Individual differences in adaptive norm-based coding and holistic coding are associated yet each contributes uniquely to unfamiliar face recognition ability.

2017 ◽  
Vol 43 (2) ◽  
pp. 281-293 ◽  
Author(s):  
Laura M. Engfors ◽  
Linda Jeffery ◽  
Gilles E. Gignac ◽  
Romina Palermo
2017 ◽  
Vol 26 (3) ◽  
pp. 218-224 ◽  
Author(s):  
Gillian Rhodes

Face adaptation generates striking face aftereffects, but is this adaptation useful? The answer appears to be yes, with several lines of evidence suggesting that it contributes to our face-recognition ability. Adaptation to face identity is reduced in a variety of clinical populations with impaired face recognition. In addition, individual differences in face adaptation are linked to face-recognition ability in typical adults. People who adapt more readily to new faces are better at recognizing faces. This link between adaptation and recognition holds for both identity and expression recognition. Adaptation updates face norms, which represent the typical or average properties of the faces we experience. By using these norms to code how faces differ from average, the visual system can make explicit the distinctive information that we need to recognize faces. Thus, adaptive norm-based coding may help us to discriminate and recognize faces despite their similarity as visual patterns.


2015 ◽  
Vol 2 (6) ◽  
pp. 140343 ◽  
Author(s):  
Punit Shah ◽  
Anne Gaule ◽  
Sophie Sowden ◽  
Geoffrey Bird ◽  
Richard Cook

Self-report plays a key role in the identification of developmental prosopagnosia (DP), providing complementary evidence to computer-based tests of face recognition ability, aiding interpretation of scores. However, the lack of standardized self-report instruments has contributed to heterogeneous reporting standards for self-report evidence in DP research. The lack of standardization prevents comparison across samples and limits investigation of the relationship between objective tests of face processing and self-report measures. To address these issues, this paper introduces the PI20; a 20-item self-report measure for quantifying prosopagnosic traits. The new instrument successfully distinguishes suspected prosopagnosics from typically developed adults. Strong correlations were also observed between PI20 scores and performance on objective tests of familiar and unfamiliar face recognition ability, confirming that people have the necessary insight into their own face recognition ability required by a self-report instrument. Importantly, PI20 scores did not correlate with recognition of non-face objects, indicating that the instrument measures face recognition, and not a general perceptual impairment. These results suggest that the PI20 can play a valuable role in identifying DP. A freely available self-report instrument will permit more effective description of self-report diagnostic evidence, thereby facilitating greater comparison of prosopagnosic samples, and more reliable classification.


Author(s):  
Michael Jeanne Childs ◽  
Alex Jones ◽  
Peter Thwaites ◽  
Sunčica Zdravković ◽  
Craig Thorley ◽  
...  

2020 ◽  
Author(s):  
Ashok Jansari ◽  
E. Green ◽  
Francesco Innocenti ◽  
Diego Nardi ◽  
Elena Belanova ◽  
...  

Unfamiliar face identification ability varies widely in the population. Those at the extreme top and bottom ends of the continuum have been labelled super-recognisers and prosopagnosics, respectively. Here we describe the development of two new tests - the Goldsmiths Unfamiliar Face Memory Test (GUFMT) and the Before They Were Adult Test (BTWA), that have been designed to measure different aspects of face identity ability across the spectrum. The GUFMT is a test of face memory, the BTWA a test of simultaneous adult-to-child face matching. Their designs draw on theories suggesting face identification is achieved by the recognition of facial features, the consistency across time of configurations between those features, and holistic processing of faces as a Gestalt. In four phases, participants (n = 16737), recruited using different methods, allowed evaluations to drive GUFMT development, the creation of likely population norms, as well as correlations with established face recognition tests. Recommendations for criteria for classification of super-recognition ability are also made.


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