance addiction
Wu, M., Wenhua, Z. H. O. U., & Min, Z. H. A. O. (2026) · Journal of Zhejiang University (Medical Sciences) · doi:10.3724/zdxbyxb-2025-0893
Karlsson, H., Asutay, E., & Västfjäll, D. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1797253
Stress reduces loss aversion without increasing reward-cue attentional salience
Tommaso, M. D., Coelli, S., Reali, P., Bianchi, A. M., & Actis-Grosso, R. (2026) · Motivation and Emotion · doi:10.1007/s11031-026-10286-7
Lazovskiy, V. A., Викторович, С. С., Kipelkin, I. M., & Kazantsev, V. (2026) · Chaos Solitons & Fractals · doi:10.1016/j.chaos.2026.119300
Cope, L. M. (2013) · UNM’s Digital Repository (University of New Mexico)
Salience attribution in addiction and psychosis
Freeman, T. P. (2013) · UCL Discovery (University College London)
Metadata
- Authors
- Berridge, K. C.
- Affiliations
- University of Michigan (US)
- Corresponding author
- Berridge, Kent C.
- ORCID
- Berridge, Kent C.
- Venue
- European Journal of Neuroscience
- Publisher
- Wiley
- Published
- 2012-04
- Volume
- 35
- Issue
- 7
- Pages
- 1124-1143
- ISSN
- 0953-816X (ISSN-L)
- 1460-9568
- PMC
- PMC3325516
- OpenAlex
- W2171592792
- Cited by
- 700
- References
- 175
- Citations by year
- 2026: 25 · 2025: 32 · 2024: 29 · 2023: 43 · 2022: 49 · 2021: 57 · 2020: 94 · 2019: 90 · 2018: 49 · 2017: 37 · 2016: 50 · 2015: 46 · 2014: 43 · 2013: 39 · 2012: 16
- FWCI
- 4.82
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- European Journal of Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Deep Blue (University of Michigan) (submittedVersion)
- Funders
- National Institutes of Health
- National Institute of Mental Health (MH-63649, R01MH063649)
- National Institute on Drug Abuse (R01DA017752, DA-017752, DA015188, R01DA015188)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Keywords
- incentive salience, reward motivation, mesolimbic system, mesocorticolimbic circuitry, Pavlovian learning, satiety, appetite, addiction, reward prediction error
- MeSH terms
- Animals, Computer Simulation, Forecasting, Humans, Learning, Limbic System, Models, Neurological, Motivation, Reward
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
