Functional morphological imaging of autism spectrum disorders: Current position and theories proposed

AbstractAutism is a pervasive disorder of childhood development. Polymorphous clinical profiles combining various degrees of communication and social interaction with restricted and stereotyped behaviour are grouped under the heading of ‘autism spectrum disorders’ (ASD). Many teams are trying to pick out the underlying cerebral abnormalities in order to understand the neuronal networks involved in relationships with others. Here we review the morphological, spectroscopic and functional abnormalities in the amygdala-hippocampal circuit, the caudate nuclei, the cerebellum, and the frontotemporal regions, which have been described in subjects with ASD. White matter abnormalities have also been described in diffusion tensor imaging, leading to suspected damage to the subjacent neural networks, such as mirror neurones or the social brain

State-Dependent Differences in Functional Connectivity in Young Children With Autism Spectrum Disorder

AbstractBackgroundWhile there is increasing evidence of altered brain connectivity in autism, the degree and direction of these alterations in connectivity and their uniqueness to autism has not been established. The aim of the present study was to compare connectivity in children with autism to that of typically developing controls and children with developmental delay without autism.MethodsWe assessed EEG spectral power, coherence, phase lag, Pearson and partial correlations, and epileptiform activity during the awake, slow wave sleep, and REM sleep states in 137 children aged 2 to 6years with autism (n=87), developmental delay without autism (n=21), or typical development (n=29).FindingsWe found that brain connectivity, as measured by coherence, phase lag, and Pearson and partial correlations distinguished children with autism from both neurotypical and developmentally delayed children. In general, children with autism had increased coherence which was most prominent during slow wave sleep.InterpretationFunctional connectivity is distinctly different in children with autism compared to samples with typical development and developmental delay without autism. Differences in connectivity in autism are state and region related. In this study, children with autism were characterized by a dynamically evolving pattern of altered connectivity

ANS: Aberrant Neurodevelopment of the Social Cognition Network in Adolescents with Autism Spectrum Disorders

Background: Autism spectrum disorders (ASD) are characterized by aberrant neurodevelopment. Although the ASD brain undergoes precocious growth followed by decelerated maturation during early postnatal period of childhood, the neuroimaging approach has not been empirically applied to investigate how the ASD brain develops during adolescence. Methodology/Principal Findings: We enrolled 25 male adolescents with high functioning ASD and 25 typically developing controls for voxel-based morphometric analysis of structural magnetic resonance image. Results indicate that there is an imbalance of regional gray matter volumes and concentrations along with no global brain enlargement in adolescents with high functioning ASD relative to controls. Notably, the right inferior parietal lobule, a role in social cognition, have a significant interaction of age by groups as indicated by absence of an age-related gain of regional gray matter volume and concentration for neurodevelopmental maturation during adolescence. Conclusions/Significance: The findings indicate the neural correlates of social cognition exhibits aberrant neurodevelopment during adolescence in ASD, which may cast some light on the brain growth dysregulation hypothesis. The period of abnormal brain growth during adolescence may be characteristic of ASD. Age effects must be taken into account while measures of structural neuroimaging have been clinically put forward as potential phenotypes for ASD

The correlation between white-matter microstructure and the complexity of spontaneous brain activity: A difussion tensor imaging-MEG study

The advent of new signal processing methods, such as non-linear analysis techniques, represents a new perspective which adds further value to brain signals' analysis. Particularly, Lempel–Ziv's Complexity (LZC) has proven to be useful in exploring the complexity of the brain electromagnetic activity. However, an important problem is the lack of knowledge about the physiological determinants of these measures. Although acorrelation between complexity and connectivity has been proposed, this hypothesis was never tested in vivo. Thus, the correlation between the microstructure of the anatomic connectivity and the functional complexity of the brain needs to be inspected. In this study we analyzed the correlation between LZC and fractional anisotropy (FA), a scalar quantity derived from diffusion tensors that is particularly useful as an estimate of the functional integrity of myelinated axonal fibers, in a group of sixteen healthy adults (all female, mean age 65.56 ± 6.06 years, intervals 58–82). Our results showed a positive correlation between FA and LZC scores in regions including clusters in the splenium of the corpus callosum, cingulum, parahipocampal regions and the sagittal stratum. This study supports the notion of a positive correlation between the functional complexity of the brain and the microstructure of its anatomical connectivity. Our investigation proved that a combination of neuroanatomical and neurophysiological techniques may shed some light on the underlying physiological determinants of brain's oscillation

