Microstructural connectivity of the arcuate fasciculus in adolescents with high-functioning autism

Comparison of white matter integrity between autism spectrum disorder subjects and typically developing individuals: a meta-analysis of diffusion tensor imaging tractography studies

BACKGROUND

Aberrant brain connectivity, especially with long-distance underconnectivity, has been recognized as a candidate pathophysiology of autism spectrum disorders. However, a number of diffusion tensor imaging studies investigating people with autism spectrum disorders have yielded inconsistent results.

METHODS

To test the long-distance underconnectivity hypothesis, we performed a systematic review and meta-analysis of diffusion tensor imaging studies in subjects with autism spectrum disorder. Diffusion tensor imaging studies comparing individuals with autism spectrum disorders with typically developing individuals were searched using MEDLINE, Web of Science and EMBASE from 1980 through 1 August 2012. Standardized mean differences were calculated as an effect size of the tracts.

RESULTS

A comprehensive literature search identified 25 relevant diffusion tensor imaging studies comparing autism spectrum disorders and typical development with regions-of-interest methods. Among these, 14 studies examining regions of interest with suprathreshold sample sizes were included in the meta-analysis. A random-effects model demonstrated significant fractional anisotropy reductions in the corpus callosum (P = 0.023, n = 387 (autism spectrum disorders/typically developing individuals: 208/179)), left uncinate fasciculus (P = 0.011, n = 242 (117/125)), and left superior longitudinal fasciculus (P = 0.016, n = 182 (96/86)), and significant increases of mean diffusivity in the corpus callosum (P = 0.006, n = 254 (129/125)) and superior longitudinal fasciculus bilaterally (P = 0.031 and 0.011, left and right, respectively, n = 109 (51/58)), in subjects with autism spectrum disorders compared with typically developing individuals with no significant publication bias.

CONCLUSION

The current meta-analysis of diffusion tensor imaging studies in subjects with autism spectrum disorders emphasizes important roles of the superior longitudinal fasciculus, uncinate fasciculus, and corpus callosum in the pathophysiology of autism spectrum disorders and supports the long-distance underconnectivity hypothesis.

Selective disruption of sociocognitive structural brain networks in autism and alexithymia

Autism spectrum conditions (ASC) are neurodevelopmental disorders characterized by abnormal social cognition. A core feature of ASC is disrupted Theory of Mind (ToM), our ability to take the mental perspective of others. ASC is also associated with alexithymia, a trait characterized by altered emotional interoception and empathy. Here, we applied structural MRI covariance analysis to assess whether ASC and alexithymia differentially affect structural brain networks associated with sociocognitive and socioaffective functions. Based on previous functional MRI findings, we expected disrupted ToM networks (centered on dorsomedial prefontal cortex [dmPFC], and temporo-parietal junction [TPJ]) in ASC, while alexithymia would affect networks centered on fronto-insular cortex (FI), regions associated with interoception of emotion and empathy. Relative to controls, ASC indeed showed reduced covariance in networks centered on dmPFC and TPJ, but not within FI networks. Irrespective of ASC, covariance was negatively modulated by alexithymia in networks extending from FI to posterior regions. Network findings were complemented by self-reports, indicating decreased perspective taking but normal empathic concern in ASC. Our results show divergent effects of ASC and alexithymia on inter-regional structural networks, suggesting that networks mediating socioaffective processes may be separable from networks mediating sociocognitive processing.

Tract-based spatial statistics reveal altered relationship between non-verbal reasoning abilities and white matter integrity in autism spectrum disorder

Altered brain connectivity accompanies autism spectrum disorders (ASD), but the relationship between connectivity and intellectual abilities, which often differs within ASD, and between ASD and typically developing (TD) children, is not understood. Here, diffusion tensor imaging (DTI) was used to explore the relationship between white matter integrity and non-verbal intelligence quotients (IQ) in children with ASD and in age- and gender-matched TD children. Tract-based spatial statistical analyses (TBSS) of DTI fractional anisotropy (FA) revealed altered relationships between white matter and IQ. Different relationships were found using within-group analyses, where regions of significant (p < .05, corrected) correlations in ASD overlapped minimally with regions of FA-IQ correlations in TD subjects. An additional between-groups analysis revealed significant correlation differences in widespread cortical and subcortical areas. These preliminary findings suggest altered brain connectivity may underlie some differences in intellectual abilities of ASD, and should be investigated further in larger samples as a function of development.

Pathways to seeing music: enhanced structural connectivity in colored-music synesthesia

Synesthesia, a condition in which a stimulus in one sensory modality consistently and automatically triggers concurrent percepts in another modality, provides a window into the neural correlates of cross-modal associations. While research on grapheme-color synesthesia has provided evidence for both hyperconnectivity-hyperbinding and disinhibited feedback as potential underlying mechanisms, less research has explored the neuroanatomical basis of other forms of synesthesia. In the current study we investigated the white matter correlates of colored-music synesthesia. As these synesthetes report seeing colors upon hearing musical sounds, we hypothesized that they might show unique patterns of connectivity between visual and auditory association areas. We used diffusion tensor imaging to trace the white matter tracts in temporal and occipital lobe regions in 10 synesthetes and 10 matched non-synesthete controls. Results showed that synesthetes possessed hemispheric patterns of fractional anisotropy, an index of white matter integrity, in the inferior fronto-occipital fasciculus (IFOF), a major white matter pathway that connects visual and auditory association areas to frontal regions. Specifically, white matter integrity within the right IFOF was significantly greater in synesthetes than controls. Furthermore, white matter integrity in synesthetes was correlated with scores on audiovisual tests of the Synesthesia Battery, especially in white matter underlying the right fusiform gyrus. Our findings provide the first evidence of a white matter substrate of colored-music synesthesia, and suggest that enhanced white matter connectivity is involved in enhanced cross-modal associations.

Global cerebral and regional multimodal neuroimaging markers of the neurobiology of autism: development and cognition

Quantitative magnetic resonance imaging (MRI) studies of the microstructure and macrostructure in children with autism report contradictory results due, in part, to the autistic population heterogeneity from factors such as variation in intellect and inadequately accounting for age-related changes in brain development. In this report, the authors compared global and regional volumetry, relaxometry, anisotropy, and diffusometry of gray and white matter in 10 autism spectrum disorder children relative to the age-related trajectories obtained from 38 typically developing controls while controlling for nonverbal intellect using a validated quantitative MRI method. The normalized hippocampus volume increased with age in both autistic and typically developing individuals with limbic structures larger in autistic patients. Hippocampus volume, but not diffusivity or relaxation time, was larger in autistic children. Hippocampus volume was inversely correlated with nonverbal intellect across control individuals. The pattern of hippocampal abnormalities suggests a disturbance in early brain development in autistic children independent of intellect.

