Language comprehension and brain function in individuals with an optimal outcome from autism

The Autism Constellation and Neurodiversity: Long-Term and Adult Outcomes in Autism Spectrum Disorder

Research on autistic adults suggests significant heterogeneity in outcomes. A significant proportion of individuals struggle with intellectual disability and limited communication skills. Of the 67% who have age-appropriate cognitive skills, around half are expected to attain a college education, and 25% are likely to hold a full-time job. Outcomes have been improving over time, in part because of earlier diagnosis and earlier intervention. Indeed, an estimated 10% to 20% are expected to lose all symptoms of autism by adolescence.

The Comprehension of Grammatical Structures in a Pediatric Population with ASD and Epilepsy: A Comparative Study

Autism Spectrum Disorder (ASD) and epilepsy represent a comorbidity that negatively influences the proper development of linguistic competencies, particularly in receptive language, in the pediatric population. This group displays impairments in the auditory comprehension of both simple and complex grammatical structures, significantly limiting their performance in language-related activities, hampering their integration into social contexts, and affecting their quality of life. The main objective of this study was to assess auditory comprehension of grammatical structures in individuals with ASD and epilepsy and compare the results among the three groups. A non-experimental cross-sectional study was designed, including a total of 170 participants aged between 7 and 9 years, divided into three groups: a group with ASD, a group with epilepsy, and a comorbid group with both ASD and epilepsy (ASDEP). The comprehension of grammatical structures was assessed using the CEG and CELF-5 instruments. Statistical analyses included MANOVA and ANOVA to compare scores between groups to verify associations between study variables. The results indicate that the group with ASD and epilepsy performed worse compared to the ASD and epilepsy-only groups, respectively. Additionally, a significant and directly proportional association was observed among all variables within the measures of grammatical structure comprehension. The neurological damage caused by epilepsy in the pediatric population with ASD leads to difficulties in understanding oral language. This level of functioning significantly limits the linguistic performance of these children, negatively impacting their quality of life and the development of core language skills.

Atypical Associations between Functional Connectivity during Pragmatic and Semantic Language Processing and Cognitive Abilities in Children with Autism

Autism Spectrum Disorder (ASD) is characterized by both atypical functional brain connectivity and cognitive challenges across multiple cognitive domains. The relationship between task-dependent brain connectivity and cognitive abilities, however, remains poorly understood. In this study, children with ASD and their typically developing (TD) peers engaged in semantic and pragmatic language tasks while their task-dependent brain connectivity was mapped and compared. A multivariate statistical approach revealed associations between connectivity and psychometric assessments of relevant cognitive abilities. While both groups exhibited brain-behavior correlations, the nature of these associations diverged, particularly in the directionality of overall correlations across various psychometric categories. Specifically, greater disparities in functional connectivity between the groups were linked to larger differences in Autism Questionnaire, BRIEF, MSCS, and SRS-2 scores but smaller differences in WASI, pragmatic language, and Theory of Mind scores. Our findings suggest that children with ASD utilize distinct neural communication patterns for language processing. Although networks recruited by children with ASD may appear less efficient than those typically engaged, they could serve as compensatory mechanisms for potential disruptions in conventional brain networks.

Extracting transition features among brain states based on coarse-grained similarity measurement for autism spectrum disorder analysis

BACKGROUND

The abnormal brain functional connectivity (FC) of patients with mental diseases is closely linked to the transition features among brain states. However, the current research on state transition will produce certain division deviations in the measurement method of state division, and also ignore the transition features among multiple states that contain more abundant information for analyzing brain diseases.

PURPOSE

To investigate the potential of the proposed method based on coarse-grained similarity measurement to solve the problem of state division, and consider the transition features among multiple states to analyze the FC abnormalities of autism spectrum disorder (ASD) patients.

METHODS

We used resting-state functional magnetic resonance imaging to examine 45 ASD and 47 healthy controls (HC). The FC between brain regions was calculated by the sliding window and correlation algorithm, and a novel coarse-grained similarity measure method was used to cluster the FC networks into five states, and then extract the features both of the state itself and the transition features among multiple states for analysis and diagnosis.