Impaired Structural Connectivity of Socio-Emotional Circuits in Autism Spectrum Disorders: A Diffusion Tensor Imaging Study

Abnormal white matter development may disrupt integration within neural circuits, causing particular impairments in higher-order behaviours. In autism spectrum disorders (ASDs), white matter alterations may contribute to characteristic deficits in complex socio-emotional and communication domains. Here, we used diffusion tensor imaging (DTI) and tract based spatial statistics (TBSS) to evaluate white matter microstructure in ASD.DTI scans were acquired for 19 children and adolescents with ASD (∼8-18 years; mean 12.4±3.1) and 16 age and IQ matched controls (∼8-18 years; mean 12.3±3.6) on a 3T MRI system. DTI values for fractional anisotropy, mean diffusivity, radial diffusivity and axial diffusivity, were measured. Age by group interactions for global and voxel-wise white matter indices were examined. Voxel-wise analyses comparing ASD with controls in: (i) the full cohort (ii), children only (≤12 yrs.), and (iii) adolescents only (>12 yrs.) were performed, followed by tract-specific comparisons. Significant age-by-group interactions on global DTI indices were found for all three diffusivity measures, but not for fractional anisotropy. Voxel-wise analyses revealed prominent diffusion measure differences in ASD children but not adolescents, when compared to healthy controls. Widespread increases in mean and radial diffusivity in ASD children were prominent in frontal white matter voxels. Follow-up tract-specific analyses highlighted disruption to pathways integrating frontal, temporal, and occipital structures involved in socio-emotional processing.Our findings highlight disruption of neural circuitry in ASD, particularly in those white matter tracts that integrate the complex socio-emotional processing that is impaired in this disorder

Review of neuroimaging in autism spectrum disorders: what have we learned and where we go from here

Autism spectrum disorder (ASD) refers to a syndrome of social communication deficits and repetitive behaviors or restrictive interests. It remains a behaviorally defined syndrome with no reliable biological markers. The goal of this review is to summarize the available neuroimaging data and examine their implication for our understanding of the neurobiology of ASD

White matter microstructure correlates with autism trait severity in a combined clinical–control sample of high-functioning adults

AbstractDiffusion tensor imaging (DTI) studies have demonstrated white matter (WM) abnormalities in tracts involved in emotion processing in autism spectrum disorder (ASD), but little is known regarding the nature and distribution of WM anomalies in relation to ASD trait severity in adults. Increasing evidence suggests that ASD occurs at the extreme of a distribution of social abilities. We aimed to examine WM microstructure as a potential marker for ASD symptom severity in a combined clinical–neurotypical population. SIENAX was used to estimate whole brain volume. Tract-based spatial statistics (TBSS) was used to provide a voxel-wise comparison of WM microstructure in 50 high-functioning young adults: 25 ASD and 25 neurotypical. The severity of ASD traits was measured by autism quotient (AQ); we examined regressions between DTI markers of WM microstructure and ASD trait severity. Cognitive abilities, measured by intelligence quotient, were well-matched between the groups and were controlled in all analyses. There were no significant group differences in whole brain volume. TBSS showed widespread regions of significantly reduced fractional anisotropy (FA) and increased mean diffusivity (MD) and radial diffusivity (RD) in ASD compared with controls. Linear regression analyses in the combined sample showed that average whole WM skeleton FA was negatively influenced by AQ (p=0.004), whilst MD and RD were positively related to AQ (p=0.002; p=0.001). Regression slopes were similar within both groups and strongest for AQ social, communication and attention switching scores. In conclusion, similar regression characteristics were found between WM microstructure and ASD trait severity in a combined sample of ASD and neurotypical adults. WM anomalies were relatively more severe in the clinically diagnosed sample. Both findings suggest that there is a dimensional relationship between WM microstructure and severity of ASD traits from neurotypical subjects through to clinical ASD, with reduced coherence of WM associated with greater ASD symptoms. General cognitive abilities were independent of the relationship between WM indices and ASD traits

