Artificial faces are harder to remember

Different facets of age perception in people with developmental prosopagnosia and "super-recognisers"

The interplay between facial age and facial identity is evident from several scenarios experienced in daily life, such as when recognising a face several decades after the last exposure. However, the link between age and identity processing, and how age perception abilities might diverge in individuals with different face processing abilities, has scarcely been considered. Furthermore, the approach used to test age perception ability may also influence outcome, but the effect of different paradigms on performance is not yet known. Across three studies, we compare super-recognisers (SRs), people with developmental prosopagnosia (DPs), and a group of neurotypical controls, on three age perception paradigms. There were no differences on the numeric age estimation task (i.e. providing precise age estimates for a series of faces; Study 1), and numeric age estimation task with added noise-distortion to stimuli (Study 2). However, SRs were more accurate when instructed to classify ambient faces as either over- or under- the age of 18 compared to both DPs and controls (Study 3). Thus, there may be nuanced differences in age processing which can be tapped into using separate paradigms; however, given that the difference is only with SRs it remains unclear to what extent these are linked to facial identity processing.

Racial Bias in Pediatric Pain Perception

Racial disparities in pediatric pain care are prevalent across a variety of health care settings, and likely contribute to broader disparities in health, morbidity, and mortality. The present research expands on prior work demonstrating potential perceptual contributions to pain care disparities in adults and tests whether racial bias in pain perception extends to child targets. We examined the perception and hypothetical treatment of pain in Black and White boys (experiment 1), Black and White boys and girls (experiment 2), Black and White boys and adult men (experiment 3), and Black, White, Asian, and Latinx boys (experiment 4). Across this work, pain was less readily perceived on Black (vs White) boys' faces-though this bias was not observed within girls. Moreover, this perceptual bias was comparable in magnitude to the same bias measured with adult targets and consistently predicted bias in hypothetical treatment. Notably, bias was not limited to Black targets-pain on Hispanic/Latinx boys' faces was also relatively underperceived. Taken together, these results offer strong evidence for racial bias in pediatric pain perception. PERSPECTIVE: This article demonstrates perceptual contributions to racial bias in pediatric pain recognition. Participants consistently saw pain less readily on Black boys' faces, compared with White boys, and this perceptual bias consistently predicted race-based gaps in treatment. This work reveals a novel factor that may support pediatric pain care disparities.

The role of the differential outcomes procedure and schizotypy in the recognition of dynamic facial expressions of emotions

Emotional facial expression recognition is a key ability for adequate social functioning. The current study aims to test if the differential outcomes procedure (DOP) may improve the recognition of dynamic facial expressions of emotions and to further explore whether schizotypal personality traits may have any effect on performance. 183 undergraduate students completed a task where a face morphed from a neutral expression to one of the six basic emotions at full intensity over 10 s. Participants had to press spacebar as soon as they identified the emotion and choose which had appeared. In the first block, participants received no outcomes. In the second block, a group received specific outcomes associated to each emotion (DOP group), while another group received non-differential outcomes after correctly responding (NOP group). Employing generalized linear models (GLMs) and Bayesian inference we estimated different parameters to answer our research goals. Schizotypal personality traits did not seem to affect dynamic emotional facial expression recognition. Participants of the DOP group were less likely to respond incorrectly to faces showing Fear and Surprise at fewer intensity levels. This may suggest that the DOP could lead to better identification of the main features that differentiate each facial expression of emotion.

The role of facial skin tone and texture in the perception of age

Age and gender perception from looking at people's faces, without any cultural or conventional cues, is primarily based on two independent components: a) the shape or facial structure, and b) surface reflectance (skin tone and texture, STT). This study examined the relative contribution of facial STT to the perception of age. A total of 204 subjects participated in four experiments presenting artificial 3D realistic faces of different age versions under two key experimental conditions: with and without STT. Two experiments involved a discrimination-age task, and other two involved a direct age-estimation task. The faces for the last experiment were generated from the photographs of real people. The results were quite consistent throughout the experiments. Data suggest that the contribution of the STT information leads to roughly 25-33 % of accuracy in age perception. Interestingly, a differential pattern emerges in relation to facial age: the relative contribution of skin information increases sharply with advancing age, to the point that age judgments of the older faces (60 years old) without STT information fall to the chance level. This pattern suggests that facial skin tone and texture are the main sources of information for estimating the age of people past their maturity as those are the principal visual signs of aging beyond the anatomical changes of facial structure.

