Figurative language processing in autism spectrum disorders: A review

Bilingualism Effects in Metaphor and Simile Comprehension and Production in Children With Autism Spectrum Disorder

Figurative language, including metaphors and similes, is a crucial component of communication; yet, it presents significant challenges for individuals with autism spectrum disorder (ASD). A critical gap in existing research is the impact of bilingualism on the ability of children with ASD to understand and produce non-literal speech. This study addresses this gap by examining the comprehension and production of metaphors and similes in monolingual and bilingual Greek-speaking children with high-functioning ASD. To the best of our knowledge, this is the first study to investigate these abilities in bilingual children with ASD. Thirty-three monolingual and 18 bilingual children participated in tasks designed to assess comprehension, production, and error patterns for metaphors and similes. The study has also investigated the roles of non-verbal intelligence, language skills (expressive vocabulary), and executive functions (working memory) in the children's performance in the metaphor and simile tasks. Results showed that the two groups did not differ in metaphor comprehension; however, bilingual autistic children with higher non-verbal intelligence appeared to have superior performance in metaphor comprehension compared to their bilingual peers with lower non-verbal intelligence. The bilingual autistic children outperformed their monolingual peers in metaphor production, likely due to their higher non-verbal intelligence ability, despite the fact that the bilingual group had lower expressive vocabulary scores than the monolingual children. Simile comprehension, on the other hand, favored monolingual children, while no significant group differences were observed in simile production. Regarding errors, both groups exhibited similar error patterns, with literal interpretations being the dominant error type across both groups, suggesting that pragmatic language difficulty is a hallmark feature in ASD. The findings challenge the misconception that bilingualism hinders language development in children with ASD and highlight its potential to provide benefits in the realm of non-literal language processing.

How (and why) languages became more complex as we evolved more prosocial: the human self-domestication view

This paper aims to re-examine the problem of the emergence of present-day languages from the specific perspective of the self-domestication account of human evolution. According to this view, our species went through an evolutionary process that parallels the changes experienced by domesticated mammals. Relying on evidence of diverse kind (from paleogenetic to clinical), the paper argues that our self-domestication might have potentiated the cognitive and behavioral features of the human phenotype with an impact on language acquisition and use. Specifically, it might have facilitated the creation of the cultural niche that favors the complexification of languages via a cultural mechanism. The paper further proposes a model of language complexification in the past under the effects of human self-domestication, including the complexification of the structural aspects of language (grammar, prosody, and semantics) and the potentiation of its functional properties (pragmatics). The paper concludes with some suggestions for any future research aimed to test and improve this view.

Metaphor comprehension and production in verbally able children with Autism Spectrum Disorder

Research in the field of figurative language processing in Autism Spectrum Disorders (ASD) has demonstrated that autistic individuals experience systematic difficulties in the comprehension of different types of metaphors. However, there is scarce evidence regarding metaphor production skills in ASD. Importantly, the exact source of metaphor processing difficulties in ASD remains largely controversial. The debate has mainly focused on the mediating role of structural language skills (i.e., lexical knowledge) and cognitive abilities (i.e., Theory of Mind and executive functions) in ASD individuals' ability to comprehend and generate metaphors. The present study examines metaphor comprehension and production in 18 Greek-speaking verbally able children with ASD and 31 typically-developing (TD) controls. Participants completed two tasks, namely, a low-verbal multiple-choice sentence-picture matching task that tested their ability to comprehend conventional predicate metaphors, and a sentence continuation task that assessed their ability to generate metaphors. The study also included measures of fluid intelligence, expressive vocabulary, and working memory within the sample. The results show that the ASD group had significantly lower performance than the TD group in both metaphor comprehension and production. The findings also reveal that expressive vocabulary skills were a key factor in the metaphor comprehension and production performance of the children with ASD. Working memory capacity was also found to correlate significantly with metaphor comprehension performance in the ASD group. Conversely, no correlations were found in the TD group with neither of the above factors. Of note, children with ASD generated significantly more inappropriate responses and no-responses to the metaphor production task compared with the control group. The overall results reveal that children with ASD had difficulty with both comprehending and using metaphorical language. The findings also indicate that TD children may employ diverse cognitive strategies or rely on different underlying skills when processing metaphors compared with children with ASD.

Processing of Emotional Words in Children and Adolescents with Autism Spectrum Disorders

Individuals with autism spectrum disorder (ASD) have difficulties in understanding emotional language, but little research has discussed the developmental course of the processing of emotional words in the clinical population. Previous studies have revealed distinct processing for emotion-label (e.g., happiness) and emotion-laden (e.g., birthday) words in typically developing (TD) children and adolescents. Extending these findings, the study used event-related potentials (ERPs) to explore the processing of these two types of emotional words in children and adolescents with ASD. The stimuli included two-character Chinese words with factors of word type (emotion-label versus emotion-laden) and valence (positive versus negative). The participants were 11 to 14-year-old children and adolescents with ASD (N = 23) and age-matched TD peers (N = 23). They categorized emotion valence for words while their brain responses were recorded. Both the TD and the ASD groups exhibited emotional processing for all emotional words across the N400 and late positivity component (LPC). The emotional processing was modulated by word type but varied with group and valence. A trend for group differences was observed in processing positive words at 500-600 ms. In particular, the emotion effects of positive emotion-label words were positively correlated with social dysfunction across all participants. These findings suggested that children and adolescents with ASD have a selective impairment in understanding emotional concepts from language. The ERP measurements may reflect atypical emotional word processing for individuals with higher autistic severity in positive valence contexts.