Gray matter volume correlates of Comorbid Depression in Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) involves diverse neurodevelopmental syndromes with significant deficits in communication, motor behaviours, emotional and social comprehension. Often, individuals with ASD exhibit comorbid conditions, one of the most prevalent being depression characterized by a persistent change in mood and diminished interest in previously enjoyable activities. Due to communicative challenges and lack of appropriate assessments in individuals with ASD, comorbid depression can often go undiagnosed during routine clinical examinations, which may aggravate their problems. The current literature on comorbid depression in adults with ASD is limited. Therefore, understanding the neural basis of the comorbid psychopathology of depression in ASD is crucial for identifying objective brain-based markers for its timely and effective management. Towards this end, using structural MRI and phenotypic data from the Autism Brain Imaging Data Exchange II (ABIDE II) repository, we specifically examined the pattern of relationship regional grey matter volume (rGMV) has with comorbid depression and autism severity within regions of a priori interest in adults with ASD (n = 44). The severity of comorbid depression correlated negatively with the rGMV of the right thalamus. Additionally, a significant interaction was evident between the severity of comorbid depression and core ASD symptoms towards explaining the rGMV in the left cerebellum crus II. The whole-brain regional rGMV differences between ASD and typically developed (TD, n = 39) adults remained inconclusive. The results further the understanding of the neurobiological underpinnings of comorbid depression in adults with ASD and are relevant in exploring structural neuroimaging-based biomarkers in the same cohort.Comment: 33 pages, 3 figures, 3 tables, journal submissio

Structural connectivity of the amygdala in young adults with autism spectrum disorder

Autism spectrum disorder (ASD) is characterized by impairments in social cognition, a function associated with the amygdala. Subdivisions of the amygdala have been identified which show specificity of structure, connectivity, and function. Little is known about amygdala connectivity in ASD. The aim of this study was to investigate the microstructural properties of amygdala-cortical connections and their association with ASD behaviours, and whether connectivity of specific amygdala subregions is associated with particular ASD traits. The brains of 51 high-functioning young adults (25 with ASD; 26 controls) were scanned using MRI. Amygdala volume was measured, and amygdala-cortical connectivity estimated using probabilistic tractography. An iterative 'winner takes all' algorithm was used to parcellate the amygdala based on its primary cortical connections. Measures of amygdala connectivity were correlated with clinical scores. In comparison with controls, amygdala volume was greater in ASD (F(1,94) = 4.19; p = .04). In white matter (WM) tracts connecting the right amygdala to the right cortex, ASD subjects showed increased mean diffusivity (t = 2.35; p = .05), which correlated with the severity of emotion recognition deficits (rho = -0.53; p = .01). Following amygdala parcellation, in ASD subjects reduced fractional anisotropy in WM connecting the left amygdala to the temporal cortex was associated with with greater attention switching impairment (rho = -0.61; p = .02). This study demonstrates that both amygdala volume and the microstructure of connections between the amygdala and the cortex are altered in ASD. Findings indicate that the microstructure of right amygdala WM tracts are associated with overall ASD severity, but that investigation of amygdala subregions can identify more specific associations

White and Grey Matter Abnormalities in Autism Align with Verbal Ability

This whole-brain structural magnetic resonance imaging (MRI) investigation of autism spectrum disorder (ASD) analyzed white and grey matter concentrations, shape differences, and brain microstructure in 20 adolescents with ASD and 10 neurotypical controls. Evidence for significant group-related differences was found in nine regions, most associated with language processing, including the precentral gyrus, the anterior cingulate, the operculum, superior frontal, and superior temporal gyri. An additional analysis revealed that lower scores from a standardized measure of receptive verbal ability correlated with reduced white matter in the arcuate and uncinate fascicles, inthalamo-frontal and thalamo-cerebellar connections, and in interhemispheric connections passing through the callosal sections I and V. Our findings point to distinct neurological subgroups in ASD which align with the level of verbal ability