Autism Spectrum Disorder Participants Research Articles

The relationship between gamma-band neural oscillations and language skills in youth with Autism Spectrum Disorder and their first-degree relatives

BackgroundMost children with Autism Spectrum Disorder (ASD) have co-occurring language impairments and some of these autism-specific language difficulties are also present in their non-autistic first-degree relatives. One of the possible neural mechanisms associated with variability in language functioning is alterations in cortical gamma-band oscillations, hypothesized to be related to neural excitation and inhibition balance.MethodsWe used a high-density 128-channel electroencephalography (EEG) to register brain response to speech stimuli in a large sex-balanced sample of participants: 125 youth with ASD, 121 typically developing (TD) youth, and 40 unaffected siblings (US) of youth with ASD. Language skills were assessed with Clinical Evaluation of Language Fundamentals.ResultsFirst, during speech processing, we identified significantly elevated gamma power in ASD participants compared to TD controls. Second, across all youth, higher gamma power was associated with lower language skills. Finally, the US group demonstrated an intermediate profile in both language and gamma power, with nonverbal IQ mediating the relationship between gamma power and language skills.LimitationsWe only focused on one of the possible neural contributors to variability in language functioning. Also, the US group consisted of a smaller number of participants in comparison to the ASD or TD groups. Finally, due to the timing issue in EEG system we have provided only non-phase-locked analysis.ConclusionsAutistic youth showed elevated gamma power, suggesting higher excitation in the brain in response to speech stimuli and elevated gamma power was related to lower language skills. The US group showed an intermediate pattern of gamma activity, suggesting that the broader autism phenotype extends to neural profiles.

Autonomic and hedonic response to affective touch in autism spectrum disorder.

Interpersonal touch plays a crucial role in shaping relationships and encouraging social connections. Failure in processing tactile input or abnormal tactile sensitivity may hamper social behaviors and have severe consequences in individuals' relational lives. Autism Spectrum Disorder (ASD) is characterized by both sensory disruptions and social impairments, making affective touch an ideal meeting point for understanding these features in ASD individuals. By integrating behavioral and physiological measures, we investigated the effects of affective touch on adult individuals with ASD from both an implicit and explicit perspective. Specifically, at an implicit level, we investigated whether and how receiving an affective touch influenced participants' skin conductance tonic and phasic components. At the explicit level, we delved into the affective and unpleasant features of affective touch. Overall, we observed lower skin conductance level in ASD compared to TD subjects. Interestingly, the typically developing (TD) group showed an increased autonomic response for affective touch compared to a control touch, while ASD subjects' autonomic response did not differ between the two conditions. Furthermore, ASD participants provided higher ratings for both the affective and unpleasant components of the touch, compared to TD subjects. Our results reveal a noteworthy discrepancy in ASD population between the subjective experience, characterized by amplified hedonic but also unpleasant responses, and the physiological response, marked by a lack of autonomic activation related to affective touch. This insightful dissociation seems crucial for a deeper understanding of the distinctive challenges characterizing people with ASD and may have implications for diagnosis and therapeutic approaches.

Conduction velocity, G-ratio, and extracellular water as microstructural characteristics of autism spectrum disorder.

The neuronal differences contributing to the etiology of autism spectrum disorder (ASD) are still not well defined. Previous studies have suggested that myelin and axons are disrupted during development in ASD. By combining structural and diffusion MRI techniques, myelin and axons can be assessed using extracellular water, aggregate g-ratio, and a new approach to calculating axonal conduction velocity termed aggregate conduction velocity, which is related to the capacity of the axon to carry information. In this study, several innovative cellular microstructural methods, as measured from magnetic resonance imaging (MRI), are combined to characterize differences between ASD and typically developing adolescent participants in a large cohort. We first examine the relationship between each metric, including microstructural measurements of axonal and intracellular diffusion and the T1w/T2w ratio. We then demonstrate the sensitivity of these metrics by characterizing differences between ASD and neurotypical participants, finding widespread increases in extracellular water in the cortex and decreases in aggregate g-ratio and aggregate conduction velocity throughout the cortex, subcortex, and white matter skeleton. We finally provide evidence that these microstructural differences are associated with higher scores on the Social Communication Questionnaire (SCQ) a commonly used diagnostic tool to assess ASD. This study is the first to reveal that ASD involves MRI-measurable in vivo differences of myelin and axonal development with implications for neuronal and behavioral function. We also introduce a novel formulation for calculating aggregate conduction velocity, that is highly sensitive to these changes. We conclude that ASD may be characterized by otherwise intact structural connectivity but that functional connectivity may be attenuated by network properties affecting neural transmission speed. This effect may explain the putative reliance on local connectivity in contrast to more distal connectivity observed in ASD.

