Learning of skilled movements via imitation in ASD

A Multi-Trait Multi-Method Examination of Psychometric Instrument Performance in Autism Spectrum Disorder

Anecdotal evidence has suggested that rater-based measures (e.g., parent report) may have strong across-trait/within-individual covariance that detracts from trait-specific measurement precision; rater measurement-related bias may help explain poor correlation within Autism Spectrum Disorder (ASD) samples between rater-based and performance-based measures of the same trait. We used a multi-trait, multi-method approach to examine method-associated bias within an ASD sample (n = 83). We examined performance/rater-instrument pairs for attention, inhibition, working memory, motor coordination, and core ASD features. Rater-based scores showed an overall greater methodology bias (57% of variance in score explained by method), while performance-based scores showed a weaker methodology bias (22%). The degree of inter-individual variance explained by method alone substantiates an anecdotal concern associated with the use of rater measures in ASD.

Connectivity differences between inferior frontal gyrus and mentalizing network in autism as compared to developmental coordination disorder and non-autistic youth

Prior studies have compared neural connectivity during mentalizing tasks in autism (ASD) to non-autistic individuals and found reduced connectivity between the inferior frontal gyrus (IFG) and mentalizing regions. However, given that the IFG is involved in motor processing, and about 80% of autistic individuals have motor-related difficulties, it is necessary to explore if these differences are specific to ASD or instead similar across other developmental motor disorders, such as developmental coordination disorder (DCD). Participants (29 ASD, 20 DCD, 31 typically developing [TD]; ages 8-17) completed a mentalizing task in the fMRI scanner, where they were asked to think about why someone was performing an action. Results indicated that the ASD group, as compared to both TD and DCD groups, showed significant functional connectivity differences when mentalizing about other's actions. The left IFG seed revealed ASD connectivity differences with the: bilateral temporoparietal junction (TPJ), left insular cortex, and bilateral dorsolateral prefrontal cortex (DLPFC). Connectivity differences using the right IFG seed revealed ASD differences in the: left insula, and right DLPFC. These results indicate that connectivity differences between the IFG, mentalizing regions, emotion and motor processing regions are specific to ASD and not a result of potentially co-occurring motor differences.

Autism-Related Differences in Cortical Activation When Observing, Producing, and Imitating Communicative Gestures: An fNIRS Study

Children with autism spectrum disorder (ASD) have difficulties in gestural communication during social interactions. However, the neural mechanisms involved in naturalistic gestural communication remain poorly understood. In this study, cortical activation patterns associated with gestural communication were examined in thirty-two children with and without ASD (mean age: 11.0 years, SE: 0.6 years). Functional near-infrared spectroscopy (fNIRS) was used to record cortical activation while children produced, observed, or imitated communicative gestures. Children with ASD demonstrated more spatial and temporal errors when performing and imitating communicative gestures. Although both typically developing (TD) children and children with ASD showed left-lateralized cortical activation during gesture production, children with ASD showed hyperactivation in the middle/inferior frontal gyrus (MIFG) during observation and imitation, and hypoactivation in the middle/superior temporal gyrus (MSTG) during gesture production compared to their TD peers. More importantly, children with ASD exhibited greater MSTG activation during imitation than during gesture production, suggesting that imitation could be an effective intervention strategy to engage cortical regions crucial for processing and producing gestures. Our study provides valuable insights into the neural mechanisms underlying gestural communication difficulties in ASD, while also identifying potential neurobiomarkers that could serve as objective measures for evaluating intervention effectiveness in children with ASD.

