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Determinants of Face Recognition: The Role of Target Prevalence and Similarity Cover

Determinants of Face Recognition: The Role of Target Prevalence and Similarity

Open Access
|Feb 2024

Abstract

Studies of facial identity processing typically assess perception (via matching) and/or memory (via recognition), with experimental designs differing with respect to one important aspect: Target Prevalence. Some designs include “target absent” (TA) among “target present” (TP) trials. In visual search tasks, TA trials shift an observer’s decisional criterion towards a stricter one, increasing misses. However, decisional biases will differ between individuals and across an individual’s decisions as well. In this way, excluding TA trials ensures comparable levels of expectation and thus a more controlled decisional bias both within and between observers by not considering correct rejections and false alarms. However, TA trials may occur, e.g., in police line-ups, where it is important to consider observers’ face recognition ability net of the potential biases introduced by TA and TP trials. And, while these have been investigated in numerous other stimulus domains, their effects have not yet been extended to face recognition. We therefore sought to fill this void by testing different versions of the previously established Models Memory Test, which measures old/new recognition of experimentally learned facial identities. Our study found significant expectation effects, driven by target prevalence that persist even given prevalence changes. This implies that face recognition – even measured with naturalistic changes – is influenced by prior perceptual decisions.

DOI: https://doi.org/10.5334/joc.339 | Journal eISSN: 2514-4820
Language: English
Submitted on: Jun 28, 2023
Accepted on: Dec 13, 2023
Published on: Feb 21, 2024
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2024 Lionel Boudry, Jeffrey D. Nador, Meike Ramon, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.