White matter microstructure correlates of narrative production in typically developing children and children with high functioning autism

This study investigated the relationship between white matter microstructure and the development of morphosyntax in a spoken narrative in typically developing children (TD) and in children with high functioning autism (HFA). Autism is characterized by language and communication impairments, yet the relationship between morphosyntactic development in spontaneous discourse contexts and neural development is not well understood in either this population or typical development. Diffusion tensor imaging (DTI) was used to assess multiple parameters of diffusivity as indicators of white matter tract integrity in language-related tracts in children between 6 and 13 years of age. Children were asked to spontaneously tell a story about at time when someone made them sad, mad, or angry. The story was evaluated for morphological accuracy and syntactic complexity. Analysis of the relationship between white matter microstructure and language performance in TD children showed that diffusivity correlated with morphosyntax production in the superior longitudinal fasciculus (SLF), a fiber tract traditionally associated with language. At the anatomical level, the HFA group showed abnormal diffusivity in the right inferior longitudinal fasciculus (ILF) relative to the TD group. Within the HFA group, children with greater white matter integrity in the right ILF displayed greater morphological accuracy during their spoken narrative. Overall, the current study shows an association between white matter structure in a traditional language pathway and narrative performance in TD children. In the autism group, associations were only found in the ILF, suggesting that during real world language use, children with HFA rely less on typical pathways and more on alternative ventral pathways that possibly mediate visual elements of language.

Functional magnetic resonance imaging of autism spectrum disorders

This review presents an overview of functional magnetic resonance imaging findings in autism spectrum disorders (ASDS), although there is considerable heterogeneity with respect to results across studies, common themes have emerged, including: (i) hypoactivation in nodes of the "social brain" during social processing tasks, including regions within the prefrontal cortex, the posterior superior temporal sulcus, the amygdala, and the fusiform gyrus; (ii) aberrant frontostriatal activation during cognitive control tasks relevant to restricted and repetitive behaviors and interests, including regions within the dorsal prefrontal cortex and the basal ganglia; (iii) differential lateralization and activation of language processing and production regions during communication tasks; (iv) anomalous mesolimbic responses to social and nonsocial rewards; (v) task-based long-range functional hypoconnectivity and short-range hyper-connectivity; and (vi) decreased anterior-posterior functional connectivity during resting states. These findings provide mechanistic accounts of ASD pathophysiology and suggest directions for future research aimed at elucidating etiologic models and developing rationally derived and targeted treatments.

White matter and visuospatial processing in autism: a constrained spherical deconvolution tractography study

Autism spectrum disorders (ASDs) are associated with a marked disturbance of neural functional connectivity, which may arise from disrupted organization of white matter. The aim of this study was to use constrained spherical deconvolution (CSD)-based tractography to isolate and characterize major intrahemispheric white matter tracts that are important in visuospatial processing. CSD-based tractography avoids a number of critical confounds that are associated with diffusion tensor tractography, and to our knowledge, this is the first time that this advanced diffusion tractography method has been used in autism research. Twenty-five participants with ASD and aged 25, intelligence quotient-matched controls completed a high angular resolution diffusion imaging scan. The inferior fronto-occipital fasciculus (IFOF) and arcuate fasciculus were isolated using CSD-based tractography. Quantitative diffusion measures of white matter microstructural organization were compared between groups and associated with visuospatial processing performance. Significant alteration of white matter organization was present in the right IFOF in individuals with ASD. In addition, poorer visuospatial processing was associated in individuals with ASD with disrupted white matter in the right IFOF. Using a novel, advanced tractography method to isolate major intrahemispheric white matter tracts in autism, this research has demonstrated that there are significant alterations in the microstructural organization of white matter in the right IFOF in ASD. This alteration was associated with poorer visuospatial processing performance in the ASD group. This study provides an insight into structural brain abnormalities that may influence atypical visuospatial processing in autism.

Brain function differences in language processing in children and adults with autism

Comparison of brain function between children and adults with autism provides an understanding of the effects of the disorder and associated maturational differences on language processing. Functional imaging (functional magnetic resonance imaging) was used to examine brain activation and cortical synchronization during the processing of literal and ironic texts in 15 children with autism, 14 children with typical development, 13 adults with autism, and 12 adult controls. Both the children and adults with autism had lower functional connectivity (synchronization of brain activity among activated areas) than their age and ability comparison group in the left hemisphere language network during irony processing, and neither autism group had an increase in functional connectivity in response to increased task demands. Activation differences for the literal and irony conditions occurred in key language-processing regions (left middle temporal, left pars triangularis, left pars opercularis, left medial frontal, and right middle temporal). The children and adults with autism differed from each other in the use of some brain regions during the irony task, with the adults with autism having activation levels similar to those of the control groups. Overall, the children and adults with autism differed from the adult and child controls in (a) the degree of network coordination, (b) the distribution of the workload among member nodes, and (3) the dynamic recruitment of regions in response to text content. Moreover, the differences between the two autism age groups may be indicative of positive changes in the neural function related to language processing associated with maturation and/or educational experience.

Autism, lateralisation, and handedness: a review of the literature and meta-analysis

A number of recent investigators have hypothesised a link between autism, left-handedness, and brain laterality. Their findings have varied widely, in part because these studies have relied on different methodologies and definitions. We conducted a systematic review and meta-analysis to assess the literature, with the hypothesis that there would be an association between autism and laterality that would be moderated by handedness, sex, age, brain region studied, and level of autism. From a broad search resulting in 259 papers, 54 were identified for inclusion in the literature review. This list was narrowed further to include only studies reporting results in the inferior frontal gyrus for meta-analysis, resulting in four papers. The meta-analysis found a moderate but non-significant effect size of group on lateralisation, suggesting a decrease in strength of lateralisation in the autistic group, a trend supported by the literature review. A subgroup analysis of sex and a meta-regression of handedness showed that these moderating variables did not have a significant effect on this relationship. Although the results are not conclusive, there appears to be a trend towards a relationship between autism and lateralisation. However, more rigorous studies with better controls and clearer reporting of definitions and results are needed.

Tracing superior longitudinal fasciculus connectivity in the human brain using high resolution diffusion tensor tractography

The major language pathways such as superior longitudinal fasciculus (SLF) pathways have been outlined by experimental and diffusion tensor imaging (DTI) studies. The SLF I and some of the superior parietal lobule connections of the SLF pathways have not been depicted by prior DTI studies due to the lack of imaging sensitivity and adequate spatial resolution. In the current study, the trajectory of the SLF fibers has been delineated on five healthy human subjects using diffusion tensor tractography on a 3.0-T scanner at high spatial resolution. We also demonstrate for the first time the trajectory and connectivity of the SLF fibers in relation to other language pathways as well as the superior parietal lobule connections of the language circuit using high spatial resolution DTI in the healthy adult human brain.