From "one big clumsy mess" to "a fundamental part of my character." Autistic adults' experiences of motor coordination

Altered motor coordination is common in autistic individuals affecting a range of movements such as manual dexterity, eye-hand coordination, balance and gait. However, motor coordination is not routinely assessed leading to undiagnosed and untreated motor coordination difficulties, particularly in adults. Few studies have investigated motor coordination difficulties and their impact from the viewpoint of autistic people. Therefore, the current study used FGs and thematic analysis to document the experience of motor coordination difficulties from the viewpoint of 17 autistic adults. Four main themes were identified. First, motor coordination difficulties were pervasive and variable, being present life-long and within multiple movements and affecting many aspects of life. Furthermore, the nature of the difficulties was variable within and between participants along with differing awareness of coordination ability. Second, participants described motor coordination as an active process, requiring concentration for most actions and at a level seemingly greater than other people. Third, motor coordination difficulties impacted upon social and emotional wellbeing by placing strain on relationships, prompting bullying and exclusion, putting safety at risk and causing a range of negative emotions. Fourth, in the absence of any support, participants described multiple learning and coping strategies. Findings highlight how it is essential to address the current lack of support for motor coordination considering the significant social and emotional consequences described by our participants. Further investigation of motor learning and interactions between sensory and motor performance in autistic adults is also warranted.

New Methods for Unraveling Imitation Accuracy Differences Between Children with Autism and Typically Developing Peers

This study applies methods used in sign language and gesture research to better understand reduced imitation accuracy (IA) of actions and gestures in children with autism spectrum disorder (ASD), and we addressed contrasting theories on IA in ASD and the role of objects and meanings in imitation. Eight male children with ASD with a mean chronological age (CA) of 86.76 months (SD = 10.74, range 70.5-104.4) and 22 male and female peers with typical development (TD) and a mean CA of 85.44 months (SD = 7.95, range 73.4-96.7) imitated videos of an adult performing actions with objects, representational gestures, conventional gestures and meaningless gestures. We measured accuracy as ability to effectively reproduce features (handshape, palm orientation, location, movement direction and type) and timing (speed) of observed actions/gestures, after ruling out cases of specular (i.e., mirror-like) versus anatomical imitation. Results highlighted significantly lower feature and timing accuracy in children with ASD with respect to the TD group across tasks, and these findings supported sensory-motor theories of IA in ASD. Our data also showed the different impact of objects and meanings within groups. Overall, these results suggest validity to our assessment method and suggested the importance of considering both discreet variables (i.e., variables describing action/gesture feature accuracy, e.g. handshape, movement direction) and continuous variables (i.e., kinematic variables, e.g. speed) in evaluating IA in autism.

What affects gestural learning in children with and without Autism? The role of prior knowledge and imitation

The present study examined whether prior knowledge to the learning target and imitation during learning affected learning outcomes in preschool children with autism spectrum disorder (ASD, N = 22) compared to their typically developing (TD, N = 15) peers. Children's gestural skills in recognizing and producing the target gestures before and after the training, as well as their imitative behavior during the training were coded. Results showed that consistent prior knowledge benefited gestural learning in both groups. Besides, only children with ASD were hindered by inconsistent prior knowledge. Notably, the effect of imitation was not significant in the ASD group. In conclusion, the learning process in children with ASD may differ from those with typical development, suggesting special-designed interventions are required.

B-value and empirical equivalence bound: A new procedure of hypothesis testing

In this study, we propose a two-stage procedure for hypothesis testing, where the first stage is conventional hypothesis testing and the second is an equivalence testing procedure using an introduced empirical equivalence bound (EEB). In 2016, the American Statistical Association released a policy statement on P-values to clarify the proper use and interpretation in response to the criticism of reproducibility and replicability in scientific findings. A recent solution to improve reproducibility and transparency in statistical hypothesis testing is to integrate P-values (or confidence intervals) with practical or scientific significance. Similar ideas have been proposed via the equivalence test, where the goal is to infer equality under a presumption (null) of inequality of parameters. However, the definition of scientific significance/equivalence can sometimes be ill-justified and subjective. To circumvent this drawback, we introduce the B-value and the EEB, which are both estimated from the data. Performing a second-stage equivalence test, our procedure offers an opportunity to improve the reproducibility of findings across studies.