RESULTS

(1) The state as divided by the coarse-grained measurement method improves the diagnostic performance of individuals with ASD compared with previous methods. (2) The transition features among multiple states can provide complementary information to the features of the state itself in the ASD analysis and diagnosis. (3) ASD individuals have different brain state transitions than HC. Specifically, the abnormalities in intra- and inter-network connectivity of ASD patients mainly occur in the default mode network, the visual network, and the cerebellum.

CONCLUSIONS

Such results demonstrate that our approach with new measurements and new features is effective and promising in brain state analysis and ASD diagnosis.

Mapping access to meaning in adolescents with autism: Atypical lateralization and spatiotemporal patterns as a function of language ability

Individuals with autism spectrum disorders (ASD) vary in their language abilities, associated with atypical patterns of brain activity. However, few studies have examined the spatiotemporal profiles of lexico-semantic processing in ASD, particularly as a function of language heterogeneity. Thirty-nine high-functioning adolescents with ASD and 21 typically developing (TD) peers took part in a lexical decision task that combined semantic access with demands on cognitive control. Spatiotemporal characteristics of the processing stages were examined with a multimodal anatomically-constrained magnetoencephalography (aMEG) approach, which integrates MEG with structural MRI. Additional EEG data were acquired from a limited montage simultaneously with MEG. TD adolescents showed the canonical left-dominant activity in frontotemporal regions during both early (N250m) and late (N400m) stages of lexical access and semantic integration. In contrast, the ASD participants showed bilateral engagement of the frontotemporal language network, indicative of compensatory recruitment of the right hemisphere. The left temporal N400m was prominent in both groups, confirming preserved attempts to access meaning. In contrast, the left prefrontal N400m was reduced in ASD participants, consistent with impaired semantic/contextual integration and inhibitory control. To further investigate the impact of language proficiency, the ASD sample was stratified into high- and low-performing (H-ASD and L-ASD) subgroups based on their task accuracy. The H-ASD subgroup performed on par with the TD group and showed greater activity in the right prefrontal and bilateral temporal cortices relative to the L-ASD subgroup, suggesting compensatory engagement. The L-ASD subgroup additionally showed reduced and delayed left prefrontal N400m, consistent with more profound semantic and executive impairments in this subgroup. These distinct spatiotemporal activity profiles reveal the neural underpinnings of the ASD-specific access to meaning and provide insight into the phenotypic heterogeneity of language in ASD, which may be a result of different neurodevelopmental trajectories and adoption of compensatory strategies.

Brain white matter microstructure abnormalities in children with optimal outcome from autism: a four-year follow-up study

Autism spectrum disorder (ASD) is a lifelong neurodevelopmental disorder, with only a small proportion of people obtaining optimal outcomes. We do not know if children with ASD exhibit abnormalities in the white matter (WM) microstructure or if this pattern would predict ASD prognosis in a longitudinal study. 182 children with ASD were recruited for MRI and clinical assessment; 111 completed a four-year follow-up visit (30 with optimal outcomes, ASD-; 81 with persistent diagnosis, ASD+). Additionally, 72 typically developing controls (TDC) were recruited. The microstructural integrity of WM fiber tracts was revealed using tract-based spatial statistics (TBSS) and probabilistic tractography analyses. We examined the neuroimaging abnormality associated with ASD and its relationship to ASD with optimal outcome. The ASD+ and TDC groups were propensity score matched to the ASD- group in terms of age, gender, and IQ. TBSS indicated that children with ASD exhibited abnormalities in the superior longitudinal fasciculus (SLF), inferior longitudinal fasciculus (ILF), and extending to the anterior thalamic radiation (ATR) and cingulum; whereas the ASD+ group showed more severe abnormalities than the ASD- group. Probabilistic tractography analysis revealed that ASD+ group exhibited lower Fractional Anisotropy (FA) of the left superior thalamic radiation (STR L) than ASD- group, and that FA value of the STR L was a significant predictor of optimal outcome (EX(B), 6.25; 95% CI 2.50-15.63; p < 0.001). Children with ASD showed significant variations in SLF_L and STR_L, and STR_L was a predictor of 'ASD with optimal outcome'. Our findings may aid in comprehension of the mechanisms of 'ASD with optimal outcome'.