The effects of social presence on cooperative trust with algorithms

Algorithms support many processes in modern society. Research using trust games frequently reports that people are less inclined to cooperate when believed to play against an algorithm. Trust is, however, malleable by contextual factors and social presence can increase the willingness to collaborate. We investigated whether situating cooperation with an algorithm in the presence of another person increases cooperative trust. Three groups of participants played a trust game against a pre-programmed algorithm in an online webhosted experiment. The first group was told they played against another person who was present online. The second group was told they played against an algorithm. The third group was told they played against an algorithm while another person was present online. More cooperative responses were observed in the first group compared to the second group. A difference in cooperation that replicates previous findings. In addition, cooperative trust dropped more over the course of the trust game when participants interacted with an algorithm in the absence another person compared to the other two groups. This latter finding suggests that social presence can mitigate distrust in interacting with an algorithm. We discuss the cognitive mechanisms that can mediate this effect.

Investigating the role of the fusiform face area and occipital face area using multifocal transcranial direct current stimulation

The functional role of the occipital face area (OFA) and the fusiform face area (FFA) in face recognition is inconclusive to date. While some research has shown that the OFA and FFA are involved in early (i.e., featural processing) and late (i.e., holistic processing) stages of face recognition respectively, other research suggests that both regions are involved in both early and late stages of face recognition. Thus, the current study aims to further examine the role of the OFA and the FFA using multifocal transcranial direct current stimulation (tDCS). In Experiment 1, we used computer-generated faces. Thirty-five participants completed whole face and facial features (i.e., eyes, nose, mouth) recognition tasks after OFA and FFA stimulation in a within-subject design. No difference was found in recognition performance after either OFA or FFA stimulation. In Experiment 2 with 60 participants, we used real faces, provided stimulation following a between-subjects design and included a sham control group. Results showed that FFA stimulation led to enhanced efficiency of facial features recognition. Additionally, no effect of OFA stimulation was found for either facial feature or whole face recognition. These results suggest the involvement of FFA in the recognition of facial features.

Trustworthiness judgments without the halo effect: A data-driven computational modeling approach

Trustworthy-looking faces are also perceived as more attractive, but are there other meaningful cues that contribute to perceived trustworthiness? Using data-driven models, we identify these cues after removing attractiveness cues. In Experiment 1, we show that both judgments of trustworthiness and attractiveness of faces manipulated by a model of perceived trustworthiness change in the same direction. To control for the effect of attractiveness, we build two new models of perceived trustworthiness: a subtraction model, which forces the perceived attractiveness and trustworthiness to be negatively correlated (Experiment 2), and an orthogonal model, which reduces their correlation (Experiment 3). In both experiments, faces manipulated to appear more trustworthy were indeed perceived to be more trustworthy, but not more attractive. Importantly, in both experiments, these faces were also perceived as more approachable and with more positive expressions, as indicated by both judgments and machine learning algorithms. The current studies show that the visual cues used for trustworthiness and attractiveness judgments can be separated, and that apparent approachability and facial emotion are driving trustworthiness judgments and possibly general valence evaluation.

What is the prevalence of developmental prosopagnosia? An empirical assessment of different diagnostic cutoffs

The prevalence of developmental prosopagnosia (DP), lifelong face recognition deficits, is widely reported to be 2-2.5%. However, DP has been diagnosed in different ways across studies, resulting in differing prevalence rates. In the current investigation, we estimated the range of DP prevalence by administering well-validated objective and subjective face recognition measures to an unselected web-based sample of 3116 18-55 year-olds and applying DP diagnostic cutoffs from the last 14 years. We found estimated prevalence rates ranged from .64-5.42% when using a z-score approach and .13-2.95% when using a percentile approach, with the most commonly used cutoffs by researchers having a prevalence rate of .93% (z-score, .45% when using percentiles). We next used multiple cluster analyses to examine whether there was a natural grouping of poorer face recognizers but failed to find consistent grouping beyond those with generally above versus below average face recognition. Lastly, we investigated whether DP studies with more relaxed diagnostic cutoffs were associated with better performance on the Cambridge Face Perception Test. In a sample of 43 studies, there was a weak nonsignificant association between greater diagnostic strictness and better DP face perception accuracy (Kendall's tau-b correlation, τb =.18 z-score; τb = .11 percentiles). Together, these results suggest that researchers have used more conservative DP diagnostic cutoffs than the widely reported 2-2.5% prevalence. We discuss the strengths and weaknesses of using more inclusive cutoffs, such as identifying mild and major forms of DP based on DSM-5.

