Search

Nonliteral language understanding has always been recognized as problematic in autistic individuals. We ran a study on 26 autistic children (mean age = 7.3 years) and 2 comparison groups of typically developing children, 1 matched for chronological age, and 1 of younger peers (mean age = 6.11 years) matched for linguistic abilities, aiming at assessing their understanding of ironic criticisms and compliments, and identifying the cognitive and linguistic factors that may underpin this ability. Autistic participants lagged behind the comparison groups in the comprehension of both types of irony, and their performance was related to mindreading and linguistic abilities. Significant correlations were found between first-order Theory of Mind (ToM) and both types of irony, between second-order ToM and ironic compliments, and between linguistic abilities and ironic criticisms. The autistic group displayed an interesting, and previously unattested in the literature, bimodal distribution: the great majority of them (n = 18) displayed a very poor performance in irony understanding, whereas some (n = 6) were at ceiling. We discuss these results in terms of two different profiles of autistic children.

Early identification of children on the autism spectrum is crucial for early intervention with long-term positive effects on symptoms and skills. The need for improved objective autism detection tools is emphasized by the poor diagnostic power in current tools. Here, we aim to evaluate the diagnostic power of genuine acoustic features of the voice in children with autism spectrum disorder (ASD) with respect to a heterogeneous control group (composed of neurotypical children and children with Developmental Language Disorder [DLD] and children with sensorineural hearing loss with Cochlear Implant [CI]). This retrospective diagnostic study was conducted at the University Child Psychiatry Center of Tours (France). A total of 108 children, including 38 diagnosed with ASD (8.5 ± 0.25 years), 24 typically developing (TD; 8.2 ± 0.32 years) children and 46 children with atypical development (DLD and CI; 7.9 ± 0.36 years) were enrolled in our studies. We applied a ROC (Receiving Operator Characteristic) supervised clustering algorithm combined with cross-validation to develop a diagnostic model that can differentially diagnose a child with unknown disorder. The acoustic properties of speech samples produced by children in the context of a nonword repetition task were examined. We showed that voice acoustics predicted the diagnosis of autism with an overall accuracy of 91% [CI95%, 90.40%-91.65%] against TD children, and of 85% [CI95%, 84.5%-86.6%] against an heterogenous group of non-autistic children. Accuracy reported here with multivariate analysis is higher than in previous studies. Our findings demonstrate that easy-to-measure voice acoustic parameters could be used as a diagnostic aid tool, specific of ASD.

Children with autism often display discrepancies in their intellectual functioning, with nonverbal skills frequently being more developed than verbal. Compared to monolingual autistic children, however, much less is known about how bilingualism affects intelligence in autism. The current study examined the intelligence profiles of 146 bilingual and 170 age- and gender-matched monolingual children with autism (6–17 years) using the Wechsler Intelligence Scales for Children-Third Edition, by tracking cluster profiles across children and by modeling verbal and nonverbal IQ performance in each cluster as a function of language experience (monolinguals vs bilinguals), socioeconomic status, and age. The results reveal that socioeconomic status, operationalized as mother’s years of education, mediated by bilingualism was strongly related to autistic children’s intelligence. Low-socioeconomic status bilingual autistic children exhibited better performance than their monolingual peers across both the verbal and nonverbal intelligence subtests. However, the difference found in the intelligence profiles between monolinguals and bilinguals belonging to high-socioeconomic status was limited to the Comprehension Wechsler Intelligence Scales for Children test, with high-socioeconomic status monolingual autistic children outperforming their bilingual peers. The findings highlight the importance of investigating bilingualism effects in relation to socioeconomic status in autism. Lay abstract Previous research has suggested that bilingualism may improve cognition in children with autism, and that this boost may stem from improvement in executive functions. The Wechsler Intelligence Scales for Children are considered to be reliable and valid measures of intelligence when administered to autistic children. These measures have so far revealed unusual psychometric properties in monolingual autistic children, notably distinctive patterns of strengths and weaknesses and low inter-correlation among verbal and nonverbal IQ subtests. The way bilingualism affects the intellectual functioning of autistic children has not been explored yet. Nor has there been a satisfactory factor structure that explains monolingual and bilingual autistic children’s IQ performance in terms of individual factors, such as age and socioeconomic status. The current study examined the intelligence profiles of 316 bilingual and age- and gender-matched monolingual children with autism using the Wechsler Intelligence Scales for Children–Third Edition. The study applied clustering models to extract intelligence subtypes of autism, and mediation analyses to examine potential mediation effects of age and socioeconomic status on the children’s verbal and nonverbal IQ performance. The results support the mediational role of the children’s socioeconomic status in the association between bilingualism and intelligence. Low-socioeconomic status bilingual autistic children outperformed their monolingual peers on both verbal and nonverbal subtests, while the differences faded in medium-socioeconomic status and high-socioeconomic status children. The findings emphasize the positive effects of bilingualism on low-socioeconomic status autistic children’s intelligence and also highlight high-socioeconomic status as a factor that may mitigate discrepant patterns of strengths and weaknesses in monolingual children’s IQ performance.