Structural language impairment in Autism Spectrum Disorder versus Loss of Autism Diagnosis: Behavioral and neural characteristics

This study probed for structural language impairment using behavioral and functional neuroimaging methods in individuals with Autism Spectrum Disorder (ASD) and those diagnosed with ASD in childhood who no longer meet criteria for ASD, referred to as Loss of Autism Diagnosis (LAD¹). Participants were drawn from Fein et al. (2013): ASD (n = 35), LAD (n = 31), and Neurotypical (NT; n = 34). Criteria for structural language impairment were: Scores ≤ 82 on Clinical Evaluation of Language Fundamentals-4 (CELF) Core Language, an omnibus measure of language; and scores ≤ 7 on CELF Recalling Sentences, a clinical marker of structural language impairment. Task-based fMRI examined lateralization of significantly activated language-related brain regions in groups with structural language impairment (LI²) versus normal-range language (LN³), collapsed across ASD, LAD¹, and NT status. Results showed no ASD versus LAD group differences in the proportion of participants with structural language impairment according to either metric (Recalling Sentences or Core Language). Functional MRI results indicated greater left hemisphere lateralization within significantly activated regions in the LI² group. Structural language abilities were not meaningfully associated with either social abilities or lifetime ADHD symptoms in LI² subgroups, further suggesting the presence of structural language impairment. Findings indicate the presence of persistent structural language difficulty even in the absence of ASD symptoms in some individuals within the LAD¹ group and unique patterns of language-related neural specialization for language function in LI² relative to LN³.

Developmental differences in neural connectivity for semantic processing in youths with autism

BACKGROUND

Youths with autism spectrum disorder (ASD) rely more on lower-level visual processing as revealed by greater occipital activation, yet less effectively engage higher-level processing of modality-independent semantic knowledge as indicated by reduced frontal activation, compared to typically developing (TD) youths. However, little is known about age-dependent differences in neural connectivity during semantic processing in youths with ASD as compared to TD youths.

METHODS

Four groups were recruited: 31 ASD children (mean age = 10.5 years old), 33 TD children (mean age = 10.4), 30 ASD adolescents (mean age = 14.9), and 34 TD adolescents (mean age = 15.1). We explored their differences in neural connectivity by using functional magnetic resonance imaging (fMRI) with psychophysiological interaction (PPI) during semantic judgments.

RESULTS

In comparison with TD children, children with ASD showed greater activation in the left cuneus and weaker connectivity between the left cuneus and left middle temporal gyrus (MTG). In comparison with TD adolescents, adolescents with ASD showed less activation in the left inferior frontal gyrus (IFG) and weaker functional connectivity between the left IFG and left MTG.

CONCLUSIONS

Children with ASD may rely more on visual processes in the occipital cortex that are disconnected from modality-independent semantics in the temporal cortex. However, adolescents with ASD may less effectively engage frontal mechanisms involved in the top-down control of modality-independent semantic knowledge in the temporal cortex. Our findings provide evidence of developmental differences in the neural substrates of the alterations in semantic processing in youths with ASD compared to TD youths.

Influence of Primary Auditory Cortex in the Characterization of Autism Spectrum in Young Adults using Brain Connectivity Parameters and Deep Belief Networks: An fMRI Study

BACKGROUND

The spectrum of autism encompasses High Functioning Autism (HFA) and Low Functioning Autism (LFA). Brain mapping studies have revealed that autism individuals have overlaps in brain behavioural characteristics. Generally, high functioning individuals are known to exhibit higher intelligence and better language processing abilities. However, specific mechanisms associated with their functional capabilities are still under research.

OBJECTIVE

This work addresses the overlapping phenomenon present in autism spectrum through functional connectivity patterns along with brain connectivity parameters and distinguishes the classes using deep belief networks.

