White matter reduced streamline coherence in young men with autism and mental retardation

Automatic classification of autism spectrum disorder in children using cortical thickness and support vector machine

OBJECTIVE

Autism spectrum disorder (ASD) is a neurodevelopmental condition with a heterogeneous phenotype. The role of biomarkers in ASD diagnosis has been highlighted; cortical thickness has proved to be involved in the etiopathogenesis of ASD core symptoms. We apply support vector machine, a supervised machine learning method, in order to identify specific cortical thickness alterations in ASD subjects.

METHODS

A sample of 76 subjects (9.5 ± 3.4 years old) has been selected, 40 diagnosed with ASD and 36 typically developed subjects. All children underwent a magnetic resonance imaging (MRI) examination; T1-MPRAGE sequences were analyzed to extract features for the characterization and parcellation of regions of interests (ROI); average cortical thickness (CT) has been measured for each ROI. For the classification process, the extracted features were used as input for a classifier to identify ASD subjects through a "learning by example" procedure; the features with best performance was then selected by "greedy forward-feature selection." Finally, this model underwent a leave-one-out cross-validation approach.

RESULTS

From the training set of 68 ROIs, five ROIs reached accuracies of over 70%. After this phase, we used a recursive feature selection process in order to identify the eight features with the best accuracy (84.2%). CT resulted higher in ASD compared to controls in all the ROIs identified at the end of the process.

CONCLUSION

We found increased CT in various brain regions in ASD subjects, confirming their role in the pathogenesis of this condition. Considering the brain development curve during ages, these changes in CT may normalize during development. Further validation on a larger sample is required.

Role of Oligodendrocytes and Myelin in the Pathophysiology of Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is an early neurodevelopmental disorder that involves deficits in interpersonal communication, social interaction, and repetitive behaviors. Although ASD pathophysiology is still uncertain, alterations in the abnormal development of the frontal lobe, limbic areas, and putamen generate an imbalance between inhibition and excitation of neuronal activity. Interestingly, recent findings suggest that a disruption in neuronal connectivity is associated with neural alterations in white matter production and myelination in diverse brain regions of patients with ASD. This review is aimed to summarize the most recent evidence that supports the notion that abnormalities in the oligodendrocyte generation and axonal myelination in specific brain regions are involved in the pathophysiology of ASD. Fundamental molecular mediators of these pathological processes are also examined. Determining the role of alterations in oligodendrogenesis and myelination is a fundamental step to understand the pathophysiology of ASD and identify possible therapeutic targets.

A machine learning approach for retinal images analysis as an objective screening method for children with autism spectrum disorder

BACKGROUND

Autism spectrum disorder (ASD) is characterised by many of features including problem in social interactions, different ways of learning, some children showing a keen interest in specific subjects, inclination to routines, challenges in typical communication, and particular ways of processing sensory information. Early intervention and suitable supports for these children may make a significant contribution to their development. However, considerable difficulties have been encountered in the screening and diagnosis of ASD. The literature has indicated that certain retinal features are significantly associated with ASD. In this study, we investigated the use of machine learning approaches on retinal images to further enhance the classification accuracy.

METHODS

Forty-six ASD participants were recruited from three special needs schools and 24 normal control were recruited from the community. Among them, 23 age-gender matched ASD and normal control participant-pairs were constructed for the primary analysis. All retinal images were captured using a nonmydriatic fundus camera. Automatic retinal image analysis (ARIA) methodology applying machine-learning technology was used to optimise the information of the retina to develop a classification model for ASD. The model's validity was then assessed using a 10-fold cross-validation approach to assess its validity.

FINDINGS

The sensitivity and specificity were 95.7% (95% CI 76.0%, 99.8%) and 91.3% (95% CI 70.5%, 98.5%) respectively. The area under the ROC curve was 0.974 (95% CI 0.934, 1.000); however, it was noted that the specificity for female participants might not be as high as that for male participants.

