Typically Developing Group Research Articles

Developmental Coordination Disorder and Early Childhood Trajectories of Physical Activity.

Purpose: Developmental Coordination Disorder (DCD) is a common neurodevelopmental disorder characterized by motor impairments and subsequent physical activity (PA) deficits in middle childhood. It is not well understood when this gap in PA emerges. The purpose of the current study was to examine the longitudinal trajectories of device-assessed PA in a large cohort of children with and without DCD from age 4 to 8.Methods: Children (n = 535, 4- to 5-years old) completed 4 annual assessments as part of a prospective cohort study. Children were classified into 3 groups based on their average performance on the Movement Assessment Battery for Children- 2nd Edition: probable DCD (pDCD) <6th percentile (n = 72); at-risk for DCD (DCDr) between the 6 to 16th percentile (n = 127), and typically developing (TD) >16th percentile (n = 336). Moderate-to-vigorous PA (MVPA) and average PA volume (vector counts per minute) were assessed using ActiGraph accelerometers. A series of linear mixed effects models were used to examine longitudinal PA trajectories between groups.Results: Children in both the pDCD and DCDr groups engaged in significantly less MVPA compared to the TD group, whereas the deficit in PA volume was only evident in the DCD group. The rate of change did not differ by group indicating that this deficit is relatively consistent across the early childhood period.Conclusions: Young children with DCD are in a MVPA deficit that persists across early childhood. Early interventions targeting motor skills and PA may help to reduce this gap and promote positive trajectories of health among children with motor difficulties.

Exploring the Development of Past and Future Episodic Memory in Adolescents with Autism Spectrum Disorder: A Preliminary Longitudinal Study

Adolescence is a critical period where individuals build their identity and consolidate how they interact with others. However, for adolescents with autism spectrum disorder (ASD), the development of identity and social bounds is at stake. These challenges with the development of identity and social bonds could be linked to difficulties in autobiographical memory (AM), whether recalling past events (past episodic memory; past EM) or imagining future scenarios (episodic future thinking; EFT). To date, developmental patterns of AM over time remain poorly understood in ASD. Eleven adolescents with ASD or typical development (TD) completed an assessment of past EM and EFT once per year for three years. Preliminary results show that past EM becomes more detailed over the years for adolescents with ASD, while there is no change for TD adolescents. Interestingly, only the content elements of the narrated events are increasing, not the context elements. Furthermore, EFT evolves in the TD group but remains stable in the ASD group. This first multi-case longitudinal study of AM needs to be replicated with more participants, but it seems to indicate a heterogeneous evolution of AM in ASD. For future studies, these results will lead us to explore the hypothesis of developmental delay and the factors influencing AM development in ASD. Finally, understanding these developmental pathways highlights the importance of personalized therapeutic approaches to support social integration, identity construction, and future projects for adolescents with ASD.

Salivary IL-1 Beta Level Associated with Poor Sleep Quality in Children/Adolescents with Autism Spectrum Disorder

Background: Sleep disorders are common in youths with autism spectrum disorders. Inflammatory cytokines such as Il-1 beta and Il-6 in saliva have been associated with alterations in sleep quality in various conditions. We assessed whether there were associations between the salivary concentration of IL-1 beta and IL-6 and sleep quality in youths with ASD versus typically developing (TD) age- and gender-matched youths. Method: Forty children and adolescents with ASD or TD participated in this study (20% females). Their parents answered the items of a validated questionnaire on sleep quality (Pittsburgh Sleep Quality Index). Results: The mean Pittsburgh score was significantly higher (i.e., the quality of sleep was poorer) in the ASD group (8.68 ± 0.35 (SEM), ranging from 7 to 12 points), compared to the TD group (7.35 ± 0.54 (SEM), ranging from 2 to 12 points) (p = 0.02, Mann–Whitney U test). There were no significant differences in the salivary concentration of Il-1 beta and IL-6 receptor between the two groups, but salivary IL-1 beta concentration was inversely associated with poor sleep quality in the ASD group. No associations between the salivary Il-6 concentration and sleep quality were found in either group. Linear regression analysis by separate groups revealed significant associations between the sleep quality score and the concentration of IL-1 beta in the ASD group (p = 0.01, OR = −0.53, 95% CI −0.008–0.001). In contrast, no significant associations were observed in the TD group, or for IL-6 in either group. No significant effects of sex, age, or use of psychotropic medications were found. Conclusions: Children and adolescents with ASD showed significantly poorer sleep quality based on their parents’ reports compared to the TD group, and the salivary IL-1 beta concentration was inversely associated with sleep quality only in the ASD group. Further studies on the associations between inflammatory cytokines and sleep in ASD are needed.