METHODS

The task-based functional Magnetic Resonance Images (fMRI) of both high and low functioning autistic groups were acquired from ABIDE database, for 58 low functioning against 43 high functioning individuals while they were involved in a defined language processing task. The language processing regions of the brain, along with Default Mode Network (DMN) have been considered for the analysis. The functional connectivity maps have been plotted through graph theory procedures. Brain connectivity parameters such as Granger Causality (GC) and Phase Slope Index (PSI) have been calculated for the individual groups. These parameters have been fed to Deep Belief Networks (DBN) to classify the subjects under consideration as either LFA or HFA.

RESULTS

Results showed increased functional connectivity in high functioning subjects. It was found that the additional interaction of the Primary Auditory Cortex lying in the temporal lobe, with other regions of interest complimented their enhanced connectivity. Results were validated using DBN measuring the classification accuracy of 85.85% for high functioning and 81.71% for the low functioning group.

CONCLUSION

Since it is known that autism involves enhanced, but imbalanced components of intelligence, the reason behind the supremacy of high functioning group in language processing and region responsible for enhanced connectivity has been recognized. Therefore, this work that suggests the effect of Primary Auditory Cortex in characterizing the dominance of language processing in high functioning young adults seems to be highly significant in discriminating different groups in autism spectrum.

Autism Spectrum Disorder and Childhood Apraxia of Speech: Early Language-Related Hallmarks across Structural MRI Study

Autism Spectrum Disorder (ASD) and Childhood Apraxia of Speech (CAS) are developmental disorders with distinct diagnostic criteria and different epidemiology. However, a common genetic background as well as overlapping clinical features between ASD and CAS have been recently reported. To date, brain structural language-related abnormalities have been detected in both the conditions, but no study directly compared young children with ASD, CAS and typical development (TD). In the current work, we aim: (i) to test the hypothesis that ASD and CAS display neurostructural differences in comparison with TD through morphometric Magnetic Resonance Imaging (MRI)-based measures (ASD vs. TD and CAS vs. TD); (ii) to investigate early possible disease-specific brain structural patterns in the two clinical groups (ASD vs. CAS); (iii) to evaluate predictive power of machine-learning (ML) techniques in differentiating the three samples (ASD, CAS, TD). We retrospectively analyzed the T1-weighted brain MRI scans of 68 children (age range: 34-74 months) grouped into three cohorts: (1) 26 children with ASD (mean age ± standard deviation: 56 ± 11 months); (2) 24 children with CAS (57 ± 10 months); (3) 18 children with TD (55 ± 13 months). Furthermore, a ML analysis based on a linear-kernel Support Vector Machine (SVM) was performed. All but one brain structures displayed significant higher volumes in both ASD and CAS children than TD peers. Specifically, ASD alterations involved fronto-temporal regions together with basal ganglia and cerebellum, while CAS alterations are more focused and shifted to frontal regions, suggesting a possible speech-related anomalies distribution. Caudate, superior temporal and hippocampus volumes directly distinguished the two conditions in terms of greater values in ASD compared to CAS. The ML analysis identified significant differences in brain features between ASD and TD children, whereas only some trends in the ML classification capability were detected in CAS as compared to TD peers. Similarly, the MRI structural underpinnings of two clinical groups were not significantly different when evaluated with linear-kernel SVM. Our results may represent the first step towards understanding shared and specific neural substrate in ASD and CAS conditions, which subsequently may contribute to early differential diagnosis and tailoring specific early intervention.

Tell me where it is: Selective difficulties in spatial language on the autism spectrum

LAY ABSTRACT

How we think and talk about space is an essential ability, necessary for understanding the world around us. We recruit spatial thinking every day when finding our way or using tools but also in more advanced tasks, such as reading complex graphs or maps. We do so also in daily communication when we use spatial language, terms such as under, over, to the left of or in front of, and when we give instructions. Spatial terms appear in children's early vocabularies and continue to develop until late childhood or even early adolescence. Because spatial language develops over many years, some spatial terms are mastered very early, whereas others take longer to acquire. In the current set of studies, we tested how intellectually high-functioning children and adults on the autism spectrum use and understand these early- and late-acquired spatial terms in comparison to typically developing age-matched individuals. We found that children and adults on the autism spectrum experience difficulties with the use of some spatial terms (e.g. near and far or out of and down off) but not with others, which are acquired early (e.g. in and on or over and under). We also found that remembering spatial terms from short stories was more difficult for the individuals on the autism spectrum compared with typically developing individuals. These results reveal difficulties that can profoundly affect everyday communication of children and adults on the autism spectrum but also open new directions of research on language development in autism spectrum disorders.

