Age of smile: a cross-cultural replication report of Ganel and Goodale (2018)

Perception and memory-based representations of facial emotions: Associations with personality functioning, affective states and recognition abilities

Personality traits and affective states are associated with biases in facial emotion perception. However, the precise personality impairments and affective states that underlie these biases remain largely unknown. To investigate how relevant factors influence facial emotion perception and recollection, Experiment 1 employed an image reconstruction approach in which community-dwelling adults (N = 89) rated the similarity of pairs of facial expressions, including those recalled from memory. Subsequently, perception- and memory-based expression representations derived from such ratings were assessed across participants and related to measures of personality impairment, state affect, and visual recognition abilities. Impairment in self-direction and level of positive affect accounted for the largest components of individual variability in perception and memory representations, respectively. Additionally, individual differences in these representations were impacted by face recognition ability. In Experiment 2, adult participants (N = 81) rated facial image reconstructions derived in Experiment 1, revealing that individual variability was associated with specific visual face properties, such as expressiveness, representation accuracy, and positivity/negativity. These findings highlight and clarify the influence of personality, affective state, and recognition abilities on individual differences in the perception and recollection of facial expressions.

The Medusa effect: a registered replication report of Will, Merritt, Jenkins and Kingstone (2021)

Will et al.'s (2021 Proc. Natl Acad. Sci. USA 118, e2106640118 (doi:10.1073/pnas.2106640118)) found the Medusa effect, which refers to the tendency that people evaluate a 'person in picture' more mindful than a 'person in picture of a picture'. The present study tried to directly replicate the Experiments 2 and 5 of Will et al.'s (2021), to examine the reliability, validity and generalization of the Medusa effect, as well as its effect on prosocial behaviour. We used the same stimuli and methodology as the original research, but recruited participants in Japan with a larger sample size (N = 1387 in total) as a registered report. In our two replication experiments, we again found that pictures with lower levels of abstraction (L1) were perceived to convey more mind and lead to higher levels of prosocial behaviour, successfully replicating the original findings. The results of the present study suggested the high reproducibility and generalizability of the Medusa effect. Pre-registered Stage 1 protocol: https://osf.io/xj46z (date of in-principle acceptance: 9 February 2023).

Biases in human perception of facial age are present and more exaggerated in current AI technology

Our estimates of a person's age from their facial appearance suffer from several well-known biases and inaccuracies. Typically, for example, we tend to overestimate the age of smiling faces compared to those with a neutral expression, and the accuracy of our estimates decreases for older faces. The growing interest in age estimation using artificial intelligence (AI) technology raises the question of how AI compares to human performance and whether it suffers from the same biases. Here, we compared human performance with the performance of a large sample of the most prominent AI technology available today. The results showed that AI is even less accurate and more biased than human observers when judging a person's age-even though the overall pattern of errors and biases is similar. Thus, AI overestimated the age of smiling faces even more than human observers did. In addition, AI showed a sharper decrease in accuracy for faces of older adults compared to faces of younger age groups, for smiling compared to neutral faces, and for female compared to male faces. These results suggest that our estimates of age from faces are largely driven by particular visual cues, rather than high-level preconceptions. Moreover, the pattern of errors and biases we observed could provide some insights for the design of more effective AI technology for age estimation from faces.

Smiling makes you look older, even when you wear a mask: the effect of face masks on age perception

The widespread use of face masks in the era of the Covid-19 pandemic has promoted research on their effect on the perception and recognition of faces. There is growing evidence that masks hinder the recognition of identity and expression, as well as the interpretation of speech from facial cues. It is less clear whether and in what manner masks affect the perception of age from facial cues. Recent research has emphasized the role of the upper region of the face, a part not covered by a mask, in the evaluation of age. For example, smile-related wrinkles in the region of the eyes make smiling faces appear older than neutral faces of the same individuals (the aging effect of smiling, AES). In two experiments, we tested the effect of face masks on age evaluations of neutral and smiling faces in a range of different age groups from 20 to 80 years. The results showed that smiling faces were perceived as older than neutral faces even when individuals were wearing a face mask—and there was no effect of masks on bias in age evaluations. Additional analyses showed reduced accuracy in age evaluations for smiling compared to neutral faces and for masked compared to unmasked faces. The results converge on previous studies emphasizing the importance of the upper region of the face in evaluations of age.