Does ChatGPT have a typical or atypical theory of mind?

In recent years, the capabilities of Large Language Models (LLMs), such as ChatGPT, to imitate human behavioral patterns have been attracting growing interest from experimental psychology. Although ChatGPT can successfully generate accurate theoretical and inferential information in several fields, its ability to exhibit a Theory of Mind (ToM) is a topic of debate and interest in literature. Impairments in ToM are considered responsible for social difficulties in many clinical conditions, such as Autism Spectrum Disorder (ASD). Some studies showed that ChatGPT can successfully pass classical ToM tasks, however, the response style used by LLMs to solve advanced ToM tasks, comparing their abilities with those of typical development (TD) individuals and clinical populations, has not been explored. In this preliminary study, we administered the Advanced ToM Test and the Emotion Attribution Task to ChatGPT 3.5 and ChatGPT-4 and compared their responses with those of an ASD and TD group. Our results showed that the two LLMs had higher accuracy in understanding mental states, although ChatGPT-3.5 failed with more complex mental states. In understanding emotional states, ChatGPT-3.5 performed significantly worse than TDs but did not differ from ASDs, showing difficulty with negative emotions. ChatGPT-4 achieved higher accuracy, but difficulties with recognizing sadness and anger persisted. The style adopted by both LLMs appeared verbose, and repetitive, tending to violate Grice's maxims. This conversational style seems similar to that adopted by high-functioning ASDs. Clinical implications and potential applications are discussed.

Clinical Utility of Virtual Kitchen Errand Task for Children (VKET-C) as a Functional Cognition Evaluation for Children with Developmental Disabilities

Background/Objectives: This study evaluated the clinical utility of a virtual reality (VR)-based kitchen error task for children (VKET-C) to assess functional cognition in children. Methods: In total, 38 children aged 7–12 years were included, comprising 23 typically developing (TD) children and 15 children with developmental disabilities (DDs), including autism spectrum disorder, attention deficit hyperactivity disorder, and intellectual disability. While performing the VKET-C, performance errors were analyzed. The Stockings of Cambridge (SOC) and Spatial Working Memory (SWM) tasks from the Cambridge Neuropsychological Test Automated Battery (CANTAB) were used to assess cognitive function. The Brunner–Munzel test was performed to compare performance errors between the TD and DD groups, and correlations between performance errors and cognitive measures were analyzed. Results: Omission and commission errors were significantly different between the groups (p &lt; 0.001), with no significant difference in motor errors (p &gt; 0.05). Omission errors were correlated with the initial thinking time mean (ITMN) in all items of the SOC task and the between errors (BE) of the SWM task. Commission errors were correlated with the ITMN in the difficult items of the SOC task and the BE of the SWM task. Additionally, motor errors were significantly correlated with problems solved in minimum moves (PSMM) and ITMN in the difficult items of the SOC task and BE in the SWM task. Conclusions: The VKET-C shows promise as an effective tool for assessing executive function and working memory in children with DDs, offering an engaging and ecologically valid alternative to traditional methods.

Multiclass classification of Autism Spectrum Disorder, attention deficit hyperactivity disorder, and typically developed individuals using fMRI functional connectivity analysis.