The rise and fall of face recognition awareness across the life span

A core component of metacognition is cognitive awareness, insight into how one's cognitive abilities compare with others. Previous studies of cognitive awareness have focused on basic aspects of perception, memory, and learning. Further, studies of the awareness of one's social-cognitive abilities have been limited to examining awareness of others' thinking (i.e., theory of mind). The current study characterizes awareness of one's own social-cognitive abilities, specifically face recognition awareness, and examines its change across the life span. We used a large, web-based sample (N = 4,143) with a broad age range (ages 10-70), administering well-validated measures of objective (Cambridge Face Memory Test 3) and self-reported (Cambridge Face Memory Questionnaire) face recognition. We found a robust overall association between objective and self-reported face recognition (r = .42 in females, r = .36 in males). While we found that face recognition ability peaked in the early- to mid-30s, face recognition awareness peaked in the early- to mid-20s, was relatively stable throughout the 20s-40s, and declined in the 50s-60s. Relative subjective versus objective face recognition bias measures demonstrated that 10- to 18- and 51- to 70-year-olds overestimated their self-reported face recognition abilities in comparison with 19- to 50-year-olds. Finally, compared with males, females had greater face recognition awareness and a bias to relatively underestimate their face recognition abilities. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Sex perception from facial structure: Categorization with and without skin texture and color

Sex identification of faces without any cultural or conventional sex cue is primarily based on two independent components: a) shape or facial structure, and b) surface reflectance (skin texture and color). The present work studied the relative contribution of each component by means of two experiments based on 3D face models created with different degrees of masculinity-femininity within a sex continuum. The first experiment utilized totally artificial faces created ex novo by computer. The second employed face models created from photographs of real people. The results of both experiments were consistent. As expected, when both components were present in a face, sex was correctly classified in almost all the cases. More interestingly, the contribution of the "pure" facial structure to the sex perception (with no surface reflectance) was about 80%, whereas 20% of the total information was provided by the surface reflectance. Furthermore, examination of the psychometric curves suggests that the information provided by surface reflectance contributes to a categorical perception of facial sex, since when it is removed the sex is perceived in a more continuous / less categorical way. On the other hand, our stimuli presented a certain "male" bias, repeatedly found in the literature on facial sex perception.

Corneal reflections and skin contrast yield better memory of human and virtual faces

Virtual faces have been found to be rated less human-like and remembered worse than photographic images of humans. What it is in virtual faces that yields reduced memory has so far remained unclear. The current study investigated face memory in the context of virtual agent faces and human faces, real and manipulated, considering two factors of predicted influence, i.e., corneal reflections and skin contrast. Corneal reflections referred to the bright points in each eye that occur when the ambient light reflects from the surface of the cornea. Skin contrast referred to the degree to which skin surface is rough versus smooth. We conducted two memory experiments, one with high-quality virtual agent faces (Experiment 1) and the other with the photographs of human faces that were manipulated (Experiment 2). Experiment 1 showed better memory for virtual faces with increased corneal reflections and skin contrast (rougher rather than smoother skin). Experiment 2 replicated these findings, showing that removing the corneal reflections and smoothening the skin reduced memory recognition of manipulated faces, with a stronger effect exerted by the eyes than the skin. This study highlights specific features of the eyes and skin that can help explain memory discrepancies between real and virtual faces and in turn elucidates the factors that play a role in the cognitive processing of faces.