Sensory phenomena in children with Tourette syndrome or autism spectrum disorder.

Tourette syndrome (TS) and autism spectrum disorder (ASD) are two neurodevelopmental disorders with an onset before the age of 18 years. TS patients frequently reported atypical sensory phenomena (SP). Sensory processing abnormalities are also particularly frequent in ASD individuals. Considering the higher rate of atypical sensory behaviours in both neurodevelopmental disorders, in the present study we analysed sensory experiences in patients with ASD and in patients with TS. We enrolled patients with a primary diagnosis of TS or ASD. All participants were assessed for primary diagnosis and associated comorbidities. The presence of sensory behaviours was investigated using the University of Sao Paulo's Sensory Phenomena Scale (USP-SPS). SP were significantly more represented in the ASD-group versus TS-group, except for sound just-right perceptions and energy to released. ASD participants presented higher mean scores in all fields of USP-SPS severity scale respect on TS patients and healthy controls. The USP-SPS total score had significant positive correlations with the CYBOCS and MASC total scores in the TS cohort. In the ASD group, the USP-SPS total score was significantly negative correlated with the total IQ and marginally positive correlated with ADOS total score. SP are a frequently reported characteristic both of ASD and TS. Future studies are needed to better evaluate the differences on their phenomenology in patients with TS and ASD.

Comparison of The Effectiveness of Fones and Modified Bass Teeth Brushing Methods on Reducing Plaque Index in Autism Spectrum Disorders Children Aged 6-12 Years

Children with special needs, such as Autism Spectrum Disorders (ASD), are at a higher risk of developing caries. Brushing teeth is the most effective preventive measure to avoid the risk of developing dental and oral diseases. The Fones teeth brushing method has been proven to reduce dental plaque in ASD patients due to its simplicity. The modified Bass method is also reported to be effective in removing interdental plaque. This study is to investigate whether there is a difference in the effectiveness of teeth brushing techniques, specifically the Fones method and the modified Bass method, in reducing the plaque index in children with ASD. A quasi-experimental study with a pre-test and post-test design was conducted, with 24 ASD participants aged between 6-12 years. The Loe and Silness Plaque Index was used to measure the plaque index. Data analysis was conducted by comparing the two methods using a Paired t-test and a one-way ANOVA test. Indicate that there is a significant difference between the two treatments with a significance value of 0.039 (P<0.05). The average plaque index from the Fones method was found to be 0.444 greater than the modified Bass method. In conclusion: There is a difference in effectiveness between the Fones teeth brushing method and the modified Bass teeth brushing method in reducing the plaque index in children with ASD aged 6-12 years.

Differences in the link between social trait judgment and socio-emotional experience in neurotypical and autistic individuals

Neurotypical (NT) individuals and individuals with autism spectrum disorder (ASD) make different judgments of social traits from others’ faces; they also exhibit different social emotional responses in social interactions. A common hypothesis is that the differences in face perception in ASD compared with NT is related to distinct social behaviors. To test this hypothesis, we combined a face trait judgment task with a novel interpersonal transgression task that induces measures social emotions and behaviors. ASD and neurotypical participants viewed a large set of naturalistic facial stimuli while judging them on a comprehensive set of social traits (e.g., warm, charismatic, critical). They also completed an interpersonal transgression task where their responsibility in causing an unpleasant outcome to a social partner was manipulated. The purpose of the latter task was to measure participants’ emotional (e.g., guilt) and behavioral (e.g., compensation) responses to interpersonal transgression. We found that, compared with neurotypical participants, ASD participants’ self-reported guilt and compensation tendency was less sensitive to our responsibility manipulation. Importantly, ASD participants and neurotypical participants showed distinct associations between self-reported guilt and judgments of criticalness from others' faces. These findings reveal a novel link between perception of social traits and social emotional responses in ASD.

