A signal detection theoretic approach for estimating metacognitive sensitivity from confidence ratings
Abstract
How should we measure metacognitive ("type 2") sensitivity, i.e. the efficacy with which observers' confidence ratings discriminate between their own correct and incorrect stimulus classifications? We argue that currently available methods are inadequate because they are influenced by factors such as response bias and type 1 sensitivity (i.e. ability to distinguish stimuli). Extending the signal detection theory (SDT) approach of Galvin, Podd, Drga, and Whitmore (2003), we propose a method of measuring type 2 sensitivity that is free from these confounds. We call our measure meta-d', which reflects how much information, in signal-to-noise units, is available for metacognition. Applying this novel method in a 2-interval forced choice visual task, we found that subjects' metacognitive sensitivity was close to, but significantly below, optimality. We discuss the theoretical implications of these findings, as well as related computational issues of the method. We also provide free Matlab code for implementing the analysis.
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The meta-d' model offers a performance-controlled metric of metacognitive sensitivity by estimating the level of first-order performance that would have given rise to the observed confidence data under a signal detection theoretic model.
“The meta-d ′ model offers a performance-controlled metric of metacognitive sensitivity by estimating the level of first-order performance (d ′ ) that would have given rise to the observed confidence data under a signal detection theoretic model (Maniscalco & Lau 2012).”
From Metacognition and Confidence: A Review and Synthesis (2024) · cites this paper as Maniscalco & Lau 2012
Cites
A comparison of current measures of the accuracy of feeling-of-knowing predictions
Nelson, T. O. (1984) · Psychological Bulletin · doi:10.1037/0033-2909.95.1.109 · Cited by 976 · see citing works
Empirical support for higher-order theories of conscious awareness
Lau, H., & Rosenthal, D. (2011) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2011.05.009 · Cited by 869 · cited 1× · see citing works
“For instance, on some models, type 2 decisions are based upon further processing of the same information used to make type 1 decisions (Lau & Rosenthal, 2011; Maniscalco & Lau, 2010; Pleskac & Busemeyer, 2010).”
MethodSelf-citationTwo-stage dynamic signal detection: A theory of choice, decision time, and confidence.
Pleskac, T. J., & Busemeyer, J. R. (2010) · Psychological Review · doi:10.1037/a0019737 · Cited by 722 · see citing works
Transfer of metacognitive skills and hint seeking in monkeys
Kornell, N., Son, L. K., & Terrace, H. S. (2007) · Psychological Science · doi:10.1111/j.1467-9280.2007.01850.x · Cited by 341 · see citing works
Confidence and accuracy of near-threshold discrimination responses
Kunimoto, C., Miller, J., & Pashler, H. (2001) · Consciousness and Cognition · doi:10.1006/ccog.2000.0494 · Cited by 291 · see citing works
Blindsight in normal observers
Kolb, F. C., & Braun, J. (1995) · Nature · doi:10.1038/377336a0 · Cited by 198 · see citing works
Comparing signal detection models of perceptual decision confidence
Maniscalco, B., & Lau, H. (2010) · Journal of Vision · doi:10.1167/10.7.213 · Cited by 15 · cited 1× · see citing works
“For instance, on some models, type 2 decisions are based upon further processing of the same information used to make type 1 decisions (Lau & Rosenthal, 2011; Maniscalco & Lau, 2010; Pleskac & Busemeyer, 2010).”
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“The recently developed meta-d′ measure (Maniscalco and Lau, 2012, 2014) exploits the fact that given Gaussian variance assumptions at the type 1 level, the shapes of the type 2 distributions are known even if they are not themselves Gaussian (Galvin et al., 2003).”
Self-citationThe neural basis of metacognitive ability
Fleming, S. M., & Dolan, R. J. (2012) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2011.0417 · Cited by 747 · see citing works
Understanding the Higher-Order Approach to Consciousness
Brown, R., Lau, H., & LeDoux, J. E. (2019) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2019.06.009 · Cited by 573 · see citing works
Self-citationPrefrontal Contributions to Metacognition in Perceptual Decision Making
Fleming, S. M., Huijgen, J., & Dolan, R. J. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.6489-11.2012 · Cited by 391 · see citing works
The role of metacognition in human social interactions
Frith, C. D. (2012) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2012.0123 · Cited by 407 · see citing works
Suboptimality in perceptual decision making
Rahnev, D., & Denison, R. N. (2018) · Behavioral and Brain Sciences · doi:10.1017/s0140525x18000936 · Cited by 342 · see citing works
Metacognition: computation, biology and function
Fleming, S. M., Dolan, R. J., & Frith, C. D. (2012) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2012.0021 · Cited by 344 · see citing works
Baird, B., Smallwood, J., Gorgolewski, K. J., & Margulies, D. S. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.0786-13.2013 · Cited by 315 · see citing works
Consciousness in humans and non-human animals: recent advances and future directions
Boly, M., Seth, A. K., Wilke, M., Ingmundson, P., Baars, B., Laureys, S., Edelman, D. B., & Tsuchiya, N. (2013) · Frontiers in Psychology · doi:10.3389/fpsyg.2013.00625 · Cited by 291 · see citing works
Anatomical coupling between distinct metacognitive systems for memory and visual perception
McCurdy, L. Y., Maniscalco, B., Metcalfe, J., Liu, K. Y., de Lange, F. P., & Lau, H. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.1890-12.2013 · Cited by 299 · see citing works
Self-citationShould a Few Null Findings Falsify Prefrontal Theories of Conscious Perception?
