Children with Autism Spectrum Disorder scan own-race faces differently from other-race faces

Can group membership modulate the social abilities of autistic people? An intergroup bias in smile perception

Autistic adults struggle to reliably differentiate genuine and posed smiles. Intergroup bias is a promising factor that may modulate smile discrimination performance, which has been shown in neurotypical adults, and which could highlight ways to make social interactions easier. However, it is not clear whether this bias also exists in autistic people. Thus, the current study aimed to investigate this in autism using a minimal group paradigm. Seventy-five autistic and sixty-one non-autistic adults viewed videos of people making genuine or posed smiles and were informed (falsely) that some of the actors were from an in-group and others were from an out-group. The ability to identify smile authenticity of in-group and out-group members and group identification were assessed. Our results revealed that both groups seemed equally susceptible to ingroup favouritism, rating ingroup members as more genuine, but autistic adults also generally rated smiles as less genuine and were less likely to identify with ingroup members. Autistic adults showed reduced sensitivity to the different smile types but the absence of an intergroup bias in smile discrimination in both groups seems to indicate that membership can only modulate social judgements but not social abilities. These findings suggest a reconsideration of past findings that might have misrepresented the social judgements of autistic people through introducing an outgroup disadvantage, but also a need for tailored support for autistic social differences that emphasizes similarity and inclusion between diverse people.

Event-related potential correlates of implicit processing of own- and other-race faces in children

Human adults typically experience difficulties in recognizing and discriminating individual faces belonging to racial groups other than their own. The origin of this "other-race" effect is set in infancy, but the understanding of its developmental course is fragmented. We aimed to access the mechanisms of the other-race effect in childhood by unraveling the neural time course of own- and other-race face processing during a masked priming paradigm. White 6- and 7-year-old children (N = 19) categorized fully visible Asian (other-race) or White (own-race) target faces according to gender. Target faces were preceded by masked same-identity or different-identity prime faces, matching the target for race and gender. We showed an early priming effect on the N100 component, with larger amplitude to different-face pairs than to same-face pairs, and a later race effect on the N200 component, with larger amplitude to own-race face pairs than to other-race face pairs. Critically, race did not interact with priming at any processing stage (P100, N100, P200, N200, or P300). Our results suggest that race could have a temporally limited impact on face processing and that the implicit and unconscious identity processing of own- and other-race faces could be similar in 6- and 7-year-olds, depicting an immature other-race effect during childhood.

Discriminative Dictionary Learning for Autism Spectrum Disorder Identification

Autism Spectrum Disorder (ASD) is a group of lifelong neurodevelopmental disorders with complicated causes. A key symptom of ASD patients is their impaired interpersonal communication ability. Recent study shows that face scanning patterns of individuals with ASD are often different from those of typical developing (TD) ones. Such abnormality motivates us to study the feasibility of identifying ASD children based on their face scanning patterns with machine learning methods. In this paper, we consider using the bag-of-words (BoW) model to encode the face scanning patterns, and propose a novel dictionary learning method based on dual mode seeking for better BoW representation. Unlike k-means which is broadly used in conventional BoW models to learn dictionaries, the proposed method captures discriminative information by finding atoms which maximizes both the purity and coverage of belonging samples within one class. Compared to the rich literature of ASD studies from psychology and neural science, our work marks one of the relatively few attempts to directly identify high-functioning ASD children with machine learning methods. Experiments demonstrate the superior performance of our method with considerable gain over several baselines. Although the proposed work is yet too preliminary to directly replace existing autism diagnostic observation schedules in the clinical practice, it shed light on future applications of machine learning methods in early screening of ASD.

Atypical gaze patterns to facial feature areas in autism spectrum disorders reveal age and culture effects: A meta-analysis of eye-tracking studies

