First impressions from faces in dynamic approach-avoidance contexts.

Theoretical understanding of first impressions from faces has been closely associated with the proposal that rapid approach-avoidance decisions are needed during social interactions. Nevertheless, experimental work has rarely examined first impressions of people who are actually moving-instead extrapolating from photographic images. In six experiments, we describe the relationship between social attributions (dominance and trustworthiness) and the motion and apparent intent of a perceived person. We first show strong correspondence between judgments of photos and avatars of the same people (Experiment 1). Avatars were rated as more dominant and trustworthy when walking toward the viewer than when stationary (Experiment 2). Furthermore, avatars approaching the viewer were rated as more dominant than those avoiding (walking past) the viewer, or remaining stationary (Experiment 3). Trustworthiness was increased by movement, but not affected by approaching/avoiding paths. Surprisingly, dominance ratings increased both when avatars were approaching and being approached (Experiments 4-6), independently of agency. However, diverging movement (moving backward) reduced dominance ratings-again independently of agency (Experiment 6). These results demonstrate the close link between dominance judgments and approach and show the updatable nature of first impressions-their formation depended on the immediate dynamic context in a more subtle manner than previously suggested. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

How neural representations of newly learnt faces change over time: Event-related brain potential evidence for overnight consolidation.

Previous experiments have shown that a brief encounter with a previously unfamiliar person leads to the establishment of new facial representations, which can be activated by completely novel pictures of the newly learnt face. The present study examined how stable such novel neural representations are over time, and, specifically, how they become consolidated within the first 24 h after learning. Using event-related brain potentials (ERPs) in a between-participants design, we demonstrate that clear face familiarity effects in the occipito-temporal N250 are evident immediately after learning. These effects then undergo change, with a nearly complete absence of familiarity-related ERP differences 4 h after the initial encounter. Critically, 24 h after learning, the original familiarity effect re-emerges. These findings suggest that the neural correlates of novel face representations are not stable over time but change during the first day after learning. The resulting pattern of change is consistent with a process of consolidation.

Provoked overt recognition in acquired prosopagnosia using multiple different images of famous faces.

Provoked overt recognition refers to the fact that patients with acquired prosopagnosia can sometimes recognize faces when presented in arrays of individuals from the same category (e.g., actors or politicians). We ask whether a prosopagnosic patient might experience recognition when presented with multiple different images of the same face simultaneously. Over two sessions, patient Herschel, a 66-year-old British man with acquired prosopagnosia, viewed face images individually or in arrays. On several occasions he failed to recognize single photos of an individual but successfully identified that person when the same photos were presented together. For example, Herschel failed to recognize any individual images of King Charles or Paul McCartney but recognised both in arrays of the same photos. Like reports based on category membership, overt recognition was transient and inconsistent. These findings are discussed in terms of models of covert recognition, alongside more recent research on within-person variability for face perception.

Queues, crowds, and angry mobs: Face identification under distraction in a virtual airport.

In visual environments, selective attention must be employed to focus on task-relevant stimuli. A key question here concerns the extent to which other stimuli within the visual field influence target processing. In this study, we ask whether face identity matching is subject to similar effects from irrelevant stimuli in the visual field, specifically task-irrelevant people. Although most previous studies rely on highly controlled face and body stimuli presented in isolation, here we use a more realistic environment. Participants take the role of passport officers and must match a person's face to their photo-ID, while other people appear in the background, waiting to be processed. Presenting an interactive virtual environment on screen (Experiments 1 and 2) or in immersive VR (Experiment 3), we generally found no evidence for distraction from background people on face-matching accuracy. However, when immersed in VR, an angry crowd in the background delayed matching speed while not affecting accuracy. We discuss the theoretical implications of these results and their potential importance in practical settings.

Personal familiarity of faces, animals, objects, and scenes: Distinct perceptual and overlapping conceptual representations.