Diffusion tensor imaging in young children with autism: biological effects and potential confounds

BACKGROUND

Diffusion tensor imaging (DTI) has been used over the past decade to study structural differences in the brains of children with autism compared with typically developing children. These studies generally find reduced fractional anisotropy (FA) and increased mean diffusivity (MD) in children with autism; however, the regional pattern of findings varies greatly.

METHODS

We used DTI to investigate the brains of sedated children with autism (n = 39) and naturally asleep typically developing children (n = 39) between 2 and 8 years of age. Tract based spatial statistics and whole brain voxel-wise analysis were performed to investigate the regional distribution of differences between groups.

RESULTS

In children with autism, we found significantly reduced FA in widespread regions and increased MD only in posterior brain regions. Significant age × group interaction was found, indicating a difference in developmental trends of FA and MD between children with autism and typically developing children. The magnitude of the measured differences between groups was small, on the order of approximately 1%-2%. Subjects and control subjects showed distinct regional differences in imaging artifacts that can affect DTI measures.

CONCLUSIONS

We found statistically significant differences in DTI metrics between children with autism and typically developing children, including different developmental trends of these metrics. However, this study indicates that between-group differences in DTI studies of autism should be interpreted with caution, because their small magnitude make these measurements particularly vulnerable to the effects of artifacts and confounds, which might lead to false positive and/or false negative biological inferences.

White matter microstructure asymmetry: effects of volume asymmetry on fractional anisotropy asymmetry

Diffusion tensor imaging (DTI) provides information regarding white matter microstructure; however, macroscopic fiber architectures can affect DTI measures. A larger brain (fiber tract) has a 'relatively' smaller voxel size, and the voxels are less likely to contain more than one fiber orientation and more likely to have higher fractional anisotropy (FA). Previous DTI studies report left-to-right differences in the white matter; however, these may reflect true microscopic differences or be caused purely by volume differences. Using tract-based spatial statistics, we investigated left-to-right differences in white matter microstructure across the whole brain. Voxel-wise analysis revealed a large number of white matter volume asymmetries, including leftward asymmetry of the arcuate fasciculus and cingulum. In many white matter regions, FA asymmetry was positively correlated with volume asymmetry. Voxel-wise analysis with adjustment for volume asymmetry revealed many white matter FA asymmetries, including leftward asymmetry of the arcuate fasciculus and cingulum. The voxel-wise analysis showed a reduced number of regions with significant FA asymmetry compared with analysis performed without adjustment for volume asymmetry; however, the overall trend of the results was unchanged. The results of the present study suggest that these FA asymmetries are not caused by volume differences and reflect microscopic differences in the white matter.

White matter connectivity in children with autism spectrum disorders: a tract-based spatial statistics study

Background

Autism spectrum disorders (ASD) are associated with widespread alterations in white matter (WM) integrity. However, while a growing body of studies is shedding light on microstructural WM alterations in high-functioning adolescents and adults with ASD, literature is still lacking in information about whole brain structural connectivity in children and low-functioning patients with ASD. This research aims to investigate WM connectivity in ASD children with and without mental retardation compared to typically developing controls (TD).

Methods

Diffusion tensor imaging (DTI) was performed in 22 young children with ASD (mean age: 5.54 years) and 10 controls (mean age: 5.25 years). Data were analysed both using the tract-based spatial statistics (TBSS) and the tractography. Correlations were investigated between the WM microstructure in the identified altered regions and the productive language level.

Results

The TBSS analysis revealed widespread increase of fractional anisotropy (FA) in major WM pathways. The tractographic approach showed an increased fiber length and FA in the cingulum and in the corpus callosum and an increased mean diffusivity in the indirect segments of the right arcuate and the left cingulum. Mean diffusivity was also correlated with expressive language functioning in the left indirect segments of the arcuate fasciculus.

Conclusions

Our study confirmed the presence of several structural connectivity abnormalities in young ASD children. In particular, the TBSS profile of increased FA that characterized the ASD patients extends to children a finding previously detected in ASD toddlers only. The WM integrity abnormalities detected may be relevant to the pathophysiology of ASD, since the structures involved participate in some core atypical characteristics of the disorder.

State-dependent changes of connectivity patterns and functional brain network topology in autism spectrum disorder

Anatomical and functional brain studies have converged to the hypothesis that autism spectrum disorders (ASD) are associated with atypical connectivity. Using a modified resting-state paradigm to drive subjects' attention, we provide evidence of a very marked interaction between ASD brain functional connectivity and cognitive state. We show that functional connectivity changes in opposite ways in ASD and typicals as attention shifts from external world towards one's body generated information. Furthermore, ASD subject alter more markedly than typicals their connectivity across cognitive states. Using differences in brain connectivity across conditions, we ranked brain regions according to their classification power. Anterior insula and dorsal-anterior cingulate cortex were the regions that better characterize ASD differences with typical subjects across conditions, and this effect was modulated by ASD severity. These results pave the path for diagnosis of mental pathologies based on functional brain networks obtained from a library of mental states.

Diffusion tensor imaging in autism spectrum disorder: a review

White matter tracts of the brain allow neurons and neuronal networks to communicate and function with high efficiency. The aim of this review is to briefly introduce diffusion tensor imaging methods that examine white matter tracts and then to give an overview of the studies that have investigated white matter integrity in the brains of individuals with autism spectrum disorder (ASD). From the 48 studies we reviewed, persons with ASD tended to have decreased fractional anisotropy and increased mean diffusivity in white matter tracts spanning many regions of the brain but most consistently in regions such as the corpus callosum, cingulum, and aspects of the temporal lobe. This decrease in fractional anisotropy was often accompanied by increased radial diffusivity. Additionally, the review suggests possible atypical lateralization in some white matter tracts of the brain and a possible atypical developmental trajectory of white matter microstructure in persons with ASD. Clinical implications and future research directions are discussed.

Elevated mean diffusivity in the left hemisphere superior longitudinal fasciculus in autism spectrum disorders increases with more profound language impairment

BACKGROUND AND PURPOSE

Language impairments are observed in a subset of individuals with ASD. To examine microstructural brain white matter features associated with language ability in ASD, we measured the DTI parameters of language-related white matter tracts (SLF) as well as non-language-related white matter tracts (CST) in children with ASD/+LI and ASD/-LI) and in TD.

MATERIALS AND METHODS

Eighteen children with ASD/-LI (age range, 6.7-17.5 years), 17 with ASD/+LI (age range, 6.8-14.8 years), and 25 TD (age range, 6.5-18 years) were evaluated with DTI and tractography. Primary DTI parameters considered for analysis were MD and FA.