Children and adults with autism spectrum disorder (ASD) often present with atypical gaze patterns to others' faces, a finding substantiated throughout the literature. Yet, a quantification of atypical gaze patterns to different facial regions (e.g., eyes versus mouth) in ASD remains controversial. Also few study has investigated how age and culture impacted the pattern of gaze abnormalities in ASD. This research therefore conducted a meta-analysis of eye-tracking studies to evaluate age and culture effect on atypical gaze patterns of face processing in ASD. A total of 75 articles (91 studies) and 4209 individuals (ASD: 2027; controls: 2182) across all age ranges (i.e., childhood through to adulthood) from both Eastern and Western cultures were included in this meta-analysis. Individuals with ASD yielded shorter fixation durations to the eyes than individuals without ASD. Group differences in the time spent fixating on the eyes were not modulated by age, but affected by culture. Effect size in the eastern culture was larger than that in the western culture. In contrast, group differences on time spent looking at the mouth were not significant, but changed with age and modulated by culture. Relative to the neurotypical controls, Western individuals with ASD spent more time looking at the mouth from school age, whereas Eastern individuals with ASD did not gaze longer on mouth until adulthood. These results add to the body of evidence supporting atypical gaze behaviors to eyes in ASD and provide new insights into a potential mouth compensation strategy that develops with age in ASD. LAY SUMMARY: Individuals with autism spectrum disorder (ASD) often show atypical gaze patterns when looking at others' faces compared to neurotypical individuals. This paper examines the role of age and culture on pattern of gaze abnormalities in individuals with ASD. Results show that reduction of gaze on eyes in ASD is stable across all ages and cultures, while increase of gaze on mouth emerges as individuals with ASD get older. The findings provide a developmental insight to the gaze patterns on the autism spectrum across culture.

Accuracy comparison across face recognition algorithms: Where are we on measuring race bias?

Previous generations of face recognition algorithms differ in accuracy for images of different races (race bias). Here, we present the possible underlying factors (data-driven and scenario modeling) and methodological considerations for assessing race bias in algorithms. We discuss data-driven factors (e.g., image quality, image population statistics, and algorithm architecture), and scenario modeling factors that consider the role of the "user" of the algorithm (e.g., threshold decisions and demographic constraints). To illustrate how these issues apply, we present data from four face recognition algorithms (a previous-generation algorithm and three deep convolutional neural networks, DCNNs) for East Asian and Caucasian faces. First, dataset difficulty affected both overall recognition accuracy and race bias, such that race bias increased with item difficulty. Second, for all four algorithms, the degree of bias varied depending on the identification decision threshold. To achieve equal false accept rates (FARs), East Asian faces required higher identification thresholds than Caucasian faces, for all algorithms. Third, demographic constraints on the formulation of the distributions used in the test, impacted estimates of algorithm accuracy. We conclude that race bias needs to be measured for individual applications and we provide a checklist for measuring this bias in face recognition algorithms.

Does culture shape face perception in autism? Cross-cultural evidence of the own-race advantage from the UK and Japan

Autism spectrum disorders (ASD) are associated with face perception atypicalities, and atypical experience with faces has been proposed as an underlying explanation. Studying the own-race advantage (ORA) for face recognition can reveal the effect of experience on face perception in ASD, although the small number of studies in the area present mixed findings. This study probed the ORA in ASD by comparing two cultural groups simultaneously for the first time. Children with ASD in the UK (N = 16) and Japan (N = 26) were compared with age- and ability-matched typically developing (TD) children in the UK (N = 16) and Japan (N = 26). Participants completed a two-alternative forced-choice task, whereby they had to recognize a just seen face from a foil which was manipulated in one of four ways (IC: identity change; EE: easy eyes; HE: hard eyes; HM: hard mouth). Face stimuli were Asian and Caucasian, and thus the same stimuli were own and other race depending on the cultural group. The ASD groups in the UK and Japan did not show impaired face recognition abilities, or impairments with recognizing faces depending on manipulations to the eye region, and importantly they showed an ORA. There was considerable heterogeneity in the presence of the ORA in ASD and TD and also across cultures. Children in Japan had higher accuracy than children in the UK, and TD children in Japan did not show an ORA. This cross-cultural study challenges the view that atypical experiences with faces lead to a reduced/absent ORA in ASD.

What Can Eye Movements Tell Us about Subtle Cognitive Processing Differences in Autism?

Autism spectrum disorder (ASD) is neurodevelopmental condition principally characterised by impairments in social interaction and communication, and repetitive behaviours and interests. This article reviews the eye movement studies designed to investigate the underlying sampling or processing differences that might account for the principal characteristics of autism. Following a brief summary of a previous review chapter by one of the authors of the current paper, a detailed review of eye movement studies investigating various aspects of processing in autism over the last decade will be presented. The literature will be organised into sections covering different cognitive components, including language and social communication and interaction studies. The aim of the review will be to show how eye movement studies provide a very useful on-line processing measure, allowing us to account for observed differences in behavioural data (accuracy and reaction times). The subtle processing differences that eye movement data reveal in both language and social processing have the potential to impact in the everyday communication domain in autism.

[Clinical efficacy of interactive group sandplay versus individual sandplay in the treatment of preschool children with autism spectrum disorder]

OBJECTIVE

To study the clinical efficacy of interactive group sandplay versus individual sandplay in the treatment of preschool children with autism spectrum disorder (ASD).