Odegaard, B., Knight, R. T., & Lau, H. (2017) · The Journal of Neuroscience · doi:10.1523/jneurosci.3217-16.2017 · Cited by 316 · see citing works
Self-citationA common mechanism underlies changes of mind about decisions and confidence
van den Berg, R., Anandalingam, K., Zylberberg, A., Kiani, R., Shadlen, M. N., & Wolpert, D. M. (2016) · eLife · doi:10.7554/elife.12192 · Cited by 270 · see citing works
Metacognition and Confidence: A Review and Synthesis
Fleming, S. M. (2024) · Annual Review of Psychology · doi:10.1146/annurev-psych-022423-032425 · Cited by 256 · see citing works
“For instance, when combining information from two different sensory modalities, the normative (Bayesian) solution is to weight the two sources inversely according to their respective uncertainties.”
Distinct brain mechanisms for conscious versus subliminal error detection
Charles, L., Van Opstal, F., Marti, S., & Dehaene, S. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.01.054 · Cited by 208 · see citing works
Causal evidence for frontal cortex organization for perceptual decision making
Rahnev, D., Nee, D. E., Riddle, J., Larson, A. S., & D’Esposito, M. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1522551113 · Cited by 200 · see citing works
Individual consistency in the accuracy and distribution of confidence judgments
Ais, J., Zylberberg, A., Barttfeld, P., & Sigman, M. (2016) · Cognition · doi:10.1016/j.cognition.2015.10.006 · Cited by 174 · see citing works
Human Metacognition Across Domains: Insights from Individual Differences and Neuroimaging
Rouault, M., McWilliams, A., Allen, M. G., & Fleming, S. M. (2018) · Personality Neuroscience · doi:10.1017/pen.2018.16 · Cited by 176 · see citing works
Domain-general enhancements of metacognitive ability through adaptive training.
Carpenter, J., Sherman, M. T., Kievit, R. A., Seth, A. K., Lau, H., & Fleming, S. M. (2019) · Journal of Experimental Psychology: General · doi:10.1037/xge0000505 · Cited by 174 · see citing works
Self-citationAbnormalities of confidence in psychiatry: an overview and future perspectives
Hoven, M., Lebreton, M., Engelmann, J. B., Denys, D., Luigjes, J., & van Holst, R. J. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0602-7 · Cited by 171 · see citing works
The signal processing architecture underlying subjective reports of sensory awareness
Maniscalco, B., & Lau, H. (2016) · Neuroscience of Consciousness · doi:10.1093/nc/niw002 · Cited by 133 · see citing works
Self-citationHow Local and Global Metacognition Shape Mental Health
Seow, T. X. F., Rouault, M., Gillan, C. M., & Fleming, S. M. (2021) · Biological Psychiatry · doi:10.1016/j.biopsych.2021.05.013 · Cited by 159 · see citing works
Multivoxel neurofeedback selectively modulates confidence without changing perceptual performance
Cortese, A., Amano, K., Koizumi, A., Kawato, M., & Lau, H. (2016) · Nature Communications · doi:10.1038/ncomms13669 · Cited by 157 · see citing works
Self-citationMeasures of metacognition on signal-detection theoretic models
Barrett, A. B., Dienes, Z., & Seth, A. K. (2013) · Psychological Methods · doi:10.1037/a0033268 · Cited by 155 · see citing works
Comparing Bayesian and non-Bayesian accounts of human confidence reports
Adler, W. T., & Ma, W. J. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006572 · Cited by 118 · see citing works
Compulsivity reveals a novel dissociation between action and confidence
Vaghi, M. M., Luyckx, F., Sule, A., Fineberg, N. A., Robbins, T. W., & De Martino, B. (2017) · Neuron · doi:10.1016/j.neuron.2017.09.006 · Cited by 145 · see citing works
Forming global estimates of self-performance from local confidence
Rouault, M., Dayan, P., & Fleming, S. M. (2019) · Nature Communications · doi:10.1038/s41467-019-09075-3 · Cited by 134 · see citing works
Mazancieux, A., Fleming, S. M., Souchay, C., & Moulin, C. J. A. (2020) · Journal of Experimental Psychology: General · doi:10.1037/xge0000746 · Cited by 131 · see citing works
Doubly Bayesian Analysis of Confidence in Perceptual Decision-Making
Aitchison, L., Bang, D., Bahrami, B., & Latham, P. E. (2015) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1004519 · Cited by 131 · see citing works
