No abstract

Numerous neurological, developmental, and psychiatric conditions demonstrate impaired face recognition abilities, which can be socially debilitating. These impairments could be caused by either deficient face perceptual processes, such as reduced ability to integrate face parts into a whole, or deficient face memory processes, such as reduced ability to associate a face with semantic information. Research and clinical practice have focused more on developing face memory assessments, while it currently remains unclear which face perception assessments best captures perceptual deficits. A validated face perception measure could not only help with diagnosing the causes of face recognition deficits but could also help determine the most appropriate treatment. Here, we compare several available face perception assessments to identify those that can best assess perception deficits in developmental prosopagnosics. Thirty prosopagnosics and thirty age-matched neurotypical controls completed a battery of four face perception assessments, namely, computerized Benton Face Recognition Test, Cambridge Face Perception Test, University of Southern California Face Perception Test, and Telling Faces Together Test. They were also evaluated on two face recognition/ memory measures- Cambridge face memory test and famous faces memory test. We used logistic regression for the perception tests to predict prosopagnosic vs. control group membership and used multiple linear regressions to predict continuous objective and subjective measures of face recognition memory. Our results show that the Benton face test was the most reliable (α = 0.74), sensitive (AUC= 0.83), and predictive assessment of prosopagnosia diagnosis and face memory performance across the groups. The Cambridge face perception test also performed adequately well in terms of test sensitivity (AUC=0.80) and predicted face memory performance across the groups. Further, we found that face lighting change trials better predicted DP group membership and face recognition abilities than viewpoint-change trials. Together, these results have direct clinical application in assessing populations with face processing difficulties.

Previous face matching studies provide evidence that matching same identity faces (match trials) and discriminating different face identities (non-match trials) rely on distinct processes. For example, instructional studies geared towards improving face matching in applied settings have often found selective improvements in match or non-match trials only. Additionally, a small study found that developmental prosopagnosics (DPs) have specific deficits in making match but not non-match judgments. In the current study, we sought to replicate this finding in DPs and examine how individual differences across DPs and controls in match vs. non-match performance relate to featural vs. holistic processing abilities. 43 DPs and 27 controls matched face images shown from similar front views or with varied lighting or viewpoint. Participants also performed tasks measuring featural (eyes/mouth) and holistic processing (part-whole task). We found that DPs showed worse overall matching performance than controls and that their relative match vs. non-match deficit depended on image variation condition, indicating that DPs do not consistently show match- or non-match-specific deficits. When examining the association between holistic and featural processing abilities and match vs. non-match trials in the entire group of DPs and controls, we found a very clear dissociation: Match trials significantly correlated with eye processing ability (r=.48) but not holistic processing (r=.11), whereas non-match trials significantly correlated with holistic processing (r=.32) but not eye processing (r=.03). This suggests that matching same identity faces relies more on eye processing while discriminating different faces relies more on holistic processing.