Neuroimaging Markers of Risk and Pathways to Resilience in Autism Spectrum Disorder

Autism spectrum disorder is a complex, heterogeneous neurodevelopmental condition of largely unknown etiology. This heterogeneity of symptom presentation, combined with high rates of comorbidity with other developmental disorders and a lack of reliable biomarkers, makes diagnosing and evaluating life outcomes for individuals with autism spectrum disorder a challenge. We review the growing literature on neuroimaging-based biomarkers of risk for the development of autism and explore evidence for resilience in some autistic individuals. The current literature suggests that neuroimaging during early infancy, in combination with prebirth and early genetic studies, is a promising tool for identifying biomarkers of risk, while studies of gene expression and DNA methylation have provided some key insights into mechanisms of resilience. With genetics and the environment contributing to both risk for the development of autism spectrum disorder and conditions for resilience, additional studies are needed to understand how risk and resilience interact mechanistically, whereby factors of risk may engender conditions for adaptation. Future studies should prioritize longitudinal designs in global cohorts, with the involvement of the autism community as partners in research to help identify domains of functioning that hold value and importance to the community.

Research Review: Outcomes of 24- to 36-month-old children with autism spectrum disorder vary by ascertainment strategy: a systematic review and meta-analysis

BACKGROUND

Despite widespread recommendations for early surveillance of risk for autism spectrum disorder (ASD), no research to date has shown that early surveillance leads to better clinical outcomes. Preliminary research has suggested that children with ASD ascertained via prospective follow-up have better outcomes than those ascertained via community referral. Because prospective studies include early surveillance, by comparing outcomes of children with ASD across ascertainment strategies, we may gain insight into the effects of early surveillance relative to its absence.

METHODS

A systematic review was conducted to identify studies reporting outcomes of 24- to 36-month-olds with ASD ascertained via prospective follow-up, community referral, or universal screening. A meta-analysis using a random effects model was used to calculate overall effect size estimates for developmental level and symptom severity across ascertainment cohorts.

RESULTS

Eleven prospective, ten community referral, and eight universal screening studies were identified, reporting on 1,658 toddlers with ASD. We found no differences in outcomes between community referral and universal screening studies. Relative to both, prospective studies reported significantly higher developmental levels and lower symptom severities.

CONCLUSIONS

Outcomes of young children with ASD ascertained via prospective follow-up are better than those of children with ASD recruited via community referral or universal screening. Although we discuss why sampling bias is not likely the driving force behind these findings, we cannot rule out the possibility that sampling bias contributes to the observed differences; future studies should probe the effects of sociodemographic variables on clinical outcomes as a function of ascertainment strategy. This limitation notwithstanding, our results raise the possibility that prospective follow-up may confer a 'surveillance effect' that contributes to improved developmental and diagnostic outcomes in children with ASD. Future research should test this hypothesis and determine the specific mechanism by which surveillance may improve outcomes.

Gaze and Motor Traces of Language Processing: Evidence from Autism Spectrum Disorders in Comparison to Typical Controls

We investigated what strategies underlie figurative language processing in two groups of participants distinguished by the presence of a developmental deficit, highly-verbal participants with autism, and control participants without autism in two age ranges each. Individuals with autism spectrum disorder are characterised by impaired social interaction and communication. Even at the high end of the spectrum, where structural language is adequate, difficulties in comprehending non-literal aspects of language are widely attested. The exact causes of these problems are, however, still open to debate. In an interactive sentence-picture matching task participants selected the most suitable image representation of a non-literal figurative expression that matched the target meaning, while their eye-movements and hand movements were being tracked. Our results suggest that individuals with ASD have different processing patterns than typically developing peers when interpreting figurative language, even when they provide the correct answers. Both children with and without autism, and participants with autism display greater uncertainty and competition between alternatives when providing the answer, often reflected in also considering the literal interpretation of the expression against its target figurative meaning. We provide evidence that expression transparency and decomposability play a central role in figurative language processing across all groups.