While face, object, and scene recognition are often studied at a basic categorization level (e.g. "a face", "a car", "a kitchen"), we frequently recognise individual items of these categories as unique entities (e.g. "my mother", "my car", "my kitchen"). This recognition of individual identity is essential to appropriate behaviour in our world. However, relatively little is known about how we recognise individually familiar visual stimuli. Using event-related brain potentials, the present study examined whether and to what extent the underlying neural representations of personally familiar items are similar or different across different categories. In three experiments, we examined the recognition of personally highly familiar faces, animals, indoor scenes, and objects. We observed relatively distinct familiarity effects in an early time window (200-400 ms), with a clearly right-lateralized occipito-temporal scalp distribution for human faces and more bilateral and posterior distributions for other stimulus categories, presumably reflecting access to at least partly discrete visual long-term representations. In contrast, we found clearly overlapping familiarity effects in a later time window (starting 400 to 500 ms after stimulus onset), again with a mainly right occipito-temporal scalp distribution, for all stimulus categories. These later effects appear to reflect the sustained activation of conceptual properties relevant to any potential interaction. We conclude that familiarity for items from the various visual stimulus categories tested here is represented differently at the perceptual level, while relatively overlapping conceptual mechanisms allow for the preparation of impending potential interaction with the environment.

A narrow band of image dimensions is critical for face recognition.

A key challenge in human and computer face recognition is to differentiate information that is diagnostic for identity from other sources of image variation. Here, we used a combined computational and behavioural approach to reveal critical image dimensions for face recognition. Behavioural data were collected using a sorting and matching task with unfamiliar faces and a recognition task with familiar faces. Principal components analysis was used to reveal the dimensions across which the shape and texture of faces in these tasks varied. We then asked which image dimensions were able to predict behavioural performance across these tasks. We found that the ability to predict behavioural responses in the unfamiliar face tasks increased when the early PCA dimensions (i.e. those accounting for most variance) of shape and texture were removed from the analysis. Image similarity also predicted the output of a computer model of face recognition, but again only when the early image dimensions were removed from the analysis. Finally, we found that recognition of familiar faces increased when the early image dimensions were removed, decreased when intermediate dimensions were removed, but then returned to baseline recognition when only later dimensions were removed. Together, these findings suggest that early image dimensions reflect ambient changes, such as changes in viewpoint or lighting, that do not contribute to face recognition. However, there is a narrow band of image dimensions for shape and texture that are critical for the recognition of identity in humans and computer models of face recognition.

The neural dynamics of familiarity-dependent face identity representation.

Recognizing a face as belonging to a given identity is essential in our everyday life. Clearly, the correct identification of a face is only possible for familiar people, but 'familiarity' covers a wide range-from people we see every day to those we barely know. Although several studies have shown that the processing of familiar and unfamiliar faces is substantially different, little is known about how the degree of familiarity affects the neural dynamics of face identity processing. Here, we report the results of a multivariate EEG analysis, examining the representational dynamics of face identity across several familiarity levels. Participants viewed highly variable face images of 20 identities, including the participants' own face, personally familiar (PF), celebrity and unfamiliar faces. Linear discriminant classifiers were trained and tested on EEG patterns to discriminate pairs of identities of the same familiarity level. Time-resolved classification revealed that the neural representations of identity discrimination emerge around 100 ms post-stimulus onset, relatively independently of familiarity level. In contrast, identity decoding between 200 and 400 ms is determined to a large extent by familiarity: it can be recovered with higher accuracy and for a longer duration in the case of more familiar faces. In addition, we found no increased discriminability for faces of PF persons compared to those of highly familiar celebrities. One's own face benefits from processing advantages only in a relatively late time-window. Our findings provide new insights into how the brain represents face identity with various degrees of familiarity and show that the degree of familiarity modulates the available identity-specific information at a relatively early time window.

A neural measure of the degree of face familiarity.

