Autistic spectrum disorder (ASD) is accompanied by subtle and spatially distributed differences in brain anatomy that are difficult to detect using conventional mass-univariate methods (e.g., VBM). ...These require correction for multiple comparisons and hence need relatively large samples to attain sufficient statistical power. Reports of neuroanatomical differences from relatively small studies are thus highly variable. Also, VBM does not provide predictive value, limiting its diagnostic value.
Here, we examined neuroanatomical networks implicated in ASD using a whole-brain classification approach employing a support vector machine (SVM) and investigated the predictive value of structural MRI scans in adults with ASD. Subsequently, results were compared between SVM and VBM. We included 44 male adults; 22 diagnosed with ASD using “gold-standard” research interviews and 22 healthy matched controls.
SVM identified spatially distributed networks discriminating between ASD and controls. These included the limbic, frontal-striatal, fronto-temporal, fronto-parietal and cerebellar systems. SVM applied to gray matter scans correctly classified ASD individuals at a specificity of 86.0% and a sensitivity of 88.0%. Cases (68.0%) were correctly classified using white matter anatomy. The distance from the separating hyperplane (i.e., the test margin) was significantly related to current symptom severity. In contrast, VBM revealed few significant between-group differences at conventional levels of statistical stringency.
We therefore suggest that SVM can detect subtle and spatially distributed differences in brain networks between adults with ASD and controls. Also, these differences provide significant predictive power for group membership, which is related to symptom severity.
Autism spectrum disorder (ASD) is a neurodevelopmental condition with multiple causes, comorbid conditions, and a wide range in the type and severity of symptoms expressed by different individuals. ...This makes the neuroanatomy of autism inherently difficult to describe. Here, we demonstrate how a multiparameter classification approach can be used to characterize the complex and subtle structural pattern of gray matter anatomy implicated in adults with ASD, and to reveal spatially distributed patterns of discriminating regions for a variety of parameters describing brain anatomy. A set of five morphological parameters including volumetric and geometric features at each spatial location on the cortical surface was used to discriminate between people with ASD and controls using a support vector machine (SVM) analytic approach, and to find a spatially distributed pattern of regions with maximal classification weights. On the basis of these patterns, SVM was able to identify individuals with ASD at a sensitivity and specificity of up to 90% and 80%, respectively. However, the ability of individual cortical features to discriminate between groups was highly variable, and the discriminating patterns of regions varied across parameters. The classification was specific to ASD rather than neurodevelopmental conditions in general (e.g., attention deficit hyperactivity disorder). Our results confirm the hypothesis that the neuroanatomy of autism is truly multidimensional, and affects multiple and most likely independent cortical features. The spatial patterns detected using SVM may help further exploration of the specific genetic and neuropathological underpinnings of ASD, and provide new insights into the most likely multifactorial etiology of the condition.
Autism spectrum disorder (ASD) is a common neurodevelopmental disorder characterized by pervasive difficulties since early childhood across reciprocal social communication and restricted, repetitive ...interests and behaviors. Although early ASD research focused primarily on children, there is increasing recognition that ASD is a lifelong neurodevelopmental disorder. However, although health and education services for children with ASD are relatively well established, service provision for adults with ASD is in its infancy. There is a lack of health services research for adults with ASD, including identification of comorbid health difficulties, rigorous treatment trials (pharmacological and psychological), development of new pharmacotherapies, investigation of transition and aging across the lifespan, and consideration of sex differences and the views of people with ASD. This article reviews available evidence regarding the etiology, legislation, diagnosis, management, and service provision for adults with ASD and considers what is needed to support adults with ASD as they age. We conclude that health services research for adults with ASD is urgently warranted. In particular, research is required to better understand the needs of adults with ASD, including health, aging, service development, transition, treatment options across the lifespan, sex, and the views of people with ASD. Additionally, the outcomes of recent international legislative efforts to raise awareness of ASD and service provision for adults with ASD are to be determined. Future research is required to identify high-quality, evidence-based, and cost-effective models of care. Furthermore, future health services research is also required at the beginning and end of adulthood, including improved transition from youth to adult health care and increased understanding of aging and health in older adults with ASD.