Neurodevelopmental conditions, such as Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD), present unique challenges due to overlapping symptoms, making an accurate diagnosis and targeted intervention difficult. Our study employs advanced machine learning techniques to analyze functional magnetic resonance imaging (fMRI) data from individuals with ASD, ADHD, and typically developed (TD) controls, totaling 120 subjects in the study. Leveraging multiclass classification (ML) algorithms, we achieve superior accuracy in distinguishing between ASD, ADHD, and TD groups, surpassing existing benchmarks with an area under the ROC curve near 98%. Our analysis reveals distinct neural signatures associated with ASD and ADHD: individuals with ADHD exhibit altered connectivity patterns of regions involved in attention and impulse control, whereas those with ASD show disruptions in brain regions critical for social and cognitive functions. The observed connectivity patterns, on which the ML classification rests, agree with established diagnostic approaches based on clinical symptoms. Furthermore, complex network analyses highlight differences in brain network integration and segregation among the three groups. Our findings pave the way for refined, ML-enhanced diagnostics in accordance with established practices, offering a promising avenue for developing trustworthy clinical decision-support systems.

Unraveling the relative abundance of psychobiotic bacteria in children with Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder characterized by social deficits. Accumulated evidence has shown a link between alterations in the composition of gut microbiota and both neurobehavioural and gastrointestinal symptoms in children with ASD which are related to the genera Lactobacillus and Bifidobacterium. These genera have been recently categorized as “psychobiotics”. Moreover, this study aimed to compare the relative abundance of psychobiotics (L. plantarum, L. reuteri, and B. longum) to the total gut microbiome in typically developing (TD) children and those with ASD in order to correlate the distribution of psychobiotic with the severity and sensory impairments in autism. The ASD children were assessed using the Childhood Autism Rating Scale (CARS), while sensory impairments were evaluated using the Short Sensory Profile (SSP). Furthermore, the gut microbiome was analyzed using the quantitative real-time PCR. The study revealed a statistically significant increase in the relative abundance of L. reuteri and L. plantarum in the TD group in comparison to ASD children. Regarding the SSP total score of ASD children, a statistically significant negative correlation was found between both Lactobacillus and L. plantarum with the under-responsive subscale. For the Autism Treatment Evaluation Checklist (ATEC) score, B. longum and Lactobacillus showed a significant positive correlation with Health/Physical/Behaviour.

Developmental trajectories in infants and pre-school children with Neurofibromatosis 1

BackgroundChildren with Neurofibromatosis 1 (NF1) show cognitive, behavioural and social differences compared to their peers. However, the age and sequence at which these differences begin to emerge is not fully understood. This prospective cohort study examines the cognitive, behavioural, ADHD trait and autism symptom development in infant and pre-school children with NF1 compared with typically developing (TD) children without a family history of neurodevelopmental conditions.MethodsData from standardised tests was gathered at 5, 10, 14, 24 and 36 months of age (NF1 n = 35, TD n = 29). Developmental trajectories of cognitive (Mullen Scales of Early Learning, MSEL) and adaptive behavioural (Vineland Adaptive Behavior Scales, VABS) development from 5 to 36 months were analysed using linear mixed modelling. Measures of ADHD (Child Behavior Checklist) and autism traits (ADOS-2, BOSA-MV and ADI-R) were assessed at 24 and 36 months.ResultsThe developmental trajectory of cognitive skills (all domains of the MSEL) and behavioural skills (four domains of the VABS) differed significantly between NF1 and TD groups. Post-hoc tests demonstrated that the NF1 participants scored significantly lower than TD participants at 24 months on all MSEL and VABS domains. The NF1 cohort demonstrated higher mean autism and ADHD traits at 24 months and 14% of the NF1 cohort met a research diagnostic classification for autism at 36 months.LimitationsThe study has a relatively small sample size due to variable retention and rolling recruitment. Due to limitations imposed by the COVID-19 pandemic, we utilised the Brief Observation of Symptoms of Autism for Minimally Verbal children (BOSA-MV) for some participants, which was administered online and may not gather as accurate a picture of traits as ADOS-2. The BOSA-MV was utilised for 41% of participants with NF1 at 36 months compared to 11% at 24 months. This may explain the reduction in the percentage of children with NF1 that met autism criteria at 36 months.ConclusionsBy 24 months of age, the NF1 cohort show lower cognitive skills and adaptive behaviour and higher levels of autism and ADHD traits as compared to TD children. This has implications for developmental monitoring and referral for early interventions.Trial registrationNot applicable.