Robustness of the aging effect of smiling against vertical facial orientation

Background: Previous studies have shown that the association between smiling and youth is a misconception; smiling faces have been estimated to be older than neutral faces. Previous studies have indicated that this aging effect of smiling (AES) is due to eye wrinkles caused by the facial action of smiling. However, whether holistic processing for facial expressions is involved in AES has not been investigated. The present study aimed to clarify these issues. Methods: Participants were recruited to participate in an online experiment that had a 3 (facial expression: smiling/neutral/surprised) × 2 (facial orientation: upright/inverted) mixed design. Participants were presented with an upright or inverted face for each expression (neutral, smiling, and surprised) and were asked to estimate the individual's age. Results: In total, 104 participants were included in the analysis. The results show that smiling faces were estimated to be older than neutral faces, whereas there was no significant difference between upright and inverted faces. Conclusions: Our findings suggest that AES is not dependent on holistic processing.

Robustness of the aging effect of smiling against vertical facial orientation

Background: Previous studies have shown that the association between smiling and youth is a misconception; smiling faces have been estimated to be older than neutral faces. Previous studies have indicated that this aging effect of smiling (AES) is due to eye wrinkles caused by the facial action of smiling. However, whether holistic processing for facial expressions is involved in AES has not been investigated. The present study aimed to clarify these issues. Methods: Participants were recruited to participate in an online experiment that had a 3 (facial expression: smiling/neutral/surprised) × 2 (facial orientation: upright/inverted) mixed design. Participants were presented with an upright or inverted face for each expression (neutral, smiling, and surprised) and were asked to estimate the individual's age. Results: In total, 104 participants were included in the analysis. The results show that smiling faces were estimated to be older than neutral faces, whereas there was no significant difference between upright and inverted faces. Conclusions: Our findings suggest that AES is not dependent on holistic processing.

Robustness of the aging effect of smiling against vertical facial orientation

Background: Previous studies have shown that the association between smiling and youth is a misconception; smiling faces have been estimated to be older than neutral faces. Previous studies have indicated that this aging effect of smiling (AES) is due to eye wrinkles caused by the facial action of smiling. However, whether holistic processing for facial expressions is involved in AES has not been investigated. The present study aimed to clarify these issues. Methods: Participants were recruited to participate in an online experiment that had a 3 (facial expression: smiling/neutral/surprised) × 2 (facial orientation: upright/inverted) mixed design. Participants were presented with an upright or inverted face for each expression (neutral, smiling, and surprised) and were asked to estimate the individual's age. Results: In total, 104 participants were included in the analysis. The results show that smiling faces were estimated to be older than neutral faces, whereas there was no significant difference between upright and inverted faces. Conclusions: Our findings suggest that direct age estimation is not dependent on holistic processing.

The effect of smiling on the perceived age of male and female faces across the lifespan

Previous research has shown an unintuitive effect of facial expression on perceived age: smiling faces are perceived as older compared to neutral faces of the same people. The aging effect of smiling (AES), which is thought to result from the presence of smile-related wrinkles around the eyes, contradicts the common belief that smiling faces should be perceived as younger, not older. Previous research, however, has focused on faces of young adults, where the absence of inherent, age-related wrinkles and other age signs is offset by the weight of the smile-related wrinkles. In a series of experiments, we tested whether the AES extends to male and female faces in older age groups. We replicated the AES in young adults (20–39) and showed that it disappeared in older adults (60–79) of both genders. For photos of middle-aged adults (40–59), however, AES was found only for male, but not for female faces, who showed fewer and less prominent smile-related wrinkles. The results suggest that a person’s apparent age is perceived in a holistic manner in which age-related cues in the region of the eyes are weighted against age cues in other regions of the face.

The Recognition of Cross-Cultural Emotional Faces Is Affected by Intensity and Ethnicity in a Japanese Sample

Human faces convey a range of emotions and psychobiological signals that support social interactions. Multiple factors potentially mediate the facial expressions of emotions across cultures. To further determine the mechanisms underlying human emotion recognition in a complex and ecological environment, we hypothesized that both behavioral and neurophysiological measures would be influenced by stimuli ethnicity (Japanese, Caucasian) in the context of ambiguous emotional expressions (mid-happy, angry). We assessed the neurophysiological and behavioral responses of neurotypical Japanese adults (N = 27, 13 males) involved in a facial expression recognition task. Results uncover an interaction between universal and culturally-driven mechanisms. No differences in behavioral responses are found between male and female participants, male and female faces, and neutral Japanese versus Caucasian faces. However, Caucasian ambiguous emotional expressions which require more energy-consuming processing, as highlighted by neurophysiological results of the Arousal Index, were judged more accurately than Japanese ones. Additionally, a differential Frontal Asymmetry Index in neuronal activation, the signature of an approach versus avoidance response, is found in male participants according to the gender and emotional valence of the stimuli.