What is So Special About Contemporary CG Faces? Semiotics of MetaHumans

This paper analyses the features of the 2021 software for the creation of ultrarealistic digital characters "MetaHuman Creator" and reflects on the causes of such perceived effect of realism to understand if the faces produced with such software represent an actual novelty from an academic standpoint. Such realism is first of all defined as the result of semio-cognitive processes which trigger interpretative habits specifically related to faces. These habits are then related to the main properties of any realistic face: being face-looking, face-meaning and face-acting. These properties, in turn, are put in relation with our interactions with faces in terms of face detection, face recognition, face reading and face agency. Within this theoretical framework, we relate the characteristics of these artificial faces with such interpretative habits. To do so, we first of all make an examination of the technological features behind both the software and the digital faces it produces. This analysis highlights four main points of interest: the mathematical accuracy, the scanned database, the high level of details and the transformative capacities of these artificial faces. We then relate these characteristics with the cultural and cognitive aspects involved in recognizing and granting meaning to faces. This reveals how metahuman faces differs from previous artificial faces in terms of indexicality, intersubjectivity, informativity and irreducibility. But it also reveals some limits of such effect of reality in terms of intentionality and historical context. This examination consequently brings us to conclude that metahuman faces are qualitatively different from previous artificial faces and, in the light of their potentials and limits, to highlight four main lines of future research based on our findings.

A systematic survey of face stimuli used in psychological research 2000-2020

For decades, psychology has relied on highly standardized images to understand how people respond to faces. Many of these stimuli are rigorously generated and supported by excellent normative data; as such, they have played an important role in the development of face science. However, there is now clear evidence that testing with ambient images (i.e., naturalistic images "in the wild") and including expressions that are spontaneous can lead to new and important insights. To precisely quantify the extent to which our current knowledge base has relied on standardized and posed stimuli, we systematically surveyed the face stimuli used in 12 key journals in this field across 2000-2020 (N = 3374 articles). Although a small number of posed expression databases continue to dominate the literature, the use of spontaneous expressions seems to be increasing. However, there has been no increase in the use of ambient or dynamic stimuli over time. The vast majority of articles have used highly standardized and nonmoving pictures of faces. An emerging trend is that virtual faces are being used as stand-ins for human faces in research. Overall, the results of the present survey highlight that there has been a significant imbalance in favor of standardized face stimuli. We argue that psychology would benefit from a more balanced approach because ambient and spontaneous stimuli have much to offer. We advocate a cognitive ethological approach that involves studying face processing in natural settings as well as the lab, incorporating more stimuli from "the wild".

Facial structure and perception of sexual orientation: Research with face models based on photographs of real people

Some evidence suggests that lay persons are able to perceive sexual orientation from face stimuli above the chance level. A morphometric study of 390 heterosexual and homosexual Canadian people of both sexes reported that facial structure differed depending on the sexual orientation. Gay and heterosexual men differed on three metrics as the most robust multivariate predictors, and lesbian and heterosexual women differed on four metrics. A later study verified the perceptual validity of these multivariate predictors using artificial three-dimensional face models created by manipulating the key parameters. Nevertheless, there is evidence of important processing differences between the perception of real faces and the perception of artificial computer-generated faces. The present study which composed of two experiments tested the robustness of the previous findings and extended the research by experimentally manipulating the facial features in face models created from photographs of real people. Participants of the Experiment 1 achieved an overall accuracy (0.67) significantly above the chance level (0.50) in a binary hetero/homosexual judgement task, with some important differences between male and female judgements. On the other hand, results of the Experiment 2 showed that participants rated the apparent sexual orientation of series of face models created from natural photographs as a continuous linear function of the multivariate predictors. Theoretical implications are discussed.

Robot faces elicit responses intermediate to human faces and objects at face-sensitive ERP components

Face recognition is supported by selective neural mechanisms that are sensitive to various aspects of facial appearance. These include event-related potential (ERP) components like the P100 and the N170 which exhibit different patterns of selectivity for various aspects of facial appearance. Examining the boundary between faces and non-faces using these responses is one way to develop a more robust understanding of the representation of faces in extrastriate cortex and determine what critical properties an image must possess to be considered face-like. Robot faces are a particularly interesting stimulus class to examine because they can differ markedly from human faces in terms of shape, surface properties, and the configuration of facial features, but are also interpreted as social agents in a range of settings. In the current study, we thus chose to investigate how ERP responses to robot faces may differ from the response to human faces and non-face objects. In two experiments, we examined how the P100 and N170 responded to human faces, robot faces, and non-face objects (clocks). In Experiment 1, we found that robot faces elicit intermediate responses from face-sensitive components relative to non-face objects (clocks) and both real human faces and artificial human faces (computer-generated faces and dolls). These results suggest that while human-like inanimate faces (CG faces and dolls) are processed much like real faces, robot faces are dissimilar enough to human faces to be processed differently. In Experiment 2 we found that the face inversion effect was only partly evident in robot faces. We conclude that robot faces are an intermediate stimulus class that offers insight into the perceptual and cognitive factors that affect how social agents are identified and categorized.