Early Oral Language and Cognitive Predictors of Emergent Literacy Skills in Arabic-Speaking Children: Evidence From Saudi Children With Developmental Language Disorder.

Although children with developmental language disorder (DLD) are known to have difficulties with emergent literacy skills, few available studies have examined emergent literacy skills in Arabic-speaking children with DLD. Even though Arabic language characteristics, such as diglossia and orthographic structure, influence the acquisition of literacy in Arabic-speaking children, research shows that oral language skills, such as vocabulary, and cognitive skills, such as verbal short-term memory (VSTM), predict literacy in Arabic-speaking children. Moreover, linguistic and memory abilities are impaired in children with DLD, including Arabic-speaking children. The current study examines the relationships between oral language, VSTM, and emergent literacy skills in Arabic-speaking typically developing (TD) children and children with DLD. Participants were 40 TD children (20 girls; aged 4;0-6;11 [years;months]) and 26 children with DLD (nine girls, aged 4;0-6;11). All participants were monolingual Arabic speakers and matched on age and socioeconomic status. A set of comprehensive Arabic language (vocabulary knowledge, morphosyntactic, and listening comprehension skills), VSTM, and emergent literacy (phonological awareness and letter knowledge skills) tests were administered. The DLD group scored significantly lower than the TD group on language, VSTM, and emergent literacy measures. Results revealed that the contributions of oral language and VSTM to emergent literacy skills across TD and DLD groups were different. In the TD group, VSTM predicted emergent literacy skills, whereas in the DLD groups, both vocabulary knowledge and VSTM predicted emergent literacy skills. This study represents an important first step in understanding emergent literacy skills and their relationships to language and memory in Arabic-speaking children with and without DLD. The implications of these findings for clinical and education provision are discussed.

Inefficient and unique processing of social-emotional interference in school-aged children with high-functioning autism spectrum disorder.

Interest is growing in investigating the ability of children with autism spectrum disorder (ASD) to process social information under conflicting and complex environments. However, few studies have employed objective behavioral measures to directly explore the underlying profile of social-emotional interference control. In the current study, 53 children with ASD and 53 typically developing (TD) control, aged 6-12 years, completed a set of modified flanker tasks involving arrows, schematic faces, same real faces (with facial interference by the same person), and different real faces (with facial interference by different people), respectively. Response time in incongruent (RTInc) and congruent conditions (RTCon), percentage of errors in incongruent (%ErrorInc) and congruent conditions (%ErrorCon), and flanker effect calculated by ΔRT = (RTInc - RTCon)/RTCon and Δ%Error = %ErrorInc - %ErrorCon were used as outcome metrics. We obtained three major results: (1) the ASD group had longer RTInc and RTCon compared to the TD group in the arrow, schematic-face, and same real-face tasks; (2) compared with the performance in the arrow flanker task, both groups exhibited longer RTs and reduced ΔRTs in the same real-face task; however, in the schematic-face task, longer RT and reduced ΔRT were exhibited in the TD group, but not in the ASD group; and (3) in the different real-face task, ASD group had higher %Error than the TD group, and %Error was negatively correlated with RT only in the ASD group. The current study delineates the inefficient processing of social-emotional interference in school-aged children with ASD and further suggests that these children might adopt a relatively optimized strategy like symbolization when dealing with emotional conflict. However, such compensatory cognitive strategies may be exhausted along with the increase in information load. These findings provide new perspectives of considering the difference more than difficulty in the cognitive profile of ASD, which will benefit the development of targeted behavioral interventions.

Exploring vowel errors produced in nonword repetition in children with speech and language disorders.