RESULTS

There was a main effect of diagnostic group on age-corrected MD (P < .05) with ASD/+LI significantly elevated compared with TD. This was most pronounced for left hemisphere SLF fiber tracts and for the temporal portion of the SLF. There was significant negative correlation between left hemisphere SLF MD values and the clinical assessment of language ability. There was no main effect of diagnostic group or diagnostic group X hemisphere interaction for FA. Although there was a main effect of diagnostic group on values of MD in the CST, this did not survive hemispheric subanalysis.

CONCLUSIONS

Abnormal DTI parameters (specifically significantly elevated MD values in ASD) of the SLF appear to be associated with language impairment in ASD. These elevations are particularly pronounced in the left cerebral hemisphere, in the temporal portion of the SLF, and in children with clinical language impairment.

Functional brain networks and white matter underlying theory-of-mind in autism

Human beings constantly engage in attributing causal explanations to one's own and to others' actions, and theory-of-mind (ToM) is critical in making such inferences. Although children learn causal attribution early in development, children with autism spectrum disorders (ASDs) are known to have impairments in the development of intentional causality. This functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) study investigated the neural correlates of physical and intentional causal attribution in people with ASDs. In the fMRI scanner, 15 adolescents and adults with ASDs and 15 age- and IQ-matched typically developing peers made causal judgments about comic strips presented randomly in an event-related design. All participants showed robust activation in bilateral posterior superior temporal sulcus at the temporo-parietal junction (TPJ) in response to intentional causality. Participants with ASDs showed lower activation in TPJ, right inferior frontal gyrus and left premotor cortex. Significantly weaker functional connectivity was also found in the ASD group between TPJ and motor areas during intentional causality. DTI data revealed significantly reduced fractional anisotropy in ASD participants in white matter underlying the temporal lobe. In addition to underscoring the role of TPJ in ToM, this study found an interaction between motor simulation and mentalizing systems in intentional causal attribution and its possible discord in autism.

Functional magnetic resonance imaging of autism spectrum disorders

This review presents an overview of functional magnetic resonance imaging findings in autism spectrum disorders (ASDS), although there is considerable heterogeneity with respect to results across studies, common themes have emerged, including: (i) hypoactivation in nodes of the "social brain" during social processing tasks, including regions within the prefrontal cortex, the posterior superior temporal sulcus, the amygdala, and the fusiform gyrus; (ii) aberrant frontostriatal activation during cognitive control tasks relevant to restricted and repetitive behaviors and interests, including regions within the dorsal prefrontal cortex and the basal ganglia; (iii) differential lateralization and activation of language processing and production regions during communication tasks; (iv) anomalous mesolimbic responses to social and nonsocial rewards; (v) task-based long-range functional hypoconnectivity and short-range hyper-connectivity; and (vi) decreased anterior-posterior functional connectivity during resting states. These findings provide mechanistic accounts of ASD pathophysiology and suggest directions for future research aimed at elucidating etiologic models and developing rationally derived and targeted treatments.

Age-related abnormalities in white matter microstructure in autism spectrum disorders

Abnormalities in structural and functional connectivity have been reported in autism spectrum disorders (ASD) across a wide age range. However, developmental changes in white matter microstructure are poorly understood. We used a cross-sectional design to determine whether white matter abnormalities measured using diffusion tensor imaging (DTI) were present in adolescents and adults with ASD and whether age-related changes in white matter microstructure differed between ASD and typically developing (TD) individuals. Participants included 28 individuals with ASD and 33 TD controls matched on age and IQ and assessed at one time point. Widespread decreased fractional anisotropy (FA), and increased radial diffusivity (RaD) and mean diffusivity (MD) were observed in the ASD group compared to the TD group. In addition, significant group-by-age interactions were observed in FA, RaD, and MD in all major tracts except the brain stem, indicating that age-related changes in white matter microstructure differed between the groups. We propose that white matter microstructural changes in ASD may reflect myelination and/or other structural differences including differences in axonal density/arborization. In addition, we suggest that white matter microstuctural impairments may be normalizing during young adulthood in ASD. Future longitudinal studies that include a wider range of ages and more extensive clinical characterization will be critical for further uncovering the neurodevelopmental processes unfolding during this dynamic time in development.

White matter integrity, fiber count, and other fallacies: the do's and don'ts of diffusion MRI

Diffusion-weighted MRI (DW-MRI) has been increasingly used in imaging neuroscience over the last decade. An early form of this technique, diffusion tensor imaging (DTI) was rapidly implemented by major MRI scanner companies as a scanner selling point. Due to the ease of use of such implementations, and the plausibility of some of their results, DTI was leapt on by imaging neuroscientists who saw it as a powerful and unique new tool for exploring the structural connectivity of human brain. However, DTI is a rather approximate technique, and its results have frequently been given implausible interpretations that have escaped proper critique and have appeared misleadingly in journals of high reputation. In order to encourage the use of improved DW-MRI methods, which have a better chance of characterizing the actual fiber structure of white matter, and to warn against the misuse and misinterpretation of DTI, we review the physics of DW-MRI, indicate currently preferred methodology, and explain the limits of interpretation of its results. We conclude with a list of 'Do's and Don'ts' which define good practice in this expanding area of imaging neuroscience.

Long-term cognitive and behavioral therapies, combined with augmentative communication, are related to uncinate fasciculus integrity in autism

Recent evidence points to white-matter abnormalities as a key factor in autism physiopathology. Using Diffusion Tensor Imaging, we studied white-matter structural properties in a convenience sample of twenty-two subjects with low-functioning autism exposed to long-term augmentative and alternative communication, combined with sessions of cognitive and behavioral therapy. Uncinate fasciculus structural properties correlated significantly with therapy length and early onset, as well as to clinical outcome, independently from IQ, age or symptoms severity at therapy onset. Moreover, adherence to therapy was linked with better clinical outcome and uncinate fasciculus structural integrity. The results point to the capability of a long-term rehabilitation of subjects with low-functioning autism to produce white-matter structural modifications, which could thus play a role in the rehabilitative outcome.

Atypical hemispheric asymmetry in the arcuate fasciculus of completely nonverbal children with autism

Despite the fact that as many as 25% of the children diagnosed with autism spectrum disorders are nonverbal, surprisingly little research has been conducted on this population. In particular, the mechanisms that underlie their absence of speech remain unknown. Using diffusion tensor imaging, we compared the structure of a language-related white matter tract (the arcuate fasciculus, AF) in five completely nonverbal children with autism to that of typically developing children. We found that, as a group, the nonverbal children did not show the expected left-right AF asymmetry--rather, four of the five nonverbal children actually showed the reversed pattern. It is possible that this unusual pattern of asymmetry may underlie some of the severe language deficits commonly found in autism, particularly in children whose speech fails to develop. Furthermore, novel interventions (such as auditory-motor mapping training) designed to engage brain regions that are connected via the AF may have important clinical potential for facilitating expressive language in nonverbal children with autism.

