Partitioning natural face image variability emphasises within-identity over between-identity representation for understanding accurate recognition

Normative face recognition ability test scores vary across online participant pools

Online participant recruitment is a cornerstone of modern psychology research. While this offers clear benefits for studying individual differences in cognitive abilities, test performance can vary across lab-based and web-based settings. Here we assess the stability of normative test scores across popular online recruitment platforms and in-person testing, for three standard measures of face identity processing ability: the GFMT2, CFMT+ , and MFMT. Participants recruited via Amazon Mechanical Turk (MTurk) scored approximately 10 percentage points lower in all tests compared to those recruited through Prolific and university students tested in the lab. Applying stricter exclusion criteria based on attention checks resulted in notably higher exclusion rates for the MTurk group (~ 62%) compared to the Prolific group (~ 22%), yet even after exclusion, some test scores remained lower for MTurk participants. Given that the GFMT2 subtests were developed using MTurk participants, we provide updated normative scores for all subtests (GFMT2-Short, GFMT2-Low, GFMT2-High) and further recommendations for their use. We also confirm the robust psychometric properties of the GFMT2-Short and GFMT2-High, demonstrating strong test-retest reliability, convergent validity with other established tests, and high diagnostic value in identifying super-recognisers. The GFMT2 subtests are freely available for use in both online and in-person research via www.gfmt2.org .

Semantic Content in Face Representation: Essential for Proficient Recognition of Unfamiliar Faces by Good Recognizers

Face recognition is adapted to achieve goals of social interactions, which rely on further processing of the semantic information of faces, beyond visual computations. Here, we explored the semantic content of face representation apart from visual component, and tested their relations to face recognition performance. Specifically, we propose that enhanced visual or semantic coding could underlie the advantage of familiar over unfamiliar faces recognition, as well as the superior recognition of skilled face recognizers. We asked participants to freely describe familiar/unfamiliar faces using words or phrases, and converted these descriptions into semantic vectors. Face semantics were transformed into quantifiable face vectors by aggregating these word/phrase vectors. We also extracted visual features from a deep convolutional neural network and obtained the visual representation of familiar/unfamiliar faces. Semantic and visual representations were used to predict perceptual representation generated from a behavior rating task separately in different groups (bad/good face recognizers in familiar-face/unfamiliar-face conditions). Comparisons revealed that although long-term memory facilitated visual feature extraction for familiar faces compared to unfamiliar faces, good recognizers compensated for this disparity by incorporating more semantic information for unfamiliar faces, a strategy not observed in bad recognizers. This study highlights the significance of semantics in recognizing unfamiliar faces.

The neuropsychological evaluation of face identity recognition

Facial identity recognition (FIR) is arguably the ultimate form of recognition for the adult human brain. Even if the term prosopagnosia is reserved for exceptionally rare brain-damaged cases with a category-specific abrupt loss of FIR at adulthood, subjective and objective impairments or difficulties of FIR are common in the neuropsychological population. Here we provide a critical overview of the evaluation of FIR both for clinicians and researchers in neuropsychology. FIR impairments occur following many causes that should be identified objectively by both general and specific, behavioral and neural examinations. We refute the commonly used dissociation between perceptual and memory deficits/tests for FIR, since even a task involving the discrimination of unfamiliar face images presented side-by-side relies on cortical memories of faces in the right-lateralized ventral occipito-temporal cortex. Another frequently encountered confusion is between specific deficits of the FIR function and a more general impairment of semantic memory (of people), the latter being most often encountered following anterior temporal lobe damage. Many computerized tests aimed at evaluating FIR have appeared over the last two decades, as reviewed here. However, despite undeniable strengths, they often suffer from ecological limitations, difficulties of instruction, as well as a lack of consideration for processing speed and qualitative information. Taking into account these issues, a recently developed behavioral test with natural images manipulating face familiarity, stimulus inversion, and correct response times as a key variable appears promising. The measurement of electroencephalographic (EEG) activity in the frequency domain from fast periodic visual stimulation also appears as a particularly promising tool to complete and enhance the neuropsychological assessment of FIR.

Multiple images captured from a single encounter do not promote face learning

Viewing multiple images of a newly encountered face improves recognition of that identity in new instances. Studies examining face learning have presented high-variability (HV) images that incorporate changes that occur from moment-to-moment (e.g., head orientation and expression) and over time (e.g., lighting, hairstyle, and health). We examined whether low-variability (LV) images (i.e., images that incorporate only moment-to-moment changes) also promote generalisation of learning such that novel instances are recognised. Participants viewed a single image, six LV images, or six HV images of a target identity before being asked to recognise novel images of that identity in a face matching task (training stimuli remained visible) or a memory task (training stimuli were removed). In Experiment 1 (n = 71), participants indicated which image(s) in 8-image arrays belonged to the target identity. In Experiment 2 (n = 73), participants indicated whether sequentially presented images belonged to the target identity. Relative to the single-image condition, sensitivity to identity improved and response biases were less conservative in the HV condition; we found no evidence of generalisation of learning in the LV condition regardless of testing protocol. Our findings suggest that day-to-day variability in appearance plays an essential role in acquiring expertise with a novel face.

Unfamiliar face matching ability predicts the slope of face learning

We provide the first examination of individual differences in the efficiency of face learning. Investigating individual differences in face learning can illuminate potential mechanisms and provide greater understanding of why certain individuals might be more efficient face learners. Participants completed two unfamiliar face matching tasks and a learning task in which learning was assessed after viewing 1, 3, 6, and 9 images of to-be-learned identities. Individual differences in the slope of face learning (i.e., increases in sensitivity to identity) were predicted by the ability to discriminate between matched (same-identity) vs. mismatched (different-identity) pairs of wholly unfamiliar faces. A Dual Process Signal Detection model showed that three parameters increased with learning: Familiarity (an unconscious type of memory that varies in strength), recollection-old (conscious recognition of a learned identity), and recollection-new (conscious/confident rejection of novel identities). Good (vs. poor) matchers had higher Recollection-Old scores throughout learning and showed a steeper increase in Recollection-New. We conclude that good matchers are better able to capitalize on exposure to within-person variability in appearance, an effect that is attributable to their conscious memory for both learned and novel faces. These results have applied implications and will inform contemporary and traditional models of face identification.

Stable individual differences in unfamiliar face identification: Evidence from simultaneous and sequential matching tasks

Matching identity in images of unfamiliar faces is difficult: Images of the same person can look different and images of different people can look similar. Recent studies have capitalized on individual differences in the ability to distinguish match (same ID) vs. mismatch (different IDs) face pairs to inform models of face recognition. We addressed two significant gaps in the literature by examining the stability of individual differences in both sensitivity to identity and response bias. In Study 1, 210 participants completed a battery of four tasks in each of two sessions separated by one week. Tasks varied in protocol (same/different, lineup, sorting) and stimulus characteristics (low vs. high within-person variability in appearance). In Study 2, 148 participants completed a battery of three tasks in a single session. Stimuli were presented simultaneously on some trials and sequentially on others, introducing short-term memory demands. Principal components analysis revealed two components that were stable across time and tasks: sensitivity to identity and bias. Analyses of response times suggest that individual differences in bias reflect decision-making processes. We discuss the implications of our findings in applied settings and for models of face recognition.