Measuring change in facial emotion recognition in individuals with autism spectrum disorder: A systematic review

Reasoning More Efficiently with Primary Knowledge Despite Extraneous Cognitive Load

Geary's evolutionary approach in educational psychology differentiates between primary (low cognitive costs and motivational advantage) and secondary knowledge (high cognitive costs and no motivational benefit). Although these features have been well demonstrated in previous work, the underlying mechanisms remain unclear. To investigate it, in a reasoning task, the present study varies (i) the content of the problems (primary knowledge vs. secondary; e.g., food vs. grammar rules), (ii) the intrinsic cognitive load (conflict or non-conflict syllogism, the former requiring more cognitive resources to be properly processed than the latter) and (iii) the extraneous cognitive load (via a Dot Memory Task with three modalities: low, medium and high cognitive load). Analyses assessed the influence of these variables on performance, problem solving speed and perceived cognitive load. Results confirmed the positive impact of primary knowledge on efficiency, particularly when intrinsic cognitive load was high. Surprisingly, the extraneous cognitive load did not influence the performance in secondary knowledge content but that in primary knowledge content: the higher the additional load was, the better the performance was, only for primary knowledge and especially for syllogisms with high intrinsic load. Findings support evolutionary theory as secondary knowledge would overload cognitive resources, preventing participants from allocating sufficient resources to solve problems. Primary knowledge would allow participants to process the additional load and to increase their performance despite this. This study also raises the hypothesis that a minimum cognitive load is necessary for participants to be invested in the task.

Autistic and non-autistic individuals show the same amygdala activity during emotional face processing

BACKGROUND

Autistic and non-autistic individuals often differ in how they perceive and show emotions, especially in their ability and inclination to infer other people's feelings from subtle cues like facial expressions. Prominent theories of autism have suggested that these differences stem from alterations in amygdala functioning and that amygdala hypoactivation causes problems with emotion recognition. Thus far, however, empirical investigations of this hypothesis have yielded mixed results and largely relied on relatively small samples.

METHODS

In a sample of 72 autistic and 79 non-autistic participants, we conducted a study in which we used the Hariri paradigm to test whether amygdala activation during emotional face processing is altered in autism spectrum disorder, and whether common mental disorders like depression, ADHD or anxiety disorders influence any potential alterations in activation patterns.

RESULTS

We found no evidence for differences in amygdala activation, neither when comparing autistic and non-autistic participants, nor when taking into account mental disorders or the overall level of functional impairment.

LIMITATIONS

Because we used one basic emotion processing task in a Dutch sample, results might not generalise to other tasks and other populations.

CONCLUSIONS

Our results challenge the view that autistic and non-autistic processing of emotional faces in the amygdala is vastly different and call for a more nuanced view of differences between non-autistic and autistic emotion processing.

Comprehensive Assessments of Theory of Mind Abilities for School-Age Children: A Systematic Review

PURPOSE

Theory of mind involves perceiving both the thoughts and emotions of others. Theory of mind skills continue to develop in school-age individuals. For children at risk for social communication difficulties, evaluating theory of mind is warranted to determine whether theory of mind should be a target of intervention. There are hundreds of tasks designed to evaluate theory of mind, but many evaluate a single facet of the construct and have uneven psychometric properties. Comprehensive assessments evaluate both cognitive and affective aspects of theory of mind. The purpose of this systematic review was to identify comprehensive theory of mind assessments for school-age individuals and to critically appraise their measurement properties.

METHOD

Four databases were searched to identify 27 included records describing the measurement properties of comprehensive theory of mind assessments for 5- to 21-year-olds. Assessments appearing in at least three records were included. The methodological quality of the studies and the sufficiency of assessments' measurement properties were evaluated using the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN).

RESULTS

Nine assessments were evaluated, and four met COSMIN standards for sufficient content validity and internal consistency to be recommended for clinical use.

CONCLUSIONS

Comprehensive assessments enable examiners to develop a profile of children's theory of mind strengths and needs. Strengths of the identified assessments include sufficient convergent validity and internal consistency. Further research is required to develop higher quality evidence for the content validity, structural validity, and reliability of the included assessments.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.23817495.