Sustained attention problems are common in people with autism spectrum disorder (ASD) and may have significant implications for the diagnosis and management of ASD and associated comorbidities. ...Furthermore, ASD has been associated with atypical structural brain development. The authors used functional MRI to investigate the functional brain maturation of attention between childhood and adulthood in people with ASD.
Using a parametrically modulated sustained attention/vigilance task, the authors examined brain activation and its linear correlation with age between childhood and adulthood in 46 healthy male adolescents and adults (ages 11-35 years) with ASD and 44 age- and IQ-matched typically developing comparison subjects.
Relative to the comparison group, the ASD group had significantly poorer task performance and significantly lower activation in inferior prefrontal cortical, medial prefrontal cortical, striato-thalamic, and lateral cerebellar regions. A conjunction analysis of this analysis with group differences in brain-age correlations showed that the comparison group, but not the ASD group, had significantly progressively increased activation with age in these regions between childhood and adulthood, suggesting abnormal functional brain maturation in ASD. Several regions that showed both abnormal activation and functional maturation were associated with poorer task performance and clinical measures of ASD and inattention.
The results provide first evidence that abnormalities in sustained attention networks in individuals with ASD are associated with underlying abnormalities in the functional brain maturation of these networks between late childhood and adulthood.
Prior work has revealed sex/gender-dependent autistic characteristics across behavioural and neural/biological domains. It remains unclear whether and how neural sex/gender differences are related to ...behavioural sex/gender differences in autism. Here, we examined whether atypical neural responses during mentalizing and self-representation are sex/gender-dependent in autistic adults and explored whether ‘camouflaging’ (acting as if behaviourally neurotypical) is associated with sex/gender-dependent neural responses. In total, N = 119 adults (33 typically developing males, 29 autistic males, 29 typically developing females and 28 autistic females) participated in a task-related functional magnetic resonance imaging paradigm to assess neural activation within right temporo-parietal junction and ventromedial prefrontal cortex during mentalizing and self-representation. Camouflaging in autism was quantified as the discrepancy between extrinsic behaviour in social–interpersonal contexts and intrinsic status. While autistic men showed hypoactive right temporo-parietal junction mentalizing and ventromedial prefrontal cortex self-representation responses compared to typically developing men, such neural responses in autistic women were not different from typically developing women. In autistic women only, increasing camouflaging was associated with heightened ventromedial prefrontal cortex self-representation response. There is a lack of impaired neural self-representation and mentalizing in autistic women compared to typically developing women. Camouflaging is heightened in autistic women and may relate to neural self-representation response. These results reveal brain-behaviour relations that help explain sex/gender-heterogeneity in social brain function in autism.
Repetitive behaviour and inhibitory control deficits are core features of autism; and it has been suggested that they result from differences in the anatomy of striatum; and/or the ‘connectivity’ of ...subcortical regions to frontal cortex. There are few studies, however, that have measured the micro-structural organisation of white matter tracts connecting striatum and frontal cortex.
To investigate differences in bulk volume of striatum and micro-structural organisation of fronto-striatal white matter in people with autism; and their association with repetitive behaviour and inhibitory control.
We compared the bulk volume of striatum (caudate nucleus, putamen and nucleus accumbens) and white matter organisation of fronto-striatal tracts using (respectively) structural magnetic resonance imaging (sMRI) and tract specific diffusion tensor imaging (DTI) measures in 21 adults with autism and 22 controls. We also assessed performance on a cognitive inhibition (go/nogo) task.
Bulk volume of striatal structures did not differ between groups. However, adults with autism had a significantly smaller total brain white matter volume, lower fractional anisotropy of white matter tracts connecting putamen to frontal cortical areas, higher mean diffusivity of white matter tracts connecting accumbens to frontal cortex and worse performance on the go/nogo task. Also, performance on the go/nogo task was significantly related to anatomical variation when both groups were combined; but not within the autism group alone.
These data suggest that autism may be associated with differences in the anatomy of fronto-striatal white matter tracts.
Sexual dimorphism in human brain structure is well recognised, but little is known about gender differences in white matter microstructure. We used diffusion tensor imaging to explore differences in ...fractional anisotropy (FA), an index of microstructural integrity.
A whole brain analysis of 135 matched subjects (90 men and 45 women) using a 1.5 T scanner. A region of interest (ROI) analysis was used to confirm those results where proximity to CSF raised the possibility of partial-volume artefact.
