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Unfamiliar face matching ability predicts the slope of face learning

Baker, Kristen A., Mondloch, Catherine J.·2023·Scientific Reports
DOI 10.1038/s41598-023-32244-wPMC PMC10066355
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Abstract

We provide the first examination of individual differences in the efficiency of face learning. Investigating individual differences in face learning can illuminate potential mechanisms and provide greater understanding of why certain individuals might be more efficient face learners. Participants completed two unfamiliar face matching tasks and a learning task in which learning was assessed after viewing 1, 3, 6, and 9 images of to-be-learned identities. Individual differences in the slope of face learning (i.e., increases in sensitivity to identity) were predicted by the ability to discriminate between matched (same-identity) vs. mismatched (different-identity) pairs of wholly unfamiliar faces. A Dual Process Signal Detection model showed that three parameters increased with learning: Familiarity (an unconscious type of memory that varies in strength), recollection-old (conscious recognition of a learned identity), and recollection-new (conscious/confident rejection of novel identities). Good (vs. poor) matchers had higher Recollection-Old scores throughout learning and showed a steeper increase in Recollection-New. We conclude that good matchers are better able to capitalize on exposure to within-person variability in appearance, an effect that is attributable to their conscious memory for both learned and novel faces. These results have applied implications and will inform contemporary and traditional models of face identification.

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  • Individual differences in response bias are stable at the individual level and transfer across different face-matching tests.

    “Again, this interpretation is strengthened by a correlation of criterion values across the two tests, which suggests that these biases are stable at the level of the individual and show transfer across different face-matching tests (Baker et al., 2023).”

    From A criterion-placement theory of face matching (2026) · cites this paper as Baker et al., 2023

  • Criterion and d' values have good test-retest reliability.

    “These values were previously reported to have good test-retest reliability (i.e., criterion: both rs > 0.52, ps < 0.001; d': both rs > 0.53, ps < 0.001; Baker et al., 2023).”

    From A criterion-placement theory of face matching (2026) · cites this paper as Baker et al., 2023

  • An additional four participants were excluded for failing attention checks.

    “As reported in Baker et al. (2023), an additional four participants were tested, but were excluded for failing attention checks.”

    From A criterion-placement theory of face matching (2026) · cites this paper as Baker et al., 2023

  • The relationship between criterion on the GFMT and AIFMT is robust.

    “This makes good sense as the relationship between criterion on the GFMT and AIFMT is robust, r = 0.59, p < 0.001 (Baker et al., 2023).”

    From A criterion-placement theory of face matching (2026) · cites this paper as Baker et al., 2023

  • Individual differences in criterion placement are stable across time and tasks.

    “For example, individual differences in criterion placement are stable across time and tasks, which indicates that this is a meaningful characteristic of behaviour (Baker et al., 2023).”

    From A criterion-placement theory of face matching (2026) · cites this paper as Baker et al., 2023

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Metadata

Authors
Baker, K. A., & Mondloch, C. J.
ORCID
Venue
Scientific Reports
Publisher
Springer Science and Business Media LLC
Published
2023-03-31
Volume
13
Issue
1
ISSN
2045-2322
DOI
10.1038/s41598-023-32244-w
PMC
PMC10066355
Cited by
6
References
2
Language
en
Licence
Funders
Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada (327520, 412323)

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