Computational modeling of interventions for developmental disorders

We evaluate the potential of connectionist models of developmental disorders to offer insights into the efficacy of interventions. Based on a range of computational simulation results, we assess factors that influence the effectiveness of interventions for reading, language, and other cognitive developmental disorders. The analysis provides a level of mechanistic detail that is generally lacking in behavioral approaches to intervention. We review an extended program of modeling work in four sections. In the first, we consider long-term outcomes and the possibility of compensated outcomes and resolution of early delays. In the second section, we address methods to remediate atypical development in a single network. In the third section, we address interventions to encourage compensation via alternative pathways. In the final section, we consider the key issue of individual differences in response to intervention. Together with advances in understanding the neural basis of developmental disorders and neural responses to training, formal computational approaches can spur theoretical progress to narrow the gap between the theory and practice of intervention.

Recognising autism: a latent transition analysis of parental reports of child autistic spectrum disorder 'red flag' traits before and after age 3

PURPOSE

It has been proposed that parents should be educated about child autistic spectrum disorder (ASD) 'red flag' traits to help professionals identify and address concerning behaviours as early as possible. This study aimed to empirically demonstrate that established/recognised 'red flag' traits in the first 3 years of life would reliably predict ASD risk severity in later childhood, associated with established ASD risk correlates and mirroring functioning diagnostic categories.

METHODS

Using retrospective parental report data from the Mental Health of Children and Young People in Great Britain survey (N = 7977), latent class analysis (LCA) and a quasi -latent transition analysis were used to (1) identify profiles of variation in parent reports of child 'red flag' traits before and after age 3 and (2) model transitions in risk from 3 years and below to ≥ 3 years, respectively, per the 'optimal outcome' model.

RESULTS

Three distinct classes, each characterised by variation in parent 'red flag' trait reporting were identified for the '≤ 3 years of age' and the '≥ 3 years of age' data. Both LCA class profiles comprised groups of children characterised by low, medium and high ASD risk. Dose-response effects for a number of recognised ASD correlates across the low, moderate and high risk '≥ 3 years of age' classes seemed to validate older classes in terms of ASD relevance. Over 54% of children characterised by the highest levels of ASD 'red flag' trait probability at 3 years and below (2% of sample), also populated the high-risk class evidenced in the '≥ 3 years of age' LCA.

CONCLUSIONS

Retrospective parental reports of child ASD 'red flag' traits ≤ 3 years of age were reliable indicators of ASD risk in later childhood.

White Matter Tract-Cognitive Relationships in Children with High-Functioning Autism Spectrum Disorder

OBJECTIVE

The purpose of the present study was to clarify the relationship between white matter tracts and cognitive symptoms in children with high-functioning autism spectrum disorder (ASD).

METHODS

We examined the cognitive functions of 17 children with high-functioning ASD and 18 typically developing (TD) controls and performed diffusion tensor imaging (DTI) tractography. We compared the results between the groups and investigated the correlations between the cognitive scores and DTI parameters within each group.

RESULTS

The Comprehension scores in the ASD group exhibited a positive correlation with mean diffusivity (MD) in the forceps minor (F minor). In the TD group, the Comprehension scores were positively correlated with fractional anisotropy (FA) in the right inferior fronto-occipital fasciculus (IFO) and left anterior thalamic radiation (ATR), and negatively correlated with MD in the left ATR, radial diffusivity (RD) in the right IFO, and RD in the left ATR. Additionally, a positive correlation was observed between the Matching Numbers scores and MD in the left uncinate fasciculus and F minor, and RD in the F minor. Furthermore, the Sentence Questions scores exhibited a positive correlation with RD in the right inferior longitudinal fasciculus. Relative to TD controls, the specific tract showing a strong correlation with the cognitive scores was reduced in the ASD group.