A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls - a large case control study

BACKGROUND

The autism rate has recently increased to 1 in 100 children. Genetic studies demonstrate poorly understood complexity. Environmental factors apparently also play a role. Magnetic resonance imaging (MRI) studies demonstrate increased brain sizes and altered connectivity. Electroencephalogram (EEG) coherence studies confirm connectivity changes. However, genetic-, MRI- and/or EEG-based diagnostic tests are not yet available. The varied study results likely reflect methodological and population differences, small samples and, for EEG, lack of attention to group-specific artifact.

METHODS

Of the 1,304 subjects who participated in this study, with ages ranging from 1 to 18 years old and assessed with comparable EEG studies, 463 children were diagnosed with autism spectrum disorder (ASD); 571 children were neuro-typical controls (C). After artifact management, principal components analysis (PCA) identified EEG spectral coherence factors with corresponding loading patterns. The 2- to 12-year-old subsample consisted of 430 ASD- and 554 C-group subjects (n = 984). Discriminant function analysis (DFA) determined the spectral coherence factors' discrimination success for the two groups. Loading patterns on the DFA-selected coherence factors described ASD-specific coherence differences when compared to controls.

RESULTS

Total sample PCA of coherence data identified 40 factors which explained 50.8% of the total population variance. For the 2- to 12-year-olds, the 40 factors showed highly significant group differences (P < 0.0001). Ten randomly generated split half replications demonstrated high-average classification success (C, 88.5%; ASD, 86.0%). Still higher success was obtained in the more restricted age sub-samples using the jackknifing technique: 2- to 4-year-olds (C, 90.6%; ASD, 98.1%); 4- to 6-year-olds (C, 90.9%; ASD 99.1%); and 6- to 12-year-olds (C, 98.7%; ASD, 93.9%). Coherence loadings demonstrated reduced short-distance and reduced, as well as increased, long-distance coherences for the ASD-groups, when compared to the controls. Average spectral loading per factor was wide (10.1 Hz).

CONCLUSIONS

Classification success suggests a stable coherence loading pattern that differentiates ASD- from C-group subjects. This might constitute an EEG coherence-based phenotype of childhood autism. The predominantly reduced short-distance coherences may indicate poor local network function. The increased long-distance coherences may represent compensatory processes or reduced neural pruning. The wide average spectral range of factor loadings may suggest over-damped neural networks.

ISP: an optimal out-of-core image-set processing streaming architecture for parallel heterogeneous systems

Image population analysis is the class of statistical methods that plays a central role in understanding the development, evolution, and disease of a population. However, these techniques often require excessive computational power and memory that are compounded with a large number of volumetric inputs. Restricted access to supercomputing power limits its influence in general research and practical applications. In this paper we introduce ISP, an Image-Set Processing streaming framework that harnesses the processing power of commodity heterogeneous CPU/GPU systems and attempts to solve this computational problem. In ISP, we introduce specially designed streaming algorithms and data structures that provide an optimal solution for out-of-core multiimage processing problems both in terms of memory usage and computational efficiency. ISP makes use of the asynchronous execution mechanism supported by parallel heterogeneous systems to efficiently hide the inherent latency of the processing pipeline of out-of-core approaches. Consequently, with computationally intensive problems, the ISP out-of-core solution can achieve the same performance as the in-core solution. We demonstrate the efficiency of the ISP framework on synthetic and real datasets.

Impaired language pathways in tuberous sclerosis complex patients with autism spectrum disorders

The purpose of this study was to examine the relationship between language pathways and autism spectrum disorders (ASDs) in patients with tuberous sclerosis complex (TSC). An advanced diffusion-weighted magnetic resonance imaging (MRI) was performed on 42 patients with TSC and 42 age-matched controls. Using a validated automatic method, white matter language pathways were identified and microstructural characteristics were extracted, including fractional anisotropy (FA) and mean diffusivity (MD). Among 42 patients with TSC, 12 had ASD (29%). After controlling for age, TSC patients without ASD had a lower FA than controls in the arcuate fasciculus (AF); TSC patients with ASD had even a smaller FA, lower than the FA for those without ASD. Similarly, TSC patients without ASD had a greater MD than controls in the AF; TSC patients with ASD had even a higher MD, greater than the MD in those without ASD. It remains unclear why some patients with TSC develop ASD, while others have better language and socio-behavioral outcomes. Our results suggest that language pathway microstructure may serve as a marker of the risk of ASD in TSC patients. Impaired microstructure in language pathways of TSC patients may indicate the development of ASD, although prospective studies of language pathway development and ASD diagnosis in TSC remain essential.

Autism as a neural systems disorder: a theory of frontal-posterior underconnectivity

The underconnectivity theory of autism attributes the disorder to lower anatomical and functional systems connectivity between frontal and more posterior cortical processing. Here we review evidence for the theory and present a computational model of an executive functioning task (Tower of London) implementing the assumptions of underconnectivity. We make two modifications to a previous computational account of performance and brain activity in typical individuals in the Tower of London task (Newman et al., 2003): (1) the communication bandwidth between frontal and parietal areas was decreased and (2) the posterior centers were endowed with more executive capability (i.e., more autonomy, an adaptation is proposed to arise in response to the lowered frontal-posterior bandwidth). The autism model succeeds in matching the lower frontal-posterior functional connectivity (lower synchronization of activation) seen in fMRI data, as well as providing insight into behavioral response time results. The theory provides a unified account of how a neural dysfunction can produce a neural systems disorder and a psychological disorder with the widespread and diverse symptoms of autism.

Neural systems for speech and song in autism

Despite language disabilities in autism, music abilities are frequently preserved. Paradoxically, brain regions associated with these functions typically overlap, enabling investigation of neural organization supporting speech and song in autism. Neural systems sensitive to speech and song were compared in low-functioning autistic and age-matched control children using passive auditory stimulation during functional magnetic resonance and diffusion tensor imaging. Activation in left inferior frontal gyrus was reduced in autistic children relative to controls during speech stimulation, but was greater than controls during song stimulation. Functional connectivity for song relative to speech was also increased between left inferior frontal gyrus and superior temporal gyrus in autism, and large-scale connectivity showed increased frontal–posterior connections. Although fractional anisotropy of the left arcuate fasciculus was decreased in autistic children relative to controls, structural terminations of the arcuate fasciculus in inferior frontal gyrus were indistinguishable between autistic and control groups. Fractional anisotropy correlated with activity in left inferior frontal gyrus for both speech and song conditions. Together, these findings indicate that in autism, functional systems that process speech and song were more effectively engaged for song than for speech and projections of structural pathways associated with these functions were not distinguishable from controls.