Accurate nonword repetition (NWR) is contingent on many underlying skills, including encoding, memory and motor planning and programming. Though vowel errors are frequently associated with childhood apraxia of speech (CAS), several recent studies have found that children with developmental language disorder (DLD) produce high rates of vowel errors in NWR tasks. This retrospective analysis explored whether the overall frequency and types of vowel errors produced in NWR distinguish children with DLD, children with CAS, children with speech sound disorder (SSD) and children with typical development (TD). We present data for 24 children (six per DLD, CAS, SSD and TD groups), ranging in age from 50-92 months. Children with DLD, CAS and SSD showed similar articulation scores and children with DLD and children with CAS showed similar expressive language scores. Total vowel errors, total monophthong errors, monophthong substitutions, diphthongization errors, total diphthong errors, diphthong substitutions and diphthong reduction errors were calculated by syllable length and group. Repeated measures analyses of variance were used to examine group differences. Children with DLD and children with CAS produced a higher frequency of total vowel errors compared to children with TD. Children with DLD produced more total monophthong errors than children with TD. Children with DLD and children with CAS produced more total diphthong errors than children with TD. For children with DLD, these were characterised by diphthong substitutions. For children with CAS, these were characterised by diphthong substitutions and diphthong reduction errors. For all measures, error rates in children with SSD did not significantly differ from any of the other three groups. Preliminary evidence indicates that children with DLD and children with CAS both show high rates of vowel errors in NWR tasks and weaknesses in encoding and memory. For children with CAS, additional motor planning difficulties are associated with an increased likelihood to reduce diphthongs. Children with SSD show more mild processing difficulties than children with DLD and children with CAS, though they do not perform as well as TD peers. Future work should replicate and further specify the processing weaknesses that affect vowel accuracy in NWR tasks in a larger sample. What is already known on the subject Nonword repetition (NWR) tasks are often included in diagnostic batteries to identify children with developmental language disorder (DLD). Poor performance on these tasks have historically been attributed to phonological working memory deficits in children with DLD. However, repeating nonwords relies on a number of underlying processing skills and many of these skills are affected to varying degrees in children with speech and language disorders. An in-depth analysis of vowel errors has the potential to reveal the shared as well as specific underlying processing weaknesses in children with DLD, children with childhood apraxia of speech (CAS) and children with speech sound disorder (SSD). What this paper adds to existing knowledge We found that children with DLD and children with CAS show low vowel competence compared to children with typical development. A nuanced examination of vowel error types further revealed that children with DLD and children with CAS show weaknesses in encoding and memory. Motor planning and programming weaknesses were unique to CAS. Children with SSD show more mild processing deficits and their performance did not significantly differ from any of the other three groups. What are the clinical implications of this work? Examining the types of vowel errors produced by children with DLD, children with CAS and children with SSD in NWR allows us to further specify the underlying processing weaknesses that differentiate these three groups. This research informs theoretical accounts of language processing in children with different types of speech and language disorders and has the potential to improve the diagnostic utility of NWR tasks.

Characteristics of Nasal Coarticulation by Nasality Visualization System in Children with Speech Sound Disorders

Objectives: In this study, we analyzed the nasal coarticulation characteristics of children with and without speech sound disorders by comparing nasalance scores according to speech contexts. Methods: The subjects of this study were 30 children, 15 children with speech sound disorder (SSD) and 15 typically developing (TD) children, aged 4 to 6 years old. Subjects were asked to speak stimuli in different speech contexts-low vs. high vowels, nasal consonant+vowel (NV) vs. vowel+nasal consonant (VN) syllables, words vs. nonwords - and nasalance scores were measured using the Nasality Visualization System (NVS) on their speech samples. Results: First, both groups showed significantly higher naslance scores for high vowels compared to low vowels, with a significant between-group difference in high vowel. Second, both groups showed significantly higher nasalance scores for VN syllables than for NV syllables, with no between-group difference. Third, both groups showed significantly lower nasalance scores in nonwords compared to words. While there was no group difference in the words, the nasalance scores of the SSD group was lower in the nonwords, which was significantly different from that of the TD groups. Conclusion: These results suggest that the SSD group exhibits somewhat different nasal characteristics than the TD group, and furthermore, that SSD children articulate phoneme sequences more segmentally in unlearned nonword contexts.

