Comparing the sensitivity of face matching assessments to detect face perception impairments

Not so fast! Response times in the computerized Benton Face Recognition Test may not reflect face recognition ability

“…shown that face RT and accuracy load on separate, largely independent factors (Wilhelm et al, 2010;Hildebrandt et al, 2013;Meyer et al, 2019), with face accuracy more consistently explained unique variance in FFMT accuracy, though RTs explained < 5% of additional variance in FFMT. There have also been a limited number of studies that have shown RT differences between DPs and controls on face tasks with appropriately high accuracy (e.g., face detection, Garrido et al, 2008), though these effect sizes have often been much smaller than with accuracy-based tasks (e.g., Mishra et al, 2021). Thus, an important area of future research will be to determine whether face RT tasks can reflect meaningful aspects of individual differences in face and object recognition abilities.…”

“…Further, in nearly all cases in the domain of face and object recognition, task RTs have not been validated as a measure of ability distinct from accuracy. The goal of the current study was to examine the computerized Benton Facial Recognition Test (BFRT-c), a version of a widely used diagnostic face matching task that emphasizes both speed and accuracy (e.g., Mishra et al, 2021;Murray et al, 2021), and to determine if RT on this task explains variance independent from accuracy in validated measures of face recognition ability. We also sought to determine if BFRT-c RT differentiates between controls and developmental prosopagnosics (DPs), individuals with lifelong face recognition difficulties (Duchaine & Nakayama, 2004).…”

“…They recently published normative BFRT-c accuracy and RT 1 data (Rossion & Michel, 2018). A recent study found that accuracy on this speeded version of the BFRT-c predicted DP group membership better than other face matching tasks (Mishra et al, 2021). Further, Murray and colleagues (2021) recently found that a computerized version of the BFRT with revised, updated stimuli (BFRT-r) robustly differentiated DPs and controls.…”

“…Beyond Arizpe et al (2018), no studies to our knowledge have demonstrated that RT explains unique variance in face recognition ability above and beyond accuracy. While the BFRT-c is a highly sensitive face matching task (Mishra et al, 2021; as is the BFRT-r with updated stimuli, Murray et al, 2021) that was designed to produce RT data useful for characterizing individual differences in face recognition, BFRT-c RTs have yet to be validated using standard measures of face recognition. To address this issue, we administered the BFRT-c and two face recognition measures, a Famous Face Memory Test (FFMT, Mishra et al, 2019) and the Cambridge Face Memory Test (CFMT; Duchaine & Nakayama, 2006), often thought of as the gold standard of individual differences in face recognition (Richler et al, 2015).…”

Two face masks are better than one: congruency effects in face matching

“…Similarly, some experimental manipulations such as task duration (Alenezi & Bindemann, 2013 ; Alenezi et al, 2015 ), face images variability (Ritchie & Burton, 2017 ; Ritchie et al, 2021 ), image degradation (Bindemann et al, 2013 ) and feature-by-feature training (Megreya, 2018 ; Megreya & Bindemann, 2018 ; Towler et al, 2021 ) have different effects on identity match and identity mismatch trials. In addition, developmental prosopagnosics—people with lifelong face identification deficits (Duchaine & Nakayama, 2006 )—tend to have specific problems in match but not in mismatch trials (Berger et al, 2022 ; Fisher et al, 2017 ; Mishra et al, 2021 ; White et al, 2017 ). Altogether, these results highlight the importance of considering the dissociable effects that different experimental manipulations might have on match and mismatch trials.…”