Serum brain-derived neurotrophic factor concentration is different between autism spectrum disorders and intellectual disability children and adolescents

PurposeRecent studies showed that mature brain-derived neurotrophic factor (mBDNF) and its precursor proBDNF are associated with autism spectrum disorders (ASD). Whether their levels are different between ASD and intellectual disability (ID) subjects is not clear. The aim of this study is to compare the serum mBDNF and proBDNF concentration, and mBNDF/proBDNF ratio in ASD and ID volunteers. MethodsChildren and adolescents with ASD or ID between the ages of 4 and 22 were recruited in Tianjin, China. Serum mBDNF and proBDNF level were tested and Wechsler Preschool and Primary Scale of Intelligence (WPPSI), Wechsler Intelligence Scale for Children (WISC), and Childhood Autism Rating Scale (CARS) evaluations were conducted. ResultsSerum mBDNF concentration and the ratio of mBDNF to proBDNF was higher in ASD subjects than that in ID subjects (P = 0.035 and P < 0.001, respectively), while serum proBDNF of ASD participants was lower compared to that of ID participants (P < 0.001). CARS score was positively correlated with serum mBDNF level (r = 0.33, P = 0.004) and m/p ratio (r = 0.39, P < 0.001), and negatively correlated with serum proBDNF level (r = −0.39, <0.001) after adjusting for age and IQ. The AUC of mBDNF, proBDNF, and m/p ratio were 0.741, 0.790, and 0.854, respectively, after adjusted for age and IQ. ConclusionSerum mBDNF, proBDNF and m/p ratio were different between ASD and ID group. The three biomarkers displayed good diagnostic values for classification of ASD and ID subjects.

Abnormal functional connectivity of the reward network is associated with social communication impairments in autism spectrum disorder: A large-scale multi-site resting-state fMRI study

BackgroundThe social motivation hypothesis proposes that the social deficits of autism spectrum disorder (ASD) are related to reward system dysfunction. However, functional connectivity (FC) patterns of the reward network in ASD have not been systematically explored yet. MethodsThe reward network was defined as eight regions of interest (ROIs) per hemisphere, including the nucleus accumbens (NAc), caudate, putamen, anterior cingulate cortex (ACC), ventromedial prefrontal cortex (vmPFC), orbitofrontal cortex (OFC), amygdala, and insula. We computed both the ROI-wise resting-state FC and seed-based whole-brain FC in 298 ASD participants and 348 typically developing (TD) controls from the Autism Brain Imaging Data Exchange I dataset. Two-sample t-tests were applied to obtain the aberrant FCs. Then, the association between aberrant FCs and clinical symptoms was assessed with Pearson's correlation or Spearman's correlation. In addition, Neurosynth Image Decoder was used to generate word clouds verifying the cognitive functions of the aberrant pathways. Furthermore, a three-way multivariate analysis of variance (MANOVA) was conducted to examine the effects of gender, subtype and age on the atypical FCs. ResultsFor the within network analysis, the left ACC showed weaker FCs with both the right amygdala and left NAc in ASD compared with TD, which were negatively correlated with the Autism Diagnostic Observation Schedule (ADOS) total scores and Social Responsiveness Scale (SRS) total scores respectively. For the whole-brain analysis, weaker FC (i.e., FC between the left vmPFC and left calcarine gyrus, and between the right vmPFC and left precuneus) accompanied by stronger FC (i.e., FC between the left caudate and right insula) were exhibited in ASD relative to TD, which were positively associated with the SRS motivation scores. Additionally, we detected the main effect of age on FC between the left vmPFC and left calcarine gyrus, of subtype on FC between the right vmPFC and left precuneus, of age and age-by-gender interaction on FC between the left caudate and right insula. ConclusionsOur findings highlight the crucial role of abnormal FC patterns of the reward network in the core social deficits of ASD, which have the potential to reveal new biomarkers for ASD.

Corneal structural alterations in autism spectrum disorder: An in vivo confocal microscopy study.