Effects of Transcranial Direct Current Stimulation on Social Attention Patterns and Emotion Recognition Ability in Male Adolescents with Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is characterized by impairments in social cognition including emotion recognition (ER) abilities. Common symptoms include unusual patterns of visual social attention, which are investigated as early developmental biomarkers for ASD. Transcranial Direct Current Stimulation (tDCS) has shown promising results in influencing social functioning in individuals with ASD. However, the effects of tDCS on social attention patterns and ER ability in adolescents with ASD remain unclear. This double-blind, sham-controlled, randomized clinical trial examined the effects of repeated sessions of tDCS on gaze behavior and ER ability in 22 male adolescents diagnosed with ASD. Participants received either 20 min of 2 mA active tDCS or sham stimulation for 10 days and an intra-stimulation training. Social allocation patterns were assessed using eye-tracking paradigms, including ER tasks. Our results indicated no tDCS-specific effects. Both groups showed improvements in ER and more frequent, faster, and longer fixations on the eyes than the mouth, and on social than nonsocial areas. In tasks with low social content, fixating the mouth seemed to increase ER accuracy. Understanding the effects of tDCS on social functioning in adolescents with ASD holds promise for the development of targeted interventions to improve their social cognition abilities.

Towards Context-Aware Facial Emotion Reaction Database for Dyadic Interaction Settings

Emotion recognition is a significant issue in many sectors that use human emotion reactions as communication for marketing, technological equipment, or human-robot interaction. The realistic facial behavior of social robots and artificial agents is still a challenge, limiting their emotional credibility in dyadic face-to-face situations with humans. One obstacle is the lack of appropriate training data on how humans typically interact in such settings. This article focused on collecting the facial behavior of 60 participants to create a new type of dyadic emotion reaction database. For this purpose, we propose a methodology that automatically captures the facial expressions of participants via webcam while they are engaged with other people (facial videos) in emotionally primed contexts. The data were then analyzed using three different Facial Expression Analysis (FEA) tools: iMotions, the Mini-Xception model, and the Py-Feat FEA toolkit. Although the emotion reactions were reported as genuine, the comparative analysis between the aforementioned models could not agree with a single emotion reaction prediction. Based on this result, a more-robust and -effective model for emotion reaction prediction is needed. The relevance of this work for human-computer interaction studies lies in its novel approach to developing adaptive behaviors for synthetic human-like beings (virtual or robotic), allowing them to simulate human facial interaction behavior in contextually varying dyadic situations with humans. This article should be useful for researchers using human emotion analysis while deciding on a suitable methodology to collect facial expression reactions in a dyadic setting.

Emo-mirror: a proposal to support emotion recognition in children with autism spectrum disorders

Autism spectrum disorder (ASD) is a neurodevelopmental disorder defined as persistent difficulty in maturing the socialization process. Health professionals have used traditional methods in the therapies performed on patients with the aim of improving the expression of emotions by patients. However, they have not been sufficient to detect the different emotions expressed in the face of people according to different sensations. Therefore, different artificial intelligence techniques have been applied to improve the results obtained in these therapies. In this article, we propose the construction of an intelligent mirror to recognize five basic emotions: angry, scared, sad, happy and neutral. This mirror uses convolutional neural networks to analyze the images that are captured by a camera and compare it with the one that the patient should perform, thus supporting the therapies performed by health professionals in children with ASD. The proposal presents the platform and computer architecture, as well as the evaluation by specialists under the technology acceptance model.

The relationship between alexithymia, reading the mind in the eyes and cognition in patients with multiple sclerosis

AIM

The purpose of this study was to determine the frequency of alexithymia, difficulty in recognizing one's own and others' emotions, to determine the ability to read the mind in the eyes that evaluates the emotions of others, and to assess the relationship between these parameters and demographic characteristics, cognition, anxiety and depression in people with multiple sclerosis (PwMS).

MATERIAL AND METHOD

Seventy patients presenting to the neurology clinic and diagnosed with MS and 70 healthy volunteers with similar demographic characteristics were included in the study. The California Verbal Learning Test II (CVLT II), Symbol Digit Modalities Test (SDMT), Revised Brief Visuospatial Memory Test (BVMT-R), and Trail-Making Test (TMT) were applied to determine all participants' cognitive status. All participants were also administered Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), Toronto Alexithymia Scale-20 (TAS-20), Reading the Mind in the Eyes Test (RMET), Fatigue Impact Scale (FIS) and Short Form 36 Health Survey (SF-36) for quality of life.