Recognizing a face as familiar is essential in our everyday life. However, 'familiarity' covers a wide range - from people we see every day to those we barely know. Although face recognition is studied extensively, little is known about how the degree of familiarity affects neural face processing, despite the critical social importance of this dimension. Here we report the results of a multivariate cross-classification EEG experiment, where we study the temporal representational dynamics of the degree of familiarity. Participants viewed highly variable face images of 20 identities. Importantly, we measured face familiarity using subjective familiarity ratings in addition to testing explicit knowledge and reaction times in a face matching task. A machine learning algorithm, trained to discriminate familiar and unfamiliar faces from a separate study, was used to predict the degree of face familiarity from the pattern of the EEG data. We found that the neural representations of the degree of familiarity emerge between 400 - 600 msec post-stimulus onset for famous persons. The correlation between decoding performance and behavioral familiarity was more reliable, occurred earlier and lasted longer when personally familiar and viewers' own faces were included in the analysis. Our findings provide new insights into how the brain represents faces with various degrees of familiarity and show that the degree of familiarity can be decoded reliably from the EEG at a relatively late time window. These results support the idea that representations of familiar faces form part of a general neural signature of the familiarity component of recognition memory processes.

Face learning via brief real-world social interactions induces changes in face-selective brain areas and hippocampus.

Making new acquaintances requires learning to recognise previously unfamiliar faces. In the current study, we investigated this process by staging real-world social interactions between actors and the participants. Participants completed a face-matching behavioural task in which they matched photographs of the actors (whom they had yet to meet), or faces similar to the actors (henceforth called foils). Participants were then scanned using functional magnetic resonance imaging (fMRI) while viewing photographs of actors and foils. Immediately after exiting the scanner, participants met the actors for the first time and interacted with them for 10 min. On subsequent days, participants completed a second behavioural experiment and then a second fMRI scan. Prior to each session, actors again interacted with the participants for 10 min. Behavioural results showed that social interactions improved performance accuracy when matching actor photographs, but not foil photographs. The fMRI analysis revealed a difference in the neural response to actor photographs and foil photographs across all regions of interest (ROIs) only after social interactions had occurred. Our results demonstrate that short social interactions were sufficient to learn and discriminate previously unfamiliar individuals. Moreover, these learning effects were present in brain areas involved in face processing and memory.

Familiarity is familiarity is familiarity: Event-related brain potentials reveal qualitatively similar representations of personally familiar and famous faces.

Humans excel in familiar face recognition, but often find it hard to make identity judgements of unfamiliar faces. Understanding of the factors underlying the substantial benefits of familiarity is at present limited, but the effect is sometimes qualified by the way in which a face is known-for example, personal acquaintance sometimes gives rise to stronger familiarity effects than exposure through the media. Given the different quality of personal versus media knowledge, for example in one's emotional response or level of interaction, some have suggested qualitative differences between representations of people known personally or from media exposure. Alternatively, observed differences could reflect quantitative differences in the level of familiarity. We present 4 experiments investigating potential contributory influences to face familiarity effects in which observers view pictures showing their friends, favorite celebrities, celebrities they dislike, celebrities about whom they have expressed no opinion, and their own face. Using event-related potential indices with high temporal resolution and multiple highly varied everyday ambient images as a strong test of face recognition, we focus on the N250 and the later Sustained Familiarity Effect (SFE). All known faces show qualitatively similar responses relative to unfamiliar faces. Regardless of personal- or media-based familiarity, N250 reflects robust visual representations, successively refined over increasing exposure, while SFE appears to reflect the amount of identity-specific semantic information known about a person. These modulations of visual and semantic representations are consistent with face recognition models which emphasize the degree of familiarity but do not distinguish between different types of familiarity. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Detecting a viewer's familiarity with a face: Evidence from event-related brain potentials and classifier analyses.