Computational Measurement of Motor Imitation and Imitative Learning Differences in Autism Spectrum Disorder: Computational Motor Imitation Measurement in ASD

Motor imitation is a critical developmental skill area that has been strongly and specifically linked to autism spectrum disorder (ASD). However, methodological variability across studies has precluded a clear understanding of the extent and impact of imitation differences in ASD, underscoring a need for more automated, granular measurement approaches that offer greater precision and consistency. In this paper, we investigate the utility of a novel motor imitation measurement approach for accurately differentiating between youth with ASD and typically developing (TD) youth. Findings indicate that youth with ASD imitate body movements significantly differently from TD youth upon repeated administration of a brief, simple task, and that a classifier based on body coordination features derived from this task can differentiate between autistic and TD youth with 82% accuracy. Our method illustrates that group differences are driven not only by interpersonal coordination with the imitated video stimulus, but also by intrapersonal coordination. Comparison of 2D and 3D tracking shows that both approaches achieve the same classification accuracy of 82%, which is highly promising with regard to scalability for larger samples and a range of non-laboratory settings. This work adds to a rapidly growing literature highlighting the promise of computational behavior analysis for detecting and characterizing motor differences in ASD and identifying potential motor biomarkers.

Unique deficit in embodied simulation in autism: An fMRI study comparing autism and developmental coordination disorder

A deficit in pre‐cognitively mirroring other people's actions and experiences may be related to the social impairments observed in autism spectrum disorder (ASD). However, it is unclear whether such embodied simulation deficits are unique to ASD or instead are related to motor impairment, which is commonly comorbid with ASD. Here we aim to disentangle how, neurologically, motor impairments contribute to simulation deficits and identify unique neural signatures of ASD. We compare children with ASD (N = 30) to children with Developmental Coordination Disorder (DCD; N = 23) as well as a typically developing group (N = 33) during fMRI tasks in which children observe, imitate, and mentalize about other people's actions. Results indicate a unique neural signature in ASD: during action observation, only the ASD group shows hypoactivity in a region important for simulation (inferior frontal gyrus, pars opercularis, IFGop). However, during a motor production task (imitation), the IFGop is hypoactive for both ASD and DCD groups. For all tasks, we find correlations across groups with motor ability, even after controlling for age, IQ, and social impairment. Conversely, across groups, mentalizing ability is correlated with activity in the dorsomedial prefrontal cortex when controlling for motor ability. These findings help identify the unique neurobiological basis of ASD for aspects of social processing. Furthermore, as no previous fMRI studies correlated brain activity with motor impairment in ASD, these findings help explain prior conflicting reports in these simulation networks.

Clustering Analysis Supports the Detection of Biological Processes Related to Autism Spectrum Disorder

Genome sequencing has identified a large number of putative autism spectrum disorder (ASD) risk genes, revealing possible disrupted biological pathways; however, the genetic and environmental underpinnings of ASD remain mostly unanswered. The presented methodology aimed to identify genetically related clusters of ASD individuals. By using the VariCarta dataset, which contains data retrieved from 13,069 people with ASD, we compared patients pairwise to build “patient similarity matrices”. Hierarchical-agglomerative-clustering and heatmapping were performed, followed by enrichment analysis (EA). We analyzed whole-genome sequencing retrieved from 2062 individuals, and isolated 11,609 genetic variants shared by at least two people. The analysis yielded three clusters, composed, respectively, by 574 (27.8%), 507 (24.6%), and 650 (31.5%) individuals. Overall, 4187 variants (36.1%) were common to the three clusters. The EA revealed that the biological processes related to the shared genetic variants were mainly involved in neuron projection guidance and morphogenesis, cell junctions, synapse assembly, and in observational, imitative, and vocal learning. The study highlighted genetic networks, which were more frequent in a sample of people with ASD, compared to the overall population. We suggest that itemizing not only single variants, but also gene networks, might support ASD etiopathology research. Future work on larger databases will have to ascertain the reproducibility of this methodology.