Individuals with autism spectrum disorder (ASD) often exhibit joint hypermobility and connective tissue disorders. However, it remains unclear if ASD individuals also have structural alterations in the connective tissue of the cornea. This study aims to determine whether the Kobayashi structure (K-structure) characteristics differ between adults with ASD and typically developing controls (TDC) and explore the clinical correlates of the K-structure abnormality. We recruited 30 ASD adults and 35 TDC. Corneal structures, particularly the K-structure in the Bowman's layer, of the participants were examined using in vivo confocal microscopy (IVCM), and a K-grading ranging from 1 to 4 was given to each eye based on the level of morphological mosaicism. The ASD participants' eyes received a significantly higher single-eye K-grading than that of the TDC eyes (p < 0.001), and the medians [25th, 75th percentile] of bilateral-eye summed K-grading were 8 [7, 8] and 5 [4, 6] in ASD and TDC, respectively (p < 0.001). A significantly higher K-grading in the ASD participants' eyes was still observed after adjusting for the within-subject inter-eye correlation (p < 0.001). Youden Index showed the optimal cutoffs to differentiate ASD from TDC by bilateral-eye summed K-grading and single-eye K-grading was >6 and >3, respectively. Additionally, a higher K-grading was associated with fewer visual sensation seeking in ASD (Spearman's correlation coefficient ρ = -0.518, p = 0.008) and low visual registration (i.e., higher sensory threshold) in TDC (ρ = 0.446, p = 0.023). This study provided novel evidence of corneal structural alterations in ASD by IVCM. Our findings may not only support the prior hypothesis of the association between ASD and connective tissue abnormalities but also shed light on the relationship between connective tissue disorder and neurodevelopmental disorders.

17 Studying the Use of Politeness in Employment Specific Scenarios in Youth with Autism Spectrum Disorder.

Objective:Employment is crucial in the lives of adults with Autism Spectrum Disorder (ASD) as gainful occupational activity creates opportunities to form meaningful social relationships, participate in community life, and become financially independent. Impairments in pragmatic language skills (i.e., use of language to achieve social goals) negatively impact the ability to make and maintain cooperative work relationships with employers and coworkers, which are critical aspects of employment. A specific pragmatic skill key to workplace communication includes using a suitable degree of politeness, loosely defined as demonstrating the appreciation of the thoughts and feelings of your listener. Politeness can be measured with politeness markers (PMs). Appropriate PM use promotes positive, cooperative relationships. There are two main categories of PMs: positive and negative PMs. Positive PMs express appreciation or praise to the listener. Negative PMs avoid conflict and marks consideration of the thoughts and feelings of the listener. Crucially, negative PMs require more monitoring of social boundaries as they require consideration of the conversational partner’s potential reactions to statements and their emotional states. This makes PMs a novel new approach to evaluating speech in persons with ASD. Because PMs serve a purely social function in language, they include non-tangible words, such as would, could, may, or might. The current study explores the utility of an employment-specific social communication assessment tool, the Voicemail Elicitation Task (VET), in persons with ASD. The VET has proven sensitive to identifying social communication deficits in persons with traumatic brain injury.Participants and Methods:The current cohort comparative study included a sample of young adults with ASD (n=22) and neurotypical controls (NTC; n=10). All participants were given the VET, which utilizes a standardized computerized language sampling procedure that assesses politeness markers (PMs) in work-related role-play scenarios. The outcome measure of the VET is PMs per minute (PMpM) which is obtained by dividing the sum of PMs by the speaking time (in minutes). Higher PMpM indicates higher PM use (more politeness), while lower PMpM indicates lower PM use (less politeness).Results:The preliminary results indicated a significantly lower total PMpM in ASD participants (mean: 13.68 SD: 6.28) compared to NTCs (mean 18.72, SD: 3.65), p = 0.026. Post hoc analysis indicated that the differences in groups were driven by significantly lower negative PMs rates used by the ASD group (mean 9.18, SD: 5.77) compared to NTCs (mean: 16.30, SD: 7.78), p = 0.002, while both groups were similar in their mean level of positive PMs use, p = 0.442.Conclusions:This study represents an important step toward validating the VET for use in ASD, which will improve the capacity of the field to address unemployment in this population. The results of the current study indicate that individuals with ASD show deficits in PM use which could impact their interpersonal relationships within the workplace environment. Designing interventions to target these deficits could help provide better employment outcomes for this population.