Men had higher fractional anisotropy (FA) in cerebellar white matter and in the left superior longitudinal fasciculus; women had higher FA in the corpus callosum, confirmed by ROI.
The size of the differences was substantial--of the same order as that attributed to some pathology--suggesting gender may be a potentially significant confound in unbalanced clinical studies. There are several previous reports of difference in the corpus callosum, though they disagree on the direction of difference; our findings in the cerebellum and the superior longitudinal fasciculus have not previously been noted. The higher FA in women may reflect greater efficiency of a smaller corpus callosum. The relatively increased superior longitudinal fasciculus and cerebellar FA in men may reflect their increased language lateralisation and enhanced motor development, respectively.
Autism spectrum disorder (ASD) is 2 to 5 times more common in male individuals than in female individuals. While the male preponderant prevalence of ASD might partially be explained by sex ...differences in clinical symptoms, etiological models suggest that the biological male phenotype carries a higher intrinsic risk for ASD than the female phenotype. To our knowledge, this hypothesis has never been tested directly, and the neurobiological mechanisms that modulate ASD risk in male individuals and female individuals remain elusive.
To examine the probability of ASD as a function of normative sex-related phenotypic diversity in brain structure and to identify the patterns of sex-related neuroanatomical variability associated with low or high probability of ASD.
This study examined a cross-sectional sample of 98 right-handed, high-functioning adults with ASD and 98 matched neurotypical control individuals aged 18 to 42 years. A multivariate probabilistic classification approach was used to develop a predictive model of biological sex based on cortical thickness measures assessed via magnetic resonance imaging in neurotypical controls. This normative model was subsequently applied to individuals with ASD. The study dates were June 2005 to October 2009, and this analysis was conducted between June 2015 and July 2016.
Sample and population ASD probability estimates as a function of normative sex-related diversity in brain structure, as well as neuroanatomical patterns associated with low or high ASD probability in male individuals and female individuals.
Among the 98 individuals with ASD, 49 were male and 49 female, with a mean (SD) age of 26.88 (7.18) years. Among the 98 controls, 51 were male and 47 female, with a mean (SD) age of 27.39 (6.44) years. The sample probability of ASD increased significantly with predictive probabilities for the male neuroanatomical brain phenotype. For example, biological female individuals with a more male-typic pattern of brain anatomy were significantly (ie, 3 times) more likely to have ASD than biological female individuals with a characteristically female brain phenotype (P = .72 vs .24, respectively; χ21 = 20.26; P < .001; difference in P values, 0.48; 95% CI, 0.29-0.68). This finding translates to an estimated variability in population prevalence from 0.2% to 1.3%, respectively. Moreover, the patterns of neuroanatomical variability carrying low or high ASD probability were sex specific (eg, in inferior temporal regions, where ASD has different neurobiological underpinnings in male individuals and female individuals).
These findings highlight the need for considering normative sex-related phenotypic diversity when determining an individual's risk for ASD and provide important novel insights into the neurobiological mechanisms mediating sex differences in ASD prevalence.
There is increasing evidence that children with autism spectrum disorder (ASD) have age-related differences from controls in cortical volume (CV). It is less clear, however, if these persist in ...adulthood and whether these reflect alterations in cortical thickness (CT) or cortical surface area (SA). Hence, we used magnetic resonance imaging to investigate the relationship between age and CV, CT, and SA in 127 males aged 10 through 60 years (76 with ASD and 51 healthy controls). “Regional” analyses (using cortical parcellation) identified significant age-by-group interactions in both CV and CT (but not SA) in the temporal lobes and within these the fusiform and middle temporal gyri. Spatially nonbiased “vertex-based” analysis replicated these results and identified additional “age-by-group” interactions for CT within superior temporal, inferior and medial frontal, and inferior parietal cortices. Here, CV and CT were 1) significantly negatively correlated with age in controls, but not in ASD, and 2) smaller in ASD than controls in childhood but vice versa in adulthood. Our findings suggest that CV dysmaturation in ASD extends beyond childhood, affects brain regions crucial to social cognition and language, and is driven by CT dysmaturation. This may reflect primary abnormalities in cortical plasticity and/or be secondary to disturbed interactions between individuals with ASD and their environment.
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