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Learning own- and other-race facial identities: Testing implicit recognition with event-related brain potentials.

Tüttenberg, Simone C. and Wiese, Holger (2019) 'Learning own- and other-race facial identities: Testing implicit recognition with event-related brain potentials.', Neuropsychologia., 134 . p. 107218.


Exposure to varying images of the same person can encourage the formation of a representation that is sufficiently robust to allow recognition of previously unseen images of this person. While behavioural work suggests that face identity learning is harder for other-race faces, the present experiment investigated the neural correlates underlying own- and other-race face learning. Participants sorted own- and other-race identities into separate identity clusters and were further familiarised with these identities in a matching task. Subsequently, we compared event-related brain potentials (ERPs) in an implicit recognition (butterfly detection) task for learnt and previously unseen identities. We observed better sorting and matching for own-than other-race identities, and behavioural learning effects were restricted to own-race identities. Similarly, the N170 ERP component showed clear learning effects for own-race faces only. The N250, a component more closely associated with face learning was more negative for learnt than novel identities. ERP findings thus suggests a processing advantage for own-race identities at an early perceptual level whereas later correlates of identity learning were unaffected by ethnicity. These results suggest learning advantages for own-race identities, which underscores the importance of perceptual expertise in the own-race bias.

Item Type:Article
Full text:(AM) Accepted Manuscript
Available under License - Creative Commons Attribution Non-commercial No Derivatives.
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Publisher statement: © 2019 This manuscript version is made available under the CC-BY-NC-ND 4.0 license
Date accepted:27 September 2019
Date deposited:02 October 2019
Date of first online publication:30 September 2019
Date first made open access:30 September 2020

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