Behavioral, Modeling, and Electrophysiological Evidence for Supramodality in Human Metacognition
Faivre, N., Filevich, E., Solovey, G., Kühn, S., & Blanke, O. (2018) · The Journal of Neuroscience · doi:10.1523/jneurosci.0322-17.2017 · Cited by 129 · see citing works
Causal neural network of metamemory for retrospection in primates
Miyamoto, K., Osada, T., Setsuie, R., Takeda, M., Tamura, K., Adachi, Y., & Miyashita, Y. (2017) · Science · doi:10.1126/science.aal0162 · Cited by 106 · see citing works
Behavioral and Neural Indices of Metacognitive Sensitivity in Preverbal Infants
Goupil, L., & Kouider, S. (2016) · Current Biology · doi:10.1016/j.cub.2016.09.004 · Cited by 116 · see citing works
The impact of evidence reliability on sensitivity and bias in decision confidence.
Boldt, A., de Gardelle, V., & Yeung, N. (2017) · Journal of Experimental Psychology: Human Perception and Performance · doi:10.1037/xhp0000404 · Cited by 110 · see citing works
Understanding neural signals of post-decisional performance monitoring: An integrative review
Desender, K., Ridderinkhof, K. R., & Murphy, P. R. (2021) · eLife · doi:10.7554/elife.67556 · Cited by 77 · see citing works
Relation between belief and performance in perceptual decision making
Drugowitsch, J., Moreno-Bote, R., & Pouget, A. (2014) · PLoS ONE · doi:10.1371/journal.pone.0096511 · Cited by 72 · see citing works
First-person view of one’s body in immersive virtual reality: Influence on episodic memory
Bréchet, L., Mange, R., Herbelin, B., Theillaud, Q., Gauthier, B., Serino, A., & Blanke, O. (2019) · PLOS ONE · doi:10.1371/journal.pone.0197763 · Cited by 85 · see citing works
Unpacking the complexities of consciousness: Theories and reflections
Mudrik, L., Boly, M., Dehaene, S., Fleming, S. M., Lamme, V., Seth, A., & Melloni, L. (2025) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2025.106053 · Cited by 81 · see citing works
The accuracy of German citizens’ confidence in their climate change knowledge
Fischer, H., Amelung, D., & Said, N. (2019) · Nature Climate Change · doi:10.1038/s41558-019-0563-0 · Cited by 78 · see citing works
Unconscious information changes decision accuracy but not confidence
Vlassova, A., Donkin, C., & Pearson, J. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1403619111 · Cited by 70 · see citing works
Modeling perceptual confidence and the confidence forced-choice paradigm.
Mamassian, P., & de Gardelle, V. (2022) · Psychological Review · doi:10.1037/rev0000312 · Cited by 70 · see citing works
Khalvati, K., Kiani, R., & Rao, R. P. N. (2021) · Nature Communications · doi:10.1038/s41467-021-25419-4 · Cited by 64 · see citing works
Consensus Goals in the Field of Visual Metacognition
Rahnev, D., Balsdon, T., Charles, L., de Gardelle, V., Denison, R., Desender, K., Faivre, N., Filevich, E., Fleming, S. M., Jehee, J., et al. (2022) · Perspectives on Psychological Science · doi:10.1177/17456916221075615 · Cited by 63 · see citing works
Self-citationCalibration in consciousness science
Michel, M. (2023) · Erkenntnis · doi:10.1007/s10670-021-00383-z · Cited by 62 · see citing works
Action information contributes to metacognitive decision-making
Wokke, M. E., Achoui, D., & Cleeremans, A. (2020) · Scientific Reports · doi:10.1038/s41598-020-60382-y · Cited by 56 · see citing works
Banellis, L., & Cruse, D. (2020) · Cerebral Cortex Communications · doi:10.1093/texcom/tgaa060 · Cited by 44 · see citing works
Lamme, V. (2015) · Theoretical Philosophy/MIND Group – JGU Mainz · doi:10.15502/9783958570092 · Cited by 45 · see citing works
Miyamoto, K., Trudel, N., Kamermans, K., Lim, M. C., Lazari, A., Verhagen, L., Wittmann, M. K., & Rushworth, M. F. S. (2021) · Neuron · doi:10.1016/j.neuron.2021.02.024 · Cited by 45 · see citing works
Examining the robustness of the relationship between metacognitive efficiency and metacognitive bias
Xue, K., Shekhar, M., & Rahnev, D. (2021) · Consciousness and Cognition · doi:10.1016/j.concog.2021.103196 · Cited by 45 · see citing works
Linking metacognition and mindreading: Evidence from autism and dual-task investigations.