Broadening the stimulus set: Introducing the American Multiracial Faces Database

Face-based perceptions form the basis for how people behave towards each other and, hence, are central to understanding human interaction. Studying face perception requires a large and diverse set of stimuli in order to make ecologically valid, generalizable conclusions. To date, there are no publicly available databases with a substantial number of Multiracial or racially ambiguous faces. Our systematic review of the literature on Multiracial person perception documented that published studies have relied on computer-generated faces (84% of stimuli), Black-White faces (74%), and male faces (63%). We sought to address these issues, and to broaden the diversity of available face stimuli, by creating the American Multiracial Faces Database (AMFD). The AMFD is a novel collection of 110 faces with mixed-race heritage and accompanying ratings of those faces by naive observers that are freely available to academic researchers. The faces (smiling and neutral expression poses) were rated on attractiveness, emotional expression, racial ambiguity, masculinity, racial group membership(s), gender group membership(s), warmth, competence, dominance, and trustworthiness. The large majority of the AMFD faces are racially ambiguous and can pass into at least two different racial categories. These faces will be useful to researchers seeking to study Multiracial person perception as well as those looking for racially ambiguous faces in order to study categorization processes in general. Consequently, the AMFD will be useful to a broad group of researchers who are studying face perception.

Sensitivity to face animacy and inversion in childhood: Evidence from EEG data

Adults exhibit relative behavioral difficulties in processing inanimate, artificial faces compared to real human faces, with implications for using artificial faces in research and designing artificial social agents. However, the developmental trajectory of inanimate face perception is unknown. To address this gap, we used electroencephalography to investigate inanimate faces processing in cross-sectional groups of 5-10-year-old children and adults. A face inversion manipulation was used to test whether face animacy processing relies on expert face processing strategies. Groups of 5-7-year-olds (N = 18), 8-10-year-olds (N = 18), and adults (N = 16) watched pictures of real or doll faces presented in an upright or inverted orientation. Analyses of event-related potentials revealed larger N170 amplitudes in response to doll faces, irrespective of age group or face orientation. Thus, the N170 is sensitive to face animacy by 5-7 years of age, but such sensitivity may not reflect high-level, expert face processing. Multivariate pattern analyses of the EEG signal additionally assessed whether animacy information could be reliably extracted during face processing. Face orientation, but not face animacy, could be reliably decoded from occipitotemporal channels in children and adults. Face animacy could be decoded from whole scalp channels in adults, but not children. Together, these results suggest that 5-10-year-old children exhibit some sensitivity to face animacy over occipitotemporal regions that is comparable to adults.

Unsupervised inference approach to facial attractiveness

The perception of facial attractiveness is a complex phenomenon which depends on how the observer perceives not only individual facial features, but also their mutual influence and interplay. In the machine learning community, this problem is typically tackled as a problem of regression of the subject-averaged rating assigned to natural faces. However, it has been conjectured that this approach does not capture the complexity of the phenomenon. It has recently been shown that different human subjects can navigate the face-space and "sculpt" their preferred modification of a reference facial portrait. Here we present an unsupervised inference study of the set of sculpted facial vectors in such experiments. We first infer minimal, interpretable and accurate probabilistic models (through Maximum Entropy and artificial neural networks) of the preferred facial variations, that encode the inter-subject variance. The application of such generative models to the supervised classification of the gender of the subject that sculpted the face reveals that it may be predicted with astonishingly high accuracy. We observe that the classification accuracy improves by increasing the order of the non-linear effective interaction. This suggests that the cognitive mechanisms related to facial discrimination in the brain do not involve the positions of single facial landmarks only, but mainly the mutual influence of couples, and even triplets and quadruplets of landmarks. Furthermore, the high prediction accuracy of the subjects' gender suggests that much relevant information regarding the subjects may influence (and be elicited from) their facial preference criteria, in agreement with the multiple motive theory of attractiveness proposed in previous works.