INTERPRETATION

Because ARIA is a fully automatic cloud-based algorithm and relies only on retinal images, it can be used as a risk assessment tool for ASD screening. Further diagnosis and confirmation can then be made by professionals, and potential treatment may be provided at a relatively early stage.

Imbalance of laminar-specific excitatory and inhibitory circuits of the orbitofrontal cortex in autism

BACKGROUND

The human orbitofrontal cortex (OFC) is involved in assessing the emotional significance of events and stimuli, emotion-based learning, allocation of attentional resources, and social cognition. Little is known about the structure, connectivity and excitatory/inhibitory circuit interactions underlying these diverse functions in human OFC, as well as how the circuit is disrupted in individuals with autism spectrum disorder (ASD).

METHODS

We used post-mortem brain tissue from neurotypical adults and individuals with ASD. We examined the morphology and distribution of myelinated axons across cortical layers in OFC, at the single axon level, as a proxy of excitatory pathways. In the same regions, we also examined the laminar distribution of all neurons and neurochemically- and functionally-distinct inhibitory neurons that express the calcium-binding proteins parvalbumin (PV), calbindin (CB), and calretinin (CR).

RESULTS

We found that the density of myelinated axons increased consistently towards layer 6, while the average axon diameter did not change significantly across layers in both groups. However, both the density and diameter of myelinated axons were significantly lower in the ASD group compared with the Control group. The distribution pattern and density of the three major types of inhibitory neurons was comparable between groups, but there was a significant reduction in the density of excitatory neurons across OFC layers in ASD.

LIMITATIONS

This study is limited by the availability of human post-mortem tissue optimally processed for high-resolution microscopy and immunolabeling, especially from individuals with ASD.

CONCLUSIONS

The balance between excitation and inhibition in OFC is at the core of its function, assessing and integrating emotional and social cues with internal states and external inputs. Our preliminary results provide evidence for laminar-specific changes in the ratio of excitation/inhibition in OFC of adults with ASD, with an overall weakening and likely disorganization of excitatory signals and a relative strengthening of local inhibition. These changes likely underlie pathology of major OFC communications with limbic or other cortices and the amygdala in individuals with ASD, and may provide the anatomic basis for disrupted transmission of signals for social interactions and emotions in autism.

White matter microstructural alterations across four major psychiatric disorders: mega-analysis study in 2937 individuals

Identifying both the commonalities and differences in brain structures among psychiatric disorders is important for understanding the pathophysiology. Recently, the ENIGMA-Schizophrenia DTI Working Group performed a large-scale meta-analysis and reported widespread white matter microstructural alterations in schizophrenia; however, no similar cross-disorder study has been carried out to date. Here, we conducted mega-analyses comparing white matter microstructural differences between healthy comparison subjects (HCS; N = 1506) and patients with schizophrenia (N = 696), bipolar disorder (N = 211), autism spectrum disorder (N = 126), or major depressive disorder (N = 398; total N = 2937 from 12 sites). In comparison with HCS, we found that schizophrenia, bipolar disorder, and autism spectrum disorder share similar white matter microstructural differences in the body of the corpus callosum; schizophrenia and bipolar disorder featured comparable changes in the limbic system, such as the fornix and cingulum. By comparison, alterations in tracts connecting neocortical areas, such as the uncinate fasciculus, were observed only in schizophrenia. No significant difference was found in major depressive disorder. In a direct comparison between schizophrenia and bipolar disorder, there were no significant differences. Significant differences between schizophrenia/bipolar disorder and major depressive disorder were found in the limbic system, which were similar to the differences in schizophrenia and bipolar disorder relative to HCS. While schizophrenia and bipolar disorder may have similar pathological characteristics, the biological characteristics of major depressive disorder may be close to those of HCS. Our findings provide insights into nosology and encourage further investigations of shared and unique pathophysiology of psychiatric disorders.