CONCLUSION

Our findings indicate that white matter tracts connecting specific brain areas may exhibit a weaker relationship with cognitive functions in children with ASD, resulting in less efficient cognitive pathways than those observed in TD children.

Dissociations in the neural substrates of language and social functioning in autism spectrum disorder

Impairments in social communication (coupled with intact nonsocial language skills) are common in autism spectrum disorder (ASD). However, the neural correlates of these social communication deficits in adolescents and young adults with ASD are not fully understood. The communication checklist self-report (CC-SR) was administered to adolescents and young adults with ASD (n = 52) and typically developing (TD) controls (n = 64) to assess structural-language, pragmatic-language, and social-engagement. One high-resolution T1-weighted structural image was obtained from each participant. FreeSurfer was used to quantify cortical thickness. A main effect of diagnosis, with the ASD group performing worse than the TD group on all three CC-SR scales, and a diagnosis by scale interaction, driven by low social-engagement self-ratings in the ASD group, were found. There were also group differences in the relationship between scores on two of the three CC-SR scales and cortical thickness in multiple regions (pragmatic-language: left rostral frontal; social-engagement: left medial prefrontal). These interactions were driven by poorer self-ratings of language/social skills associated with decreased cortical thickness in the ASD group, while in the TD group worse self-ratings were associated with thicker cortex. Self-ratings of language/social-communication were lower in the ASD than the TD group. Moreover, language/social-communication self-ratings showed a different relationship with cortical thickness for the ASD and TD groups in the left inferior frontal region for pragmatic language ratings and the left medial prefrontal cortex for social engagement ratings. These findings suggest thinner cortex is associated with more impaired pragmatic language and social communication abilities in ASD. Autism Res 2018, 11: 1175-1186. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: The present study examines the associations between brain structure and language/social communication ability in adolescents and young adults with autism spectrum disorder (ASD) as compared to neurotypical adolescents and young adults. We utilized thickness of the cerebral cortex as a measure of brain structure, and we found different correlations between language or social communication ability and cortical thickness in distinct regions for the ASD and TD groups. These findings suggest that for regions implicated in language/social communication ability, decreased cortical thickness is associated with more impaired pragmatic language and social communication abilities in ASD.

Altered Resting-State Functional Activity in Patients With Autism Spectrum Disorder: A Quantitative Meta-Analysis

Background: There is accumulating evidence showing that patients with autism spectrum disorder (ASD) have obvious changes in resting-state functional brain activity. So far, there have been no meta-analyses of the resting-state brain activity alterations in patients with ASD. We attempted to explore the resting-state functional activity changes in patients with ASD, possibly providing a new perspective for investigating the pathophysiology of patients with ASD.

Methods: We screened relevant studies published before August 2017 in PubMed, Ovid, Web of Science, China National Knowledge Infrastructure (CNKI), and the Wan-fang database. Fifteen resting-state functional neural activity datasets (including 382 patients and 348 healthy controls) were included. Through the use of the effect-size signed differential mapping (ES-SDM) method, we carried out a meta-analysis of resting-state functional activity studies of patients with ASD.

Results: Compared with healthy controls, patients with ASD showed hyperactivity in the right supplementary motor area, middle frontal gyrus, inferior frontal gyrus, the left precentral gyrus, and the bilateral cerebellum hemispheric lobule (VIII/IX), and hypoactivity in the right middle temporal gyrus, superior temporal gyrus, and the left precuneus, posterior cingulate cortex, median cingulate cortex, and bilateral cerebellum (crus I).

Conclusion: This meta-analysis indicates that patients with ASD have significant and robust resting-state brain activity alterations in the language comprehension network, inferior-posterior cerebellum, default mode network (DMN), and cerebellar crus I. These brain regions may serve as specific regions of interest for further studies of ASD, which will allow us to further clarify the neurobiological mechanisms in patients with ASD.