Foveal crowding in children with developmental dyslexia.

Excessive crowding in the visual periphery has been demonstrated in children with developmental dyslexia (DD). However, less is known about crowding in the fovea, even though foveal crowding is at least equally important, as reading is mostly accomplished through foveal vision. Here we used a special set of digitstimuli (Pelli fonts) to measure foveal crowding in DD and DD + ADHD children, and compared it to that in TD (typically developing) and ADHD children. We also used the Chinese reading acuity charts (C-READ) to assess the maximum reading speed and reading acuity, along with tests to evaluate cognitive attributes including phonological awareness, rapid automatized naming, morphological awareness, and orthographic knowledge. The results indicate significantly stronger foveal crowding in the DD and DD + ADHD groups, as well as in the ADHD group, than in the TD group. Furthermore, the DD and DD + ADHD groups exhibited poorer maximum reading speed and reading acuity compared to the ADHD and TD groups.Within the two DD groups, theslower maximum reading speed and higher reading acuitycan be predicted bystronger foveal crowding. In addition, the DD and DD + ADHD groups performed the worst in four cognitive skills, with the DD group showing negative correlations between foveal crowding and performances across all these skills. Our findings thus move beyond previously well-documented peripheral crowding in dyslexia, and the easy administration of the Pelli-font-based crowding test may be useful for early diagnosis of developmental dyslexia in young children.

Implicit learning in children and adolescents with and without autism spectrum disorders: Exploring the effects of individual differences.

Implicit learning plays an important role in the acquisition of various skills that are often deficient in individuals with autism spectrum disorder (ASD). The present study examines the implicit learning ability of children and adolescents with ASD, by comparing it to that of a typical group of peers, using the Artificial Grammar Learning (AGL) task. In addition, this study investigates whether the above ability is associated with individual characteristics, namely intelligence quotient (IQ), ASD symptoms severity, and individual perception style (global/holistic or local/focused). The sample consisted of 20 individuals with mild to relatively severe ASD symptoms and 20 age- and gender-matched typically developing (TD) individuals. The unconscious (implicit) nature of learning was assessed via a subjective measure, the "no-loss gambling" method, which allows an unbiased evaluation of the confidence accompanying each judgement. The results provided evidence of implicit learning, which was preserved in the ASD group, although reduced relative to the typical group. Multiple linear regressions with interaction terms between group and participants' scores on the Wechsler Abbreviated Scale of Intelligence (WASI), the Childhood Autism Rating Scale (CARS), and performance on a Navon-type task examined whether the possible relationships between each of the above scores and AGL and implicit learning differ in the two groups. Implicit learning was not significantly associated with IQ, ASD symptoms severity, or individual perception style (except for perception style in terms of reaction times [RTs] for the TD group). These results confirm and extend earlier findings supporting the resilience of implicit learning to individual differences.

Quantitative assessment of brain structural abnormalities in children with autism spectrum disorder based on artificial intelligence automatic brain segmentation technology and machine learning methods

Rationale and objectivesTo explore the characteristics of brain structure in Chinese children with autism spectrum disorder (ASD) using artificial intelligence automatic brain segmentation technique, and to diagnose children with ASD using machine learning (ML) methods in combination with structural magnetic resonance imaging (sMRI) features. MethodsA total of 60 ASD children and 48 age- and sex-matched typically developing (TD) children were prospectively enrolled from January 2023 to April 2024. All subjects were scanned using 3D-T1 sequences. Automated brain segmentation techniques were utilized to obtain the standardized volume of each brain structure (the ratio of the absolute volume of brain structure to the whole brain volume). The standardized volumes of each brain structure in the two groups were statistically compared, and the volume data of brain areas with significant differences were combined with ML methods to diagnose and predict ASD patients. ResultsCompared with the TD group, the volumes of the right lateral orbitofrontal cortex, right medial orbitofrontal cortex, right pars opercularis, right pars triangularis, left hippocampus, bilateral parahippocampal gyrus, left fusiform gyrus, right superior temporal gyrus, bilateral insula, bilateral inferior parietal cortex, right precuneus cortex, bilateral putamen, left pallidum, and right thalamus were significantly increased in the ASD group (P< 0.05). Among six ML algorithms, support vector machine (SVM) and adaboost (AB) had better performance in differentiating subjects with ASD from those TD children, with their average area under curve (AUC) reaching 0.91 and 0.92, respectively. ConclusionAutomatic brain segmentation technology based on artificial intelligence can rapidly and directly measure and display the volume of brain structures in children with autism spectrum disorder and typically developing children. Children with ASD show abnormalities in multiple brain structures, and when paired with sMRI features, ML algorithms perform well in the diagnosis of ASD.