Human observers recognize the faces of people they know efficiently and without apparent effort. Consequently, recognizing a familiar face is often assumed to be an automatic process beyond voluntary control. However, there are circumstances in which a person might seek to hide their recognition of a particular face. The present study therefore used event-related potentials (ERPs) and a classifier based on logistic regression to determine if it is possible to detect whether a viewer is familiar with a particular face, regardless of whether the participant is willing to acknowledge it or not. In three experiments, participants were presented with highly variable "ambient" images of personally familiar and unfamiliar faces, while performing an incidental butterfly detection task (Experiment 1), an explicit familiarity judgment task (Experiment 2), and a concealed familiarity task in which they were asked to deny familiarity with one truly known facial identity while acknowledging familiarity with a second known identity (Experiment 3). In all three experiments, we observed substantially more negative ERP amplitudes at occipito-temporal electrodes for familiar relative to unfamiliar faces starting approximately 200 ms after stimulus onset. Both the earlier N250 familiarity effect, reflecting visual recognition of a known face, and the later sustained familiarity effect, reflecting the integration of visual with additional identity-specific information, were similar across experiments and thus independent of task demands. These results were further supported by the classifier analysis. We conclude that ERP correlates of familiar face recognition are largely independent of voluntary control and discuss potential applications in forensic settings.

GFMT2: A psychometric measure of face matching ability.

We present an expanded version of a widely used measure of unfamiliar face matching ability, the Glasgow Face Matching Test (GFMT). The GFMT2 is created using the same source database as the original test but makes five key improvements. First, the test items include variation in head angle, pose, expression and subject-to-camera distance, making the new test more difficult and more representative of challenges in everyday face identification tasks. Second, short and long versions of the test each contain two forms that are calibrated to be of equal difficulty, allowing repeat tests to be performed to examine effects of training interventions. Third, the short-form tests contain no repeating face identities, thereby removing any confounding effects of familiarity that may have been present in the original test. Fourth, separate short versions are created to target exceptionally high performing or exceptionally low performing individuals using established psychometric principles. Fifth, all tests are implemented in an executable program, allowing them to be administered automatically. All tests are available free for scientific use via www.gfmt2.org .

Avatars with faces of real people: A construction method for scientific experiments in virtual reality.

Experimental psychology research typically employs methods that greatly simplify the real-world conditions within which cognition occurs. This approach has been successful for isolating cognitive processes, but cannot adequately capture how perception operates in complex environments. In turn, real-world environments rarely afford the access and control required for rigorous scientific experimentation. In recent years, technology has advanced to provide a solution to these problems, through the development of affordable high-capability virtual reality (VR) equipment. The application of VR is now increasing rapidly in psychology, but the realism of its avatars, and the extent to which they visually represent real people, is captured poorly in current VR experiments. Here, we demonstrate a user-friendly method for creating photo-realistic avatars of real people and provide a series of studies to demonstrate their psychological characteristics. We show that avatar faces of familiar people are recognised with high accuracy (Study 1), replicate the familiarity advantage typically observed in real-world face matching (Study 2), and show that these avatars produce a similarity-space that corresponds closely with real photographs of the same faces (Study 3). These studies open the way to conducting psychological experiments on visual perception and social cognition with increased realism in VR.

Understanding the document bias in face matching.

Matching unfamiliar faces is a well-studied task, apparently capturing important everyday decisions such as ID checks. In typical laboratory studies, participants make same/different judgements to pairs of faces, presented in isolation and without context. However, it has recently become clear that matching faces embedded in documents (e.g., passports and driving licences) induces a bias, resulting in elevated levels of "same person" responses. While practically important, it remains unclear whether this bias arises due to expectations induced by the ID cards or interference between textual information and faces. Here, we observe the same bias when faces are embedded in blank (i.e., non-authoritative) cards carrying basic personal information, but not when the same information is presented alongside a face without the card (Experiments 1 and 2). Cards bearing unreadable text (blurred or in an unfamiliar alphabet) do not induce the bias, but those bearing arbitrary (non-biographical) words do (Experiments 3 and 4). The results suggest a complex basis for the effect, relying on multiple factors which happen to converge in photo-ID.

Trait evaluations of faces and voices: Comparing within- and between-person variability.