20 Using Automated Sentiment Analysis to Examine Self-Evaluation in Youth with Autism Spectrum Disorder

Objective:Individuals diagnosed with autism spectrum disorder (ASD) experience negative self-evaluation, indicated by low levels of self-esteem and describing themselves more negatively to others. Variations in reading comprehension, difficulty identifying emotions, and masking (camouflaging of autistic traits) make it difficult to accurately measure self-evaluation of individuals with ASD using subjective self-report scales such as the Rosenburg Self-Esteem Scale. Therefore, it is important to explore more objective methods of measuring self-evaluation in ASD. Sentiment analysis is a popular Natural Language Processing (NLP) technique used to quantify the emotional content of language programmatically by automatically transforming text into a data frame of words represented as individual values or tokens. Each token can then be categorized as positive or negative with a sentiment dictionary. The current study aims to investigate an automated sentiment analysis approach to evaluate self-evaluation by quantifying implicit linguistic affective valence of ASD participants' verbal self-describing statements in a naturalistic setting. Specifically, we evaluated the frequency of positive or negative words used during a mock job interview in which individuals with ASD were asked to describe themselves. We then examined the relationship between positive and negative word usage and standard self-report measures of self-evaluation.Participants and Methods:Twenty-four young adults with ASD were included in this study with an age range of 15-24 and a mean age of 19.2 years. Participants completed a battery of assessments including a mock job interview in which they were asked to describe themselves as a measure of implicit self-esteem. Self-esteem and knowledge of personal strengths was assessed using the Rosenberg Self-Esteem Scale and Strengths Knowledge Scale, respectively. Interview transcripts were automatically transformed into word token data frames using the tidytext package in Rstudio. Frequencies of positive and negative words were calculated and their ratio to total word count was used to measure the implicit positivity and negativity of transcripts.Results:There was a significant negative correlation between the frequency of negative sentiment in transcripts and measure on the Rosenburg Self-Esteem Scale (r = -.376, p = .035) and the Strengths Knowledge Scale (r = -.387, p = .031) indicating that individuals with higher self-esteem and knowledge of their strengths used fewer negative words when talking during a mock interview.Conclusions:While our results are preliminary, this pilot study represents the first to use automated sentiment analysis to study self-evaluation in individuals with ASD. The use of this technique on natural linguistic data collected through a mock job interview allows researchers to quantitatively analyze the emotionality of transcriptions and create insights that would otherwise be unavailable using more subjective qualitative techniques. Limited research into self-evaluation in this population has yielded inconsistent results, relying too heavily upon qualitative or self-report measures. The ability to programmatically quantify affective valence in transcripts is a time and cost-effective technique for improving validity of future measures of self-evaluation.

Behavioral patterns in robotic collaborative assembly: comparing neurotypical and Autism Spectrum Disorder participants

IntroductionIn Industry 4.0, collaborative tasks often involve operators working with collaborative robots (cobots) in shared workspaces. Many aspects of the operator's well-being within this environment still need in-depth research. Moreover, these aspects are expected to differ between neurotypical (NT) and Autism Spectrum Disorder (ASD) operators.MethodsThis study examines behavioral patterns in 16 participants (eight neurotypical, eight with high-functioning ASD) during an assembly task in an industry-like lab-based robotic collaborative cell, enabling the detection of potential risks to their well-being during industrial human-robot collaboration. Each participant worked on the task for five consecutive days, 3.5 h per day. During these sessions, six video clips of 10 min each were recorded for each participant. The videos were used to extract quantitative behavioral data using the NOVA annotation tool and analyzed qualitatively using an ad-hoc observational grid. Also, during the work sessions, the researchers took unstructured notes of the observed behaviors that were analyzed qualitatively.ResultsThe two groups differ mainly regarding behavior (e.g., prioritizing the robot partner, gaze patterns, facial expressions, multi-tasking, and personal space), adaptation to the task over time, and the resulting overall performance.DiscussionThis result confirms that NT and ASD participants in a collaborative shared workspace have different needs and that the working experience should be tailored depending on the end-user's characteristics. The findings of this study represent a starting point for further efforts to promote well-being in the workplace. To the best of our knowledge, this is the first work comparing NT and ASD participants in a collaborative industrial scenario.