Predicting an individual's dorsal attention network activity from functional connectivity fingerprints

The cortical dorsal attention network (DAN) is a set of parietal and frontal regions that support a wide variety of attentionally demanding tasks. Whereas attentional deployment reliably drives DAN activity across subjects, there is a large degree of variation in the activation pattern in individual subjects. We hypothesize that a subject's own idiosyncratic pattern of cortical DAN activity can be predicted from that subject's own unique pattern of functional connectivity. By modeling task activation as a function of whole brain connectivity patterns, we are able to define the connectivity fingerprints for the frontal and parietal DAN, and use it to predict a subject's characteristic DAN activation pattern with high accuracy. These predictions outperform the standard group-average benchmark and predict a subject's own activation pattern above and beyond predictions from another subject's connectivity pattern. Thus an individual's distinctive connectivity pattern accounts for substantial variance in DAN functional responses. Last, we show that the set of connections that predict cortical DAN responses, the frontal and parietal DAN connectivity fingerprints, is predominantly composed of other coactive regions, including regions outside of the DAN including occipital and temporal visual cortices. These connectivity fingerprints represent defining computational characteristics of the DAN, delineating which voxels are or are not capable of exerting top-down attentional bias to other regions of the brain. NEW & NOTEWORTHY The dorsal attention network (DAN) is a set of regions in frontoparietal cortex that reliably activate during attentional tasks. We designed computational models that predict the degree of an individual's DAN activation using their resting-state connectivity pattern alone. This uncovered the connectivity fingerprints of the DAN, which define it so well that we can predict how a voxel will respond to an attentional task given only its pattern of connectivity, with outstanding accuracy.

Brain Network Organization Correlates with Autistic Features in Preschoolers with Autism Spectrum Disorders and in Their Fathers: Preliminary Data from a DWI Analysis

Autism Spectrum Disorders (ASD) is a group of neurodevelopmental disorders that is characterized by an altered brain connectivity organization. Autistic traits below the clinical threshold (i.e., the broad autism phenotype; BAP) are frequent among first-degree relatives of subjects with ASD; however, little is known regarding whether subthreshold behavioral manifestations of ASD mirror also at the neuroanatomical level in parents of ASD probands. To this aim, we applied advanced diffusion network analysis to MRI of 16 dyads consisting of a child with ASD and his father in order to investigate: (i) the correlation between structural network organization and autistic features in preschoolers with ASD (all males; age range 1.5-5.2 years); (ii) the correlation between structural network organization and BAP features in the fathers of individuals with ASD (fath-ASD). Local network measures significantly correlated with autism severity in ASD children and with BAP traits in fath-ASD, while no significant association emerged when considering the global measures of brain connectivity. Notably, an overlap of some brain regions that are crucial for social functioning (cingulum, superior temporal gyrus, inferior temporal gyrus, middle frontal gyrus, frontal pole, and amygdala) in patients with ASD and fath-ASD was detected, suggesting an intergenerational transmission of these neural substrates. Overall, the results of this study may help in elucidating the neurostructural endophenotype of ASD, paving the way for bridging connections between underlying genetic and ASD symptomatology.

The value of diffusion tensor imaging for differentiating autism spectrum disorder with language delay from developmental language disorder among toddlers

BACKGROUND

Impaired language function is frequently observed as an initial sign in people with autism spectrum disorder (ASD). However, clinically, the early stages of ASD are difficult to distinguish from those of developmental language disorder (DLD).

OBJECTIVE

To evaluate the ability of diffusion tensor imaging (DTI) parameters for language-related white matter tracts (arcuate fasciculus) to differentiate ASD from DLD among toddlers.

MATERIALS AND METHODS

We included 16 ASD toddlers with language delay and 18 DLD toddlers in this study. Magnetic resonance imaging sequences included T2-weighted imaging (T2WI), T1 3-dimensional magnetization-prepared rapid acquisition gradient-echo (3D MP-RAGE), and DTI. Tractography was performed using Neuro 3D in the Siemens Syngo Workstation, and fractional anisotropy (FA), average fiber length (AFL), tract volume (TV), and number of voxels (NV) were automatically calculated. Data were then analyzed using IBM SPSS Statistics 22.