Association between sociability and diffusion tensor imaging in BALB/cJ mice

The purpose of this study was to use high-resolution diffusion tensor imaging (DTI) to investigate the association between DTI metrics and sociability in BALB/c inbred mice. The sociability of prepubescent (30-day-old) BALB/cJ mice was operationally defined as the time that the mice spent sniffing a stimulus mouse in a social choice test. High-resolution ex vivo DTI data on 12 BALB/cJ mouse brains were acquired using a 9.4-T vertical-bore magnet. Regression analysis was conducted to investigate the association between DTI metrics and sociability. Significant positive regression (p < 0.001) between social sniffing time and fractional anisotropy was found in 10 regions located in the thalamic nuclei, zona incerta/substantia nigra, visual/orbital/somatosensory cortices and entorhinal cortex. In addition, significant negative regression (p < 0.001) between social sniffing time and mean diffusivity was found in five areas located in the sensory cortex, motor cortex, external capsule and amygdaloid region. In all regions showing significant regression with either the mean diffusivity or fractional anisotropy, the tertiary eigenvalue correlated negatively with the social sniffing time. This study demonstrates the feasibility of using DTI to detect brain regions associated with sociability in a mouse model system.

Auditory processing in autism spectrum disorder: a review

For individuals with autism spectrum disorder or 'ASD' the ability to accurately process and interpret auditory information is often difficult. Here we review behavioural, neurophysiological and imaging literature pertaining to this field with the aim of providing a comprehensive account of auditory processing in ASD, and thus an effective tool to aid further research. Literature was sourced from peer-reviewed journals published over the last two decades which best represent research conducted in these areas. Findings show substantial evidence for atypical processing of auditory information in ASD at behavioural and neural levels. Abnormalities are diverse, ranging from atypical perception of various low-level perceptual features (i.e. pitch, loudness) to processing of more complex auditory information such as prosody. Trends across studies suggest auditory processing impairments in ASD are most likely to present during processing of complex auditory information and are more severe for speech than for non-speech stimuli. The interpretation of these findings with respect to various cognitive accounts of ASD is discussed and suggestions offered for further research.

White matter in autism spectrum disorders - evidence of impaired fiber formation

BACKGROUND

Diffusion tensor imaging (DTI) enables measurements and visualization of the microstructure of neural fiber tracts. The existing literature on autism spectrum disorders (ASDs) and DTI is heterogenous both regarding methodology and results.

PURPOSE

To compare brain white matter of high-functioning individuals with ASDs and controls.

MATERIAL AND METHODS

Tract-based spatial statistics (TBSS), a voxel-based approach to DTI, was used to compare 27 subjects with ASDs (mean age 14.7 years, range 11.4-17.6 years, 20 boys, 7 girls) and 26 control subjects (mean age 14.5 years, range 11.7-17.3 years, 17 boys, 9 girls). Mean fractional anisotropy (FA) image (skeleton) was created and each subject's aligned FA data were then projected onto this skeleton. Voxelwise cross-subject statistics on the skeletonized FA data, mean diffusivity (MD), and measures of diffusion direction were calculated. Importantly, the data were corrected across the whole image instead of using ROI-based methods.

RESULTS

The ASD group showed significantly greater FA (P < 0.05, corrected) in the area containing clusters of optic radiation and the right inferior fronto-occipital fasciculus (iFOF). In the same area, λ(3) (representing transverse diffusion) was significantly reduced in the ASD group. No age-related changes were found.

CONCLUSION

The results suggest that the reduced transverse diffusion within the iFOF is related to abnormal information flow between the insular salience processing areas and occipital visual areas.

Genetic variation in CNTNAP2 alters brain function during linguistic processing in healthy individuals

Language impairments are a characteristic feature of autism and related autism spectrum disorders (ASDs). Autism is also highly heritable and one of the most promising candidate genes implicated in its pathogenesis is contactin-associated protein-like 2 (CNTNAP2), a gene also associated with language impairment. In the current study we investigated the functional effects of variants of CNTNAP2 associated with autism and language impairment (rs7794745 and rs2710102; presumed risk alleles T and C, respectively) in healthy individuals using functional magnetic resonance imaging (fMRI) during performance of a language task (n = 66). Against a background of normal performance and lack of behavioral abnormalities, healthy individuals with the putative risk allele versus those without demonstrated significant increases in activation in the right inferior frontal gyrus (Broca's area homologue) and right lateral temporal cortex. These findings demonstrate that risk associated variation in the CNTNAP2 gene impacts on brain activation in healthy non-autistic individuals during a language processing task providing evidence of the effect of genetic variation in CNTNAP2 on a core feature of ASDs.

The National Alliance for Medical Image Computing, a roadmap initiative to build a free and open source software infrastructure for translational research in medical image analysis

The National Alliance for Medical Image Computing (NA-MIC), is a multi-institutional, interdisciplinary community of researchers, who share the recognition that modern health care demands improved technologies to ease suffering and prolong productive life. Organized under the National Centers for Biomedical Computing 7 years ago, the mission of NA-MIC is to implement a robust and flexible open-source infrastructure for developing and applying advanced imaging technologies across a range of important biomedical research disciplines. A measure of its success, NA-MIC is now applying this technology to diseases that have immense impact on the duration and quality of life: cancer, heart disease, trauma, and degenerative genetic diseases. The targets of this technology range from group comparisons to subject-specific analysis.

Functional connectivity magnetic resonance imaging classification of autism

Group differences in resting state functional magnetic resonance imaging connectivity between individuals with autism and typically developing controls have been widely replicated for a small number of discrete brain regions, yet the whole-brain distribution of connectivity abnormalities in autism is not well characterized. It is also unclear whether functional connectivity is sufficiently robust to be used as a diagnostic or prognostic metric in individual patients with autism. We obtained pairwise functional connectivity measurements from a lattice of 7266 regions of interest covering the entire grey matter (26.4 million connections) in a well-characterized set of 40 male adolescents and young adults with autism and 40 age-, sex- and IQ-matched typically developing subjects. A single resting state blood oxygen level-dependent scan of 8 min was used for the classification in each subject. A leave-one-out classifier successfully distinguished autism from control subjects with 83% sensitivity and 75% specificity for a total accuracy of 79% (P = 1.1 × 10(-7)). In subjects <20 years of age, the classifier performed at 89% accuracy (P = 5.4 × 10(-7)). In a replication dataset consisting of 21 individuals from six families with both affected and unaffected siblings, the classifier performed at 71% accuracy (91% accuracy for subjects <20 years of age). Classification scores in subjects with autism were significantly correlated with the Social Responsiveness Scale (P = 0.05), verbal IQ (P = 0.02) and the Autism Diagnostic Observation Schedule-Generic's combined social and communication subscores (P = 0.05). An analysis of informative connections demonstrated that region of interest pairs with strongest correlation values were most abnormal in autism. Negatively correlated region of interest pairs showed higher correlation in autism (less anticorrelation), possibly representing weaker inhibitory connections, particularly for long connections (Euclidean distance >10 cm). Brain regions showing greatest differences included regions of the default mode network, superior parietal lobule, fusiform gyrus and anterior insula. Overall, classification accuracy was better for younger subjects, with differences between autism and control subjects diminishing after 19 years of age. Classification scores of unaffected siblings of individuals with autism were more similar to those of the control subjects than to those of the subjects with autism. These findings indicate feasibility of a functional connectivity magnetic resonance imaging diagnostic assay for autism.

