Differences Between Autistic and Non-Autistic Adults in the Recognition of Anger from Facial Motion Remain after Controlling for Alexithymia.
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ABSTRACT:
SUBMITTER: Keating CT
PROVIDER: S-EPMC8159724 | biostudies-literature | 2021 May
REPOSITORIES: biostudies-literature
Publications
Differences Between Autistic and Non-Autistic Adults in the Recognition of Anger from Facial Motion Remain after Controlling for Alexithymia.
Keating Connor T CT Fraser Dagmar S DS Sowden Sophie S Cook Jennifer L JL
Journal of autism and developmental disorders 20210528 4
To date, studies have not established whether autistic and non-autistic individuals differ in emotion recognition from facial motion cues when matched in terms of alexithymia. Here, autistic and non-autistic adults (N = 60) matched on age, gender, non-verbal reasoning ability and alexithymia, completed an emotion recognition task, which employed dynamic point light displays of emotional facial expressions manipulated in terms of speed and spatial exaggeration. Autistic participants exhibited sig ...[more]
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Project description:BackgroundAlexithymia, a personality trait characterized by difficulties interpreting one's own emotional states, is commonly elevated in autistic adults, and a growing body of literature suggests that this trait underlies a number of cognitive and emotional differences previously attributed to autism, such as difficulties in facial emotion recognition and reduced empathy. Although questionnaires such as the twenty-item Toronto Alexithymia Scale (TAS-20) are frequently used to measure alexithymia in the autistic population, few studies have attempted to determine the psychometric properties of these questionnaires in autistic adults, including whether differential item functioning (I-DIF) exists between autistic and general population adults.MethodsWe conducted an in-depth psychometric analysis of the TAS-20 in a large sample of 743 verbal autistic adults recruited from the Simons Foundation SPARK participant pool and 721 general population controls enrolled in a large international psychological study (the Human Penguin Project). The factor structure of the TAS-20 was examined using confirmatory factor analysis, and item response theory was used to further refine the scale based on local model misfit and I-DIF between the groups. Correlations between alexithymia and other clinical outcomes such as autistic traits, anxiety, and quality-of-life were used to assess the nomological validity of the revised alexithymia scale in the SPARK sample.ResultsThe TAS-20 did not exhibit adequate global model fit in either the autistic or general population samples. Empirically driven item reduction was undertaken, resulting in an eight-item unidimensional scale (TAS-8) with sound psychometric properties and practically ignorable I-DIF between diagnostic groups. Correlational analyses indicated that TAS-8 scores meaningfully predict autistic trait levels, anxiety and depression symptoms, and quality of life, even after controlling for trait neuroticism.LimitationsLimitations of the current study include a sample of autistic adults that was overwhelmingly female, later-diagnosed, and well-educated; clinical and control groups drawn from different studies with variable measures; and an inability to test several other important psychometric characteristics of the TAS-8, including sensitivity to change and I-DIF across multiple administrations.ConclusionsThese results indicate the potential of the TAS-8 as a psychometrically robust tool to measure alexithymia in both autistic and non-autistic adults. A free online score calculator has been created to facilitate the use of norm-referenced TAS-8 latent trait scores in research applications (available at http://asdmeasures.shinyapps.io/TAS8_Score ).
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Project description:BackgroundMicro-expression is a kind of expression produced by people spontaneously and unconsciously when receiving stimulus. It has the characteristics of low intensity and short duration. Moreover, it cannot be controlled and disguised. Thus, micro-expression can objectively reflect people's real emotional states. Therefore, automatic recognition of micro-expressions can help machines better understand the users' emotion, which can promote human-computer interaction. What's more, micro-expression recognition has a wide range of applications in fields like security systems and psychological treatment. Nowadays, thanks to the development of artificial intelligence, most micro-expression recognition algorithms are based on deep learning. The features extracted by deep learning model from the micro-expression video sequences mainly contain facial motion feature information and identity feature information. However, in micro-expression recognition tasks, the motions of facial muscles are subtle. As a result, the recognition can be easily interfered by identity feature information.MethodsTo solve the above problem, a micro-expression recognition algorithm which decouples facial motion features and identity features is proposed in this paper. A Micro-Expression Motion Information Features Extraction Network (MENet) and an Identity Information Features Extraction Network (IDNet) are designed. By adding a Diverse Attention Operation (DAO) module and constructing divergence loss function in MENet, facial motion features can be effectively extracted. Global attention operations are used in IDNet to extract identity features. A Mutual Information Neural Estimator (MINE) is utilized to decouple facial motion features and identity features, which can help the model obtain more discriminative micro-expression features.ResultsExperiments on the SDU, MMEW, SAMM and CASME II datasets were conducted, which achieved competitive results and proved the superiority of the proposed algorithm.
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Project description:Distress caused by sensory processing differences for autistic individuals may be reduced by repetitive behaviours (RRB), including repetitive motor (RMB) and insistence on sameness (ISB) behaviours. Intolerance of uncertainty (IU) and anxiety mediate the relationship between sensory processing and RRB in autistic children. We replicated this model in autistic adults, extending it to include alexithymia. Serial mediation, using data from 426 autistic adults, identified significant direct effects from sensory processing to RMB and ISB, and indirect effects through alexithymia-IU-anxiety for RMB, and IU alone, and alexithymia-IU for ISB. Different mechanisms may underpin RMB and ISB. Alexithymia alongside, IU and anxiety, should be considered when understanding the relationship between sensory processing and RRB, and when offering interventions to support autistic people.