RESULTS

The ASD group exhibited significantly lower FA values, as well as significantly higher TV and NV values compared with the DLD group. With age as the covariate, analysis of covariance revealed different significances in TV and NV. Analysis of variance for AFL revealed no significant differences between the 2 groups.

CONCLUSION

DTI parameters of arcuate fasciculus were useful for differentiating ASD with language delay from DLD among toddlers. DTI has the potential to provide an objective and effective method for aiding early diagnosis, early intervention and improving long-term outcomes of ASD.

Support Vector Machines, Multidimensional Scaling and Magnetic Resonance Imaging Reveal Structural Brain Abnormalities Associated With the Interaction Between Autism Spectrum Disorder and Sex

Despite substantial efforts, it remains difficult to identify reliable neuroanatomic biomarkers of autism spectrum disorder (ASD) based on magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). Studies which use standard statistical methods to approach this task have been hampered by numerous challenges, many of which are innate to the mathematical formulation and assumptions of general linear models (GLM). Although the potential of alternative approaches such as machine learning (ML) to identify robust neuroanatomic correlates of psychiatric disease has long been acknowledged, few studies have attempted to evaluate the abilities of ML to identify structural brain abnormalities associated with ASD. Here we use a sample of 110 ASD patients and 83 typically developing (TD) volunteers (95 females) to assess the suitability of support vector machines (SVMs, a robust type of ML) as an alternative to standard statistical inference for identifying structural brain features which can reliably distinguish ASD patients from TD subjects of either sex, thereby facilitating the study of the interaction between ASD diagnosis and sex. We find that SVMs can perform these tasks with high accuracy and that the neuroanatomic correlates of ASD identified using SVMs overlap substantially with those found using conventional statistical methods. Our results confirm and establish SVMs as powerful ML tools for the study of ASD-related structural brain abnormalities. Additionally, they provide novel insights into the volumetric, morphometric, and connectomic correlates of this epidemiologically significant disorder.

Damage to the left uncinate fasciculus is associated with heightened schizotypal traits: A multimodal lesion-mapping study

A growing body of evidence suggests that individuals with pronounced schizotypal traits also display particular neurophysiological and morphological features - notably with regard to left frontotemporal connectivity. However, the studies published to date have focused on subclinical subjects and psychiatric patients, rather than brain-damaged patients. Here, we used the French version of the Schizotypal Personality Questionnaire to assess schizotypal traits in a sample of 97 patients having undergone surgical resection of a diffuse low-grade glioma. Patients having received other neurooncological treatments (including chemotherapy and radiotherapy) were not included. A combination of ROI-based based voxel-wise and tract-wise lesion-symptom mapping and a disconnectome analysis were performed, in order to identify the putative neural network associated with schizotypy. The ROI-based lesion-symptom mapping revealed a significant relationship between the cognitive-perceptual (positive) dimension of schizotypy and the left inferior gyrus (including the pars opercularis and the pars orbitalis). Importantly, we found that disconnection of the left uncinate fasciculus (UF) was a powerful predictor of the positive dimension of schizotypy. Lastly, the disconnection analysis indicated that the positive dimension of schizotypy was significantly associated with the white matter fibres deep in the left orbital and inferior frontal gyri and the left superior temporal pole, which mainly correspond to the spatial topography of the left UF. Taken as a whole, our results suggest that dysconnectivity of the neural network supplied by the left UF is associated with heightened positive schizotypal traits. Our new findings may be of value in interpreting current research in the field of biological psychiatry.