Cultivating Insight: Detecting Autism Spectrum Disorder through Residual Attention Network in Facial Image Analysis

Revolutionizing Autism Spectrum Disorder Identification through Deep Learning: Unveiling Facial Activation Patterns. In this study, our primary objective is to harness the power of deep learning algorithms for the precise identification of individuals with autism spectrum disorder (ASD) solely from facial image datasets. Our investigation centers around the utilization of face activation patterns, aiming to uncover novel insights into the distinctive facial features of ASD patients. To accomplish this, we meticulously examined facial imaging data from a global and multidisciplinary repository known as the Autism Face Imaging Data Exchange. Autism spectrum disorder is characterized by inherent social deficits and manifests in a spectrum of diverse symptomatic scenarios. Recent data from the Centers for Disease Control (CDC) underscores the significance of this disorder, indicating that approximately 1 in 54 children are impacted by ASD, according to estimations from the CDC's Autism and Developmental Disabilities Monitoring Network (ADDM). Our research delved into the intricate functional connectivity patterns that objectively distinguish ASD participants, focusing on their facial imaging data. Through this investigation, we aimed to uncover the latent facial patterns that play a pivotal role in the classification of ASD cases. Our approach introduces a novel module that enhances the discriminative potential of standard convolutional neural networks (CNNs), such as ResNet-50, thus significantly advancing the state-of-the-art. Our model achieved an impressive accuracy rate of 99% in distinguishing between ASD patients and control subjects within the dataset. Our findings illuminate the specific facial expression domains that contribute most significantly to the differentiation of ASD cases from typically developing individuals, as inferred from our deep learning methodology. To validate our approach, we conducted real-time video testing on diverse children, achieving an outstanding accuracy score of 99.90% and an F1 score of 99.67%. Through this pioneering work, we not only offer a cutting-edge approach to ASD identification but also contribute to the understanding of the underlying facial activation patterns that hold potential for transforming the diagnostic landscape of autism spectrum disorder.

EEG functional connectivity in infants at elevated familial likelihood for autism spectrum disorder

BackgroundMany studies have reported that autism spectrum disorder (ASD) is associated with atypical structural and functional connectivity. However, we know relatively little about the development of these differences in infancy.MethodsWe used a high-density electroencephalogram (EEG) dataset pooled from two independent infant sibling cohorts, to characterize such neurodevelopmental deviations during the first years of life. EEG was recorded at 6 and 12 months of age in infants at typical (N = 92) or elevated likelihood for ASD (N = 90), determined by the presence of an older sibling with ASD. We computed the functional connectivity between cortical sources of EEG during video watching using the corrected imaginary part of phase-locking values.ResultsOur main analysis found no significant association between functional connectivity and ASD, showing only significant effects for age, sex, age-sex interaction, and site. Given these null results, we performed an exploratory analysis and observed, at 12 months, a negative correlation between functional connectivity and ADOS calibrated severity scores for restrictive and repetitive behaviors (RRB).LimitationsThe small sample of ASD participants inherent to sibling studies limits diagnostic group comparisons. Also, results from our secondary exploratory analysis should be considered only as potential relationships to further explore, given their increased vulnerability to false positives.ConclusionsThese results are inconclusive concerning an association between EEG functional connectivity and ASD in infancy. Exploratory analyses provided preliminary support for a relationship between RRB and functional connectivity specifically, but these preliminary observations need corroboration on larger samples.

Altered markers of mitochondrial function in adults with autism spectrum disorder.