Aberrant Flexibility of Dynamic Brain Network in Patients with Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a collection of neurodevelopmental disorders whose pathobiology remains elusive. This study aimed to investigate the possible neural mechanisms underlying ASD using a dynamic brain network model and a relatively large-sample, multi-site dataset. Resting-state functional magnetic resonance imaging data were acquired from 208 ASD patients and 227 typical development (TD) controls, who were drawn from the multi-site Autism Brain Imaging Data Exchange (ABIDE) database. Brain network flexibilities were estimated and compared between the ASD and TD groups at both global and local levels, after adjusting for sex, age, head motion, and site effects. The results revealed significantly increased brain network flexibilities (indicating a decreased stability) at the global level, as well as at the local level within the default mode and sensorimotor areas in ASD patients than TD participants. Additionally, significant ASD-related decreases in flexibilities were also observed in several occipital regions at the nodal level. Most of these changes were significantly correlated with the Autism Diagnostic Observation Schedule (ADOS) total score in the entire sample. These results suggested that ASD is characterized by significant changes in temporal stabilities of the functional brain network, which can further strengthen our understanding of the pathobiology of ASD.

Voicing discrimination as a diagnostic marker of developmental language disorder

This study examines how children with developmental language disorder (DLD) discriminate voiced and voiceless consonants and their processing speed. It also explores the contribution of factors like age, nonverbal intelligence, vocabulary, morphosyntactic skills, and sentence repetition in explaining speech perception abilities. Fourteen Cypriot Greek children with DLD and 14 peers with typical development (TD) aged 7; 10–10; 4 were recruited. Children were divided into four groups based on age and condition: young-DLD, young-TD, old-DLD, and old-TD. All children participated in an AX task, which measured their ability to discriminate sounds and their processing speed. They also completed a nonverbal intelligence test and a DVIQ test, which provided measures of various language abilities. The results demonstrated that the young-DLD group exhibited lower performance in discriminating consonants compared to the young-TD group, while such differences were not observed between the old-DLD and old-TD groups. Furthermore, while no significant differences in processing time were found between the DLD and TD groups, both young DLD and TD groups displayed longer processing times compared to their older counterparts. Age was the best-contributing factor to speech perception abilities in children with DLD in contrast to morphosyntax and vocabulary for children with TD. These findings highlight the role of voicing discrimination as a diagnostic marker of DLD as opposed to reaction time. Moreover, they underscore the crucial role of age in detecting DLD. The language developmental trajectories of children with TD appear distinct from those with DLD, as evidenced by variations in contributing factors between the two groups. These disparities can be attributed to the diverse nature of the DLD population, the therapies they receive, the compensatory strategies they employ, and the potential impact of other contributing factors.

What Silent Pauses Can 'Tell' Us About the Storytelling Skills of Autistic Children: Relations Between Pausing, Language Skills and Executive Functions.

