The DOI matches its Crossref record; 113 of the 114 references it cites were found in a registry or an index, and 1 are not checked yet.
Human Metacognition Across Domains: Insights from Individual Differences and Neuroimaging
Open accessAbstract
Metacognition is the capacity to evaluate and control one’s own cognitive processes. Metacognition operates over a range of cognitive domains, such as perception and memory, but the neurocognitive architecture supporting this ability remains controversial. Is metacognition enabled by a common, domain-general resource that is recruited to evaluate performance on a variety of tasks? Or is metacognition reliant on domain-specific modules? This article reviews recent literature on the domain-generality of human metacognition, drawing on evidence from individual differences and neuroimaging. A meta-analysis of behavioral studies found that perceptual metacognitive ability was correlated across different sensory modalities, but found no correlation between metacognition of perception and memory. However, evidence for domain-generality from behavioral data may suffer from a lack of power to identify correlations across model parameters indexing metacognitive efficiency. Neuroimaging data provide a complementary perspective on the domain-generality of metacognition, revealing co-existence of neural signatures that are common and distinct across tasks. We suggest that such an architecture may be appropriate for “tagging” generic feelings of confidence with domain-specific information, in turn forming the basis for priors about self-ability and modulation of higher-order behavioral control.
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“The generative nature of GenAI-its 'originality' [157]-means that many user workflows will or have shifted from users generating content to evaluating it [149,154], as already documented in programming [156] and manufacturing design [70].”
From The Metacognitive Demands and Opportunities of Generative AI (2024) · cites this paper as [149]
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“We argue that this imposes a distinct metacognitive demand on users that must make these decisions, akin to [149], who make a similar argument for digital storage and memory.”
From The Metacognitive Demands and Opportunities of Generative AI (2024) · cites this paper as [149]
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“Analogously, as we offload more of our cognition to today's GenAI systems, the demand for our metacognition increases [149].”
From The Metacognitive Demands and Opportunities of Generative AI (2024) · cites this paper as [149]
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Citations
Cites
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Uniting the Tribes of Fluency to Form a Metacognitive Nation
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“By applying a modification of signal detection theory (SDT), known as “ type 2 ” SDT, it is possible to quantify sensitivity and bias of ratings with respect to objective performance (Clarke, Birdsall, & Tanner, 1959; Fleming & Lau, 2014; Galvin, Podd, Drga, & Whitmore, 2003).”
MethodSelf-citationLocalization of a Neural System for Error Detection and Compensation
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Research works printed but not linked: 1
- 2008, Metacognition
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Sorted by citations
The Metacognitive Demands and Opportunities of Generative AI
Tankelevitch, L., Kewenig, V., Simkute, A., Scott, A. E., Sarkar, A., Sellen, A., & Rintel, S. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642902 · Cited by 493
“…(universally applicable across different areas of knowledge, skills, or problem-solving) or domain-specific (pertain to a particular area of expertise to which they are finely tuned, such as math) is a matter of active debate, although there is evidence for both views [11, 44, 68, 118, 151].”
BackgroundThe C factor: cognitive dysfunction as a transdiagnostic dimension in psychopathology
Abramovitch, A., Short, T., & Schweiger, A. (2021) · Clinical Psychology Review · doi:10.1016/j.cpr.2021.102007 · Cited by 269
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
Self-citationKnowing Ourselves Together: The Cultural Origins of Metacognition
Heyes, C., Bang, D., Shea, N., Frith, C. D., & Fleming, S. M. (2020) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2020.02.007 · Cited by 232
Self-citationVaccaro, A. G., & Fleming, S. M. (2018) · Brain and Neuroscience Advances · doi:10.1177/2398212818810591 · Cited by 218
Self-citation
Metadata
- Authors
- Rouault, M., McWilliams, A., Allen, M. G., & Fleming, S. M.
- Affiliations
- Wellcome Centre for Human Neuroimaging (GB)
- Max Planck Society (DE)
- Corresponding author
- Fleming, Stephen M.
- Venue
- Personality Neuroscience
- Publisher
- Cambridge University Press (CUP)
- Published
- 2018
- Volume
- 1
- Pages
- e17
- ISSN
- 2513-9886 (ISSN-L)
- PMC
- PMC6217996
- OpenAlex
- W2899651677
- Cited by
- 176
- References
- 113
- Citations by year
- 2026: 18 · 2025: 25 · 2024: 24 · 2023: 25 · 2022: 33 · 2021: 25 · 2020: 16 · 2019: 7 · 2018: 3
- FWCI
- 7.59
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by-nc-nd
- Locations
- Personality Neuroscience (publishedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Research Portal (King's College London) (publishedVersion, cc-by-nc-nd)
- HAL (submittedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- Wellcome Trust (203147/Z/16/Z, 203147, 206648, 203147/Z/16/)
- National Institute for Health and Care Research (ACF-2015-17-019)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Functions and Memory
- Keywords
- metacognition, domain generality, individual differences, confidence, self-assessment, sensory modalities, metacognitive efficiency
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