Structural neural phenotype of autism: preliminary evidence from a diffusion tensor imaging study using tract-based spatial statistics

BACKGROUND AND PURPOSE

There is mounting evidence suggesting widespread aberrations in neural connectivity as the underlying neurobiology of autism. Using DTI to assess white matter abnormalities, this study implemented a voxelwise analysis and tract-labeling strategy to test for a structural neural phenotype in autism.

MATERIALS AND METHODS

Subjects included 15 boys with autism and 8 controls, group-matched on age, cognitive functioning, sex, and handedness. DTI data were obtained by using a 3T scanner. FSL, including TBSS, was used to process and analyze DTI data where FA was chosen as the primary measure of fiber tract integrity. Affected voxels were labeled by using an integrated white matter tractography atlas. Post hoc correlation analyses were performed between FA of each affected fiber tract and scores on the Social Responsiveness Scale.

RESULTS

The autism group exhibited bilateral reductions in FA involving numerous association, commissural, and projection tracts, with the most severely affected being the forceps minor. The most affected association tracts were the inferior fronto-occipital fasciculus and superior longitudinal fasciculus. There were no areas of increased FA in the autism group. All post hoc correlation analyses became nonsignificant after controlling for multiple comparisons.

CONCLUSIONS

This study provides preliminary evidence of reduced FA along many long-range fiber tracts in autism, suggesting aberrant long-range corticocortical connectivity. Although the spatial distribution of these findings suggests widespread abnormalities, there are major differences in the degree to which different tracts are affected, suggesting a more specific neural phenotype in autism.

Brain connectivity and high functioning autism: a promising path of research that needs refined models, methodological convergence, and stronger behavioral links

Here we review findings from studies investigating functional and structural brain connectivity in high functioning individuals with autism spectrum disorders (ASDs). The dominant theory regarding brain connectivity in people with ASD is that there is long distance under-connectivity and local over-connectivity of the frontal cortex. Consistent with this theory, long-range cortico-cortical functional and structural connectivity appears to be weaker in people with ASD than in controls. However, in contrast to the theory, there is less evidence for local over-connectivity of the frontal cortex. Moreover, some patterns of abnormal functional connectivity in ASD are not captured by current theoretical models. Taken together, empirical findings measuring different forms of connectivity demonstrate complex patterns of abnormal connectivity in people with ASD. The frequently suggested pattern of long-range under-connectivity and local over-connectivity is in need of refinement.

White matter atlas generation using HARDI based automated parcellation

Most diffusion imaging studies have used subject registration to an atlas space for enhanced quantification of anatomy. However, standard diffusion tensor atlases lack information in regions of fiber crossing and are based on adult anatomy. The degree of error associated with applying these atlases to studies of children for example has not yet been estimated but may lead to suboptimal results. This paper describes a novel technique for generating population-specific high angular resolution diffusion imaging (HARDI)-based atlases consisting of labeled regions of homogenous white matter. Our approach uses a fiber orientation distribution (FOD) diffusion model and a data driven clustering algorithm. White matter regional labeling is achieved by our automated data driven clustering algorithm that has the potential to delineate white matter regions based on fiber complexity and orientation. The advantage of such an atlas is that it is study specific and more comprehensive in describing regions of white matter homogeneity as compared to standard anatomical atlases. We have applied this state of the art technique to a dataset consisting of adolescent and preadolescent children, creating one of the first examples of a HARDI-based atlas, thereby establishing the feasibility of the atlas creation framework. The white matter regions generated by our automated clustering algorithm have lower FOD variance than when compared to the regions created from a standard anatomical atlas.

Sharp curvature of frontal lobe white matter pathways in children with autism spectrum disorders: tract-based morphometry analysis

BACKGROUND AND PURPOSE

Because we had previously observed geometric changes of frontal lobe association pathways in children with ASD, in the present study we analyzed the curvature of these white matter pathways by using an objective TBM analysis.

MATERIALS AND METHODS

Diffusion tensor imaging was performed in 32 children with ASD and 14 children with typical development. Curvature, FA, AD, and RD of bilateral AF, UF, and gCC were investigated by using the TBM group analysis assessed by P(FDR) for multiple comparisons.

RESULTS

Significantly higher curvatures were found in children with ASD, especially at the parietotemporal junction for AF (left, P(FDR) < .001; right, P(FDR) < .01), at the frontotemporal junction for UF (left, P(FDR) < .005; right, P(FDR) < .03), and at the midline of the gCC (P(FDR) < .0001). RD was significantly higher in children with ASD at the same bending regions of AF (left, P(FDR) < .03, right, P(FDR) < .02), UF (left, P(FDR) < .04), and gCC (P(FDR) < .01).

CONCLUSIONS

Higher curvature and curvature-dependent RD changes in children with ASD may be the result of higher attenuation of thinner axons in these frontal lobe tracts.

Voxel-based meta-analysis of regional white-matter volume differences in autism spectrum disorder versus healthy controls

BACKGROUND

We conducted a meta-analysis of voxel-based morphometry (VBM) studies in autism spectrum disorder (ASD) to clarify the changes in regional white-matter volume underpinning this condition, and generated an online database to facilitate replication and further analyses by other researchers.

METHOD

PubMed, ScienceDirect, Web of Knowledge and Scopus databases were searched between 2002 (the date of the first white-matter VBM study in ASD) and 2010. Manual searches were also conducted. Authors were contacted to obtain additional data. Coordinates were extracted from clusters of significant white-matter difference between patients and controls. A new template for white matter was created for the signed differential mapping (SDM) meta-analytic method. A diffusion tensor imaging (DTI)-derived atlas was used to optimally localize the changes in white-matter volume.

RESULTS

Thirteen datasets comprising 246 patients with ASD and 237 healthy controls met inclusion criteria. No between-group differences were found in global white-matter volumes. ASD patients showed increases of white-matter volume in the right arcuate fasciculus and also in the left inferior fronto-occipital and uncinate fasciculi. These findings remained unchanged in quartile and jackknife sensitivity analyses and also in subgroup analyses (pediatric versus adult samples).