Previous research suggests potential mitochondrial dysfunction and changes in fatty acid metabolism in a subgroup of individuals with autism spectrum disorder (ASD), indicated by higher lactate, pyruvate levels, and mitochondrial disorder prevalence. This study aimed to further investigate potential mitochondrial dysfunction in ASD by assessing blood metabolite levels linked to mitochondrial metabolism. Blood levels of creatine kinase (CK), alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactate, pyruvate, free and total carnitine, as well as acylcarnitines were obtained in 73 adults with ASD (47 males, 26 females) and compared with those of 71 neurotypical controls (NTC) (44 males, 27 females). Correlations between blood parameters and psychometric ASD symptom scores were also explored. Lower CK (pcorr = 0.045) levels were found exclusively in males with ASD compared to NTC, with no such variation in females. ALT and AST levels did not differ significantly between both groups. After correction for antipsychotic and antidepressant medication, CK remained significant. ASD participants had lower serum lactate levels (pcorr = 0.036) compared to NTC, but pyruvate and carnitine concentrations showed no significant difference. ASD subjects had significantly increased levels of certain acylcarnitines, with a decrease in tetradecadienoyl-carnitine (C14:2), and certain acylcarnitines correlated significantly with autistic symptom scores. We found reduced serum lactate levels in ASD, in contrast to previous studies suggesting elevated lactate or pyruvate. This difference may reflect the focus of our study on high-functioning adults with ASD, who are likely to have fewer secondary genetic conditions associated with mitochondrial dysfunction. Our findings of significantly altered acylcarnitine levels in ASD support the hypothesis of altered fatty acid metabolism in a subset of ASD patients.

Neural correlates of hierarchical predictive processes in autistic adults

Bayesian theories of autism spectrum disorders (ASD) suggest that atypical predictive mechanisms could underlie the autistic symptomatology, but little is known about their neural correlates. Twenty-six neurotypical (NT) and 26 autistic adults participated in an fMRI study where they performed an associative learning task in a volatile environment. By inverting a model of perceptual inference, we characterized the neural correlates of hierarchically structured predictions and prediction errors in ASD. Behaviorally, the predictive abilities of autistic adults were intact. Neurally, predictions were encoded hierarchically in both NT and ASD participants and biased their percepts. High-level predictions were following activity levels in a set of regions more closely in ASD than NT. Prediction errors yielded activation in shared regions in NT and ASD, but group differences were found in the anterior cingulate cortex and putamen. This study sheds light on the neural specificities of ASD that might underlie atypical predictive processing.

Relative clause production abilities of Hebrew-speaking children with ASD

ABSTRACT Relative clauses (RCs) are complex syntactic structures because they consist of multiple clauses and involve syntactic movement. RCs are known as a reliable clinical marker of syntactic impairment across many different languages and populations. Children with autism spectrum disorders (ASD) struggle with the comprehension and production of RCs, and it remains unclear whether these difficulties stem from a pragmatic or a syntactic origin. The aim of the current study is to obtain evidence about the nature of the RC production difficulties of Hebrew-speaking children with ASD. To do so, we attempted to isolate the mechanism(s) that may be disrupting RC production by using a novel in-depth error analysis scheme. The current study tested 101 Hebrew-speaking children—37 children with ASD (Mage = 11.4, SD = 2.2) and 64 Typically Developing (TD) children; 25 children aged 8-9 years (Mage = 8.8, SD = 0.3) and 39 TD children aged 10-11 (Mage = 10.7, SD = 0.39) on an RC elicitation definition task. Responses were coded for correct RC production, and an error analysis scheme was built based on the productions seen among the ASD participants. TD children produced more RCs than children with ASD, and a significant difference was found between the two TD groups (older children produced more RCs). Children with ASD produced mainly pronoun errors and produced single words instead of sentences, patterns not seen among the TD group and sometimes characteristic of Hebrew-speaking children at younger ages. The current study contributes to the discussion regarding syntactic differences seen in the production of some children with ASD and whether such differences are a specific form of language deficit, or merely a delay in language acquisition.

Stratifying ASD and characterizing the functional connectivity of subtypes in resting-state fMRI

