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. 2023 Jul 14;13:11396. doi: 10.1038/s41598-023-28632-x

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© The Author(s) 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Super-recognizers show consistent and face-specific identification expertise. Violin plots show the distribution of performance for super-recognizers and controls on the test battery. Red lines show group means. Super-recognizers outperformed controls on a battery of standardised tests measuring face matching (GFMT³⁸, Models⁷¹), face recognition memory (CFMT + ⁷⁸, CFMT-Aus ⁷³), and general face identification abilities (UNSW Face Test⁷⁴). To a lesser extent, they were also better than controls on both the Primate Matching Test and Fingerprint Matching Test but not the MFFT test, suggesting some overlapping ability across domains in perceptual matching. We are unable to show the primate and fingerprint stimuli used in the test. Example primate faces were obtained from Pixabay (https://pixabay.com/images/search/monkey%20face/) and are released under the Pixabay License. Fingerprint images are by Metrónomo and licenced under SelfCC BY-SA 2.5 AR (https://creativecommons.org/licenses/by-sa/2.5/ar/deed.en).