CONCLUSIONS

Patients with ASD display increases of white-matter volume in tracts known to be important for language and social cognition. Whether the results apply to individuals with lower IQ or younger age and whether there are meaningful neurobiological differences between the subtypes of ASD remain to be investigated.

Research review: Constraining heterogeneity: the social brain and its development in autism spectrum disorder

The expression of autism spectrum disorder (ASD) is highly heterogeneous, owing to the complex interactions between genes, the brain, and behavior throughout development. Here we present a model of ASD that implicates an early and initial failure to develop the specialized functions of one or more of the set of neuroanatomical structures involved in social information processing (i.e., the 'social brain'). From this early and primary disruption, abnormal brain development is canalized because the individual with an ASD must develop in a highly social world without the specialized neural systems that would ordinarily allow him or her to partake in the fabric of social life, which is woven from the thread of opportunities for social reciprocity and the tools of social engagement. This brain canalization gives rise to other characteristic behavioral deficits in ASD including deficits in communication, restricted interests, and repetitive behaviors. We propose that focused efforts to explore the brain mechanisms underlying the core, pathognomic deficits in the development of mechanisms for social engagement in ASD will greatly elucidate our understanding and treatment of this complex, devastating family of neurodevelopmental disorders. In particular, developmental studies (i.e., longitudinal studies of young children with and without ASD, as well as infants at increased risk for being identified with ASD) of the neural circuitry supporting key aspects of social information processing are likely to provide important insights into the underlying components of the full-syndrome of ASD. These studies could also contribute to the identification of developmental brain endophenotypes to facilitate genetic studies. The potential for this kind of approach is illustrated via examples of functional neuroimaging research from our own laboratory implicating the posterior superior temporal sulcus (STS) as a key player in the set of neural structures giving rise to ASD.

Diffusion based abnormality markers of pathology: toward learned diagnostic prediction of ASD

This paper presents a paradigm for generating a quantifiable marker of pathology that supports diagnosis and provides a potential biomarker of neuropsychiatric disorders, such as autism spectrum disorder (ASD). This is achieved by creating high-dimensional nonlinear pattern classifiers using support vector machines (SVM), that learn the underlying pattern of pathology using numerous atlas-based regional features extracted from diffusion tensor imaging (DTI) data. These classifiers, in addition to providing insight into the group separation between patients and controls, are applicable on a single subject basis and have the potential to aid in diagnosis by assigning a probabilistic abnormality score to each subject that quantifies the degree of pathology and can be used in combination with other clinical scores to aid in diagnostic decision. They also produce a ranking of regions that contribute most to the group classification and separation, thereby providing a neurobiological insight into the pathology. As an illustrative application of the general framework for creating diffusion based abnormality classifiers we create classifiers for a dataset consisting of 45 children with ASD (mean age 10.5 ± 2.5 yr) as compared to 30 typically developing (TD) controls (mean age 10.3 ± 2.5 yr). Based on the abnormality scores, a distinction between the ASD population and TD controls was achieved with 80% leave one out (LOO) cross-validation accuracy with high significance of p<0.001, ~84% specificity and ~74% sensitivity. Regions that contributed to this abnormality score involved fractional anisotropy (FA) differences mainly in right occipital regions as well as in left superior longitudinal fasciculus, external and internal capsule while mean diffusivity (MD) discriminates were observed primarily in right occipital gyrus and right temporal white matter.

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.Although there is variability in the literature on structural magnetic resonance literature (MRI), there is evidence of volume abnormalities in both grey and white matter, with a suggestion of some region-specific differences. Early brain overgrowth is probably the most replicated finding in a subgroup of people with ASD, and new techniques, such as cortical-thickness measurements and surface morphometry have begun to elucidate in more detail the patterns of abnormalities as they evolve with age, and are implicating specific neuroanatomical or neurodevelopmental processes. Functional MRI and diffusion tensor imaging techniques suggest that such volume abnormalities are associated with atypical functional and structural connectivity in the brain, and researchers have begun to use magnetic resonance spectroscopy (MRS) techniques to explore the neurochemical substrate of such abnormalities. The data from multiple imaging methods suggests that ASD is associated with an atypically connected brain. We now need to further clarify such atypicalities, and start interpreting them in the context of what we already know about typical neurodevelopmental processes including migration and organization of the cortex. Such an approach will allow us to relate imaging findings not only to behavior, but also to genes and their expression, which may be related to such processes, and to further our understanding of the nature of neurobiologic abnormalities in ASD.

Altered connectivity and action model formation in autism is autism

Internal action models refer to sensory-motor programs that form the brain basis for a wide range of skilled behavior and for understanding others' actions. Development of these action models, particularly those reliant on visual cues from the external world, depends on connectivity between distant brain regions. Studies of children with autism reveal anomalous patterns of motor learning and impaired execution of skilled motor gestures. These findings robustly correlate with measures of social and communicative function, suggesting that anomalous action model formation may contribute to impaired development of social and communicative (as well as motor) capacity in autism. Examination of the pattern of behavioral findings, as well as convergent data from neuroimaging techniques, further suggests that autism-associated action model formation may be related to abnormalities in neural connectivity, particularly decreased function of long-range connections. This line of study can lead to important advances in understanding the neural basis of autism and, more critically, can be used to guide effective therapies targeted at improving social, communicative, and motor function.

Underconnected, but how? A survey of functional connectivity MRI studies in autism spectrum disorders

Growing consensus suggests that autism spectrum disorders (ASD) are associated with atypical brain networks, thus shifting the focus to the study of connectivity. Many functional connectivity studies have reported underconnectivity in ASD, but results in others have been divergent. We conducted a survey of 32 functional connectivity magnetic resonance imaging studies of ASD for numerous methodological variables to distinguish studies supporting general underconnectivity (GU) from those not consistent with this hypothesis (NGU). Distinguishing patterns were apparent for several data analysis choices. The study types differed significantly with respect to low-pass filtering, task regression, and whole-brain field of view. GU studies were more likely to examine task-driven time series in regions of interest, without the use of low-pass filtering. Conversely, NGU studies mostly applied task regression (for removal of activation effects) and low-pass filtering, testing for correlations across the whole brain. Results thus suggest that underconnectivity findings may be contingent on specific methodological choices. Whereas underconnectivity reflects reduced efficiency of within-network communication in ASD, diffusely increased functional connectivity can be attributed to impaired experience-driven mechanisms (e.g., synaptic pruning). Both GU and NGU findings reflect important aspects of network dysfunction associated with sociocommunicative, cognitive, and sensorimotor impairments in ASD.