In the last years, researchers and therapists have pinpointed a number of critical aspects in current speech-language interventions. Several studies have explored the use of technology to overcome these barriers and to support speech-therapy in children with language impairments (e.g. DLD and ASD). In this paper, we propose a conceptual framework for designing linguistic activities (for assessment and training), based on advances in psycholinguistics. Moving from this theoretical framework, we identified a development process - from the UX design to coding of activities – which is based on a novel set of Design Patterns at multiple layers of abstraction. We then put this framework into practice by implementing these patterns into two technological solutions – tablet and robots – and performing an empirical study to evaluate their benefits. Our results, although still preliminary since they assessed only a tablet experimental condition, are promising for extending the identified Design Patterns to other technological solutions.

In this paper we present Do You Speak Holo?, an application for Microsoft HoloLens co-designed with linguistics experts that aims to facilitate the learning process of a foreign language for children and adolescents with language disorders (LD). The application includes several educational activities, aimed at improving both vocabulary and morpho-syntactic aspects of the language through the interaction with virtual content immersed in the real world. The application includes a virtual assistant, which acts as a virtual teacher and guides the user step by step in the comprehension and execution of the activities.

The dramatic increment of communication impairments among children increases the demand for intensive, highly accessible and low-cost interventions as well as new assessment and therapeutic tools. Our research aims at exploring the use of Conversational Agents (CAs) to support linguistic assessment and training among children with language impairment. One of the open research issues in this arena concerns the identification of the most appropriate form of "embodiment" of the CA for children to interact with. To this end, we evaluated the linguistic performance of 14 neuro-typical children and 3 children with language impairment comparing different CAs - physical object and virtual character - with "traditional" human interaction. Based on our analysis, we identify insights for the design of CA: the physicality does influence the performance of linguistic tasks for children with linguistic impairment. In addition, children seem to show a preference for the physical CA and perceived it as smarter than the virtual one.

Our research explores game play in Wearable Collaborative Virtual Environments (WCVEs) to provide new forms of treatment for persons with Neurodevelopmental Disorders (NDD) that complement traditional methods of intervention. We investigate this issue using the Social MatchUP (SMUP) application as a case study. SMUP provides a set of games in WCVEs that have been co-designed with NDD experts and aim at improving communication skills. In SMUP, multiple users wearing a Virtual Reality visor play together to accomplish collaborative tasks that take place in shared virtual environments and require talking to each other to be completed. The paper presents an exploratory empirical study devoted to evaluate the potential of SMUP games for persons with NDD to improve their speech-based conversational capability. We organized participants (24 persons with NDD) in 2 groups, one playing a game in SMUP and one playing a similar game in the real world, and assessed likability, usability, and a number of conversational performance metrics. Our results indicate that the game experience in SMUP was usable and enjoyable, and boosted higher conversational skills with respect to its counterpart in the physical setting.

The new version of the International Classification of Diseases (ICD-11) mentions the existence of four different profiles in the verbal part of the Autism Spectrum Disorder (ASD), describing them as combinations of either spared or impaired functional language and intellectual abilities. The aim of the present study was to put ASD heterogeneity to the forefront by exploring whether clear profiles related to language and intellectual abilities emerge when investigation is extended to the entire spectrum, focusing on verbal children. Our study proposed a systematic investigation of both language (specifically, structural language abilities) and intellectual abilities (specifically, nonverbal cognitive abilities) in 51 6- to 12-year-old verbal children with ASD based on explicitly motivated measures. For structural language abilities, sentence repetition and nonword repetition tasks were selected; for nonverbal cognitive abilities, we chose Raven's Progressive Matrices, as well as Matrix Reasoning and Block Design from the Wechsler Scales. An integrative approach based on cluster analyses revealed five distinct profiles. Among these five profiles, all four logically possible combinations of structural language and nonverbal abilities mentioned in the ICD-11 were detected. Three profiles emerged among children with normal language abilities and two emerged among language-impaired children. Crucially, the existence of discrepant profiles of abilities suggests that children with ASD can display impaired language in presence of spared nonverbal intelligence or spared language in the presence of impaired nonverbal intelligence, reinforcing the hypothesis of the existence of a separate language module in the brain. Autism Res 2020, 13: 1155-1167. © 2020 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: The present work put Autism Spectrum Disorder heterogeneity to the forefront by exploring whether clear profiles related to language and cognitive abilities emerge when investigation is extended to the entire spectrum (focusing on verbal children). The use of explicitly motivated measures of both language and cognitive abilities and of an unsupervised machine learning approach, the cluster analysis, (a) confirmed the existence of all four logically possible profiles evoked in the new ICD-11, (b) evoked the existence of (at least) a fifth profile of language/cognitive abilities, and (c) reinforced the hypothesis of a language module in the brain.

This study investigates formal language abilities in French-speaking children with Autism Spectrum Disorder (ASD). We report on the usefulness of the LITMUS-Sentence-Repetition-French task in distinguishing children with impaired language (ASD-LI) from children with normal language (ASD-LN). We examined complexity of syntactic computation, to determine whether children with ASD-LI behave analogously to children with SLI. Results showed that the ASD-LI group performed like the SLI group, while the ASD-LN group performed like the TD group. Despite the existence of a link between nonverbal IQ (NVIQ) and performance on SR, this correlation was not linear, due to the presence of children with each of the four formal language ability/NVIQ profiles, indicating the possible independence of formal language from nonverbal intelligence.