Diagnosing developmental prosopagnosia: repeat assessment using the Cambridge Face Memory Test

Developmental prosopagnosia (DP) is a cognitive condition characterized by a relatively selective impairment in face recognition. Currently, people are screened for DP via a single attempt at objective face-processing tests, usually all presented on the same day. However, several variables probably influence performance on these tests irrespective of actual ability, and the influence of repeat administration is also unknown. Here, we assess, for the first known time, the test-retest reliability of the Cambridge Face Memory Test (CFMT)-the leading task used worldwide to diagnose DP. This value was found to fall just below psychometric standards, and single-case analyses revealed further inconsistencies in performance that were not driven by testing location (online or in-person), nor the time-lapse between attempts. Later administration of an alternative version of the CFMT (the CFMT-Aus) was also found to be valuable in confirming borderline cases. Finally, we found that performance on the first 48 trials of the CFMT was equally as sensitive as the full 72-item score, suggesting that the instrument may be shortened for testing efficiency. We consider the implications of these findings for existing diagnostic protocols, concluding that two independent tasks of unfamiliar face memory should be completed on separate days.

Modulation of face- and emotion-selective ERPs by the three most common types of face image manipulations

In neuroscientific studies, the naturalness of face presentation differs; a third of published studies makes use of close-up full coloured faces, a third uses close-up grey-scaled faces and another third employs cutout grey-scaled faces. Whether and how these methodological choices affect emotion-sensitive components of the event-related brain potentials (ERPs) is yet unclear. Therefore, this pre-registered study examined ERP modulations to close-up full-coloured and grey-scaled faces as well as cutout fearful and neutral facial expressions, while attention was directed to no-face oddballs. Results revealed no interaction of face naturalness and emotion for any ERP component, but showed, however, large main effects for both factors. Specifically, fearful faces and decreasing face naturalness elicited substantially enlarged N170 and early posterior negativity amplitudes and lower face naturalness also resulted in a larger P1.This pattern reversed for the LPP, showing linear increases in LPP amplitudes with increasing naturalness. We observed no interaction of emotion with face naturalness, which suggests that face naturalness and emotion are decoded in parallel at these early stages. Researchers interested in strong modulations of early components should make use of cutout grey-scaled faces, while those interested in a pronounced late positivity should use close-up coloured faces.

An Assessment of Computer-Generated Stimuli for Use in Studies of Body Size Estimation and Bias

Inaccurate body size judgments are associated with body image disturbances, a clinical feature of many eating disorders. Accordingly, body-related stimuli have become increasingly important in the study of estimation inaccuracies and body image disturbances. Technological advancements in the last decade have led to an increased use of computer-generated (CG) body stimuli in body image research. However, recent face perception research has suggested that CG face stimuli are not recognized as readily and may not fully tap facial processing mechanisms. The current study assessed the effectiveness of using CG stimuli in an established body size estimation task (the “bodyline” task). Specifically, we examined whether employing CG body stimuli alters body size judgments and associated estimation biases. One hundred and six 17- to 25-year-old females completed the CG bodyline task, which involved estimating the size of full-length CG body stimuli along a visual analogue scale. Our results show that perception of body size for CG stimuli was non-linear. Participants struggled to discriminate between extreme bodies sizes and overestimated the size change between near to average bodies. Furthermore, one of our measured size estimation biases was larger for CG stimuli. Our collective findings suggest using caution when employing CG stimuli in experimental research on body perception.

Perceiving Animacy in Own-and Other-Species Faces

Though artificial faces of various kinds are rapidly becoming more and more life-like due to advances in graphics technology (Suwajanakorn et al., 2015; Booth et al., 2017), observers can typically distinguish real faces from artificial faces. In general, face recognition is tuned to experience such that expert-level processing is most evident for faces that we encounter frequently in our visual world, but the extent to which face animacy perception is also tuned to in-group vs. out-group categories remains an open question. In the current study, we chose to examine how the perception of animacy in human faces and dog faces was affected by face inversion and the duration of face images presented to adult observers. We hypothesized that the impact of these manipulations may differ as a function of species category, indicating that face animacy perception is tuned for in-group faces. Briefly, we found evidence of such a differential impact, suggesting either that distinct mechanisms are used to evaluate the "life" in a face for in-group and out-group faces, or that the efficiency of a common mechanism varies substantially as a function of visual expertise.