Nicholson, T., Williams, D. M., Lind, S. E., Grainger, C., & Carruthers, P. (2021) · Journal of Experimental Psychology: General · doi:10.1037/xge0000878 · Cited by 42 · see citing works
Effects of different AI-driven Chatbot feedback on learning outcomes and brain activity
Yin, J., Xu, H., Pan, Y., & Hu, Y. (2025) · npj Science of Learning · doi:10.1038/s41539-025-00311-8 · Cited by 41 · see citing works
Identifying cultural differences in metacognition.
van der Plas, E., Zhang, S., Dong, K., Bang, D., Li, J., Wright, N. D., & Fleming, S. M. (2022) · Journal of Experimental Psychology: General · doi:10.1037/xge0001209 · Cited by 32 · see citing works
Natural statistics support a rational account of confidence biases
Webb, T. W., Miyoshi, K., So, T. Y., Rajananda, S., & Lau, H. (2023) · Nature Communications · doi:10.1038/s41467-023-39737-2 · Cited by 31 · see citing works
Self-citationKwok, S. C., Cai, Y., & Buckley, M. J. (2019) · The Journal of Neuroscience · doi:10.1523/jneurosci.0330-19.2019 · Cited by 28 · see citing works
Error-related cardiac response as information for visibility judgements
Łukowska, M., Sznajder, M., & Wierzchoń, M. (2018) · Scientific Reports · doi:10.1038/s41598-018-19144-0 · Cited by 26 · see citing works
Common computations for metacognition and meta-metacognition
Zheng, Y., Recht, S., & Rahnev, D. (2023) · Neuroscience of Consciousness · doi:10.1093/nc/niad023 · Cited by 15 · see citing works
Is fear perception special? Evidence at the level of decision-making and subjective confidence
Koizumi, A., Mobbs, D., & Lau, H. (2016) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsw084 · Cited by 13 · see citing works
Self-citationThe impact of feedback on metacognition: Enhancing in easy tasks, impeding in difficult ones
Luo, T., & Liu, C. (2023) · Consciousness and Cognition · doi:10.1016/j.concog.2023.103601 · Cited by 15 · see citing works
Miyamoto, K., Harbison, C., Tanaka, S., Saito, M., Luo, S., Matsui, S., Sankhe, P., Mahmoodi, A., Lin, M., Trudel, N., et al. (2025) · Nature Communications · doi:10.1038/s41467-024-55202-0 · Cited by 4 · see citing works
Blaming luck, claiming skill: Self-attribution bias in error assignment
Okamoto, N., Taylor, M., Kubo, T., Ishii, S., De Martino, B., & Cortese, A. (2025) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1013787 · Cited by 2 · see citing works
- Authors
- Maniscalco, B., & Lau, H.
- Affiliations
- Columbia University (US)
- Radboud University Nijmegen (NL)
- Corresponding author
- Maniscalco, Brian
- Venue
- Consciousness and Cognition
- Publisher
- Elsevier BV
- Published
- 2012-03
- Volume
- 21
- Issue
- 1
- Pages
- 422-430
- ISSN
- 1053-8100 (ISSN-L)
- OpenAlex
- W2158741413
- Cited by
- 883
- References
- 7
- Citations by year
- 2026: 101 · 2025: 87 · 2024: 80 · 2023: 107 · 2022: 82 · 2021: 75 · 2020: 65 · 2019: 54 · 2018: 54 · 2017: 46 · 2016: 47 · 2015: 33 · 2014: 27 · 2013: 13 · 2012: 10
- FWCI
- 8.18
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Consciousness and Cognition (publishedVersion)
- PubMed (publishedVersion)
- The HKU Scholars Hub (University of Hong Kong) (submittedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- metacognition, metacognitive sensitivity, confidence ratings, signal detection theory, response bias, visual perception
- MeSH terms
- Cognition, Humans, Judgment, Psychological Theory, Sensitivity and Specificity, Space Perception, Signal Detection, Psychological, Signal-To-Noise Ratio
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