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Capturing specific abilities as a window into human individuality: The example of face recognition
Open accessAbstract
Proper characterization of each individual's unique pattern of strengths and weaknesses requires good measures of diverse abilities. Here, we advocate combining our growing understanding of neural and cognitive mechanisms with modern psychometric methods in a renewed effort to capture human individuality through a consideration of specific abilities. We articulate five criteria for the isolation and measurement of specific abilities, then apply these criteria to face recognition. We cleanly dissociate face recognition from more general visual and verbal recognition. This dissociation stretches across ability as well as disability, suggesting that specific developmental face recognition deficits are a special case of a broader specificity that spans the entire spectrum of human face recognition performance. Item-by-item results from 1,471 web-tested participants, included as supplementary information, fuel item analyses, validation, norming, and item response theory (IRT) analyses of our three tests: (a) the widely used Cambridge Face Memory Test (CFMT); (b) an Abstract Art Memory Test (AAMT), and (c) a Verbal Paired-Associates Memory Test (VPMT). The availability of this data set provides a solid foundation for interpreting future scores on these tests. We argue that the allied fields of experimental psychology, cognitive neuroscience, and vision science could fuel the discovery of additional specific abilities to add to face recognition, thereby providing new perspectives on human individuality.
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By focusing on broad pools of shared variance across tasks, factor analysis may miss smaller but theoretically relevant differences.
“Moreover, by focusing on broad pools of shared variance across tasks, factor analysis may miss smaller but theoretically relevant differences (cf. see Wilmer et al., 2012).”
From When does cognitive functioning peak? The asynchronous rise and fall of different cognitive abilities across the life span (2015) · cites this paper as Wilmer et al., 2012
The opening Abstract (page unavailable) argues that a focus on general abilities may miss specific abilities, which supports the broader concern. But the passages located do not attribute that limitation specifically to factor analysis or its focus on shared variance across tasks. The Discussion (page unavailable) instead describes covariance-based modelling as a useful tool for identifying specific abilities. (LLM, conf=0.76)
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“The Cronbach’s alpha reliabilities for these three tests—interpretable as the mean of all possible Spearman–Brown corrected split-half reliabilities (Cortina, 1993)—are .90, .80, and .81 for CFMT, AAMT, and VPMT, respectively.”
MethodConvergent, discriminant, and incremental validity of competing measures of emotional intelligence
Brackett, M. A., & Mayer, J. D. (2003) · Personality and Social Psychology Bulletin · doi:10.1177/0146167203254596 · Cited by 1,351 · cited 2×
“It is therefore a strength of these additional tests, for establishing convergent validity, that they differ in several ways from our tests of interest.”
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Kaufman, E. A., Xia, M., Fosco, G., Yaptangco, M., Skidmore, C. R., & Crowell, S. E. (2016) · Journal of Psychopathology and Behavioral Assessment · doi:10.1007/s10862-015-9529-3 · Cited by 960
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Metadata
- Authors
- Wilmer, J. B., Germine, L., Chabris, C. F., Chatterjee, G., Gerbasi, M., & Nakayama, K.
- Affiliations
- Wellesley College (US)
- Harvard University (US)
- Union College (US)
- Massachusetts Institute of Technology (US)
- Corresponding author
- Wilmer, Jeremy B.
- Venue
- Cognitive Neuropsychology
- Publisher
- Informa UK Limited
- Published
- 2012-09-01
- Volume
- 29
- Issue
- 5-6
- Pages
- 360-392
- ISSN
- 0264-3294 (ISSN-L)
- 1464-0627
- PMC
- PMC3630451
- OpenAlex
- W2134302492
- Cited by
- 140
- References
- 3
- Citations by year
- 2026: 6 · 2025: 15 · 2024: 12 · 2023: 9 · 2022: 7 · 2021: 12 · 2020: 5 · 2019: 8 · 2018: 11 · 2017: 16 · 2016: 14 · 2015: 12 · 2014: 10 · 2013: 2 · 2012: 1
- FWCI
- 3.83
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Cognitive Neuropsychology (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- PMC
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
- Keywords
- face recognition (cognition), specific abilities, individual differences, Cambridge Face Memory Test, item response theory, visual recognition, spoken word recognition, ability assessment
- MeSH terms
- Adolescent, Adult, Aged, Child, Face, Female, Humans, Individuality, Intelligence Tests, Male, Middle Aged, Neuropsychological Tests, Pattern Recognition, Visual, Psychometrics, Reference Values, Reproducibility of Results, Prosopagnosia, Recognition, Psychology, Young Adult
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