An event-related potential comparison of facial expression processing between cartoon and real faces

Faces play important roles in the social lives of humans. Besides real faces, people also encounter numerous cartoon faces in daily life which convey basic emotional states through facial expressions. Using event-related potentials (ERPs), we conducted a facial expression recognition experiment with 17 university students to compare the processing of cartoon faces with that of real faces. This study used face type (real vs. cartoon), emotion valence (happy vs. angry) and participant gender (male vs. female) as independent variables. Reaction time, recognition accuracy, and the amplitudes and latencies of emotion processing-related ERP components such as N170, VPP (vertex positive potential), and LPP (late positive potential) were used as dependent variables. The ERP results revealed that cartoon faces caused larger N170 and VPP amplitudes as well as a briefer N170 latency than did real faces; that real faces induced larger LPP amplitudes than did cartoon faces. In addition, the results showed a significant difference in the brain regions as reflected in a right hemispheric advantage. The behavioral results showed that the reaction times for happy faces were shorter than those for angry faces; that females showed a higher accuracy than did males; and that males showed a higher recognition accuracy for angry faces than happy faces. Due to the sample size, these results may suggestively but not rigorously demonstrate differences in facial expression recognition and neurological processing between cartoon faces and real faces. Cartoon faces showed a higher processing intensity and speed than real faces during the early processing stage. However, more attentional resources were allocated for real faces during the late processing stage.

Those Virtual People all Look the Same to me: Computer-Rendered Faces Elicit a Higher False Alarm Rate Than Real Human Faces in a Recognition Memory Task

Virtual as compared with real human characters can elicit a sense of uneasiness in human observers, characterized by lack of familiarity and even feelings of eeriness (the “uncanny valley” hypothesis). Here we test the possibility that this alleged lack of familiarity is literal in the sense that people have lesser perceptual expertise in processing virtual as compared with real human faces. Sixty-four participants took part in a recognition memory study in which they first learned a set of faces and were then asked to recognize them in a testing session. We used real and virtual (computer-rendered) versions of the same faces, presented in either upright or inverted orientation. Real and virtual faces were matched for low-level visual features such as global luminosity and spatial frequency contents. Our results demonstrated a higher response bias toward responding “seen before” for virtual as compared with real faces, which was further explained by a higher false alarm rate for the former. This finding resembles a similar effect for recognizing human faces from other than one's own ethnic groups (the “other race effect”). Virtual faces received clearly higher subjective eeriness ratings than real faces. Our results did not provide evidence of poorer overall recognition memory or lesser inversion effect for virtual faces, however. The higher false alarm rate finding supports the notion that lesser perceptual expertise may contribute to the lack of subjective familiarity with virtual faces. We discuss alternative interpretations and provide suggestions for future research.

Gender Differences in Sexual Attraction and Moral Judgment: Research With Artificial Face Models

Sexual attraction in humans is influenced by cultural or moral factors, and some gender differences can emerge in this complex interaction. A previous study found that men dissociate sexual attraction from moral judgment more than women do. Two experiments consisting of giving attractiveness ratings to photos of real opposite-sex individuals showed that men, compared to women, were significantly less influenced by the moral valence of a description about the person shown in each photo. There is evidence of some processing differences between real and artificial computer-generated faces. The present study tests the robustness of González-Álvarez's findings and extends the research to an experimental design using artificial face models as stimuli. A sample of 88 young adults (61 females and 27 males, average age 19.32, SD = 2.38) rated the attractiveness of 80 3D artificial face models generated with the FaceGen Modeller 3.5 software. Each face model was paired with a "good" and a "bad" (from a moral point of view) sentence depicting a quality or activity of the person represented in the model (e.g., she/he is an altruistic nurse in Africa vs. she/he is a prominent drug dealer). Results were in line with the previous findings and showed that, with artificial faces as well, sexual attraction is less influenced by morality in men than in women. This gender difference is consistent with an evolutionary perspective on human sexuality.