RESULTS

Alexithymia levels were higher in the PwMS than in the control group, 24.2% of the PwMS and 4.2% of the control group being alexithymic. The PwMS group exhibited poorer performance on all cognitive tests and in BDI, BAI, FIS and SF-36 scale scores than the control group. No difference was determined between the groups' RMET scores. Depression and anxiety levels increased in line with alexithymia levels in the PwMS group, while RMET scores decreased. No association was determined between alexithymia levels and age, sex, duration of disease, degree of disability, cognition, or fatigue. RMET scores were not affected by age, sex, duration of disease, degree of disability, anxiety, or fatigue, but were lower among individuals with poor cognition and in depressive patients.

CONCLUSION

Neuropsychiatric symptoms have been the subject of considerable research in MS in recent years and these clinical characteristics in patients have begun being closely monitored. PwMS are capable of experiencing difficulty in identifying emotions in themselves and others, and their social lives can be affected. In addition, the fact that this exhibits an association with cognition based on RMET is particularly noteworthy.

How White American Children Develop Racial Biases in Emotion Reasoning

For decades, affective scientists have examined how adults and children reason about others' emotions. Yet, our knowledge is limited regarding how emotion reasoning is impacted by race-that is, how individuals reason about emotions displayed by people of other racial groups. In this review, we examine the developmental origins of racial biases in emotion reasoning, focusing on how White Americans reason about emotions displayed by Black faces/people. We highlight how racial biases in emotion reasoning, which emerge as early as infancy, likely contribute to miscommunications, inaccurate social perceptions, and negative interracial interactions across the lifespan. We conclude by discussing promising interventions to reduce these biases as well as future research directions, highlighting how affective scientists can decenter Whiteness in their research designs. Together, this review highlights how emotion reasoning is a potentially affective component of racial bias among White Americans.

Psychometric properties of the Cambridge-Mindreading Face-Voice Battery for Children in children with ASD

This study examined the psychometric characteristics of the Cambridge-Mindreading Face-Voice Battery for Children (CAM-C) for a sample of 333 children, ages 6-12 years with ASD (with no intellectual disability). Internal consistency was very good for the Total score (0.81 for both Faces and Voices) and respectable for the Complex emotions score (0.72 for Faces and 0.74 for Voices); however, internal consistency was lower for Simple emotions (0.65 for Faces and 0.61 for Voices). Test-retest reliability at 18 and 36 weeks was very good for the faces and voices total (0.76-0.81) and good for simple and complex faces and voices (0.53-0.75). Significant correlations were found between CAM-C Faces and scores on another measure of face-emotion recognition (Diagnostic Analysis of Nonverbal Accuracy-Second Edition), and between Faces and Voices scores and child age, IQ (except perceptual IQ and Simple Voice emotions), and language ability. Parent-reported ASD symptom severity and the Emotion Recognition scale on the SRS-2 were not related to CAM-C scores. Suggestions for future studies and further development of the CAM-C are provided. LAY SUMMARY: Facial and vocal emotion recognition are important for social interaction and have been identified as a challenge for individuals with autism spectrum disorder. Emotion recognition is an area frequently targeted by interventions. This study evaluated a measure of emotion recognition (the CAM-C) for its consistency and validity in a large sample of children with autism. The study found the CAM-C showed many strengths needed to accurately measure the change in emotion recognition during intervention.

Masking Emotions: Face Masks Impair How We Read Emotions

To date, COVID-19 has spread across the world, changing our way of life and forcing us to wear face masks. This report demonstrates that face masks influence the human ability to infer emotions by observing facial configurations. Specifically, a mask obstructing a face limits the ability of people of all ages to infer emotions expressed by facial features, but the difficulties associated with the mask’s use are significantly pronounced in children aged between 3 and 5 years old. These findings are of essential importance, as they suggest that we live in a time that may potentially affect the development of social and emotion reasoning, and young children’s future social abilities should be monitored to assess the true impact of the use of masks.