Facilitating Autism Research

Early autism research focused on behavior and cognition. In recent decades, the pace of research has accelerated, and advances in imaging and genetics have allowed the accumulation of biological data. Nevertheless, a coherent picture of the syndrome at either phenotypic or biological level has not emerged. We see two fundamental obstacles to progress in basic understanding of autism. First, the two defining features (impairment in social interactions and communication, and restricted, repetitive behaviors and interests) are historically seen as integrally related. Others hold that these two major traits are fractionable and must be studied independently, casting doubt on autism as a coherent syndrome. Second, despite much recent research on brain structure and function, environmental factors, and genetics/genomics, findings on the biological level have not generally aligned well with those on the phenotypic level. In the first two sections, we explore these challenges, and in the third section, we review approaches that may facilitate progress, such as (1) including in studies all individuals defined by social impairment without regard to repetitive behaviors, (2) forming narrowly defined subtypes by thorough characterization on specific features, both diagnostic and non-diagnostic, (3) focusing on characteristics that may be relatively robust to environmental influence, (4) studying children as early as possible, minimizing environmental influence, and including longitudinal course as an important part of the phenotype, (5) subtyping by environmental risk factors, (6) distinguishing between what participants can do and what they typically do, and (7) aggregating large data sets across sites. (JINS, 2017, 23, 903-915).

Conceptualising compensation in neurodevelopmental disorders: Reflections from autism spectrum disorder

Within research into neurodevelopmental disorders, little is known about the mechanisms underpinning changes in symptom severity across development. When the behavioural presentation of a condition improves/symptoms lessen, this may be because core underlying atypicalities in cognition/neural function have ameliorated. An alternative possibility is 'compensation'; that the behavioural presentation appears improved, despite persisting deficits at cognitive and/or neurobiological levels. There is, however, currently no agreed technical definition of compensation or its behavioural, cognitive and neural characteristics. Furthermore, its workings in neurodevelopmental disorders have not been studied directly. Here, we review current evidence for compensation in neurodevelopmental disorders, using Autism Spectrum Disorder as an example, in order to move towards a better conceptualisation of the construct. We propose a transdiagnostic framework, where compensation represents the processes responsible for an observed mismatch between behaviour and underlying cognition in a neurodevelopmental disorder, at any point in development. Further, we explore potential cognitive and neural mechanisms driving compensation and discuss the broader relevance of the concept within research and clinical settings.

Does environmental exposure to the greenhouse gas, N2O, contribute to etiological factors in neurodevelopmental disorders? A mini-review of the evidence

BACKGROUND

Neurodevelopmental disorders are increasing in prevalence worldwide. Previous work suggests that exposure to the environmental air pollutant and greenhouse gas - nitrous oxide (N₂O) - may be an etiological factor in neurodevelopmental disorders through the targeting of several neural correlates.

METHODOLOGY

While a number of recent systematic reviews have addressed the role of general anesthesia in the surgical setting and neurodevelopmental outcomes, a narrative mini-review was conducted to first define and characterize the relevant variables (i.e., N₂O, attention-deficit hyperactivity disorder [ADHD] and autism spectrum disorders [ASD]) and their potential interactions into a coherent, hypothesis-generating work. The narrative mini-review merges basic principles in environmental science, anesthesiology, and psychiatry to more fully develop the novel hypotheses that neurodevelopmental impairment found in conditions like ADHD and ASD may be due to exposure to the increasing air pollutant, N₂O.

RESULTS

The results of the present mini-review indicate that exposure to N₂O, even at non-toxic doses, may modulate central neurotransmission and target many neural substrates directly implicated in neurodevelopmental disorders, including the glutamatergic, opioidergic, cholinergic, and dopaminergic systems. Epidemiological studies also indicate that early and repeated exposure to general anesthesia, including N₂O, may contribute to later adverse neurodevelopmental outcomes in children.

CONCLUSIONS

The current evidence and subsequent hypotheses suggest that a renewed interest be taken in the toxicological assessment of environmental N₂O exposure using validated biomarkers and psychiatric endpoints. Given the relevance of N₂O as a greenhouse gas, societies may also wish to engage in a more robust monitoring and reporting of N₂O levels in the environment for climactic benefit as well.