About Face: Matching Unfamiliar Faces Across Rotations of View and Lighting

Matching the identities of unfamiliar faces is heavily influenced by variations in their images. Changes to viewpoint and lighting direction during face perception are commonplace across yaw and pitch axes and can result in dramatic image differences. We report two experiments that, for the first time, factorially investigate the combined effects of lighting and view angle on matching performance for unfamiliar faces. The use of three-dimensional head models allowed control of both lighting and viewpoint. We found viewpoint effects in the yaw axis with little to no effect of lighting. However, for rotations about the pitch axis, there were both viewpoint and lighting effects and these interacted where lighting effects were found only for front views and views from below. The pattern of effects was similar regardless of whether view variation occurred as a result of head (Experiment 1) or camera (Experiment 2) suggesting that face matching is not purely image based. Along with face inversion effects in Experiment 1, the results of this study suggest that face perception is based on shape and surface information and draws on implicit knowledge of upright faces and ecological (top) lighting conditions.

The Impact of Face Inversion on Animacy Categorization

Face animacy perception is categorical: Gradual changes in the real/artificial appearance of a face lead to nonlinear behavioral responses. Neural markers of face processing are also sensitive to face animacy, further suggesting that these are meaningful perceptual categories. Artificial faces also appear to be an “out-group” relative to real faces such that behavioral markers of expert-level processing are less evident with artificial faces than real ones. In the current study, we examined how categorical processing of real versus doll faces was impacted by the face inversion effect, which is one of the most robust markers of expert face processing. We examined how explicit categorization of faces drawn from a real/doll morph continuum was affected by face inversion (Experiment 1) and also how the response properties of the N170 were impacted by face animacy and inversion. We found that inversion does not change the position or steepness of the category boundary measured behaviorally. Further, neural markers of face processing are equally impacted by inversion regardless of whether they are elicited by real faces or doll faces. On balance, our results indicate that inversion has a limited impact on the categorical perception of face animacy.

Differential effects of face-realism and emotion on event-related brain potentials and their implications for the uncanny valley theory

Cartoon characters are omnipresent in popular media. While few studies have scientifically investigated their processing, in computer graphics, efforts are made to increase realism. Yet, close approximations of reality have been suggested to evoke sometimes a feeling of eeriness, the “uncanny valley” effect. Here, we used high-density electroencephalography to investigate brain responses to professionally stylized happy, angry, and neutral character faces. We employed six face-stylization levels varying from abstract to realistic and investigated the N170, early posterior negativity (EPN), and late positive potential (LPP) event-related components. The face-specific N170 showed a u-shaped modulation, with stronger reactions towards both most abstract and most realistic compared to medium-stylized faces. For abstract faces, N170 was generated more occipitally than for real faces, implying stronger reliance on structural processing. Although emotional faces elicited highest amplitudes on both N170 and EPN, on the N170 realism and expression interacted. Finally, LPP increased linearly with face realism, reflecting activity increase in visual and parietal cortex for more realistic faces. Results reveal differential effects of face stylization on distinct face processing stages and suggest a perceptual basis to the uncanny valley hypothesis. They are discussed in relation to face perception, media design, and computer graphics.

How Well Do Computer-Generated Faces Tap Face Expertise?

The use of computer-generated (CG) stimuli in face processing research is proliferating due to the ease with which faces can be generated, standardised and manipulated. However there has been surprisingly little research into whether CG faces are processed in the same way as photographs of real faces. The present study assessed how well CG faces tap face identity expertise by investigating whether two indicators of face expertise are reduced for CG faces when compared to face photographs. These indicators were accuracy for identification of own-race faces and the other-race effect (ORE)-the well-established finding that own-race faces are recognised more accurately than other-race faces. In Experiment 1 Caucasian and Asian participants completed a recognition memory task for own- and other-race real and CG faces. Overall accuracy for own-race faces was dramatically reduced for CG compared to real faces and the ORE was significantly and substantially attenuated for CG faces. Experiment 2 investigated perceptual discrimination for own- and other-race real and CG faces with Caucasian and Asian participants. Here again, accuracy for own-race faces was significantly reduced for CG compared to real faces. However the ORE was not affected by format. Together these results signal that CG faces of the type tested here do not fully tap face expertise. Technological advancement may, in the future, produce CG faces that are equivalent to real photographs. Until then caution is advised when interpreting results obtained using CG faces.