Silent pauses may serve communicative purposes such as demarcating boundaries between discourse units in language production. Previous research has shown that autistic children differ in their pausing behavior from typically-developing (TD) peers, however, the factors behind this difference remain underexplored. The current study was aimed at comparing the use of silent pauses in the narrative production of autistic children and age-matched TD children, and also to identify possible relations between pausing behavior and the children's language and executive function abilities. According to the study's findings, the autistic children did not differ from their TD peers in the use of grammatical pauses, however, the former tended to produce significantly less syntactically complex narratives than the TD group, which increased the likelihood that the autistic group would pause appropriately at phrasal boundaries. Thoughwe have found low rates of ungrammatical silent pauses and omitted pauses in obligatory discourse contexts across both groups, autistic children with lower cognitive flexibility tended to use more ungrammatical pauses than their peers with higher cognitive flexibility scores. Also, the autistic group tended to omit obligatory silent pauses more often as their narration became more complex. The results demonstrate that syntactic complexity in narrative production modulated autistic children's pausing behavior, and that structurally simple narrations boosted the autistic group's appropriate use of grammatical pauses. The overall findings also demonstrate the importance of studying silent pauses in the narrative discourse of autistic children, and also highlight the links between silent pauses and the children's syntactic and cognitive skills.

Caregivers’ reports of the home literacy environments of children with developmental language disorder and typically developing peers during the COVID-19 pandemic

Purpose Children with developmental language disorder (DLD) are at heightened risk for reading difficulty. We investigated the home literacy environments of kindergarten children with DLD and typically developing (TD) peers during the COVID-19 pandemic. Method We analysed scores from standardised assessments of oral language, nonverbal intelligence, and word reading in conjunction with home literacy questionnaire data at three time points. Result Frequency of engagement in home literacy activities did not differ by group during school closures or when schools reopened. Caregivers from both groups reported increased home literacy engagement during closures. Engagement returned to pre-pandemic levels when schools reopened. For the DLD group, the child’s word reading ability and interest in literacy were positively associated with the home literacy environment. Family history of language and/or literacy difficulty was negatively associated with the home literacy environment. For the TD group, only the child’s interest in literacy was positively associated with the home literacy environment. Conclusion These findings elucidate the need for further research related to home literacy and families of children with DLD, with a focus on identifying potential strengths and vulnerabilities related to child and caregiver factors.

The differential diagnostic utility of the social communication questionnaire in mild intellectual disability and autism spectrum disorder: a case control study

Objectives This study investigated the utility of specific predictive and discriminative items within the Social Communication Questionnaire (SCQ) for distinguishing between autism spectrum disorder (ASD), intellectual disability (ID), and co-occurring ASD + ID in children. Methods A total of 137 children aged 4 to 12 years (52 typically developing (TD), 34 ASD, 26 ID, 25 ASD + ID) were included in the study. Cognitive development assessments were conducted for the ASD, ID, and ASD + ID groups in suitable cases. SCQ items were evaluated both in terms of total and subscale scores and individual items across groups. Results The TD group had the lowest scores on the SCQ, while the ID group had significantly lower total and communication subscale scores on the SCQ compared to the ASD group. Additionally, there were no significant differences in SCQ scores between the ASD group and the co-occurring ASD + ID group. The ID group had lower scores on both the communication subscale and the total SCQ compared to the co-occurring ASD + ID group. The Receiver Operating Characteristic (ROC) analysis of SCQ total scores for differentiating the ASD + ID group from the ID group revealed an AUC of 0.834 for the total score, with a cutoff of 16.50 (sensitivity: 76%, specificity: 80.8%). Logistic regression identified 29 significant predictors distinguishing ASD + ID from ID, with absence of ‘Group play’ (p = 0.003, OR = 4.010) being the most predictive being in the ASD + ID group. Among the top items in the ROC analysis for the ID and ASD + ID groups, ‘Friends (absence of close or best friends)’, ‘Range of facial expression (absence of normal facial expressions)’, and absence of ‘Head shaking to mean no’ were identified as the highest discriminative factors. Conclusions This study highlights the potential of using the SCQ alongside clinical assessments to diagnose ASD in individuals with ID, emphasizing non-verbal communication, participation in group play, presence of close or best friends, and range of facial expression as key distinguishing factors. Further research with larger samples and comparisons of educational interventions based on these indicators is essential for developing tailored educational programs for the ASD + ID group.