Exploring Metalinguistic Awareness in School-Aged Autistic Children: Insights from Grammatical Judgment

Metalinguistic awareness, the ability to manipulate and reflect upon language, remains largely unexplored in the autistic population. To address this gap, this observational cross-sectional study examines the metalinguistic abilities of school-aged autistic children in comparison to neurotypical peers in a novel tablet-based Grammatical Judgment Task (GJT) of reduced linguistic complexity engaging two kinds of metacognitive resources. Children had to judge non-verbally whether pre-recorded sentences were grammatically correct or not, following the traditional GJT paradigm assessing metamorphosyntactic skills. In addition, sentences with anomalous meaning that were either grammatically correct or grammatically incorrect were introduced to test metasemantic knowledge. Findings reveal no difference in performance between the groups, with participants performing on average above chance level both on the sentences assessing mere metamorphosyntactic skills and on the sentences placing an additional demand on metasemantics. This study shows that autistic individuals are able to mobilize metalinguistic resources when tested via a task of reduced linguistic complexity.

Autism Detection in Children: Integrating Machine Learning and Natural Language Processing in Narrative Analysis

Despite the consensus that early identification leads to better outcomes for individuals with autism spectrum disorder (ASD), recent research reveals that the average age of diagnosis in the Greek population is approximately six years. However, this age of diagnosis is delayed by an additional two years for families from lower-income or minority backgrounds. These disparities result in adverse impacts on intervention outcomes, which are further burdened by the often time-consuming and labor-intensive language assessments for children with ASD. There is a crucial need for tools that increase access to early assessment and diagnosis that will be rigorous and objective. The current study leverages the capabilities of artificial intelligence to develop a reliable and practical model for distinguishing children with ASD from typically-developing peers based on their narrative and vocabulary skills. We applied natural language processing-based extraction techniques to automatically acquire language features (narrative and vocabulary skills) from storytelling in 68 children with ASD and 52 typically-developing children, and then trained machine learning models on the children's combined narrative and expressive vocabulary data to generate behavioral targets that effectively differentiate ASD from typically-developing children. According to the findings, the model could distinguish ASD from typically-developing children, achieving an accuracy of 96%. Specifically, out of the models used, hist gradient boosting and XGBoost showed slightly superior performance compared to the decision trees and gradient boosting models, particularly regarding accuracy and F1 score. These results bode well for the deployment of machine learning technology for children with ASD, especially those with limited access to early identification services.

Reading comprehension differences between children with Autism Spectrum Disorder and low cognitive abilities and children with Autism Spectrum Disorder and intact cognitive skills: the roles of decoding, fluency and morphosyntax

Introduction

Reading comprehension is one of the most important skills learned in school and it has an important contribution to the academic success of children with Autism Spectrum Disorder (ASD). Though previous studies have investigated reading comprehension difficulties in ASD and highlighted factors that contribute to these difficulties, this evidence has mainly stemmed from children with ASD and intact cognitive skills. Also, much emphasis has been placed on the relation between reading comprehension and word recognition skills, while the role of other skills, including fluency and morphosyntax, remains underexplored. This study addresses these gaps by investigating reading comprehension in two groups of school-aged children with ASD, one with intact and one with low cognitive abilities, also exploring the roles of word decoding, fluency and morphosyntax in each group's reading comprehension performance.

Methods

The study recruited 16 children with ASD and low cognitive abilities, and 22 age-matched children with ASD and intact cognitive skills. The children were assessed on four reading subdomains, namely, decoding, fluency, morphosyntax, and reading comprehension.

Results

The children with ASD and low cognitive abilities scored significantly lower than their peers with intact cognitive abilities in all reading subdomains, except for decoding, verb production and compound word formation. Regression analyses showed that reading comprehension in the group with ASD and intact cognitive abilities was independently driven by their decoding and fluency skills, and to a lesser extent, by morphosyntax. On the other hand, the children with ASD and low cognitive abilities mainly drew on their decoding, and to a lesser extent, their morphosyntactic skills to perform in reading comprehension.

Discussion

The results suggest that reading comprehension was more strongly affected in the children with ASD and low cognitive abilities as compared to those with intact cognitive skills. About half of the children with ASD and intact cognitive skills also exhibited mild-to-moderate reading comprehension difficulties, further implying that ASD may influence reading comprehension regardless of cognitive functioning. Finally, strengths in decoding seemed to predominantly drive cognitively-impaired children's reading performance, while the group with ASD and intact cognitive skills mainly recruited fluency and metalinguistic lexical skills to cope with reading comprehension demands, further suggesting that metalinguistic awareness may be a viable way to enhance reading comprehension in ASD.

Insights into Oral and Written Competencies in Neurodevelopmental Disorders

The study of language abilities offers privileged insights to access the multifaceted world of neurodevelopmental disorders (NDD, henceforth), showing how particular aspects of language may be handled differently as a function of typical neuropsychological features of specific disorders [...].