METHODS

A total of 80 ASD children, aged 4-6 years, were enrolled and randomly divided into experimental and control groups, with 40 children in each group. The children in the experimental group joined group sandplay with normal children at a ratio of 1: 3, and those in the control group were treated with individual sandplay. The Aberrant Behavior Checklist (ABC) and Autism Treatment Evaluation Checklist (ATEC) were used to evaluate the treatment outcome after three months of intervention.

RESULTS

There were 33 children in the experimental group and 28 in the control group. After three months of intervention, the experimental group had significant reductions in the scores of irritability, social withdrawal, and stereotypic behavior and the total score of the ABC scale (P<0.05), and the control group had significant reductions in the scores of behavior and inappropriate speech and the total score of the ABC scale (P<0.05). Compared with the control group, the experimental group had significantly greater improvements in the score of social withdrawal and the total score of the ABC scale after three months of intervention (P<0.05). After three months of intervention, the experimental group had significant reductions in the scores of sociability, sensory and cognitive awareness, and physical/health behavior and the total score of the ATEC scale (P<0.05), and the control group had significant reductions in the scores of speech, sociability, and physical/health behavior and the total score of the ATEC scale (P<0.05). Compared with the control group, the experimental group had significantly greater improvements in the scores of speech, sociability, and sensory and cognitive awareness and the total score of the ATEC scale after intervention (P<0.01). Compared with the control group, the experimental group also had significantly greater improvements in eye contact and sand stereotyped arrangement (P<0.05).

CONCLUSIONS

Both interactive group sandplay and individual sandplay are effective in the treatment of ASD in preschool children. Interactive group sandplay is better than individual sandplay in the treatment of ASD, with significant improvements in sociability, emotion and stereotypic behavior.

Learning context and the other-race effect: Strategies for improving face recognition

People recognize faces of their own race more accurately than faces of other races-a phenomenon known as the "Other-Race Effect" (ORE). Previous studies show that training with multiple variable images improves face recognition. Building on multi-image training, we take a novel approach to improving own- and other-race face recognition by testing the role of learning context on accuracy. Learning context was either contiguous, with multiple images of each identity seen in sequence, or distributed, with multiple images of an identity randomly interspersed among different identities. In two experiments, East Asian and Caucasian participants learned own- and other-races faces either in a contiguous or distributed order. In Experiment 1, people learned each identity from four highly variable face images. In Experiment 2, identities were learned from one image, repeated four times. In both experiments we found a robust other-race effect. The effect of learning context, however, differed depending on the variability of the learned images. The distributed presentation yielded better recognition when people learned from single repeated images (Exp. 1), but not when they learned from multiple variable images (Exp. 2). Overall, performance was better with multiple-image training than repeated single image training. We conclude that multiple-image training and distributed learning can both improve recognition accuracy, but via distinct processes. The former broadens perceptual tolerance for image variation from a face, when there are diverse images available to learn. The latter effectively strengthens the representation of differences among similar faces, when there is only a single learning image.

Identifying children with autism spectrum disorder based on their face processing abnormality: A machine learning framework

The atypical face scanning patterns in individuals with Autism Spectrum Disorder (ASD) has been repeatedly discovered by previous research. The present study examined whether their face scanning patterns could be potentially useful to identify children with ASD by adopting the machine learning algorithm for the classification purpose. Particularly, we applied the machine learning method to analyze an eye movement dataset from a face recognition task [Yi et al., 2016], to classify children with and without ASD. We evaluated the performance of our model in terms of its accuracy, sensitivity, and specificity of classifying ASD. Results indicated promising evidence for applying the machine learning algorithm based on the face scanning patterns to identify children with ASD, with a maximum classification accuracy of 88.51%. Nevertheless, our study is still preliminary with some constraints that may apply in the clinical practice. Future research should shed light on further valuation of our method and contribute to the development of a multitask and multimodel approach to aid the process of early detection and diagnosis of ASD. Autism Res 2016, 9: 888-898. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Brief Report: Sensitivity of Children with Autism Spectrum Disorders to Face Appearance in Selective Trust

The current study examined how children with Autism Spectrum Disorders (ASD) could selectively trust others based on three facial cues: the face race, attractiveness, and trustworthiness. In a computer-based hide-and-seek game, two face images, which differed significantly in one of the three facial cues, were presented as two cues for selective trust. Children had to selectively trust the own-race, attractive and trustworthy faces to get the prize. Our findings demonstrate an intact ability of selective trust based on face appearance in ASD compared to typical children: they could selectively trust the informant based on face race and attractiveness. Our results imply that despite their face recognition deficits, children with ASD are still sensitive to some aspects of face appearance.