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Project description:BackgroundAlexithymia, a personality trait characterized by difficulties interpreting emotional states, is commonly elevated in autistic adults, and a growing body of literature suggests that this trait underlies several cognitive and emotional differences previously attributed to autism. Although questionnaires such as the 20-item Toronto Alexithymia Scale (TAS-20) are frequently used to measure alexithymia in the autistic population, few studies have investigated the psychometric properties of these questionnaires in autistic adults, including whether differential item functioning (I-DIF) exists between autistic and general population adults.MethodsThis study is a revised version of a previous article that was retracted due to copyright concerns (Williams and Gotham in Mol Autism 12:1-40). We conducted an in-depth psychometric analysis of the TAS-20 in a large sample of 743 cognitively able autistic adults recruited from the Simons Foundation SPARK participant pool and 721 general population controls enrolled in a large international psychological study. The factor structure of the TAS-20 was examined using confirmatory factor analysis, and item response theory was used to generate a subset of the items that were strong indicators of a "general alexithymia" factor. Correlations between alexithymia and other clinical outcomes were used to assess the nomological validity of the new alexithymia score in the SPARK sample.ResultsThe TAS-20 did not exhibit adequate model fit in either the autistic or general population samples. Empirically driven item reduction was undertaken, resulting in an 8-item general alexithymia factor score (GAFS-8, with "TAS" no longer referenced due to copyright) with sound psychometric properties and practically ignorable I-DIF between diagnostic groups. Correlational analyses indicated that GAFS-8 scores, as derived from the TAS-20, meaningfully predict autistic trait levels, repetitive behaviors, and depression symptoms, even after controlling for trait neuroticism. The GAFS-8 also presented no meaningful decrement in nomological validity over the full TAS-20 in autistic participants.LimitationsLimitations of the current study include a sample of autistic adults that was majority female, later diagnosed, and well educated; clinical and control groups drawn from different studies with variable measures; only 16 of the TAS-20 items being administered to the non-autistic sample; and an inability to test several other important psychometric characteristics of the GAFS-8, including sensitivity to change and I-DIF across multiple administrations.ConclusionsThese results indicate the potential of the GAFS-8 to robustly measure alexithymia in both autistic and non-autistic adults. A free online score calculator has been created to facilitate the use of norm-referenced GAFS-8 latent trait scores in research applications (available at https://asdmeasures.shinyapps.io/alexithymia ).
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Project description:Facial expressions, and the ability to recognize these expressions, have evolved in humans to communicate information to one another. Face masks are equipment used in healthcare by health professionals to prevent the transmission of airborne infections. As part of the social distancing efforts related to COVID-19, wearing facial masks has been practiced globally. Such practice might influence affective information communication among humans. Previous research suggests that masks disrupt expression recognition of some emotions (e.g., fear, sadness or neutrality) and lower the confidence in their identification. To extend the previous research, in the current study we tested a larger and more diverse sample of individuals and also investigated the effect of masks on perceived intensity of expressions. Moreover, for the first time in the literature we examined these questions using individuals with autistic traits. Specifically, across three experiments using different populations (college students and general population), and the 10-item Autism Spectrum Quotient (AQ-10; lower and higher scorers), we tested the effect of facial masks on facial emotion recognition of anger, disgust, fear, happiness, sadness, and neutrality. Results showed that the ability to identify all facial expressions decreased when faces were masked, a finding observed across all three studies, contradicting previous research on fear, sad, and neutral expressions. Participants were also less confident in their judgements for all emotions, supporting previous research; and participants perceived emotions as less expressive in the mask condition compared to the unmasked condition, a finding novel to the literature. An additional novel finding was that participants with higher scores on the AQ-10 were less accurate and less confident overall in facial expression recognition, as well as perceiving expressions as less intense. Our findings reveal that wearing face masks decreases facial expression recognition, confidence in expression identification, as well as the perception of intensity for all expressions, affecting high-scoring AQ-10 individuals more than low-scoring individuals.
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Project description:Studies have examined sex differences in emotion processing in health and illness. However, it remains unclear how these neural processes may relate to individual differences in affective traits. We addressed this issue with a dataset of 970 subjects (508 women) curated from the Human Connectome Project. Participants were assessed with the NIH Toolbox Emotion Measures and fMRI while identifying negative facial emotion and neutral shape targets in alternating blocks. Imaging data were analyzed with published routines and the results were reported at a corrected threshold. Men scored similarly in Anger- but lower in Fear-Affect, as compared to women. Men as compared with women engaged the occipital-temporal visual cortex, retrosplenial cortex (RSC), and both anterior and posterior cingulate cortex to a greater extent during face versus shape identification. Women relative to men engaged higher activation of bilateral middle frontal cortex. In regional brain responses to face versus shape identification, men relative to women showed more significant modulations by both Anger- and Fear- Affect traits. The left RSC and right RSC/precuneus each demonstrated activities during face vs. shape identification in negative correlation with Anger- and Fear- Affect scores in men only. Anger affect was positively correlated with prolonged RT in identifying face vs. shape target in men but not women. In contrast, women relative to men showed higher Fear-Affect score and higher activation in the right middle frontal cortex, which was more strongly correlated with prolonged RT during face vs. shape identification. Together, men and women with higher Fear-Affect demonstrated lower accuracy in identifying negative facial emotion versus neutral shape target, a relationship mediated by activity of the RSC. These findings add to the literature of sex and trait individual differences in emotion processing and may help research of sex-shared and sex-specific behavioral and neural markers of emotional disorders.
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