Although stratifying autism spectrum disorder (ASD) into different subtypes is a common effort in the research field, few papers have characterized the functional connectivity alterations of ASD subgroups classified by their clinical presentations. This is a case-control rs-fMRI study, based on large samples of open database (Autism Brain Imaging Data Exchange, ABIDE). The rs-MRI data from n=415 ASD patients (males n=357), and n=574 typical development (TD) controls (males n=410) were included. Clinical features of ASD were extracted and classified using data from each patient's Autism Diagnostic Interview-Revised (ADI-R) evaluation. Each subtype of ASD was characterized by local functional connectivity using regional homogeneity (ReHo) for assessment, remote functional connectivity using voxel-mirrored homotopic connectivity (VMHC) for assessment, the whole-brain functional connectivity, and graph theoretical features. These identified imaging properties from each subtype were integrated to create a machine learning model for classifying ASD patients into the subtypes based on their rs-fMRI data, and an independent dataset was used to validate the model. All ASD participants were classified into Cluster-1 (patients with more severe impairment) and Cluster-2 (patients with moderate impairment) according to the dimensional scores of ADI-R. When compared to the TD group, Cluster-1 demonstrated increased local connection and decreased remote connectivity, and widespread hyper- and hypo-connectivity variations in the whole-brain functional connectivity. Cluster-2 was quite similar to the TD group in both local and remote connectivity. But at the level of whole-brain functional connectivity, the MCC-related connections were specifically impaired in Cluster-2. These properties of functional connectivity were fused to build a machine learning model, which achieved ~75% for identifying ASD subtypes (Cluster-1 accuracy = 81.75%; Cluster-2 accuracy = 76.48%). The stratification of ASD by clinical presentations can help to minimize disease heterogeneity and highlight the distinguished properties of brain connectivity in ASD subtypes.

The Neurogenetics of Functional Connectivity Alterations in Autism: Insights From Subtyping in 657 Individuals

BackgroundThere is little consensus and controversial evidence on anatomical alterations in the brains of people with autism spectrum disorder (ASD), due in part to the large heterogeneity present in ASD, which in turn is a major drawback for developing therapies. One strategy to characterize this heterogeneity in ASD is to cluster large-scale functional brain connectivity profiles. MethodsA subtyping approach based on consensus clustering of functional brain connectivity patterns was applied to a population of 657 autistic individuals with quality-assured neuroimaging data. We then used high-resolution gene transcriptomic data to characterize the molecular mechanism behind each subtype by performing enrichment analysis of the set of genes showing a high spatial similarity with the profiles of functional connectivity alterations between each subtype and a group of typically developing control participants. ResultsTwo major stable subtypes were found: subtype 1 exhibited hypoconnectivity (less average connectivity than typically developing control participants) and subtype 2, hyperconnectivity. The 2 subtypes did not differ in structural imaging metrics in any of the analyzed regions (68 cortical and 14 subcortical) or in any of the behavioral scores (including IQ, Autism Diagnostic Interview, and Autism Diagnostic Observation Schedule). Finally, only subtype 2, comprising about 43% of ASD participants, led to significant enrichments after multiple testing corrections. Notably, the dominant enrichment corresponded to excitation/inhibition imbalance, a leading well-known primary mechanism in the pathophysiology of ASD. ConclusionsOur results support a link between excitation/inhibition imbalance and functional connectivity alterations, but only in one ASD subtype, overall characterized by brain hyperconnectivity and major alterations in somatomotor and default mode networks.

Using simple economic games to assess social orienting and prosocial behavior in adolescents with autism spectrum disorder.

Deficits in socio-emotional reciprocity, in prosocial behavior and in developing social relationships are diagnostic criteria of autism spectrum disorder (ASD), usually assessed by self-report or observation. Simple social experiments developed by behavioral economists allow for quantification of ASD-related social behavior. In this study, we used such experiments to compare social-economic decision-making between ASD adolescents and neurotypical controls. Precisely, we analyzed social orienting and prosocial behavior in 17 adolescents with ASD (Asperger syndrome) and 24 matched neurotypical adolescents. We used a two-condition distribution game (possibility of punishment by fellow player versus no such possibility) and an impunity game to examine social orienting (distribution game) and prosocial behavior (both games). Participants with ASD exhibited less social orienting in the distribution game (p = 0.03, d = -0.61). In addition, there was a trend for ASD participants to behave in a more prosocial way than neurotypical participants in the impunity game (p = 0.08, d = 0.60), which was not the case in the no-punishment condition of the distribution game (p = 0.35, r = 0.17). These results demonstrate the potential of simple economic games to capture reduced social orienting in ASD. The unexpected finding of more prosocial behavior in adolescents with autism spectrum disorder than in neurotypical controls adds to the complexity of previously published results. We recommend meta-analytic efforts to determine average effect sizes across studies and elucidate the conditions for prosocial behavior in ASD to occur.