Human faces and voices are rich sources of information that can vary in many different ways. Most of the literature on face/voice perception has focused on understanding how people look and sound different to each other (between-person variability). However, recent studies highlight the ways in which the same person can look and sound different on different occasions (within-person variability). Across three experiments, we examined how within- and between-person variability relate to one another for social trait impressions by collecting trait ratings attributed to multiple face images and voice recordings of the same people. We find that within-person variability in social trait evaluations is at least as great as between-person variability. Using different stimulus sets across experiments, trait impressions of voices are consistently more variable within people than between people-a pattern that is only evident occasionally when judging faces. Our findings highlight the importance of understanding within-person variability, showing how judgments of the same person can vary widely on different encounters and quantify how this pattern differs for voice and face perception. The work consequently has implications for theoretical models proposing that voices can be considered "auditory faces" and imposes limitations to the "kernel of truth" hypothesis of trait evaluations. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Multiple-image arrays in face matching tasks with and without memory.

Previous research has shown that exposure to within-person variability facilitates face learning. A different body of work has examined potential benefits of providing multiple images in face matching tasks. Viewers are asked to judge whether a target face matches a single face image (as when checking photo-ID) or multiple face images of the same person. The evidence here is less clear, with some studies finding a small multiple-image benefit, and others finding no advantage. In four experiments, we address this discrepancy in the benefits of multiple images from learning and matching studies. We show that multiple-image arrays only facilitate face matching when arrays precede targets. Unlike simultaneous face matching tasks, sequential matching and learning tasks involve memory and require abstraction of a stable representation of the face from the array, for subsequent comparison with a target. Our results show that benefits from multiple-image arrays occur only when this abstraction is required, and not when array and target images are available at once. These studies reconcile apparent differences between face learning and face matching and provide a theoretical framework for the study of within-person variability in face perception.

Insights from computational models of face recognition: A reply to Blauch, Behrmann and Plaut.

We agree with Blauch, Behrmann, and Plaut (2020) on a number of points, and are reassured that their data bear out our previous findings. We discuss differences in modelling style, and the usefulness of different types of model for supporting psychological understanding. We emphasise the role that within-person variability plays in recognising familiar faces and clarify the range over which it is idiosyncratic. The combination of image analysis with top-down support to cohere different images of the same person seems to be an important characteristic of successful models.

The Role of Face and Voice Cues in Predicting the Outcome of Student Representative Elections.

First impressions formed after seeing someone's face or hearing their voice can affect many social decisions, including voting in political elections. Despite the many studies investigating the independent contribution of face and voice cues to electoral success, their integration is still not well understood. Here, we examine a novel electoral context, student representative ballots, allowing us to test the generalizability of previous studies. We also examine the independent contributions of visual, auditory, and audiovisual information to social judgments of the candidates, and their relationship to election outcomes. Results showed that perceived trustworthiness was the only trait significantly related to election success. These findings contrast with previous reports on the importance of perceived competence using audio or visual cues only in the context of national political elections. The present study highlights the role of real-world context and emphasizes the importance of using ecologically valid stimulus presentation in understanding real-life social judgment.

Facial identity across the lifespan.

We can recognise people that we know across their lifespan. We see family members age, and we can recognise celebrities across long careers. How is this possible, despite the very large facial changes that occur as people get older? Here we analyse the statistical properties of faces as they age, sampling photos of the same people from their 20s to their 70s. Across a number of simulations, we observe that individuals' faces retain some idiosyncratic physical properties across the adult lifespan that can be used to support moderate levels of age-independent recognition. However, we found that models based exclusively on image-similarity only achieved limited success in recognising faces across age. In contrast, more robust recognition was achieved with the introduction of a minimal top-down familiarisation procedure. Such models can incorporate the within-person variability associated with a particular individual to show a surprisingly high level of generalisation, even across the lifespan. The analysis of this variability reveals a powerful statistical tool for understanding recognition, and demonstrates how visual representations may support operations typically thought to require conceptual properties.