Modeling autism in non-human primates: Opportunities and challenges

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social communication deficits and restricted, repetitive patterns of behavior. For more than a decade, genetically-modified, risk factor-induced, as well as naturally occurring rodent models for ASD have been used as the most predominant tools to dissect the molecular and circuitry mechanisms underlying ASD. However, the apparent evolutionary differences in terms of social behavior and brain anatomy between rodents and humans have become an issue of debate regarding the translational value of rodent models for studying ASD. More recently, genome manipulation of non human primates using lentivirus-based gene expression, TALEN and CRISPR/Cas9 mediated gene editing techniques, has been reported. Genetically modified non-human primate models for ASD have been produced and characterized. While the feasibility, value, and exciting opportunities provided by the non-human primate models have been clearly demonstrated, many challenges still remain. Here, we review current progress, discuss the remaining challenges, and highlight the key issues in the development of non-human primate models for ASD research and drug development. Autism Res 2018, 11: 686-694. © 2018 International Society for Autism Research, Wiley Periodicals, Inc.

LAY SUMMARY

Over the last two decades, genetically modified rat and mouse models have been used as the most predominant tools to study mechanisms underlying autism spectrum disorder (ASD). However, the apparent evolutionary differences between rodents and humans limit the translational value of rodent models for studying ASD. Recently, several non-human primate models for ASD have been established and characterized. Here, we review current progress, discuss the challenges, and highlight the key issues in the development of non-human primate models for ASD research and drug development.

Disrupted focal white matter integrity in autism spectrum disorder: A voxel-based meta-analysis of diffusion tensor imaging studies

BACKGROUND

Autism spectrum disorder (ASD) is a mental disorder that has long been considered to result from brain underconnectivity. However, volumetric analysis of structural MRI data has failed to find consistent white matter alterations in patients with ASD. The present study aims to examine whether there are consistent focal white matter alterations as measured by diffusion tensor imaging (DTI) in individuals with ASD compared with typically developing (TD) individuals.

METHOD

Coordinate-based meta-analysis was performed on 14 studies that reported fractional anisotropy (FA) alterations between individuals with ASD and TD individuals. These studies have in total 297 subjects with ASD and 302 TD subjects.

RESULTS

Activation likelihood estimation (ALE) analysis identified two clusters of white matter regions that showed consistent reduction of FA in individuals with ASD compared with TD individuals: the left splenium of corpus callosum and the right cerebral peduncle.

CONCLUSIONS

Consistent focal white matter reductions in ASD could be identified by using FA, highlighting the cerebral peduncle which is usually overlooked in studies focusing on major white matter tracts. These focal reductions in the splenium and the cerebral peduncle may be associated with sensorimotor impairments seen in individuals with ASD.

Revolution of Alzheimer Precision Neurology. Passageway of Systems Biology and Neurophysiology

The Precision Neurology development process implements systems theory with system biology and neurophysiology in a parallel, bidirectional research path: a combined hypothesis-driven investigation of systems dysfunction within distinct molecular, cellular, and large-scale neural network systems in both animal models as well as through tests for the usefulness of these candidate dynamic systems biomarkers in different diseases and subgroups at different stages of pathophysiological progression. This translational research path is paralleled by an "omics"-based, hypothesis-free, exploratory research pathway, which will collect multimodal data from progressing asymptomatic, preclinical, and clinical neurodegenerative disease (ND) populations, within the wide continuous biological and clinical spectrum of ND, applying high-throughput and high-content technologies combined with powerful computational and statistical modeling tools, aimed at identifying novel dysfunctional systems and predictive marker signatures associated with ND. The goals are to identify common biological denominators or differentiating classifiers across the continuum of ND during detectable stages of pathophysiological progression, characterize systems-based intermediate endophenotypes, validate multi-modal novel diagnostic systems biomarkers, and advance clinical intervention trial designs by utilizing systems-based intermediate endophenotypes and candidate surrogate markers. Achieving these goals is key to the ultimate development of early and effective individualized treatment of ND, such as Alzheimer's disease. The Alzheimer Precision Medicine Initiative (APMI) and cohort program (APMI-CP), as well as the Paris based core of the Sorbonne University Clinical Research Group "Alzheimer Precision Medicine" (GRC-APM) were recently launched to facilitate the passageway from conventional clinical diagnostic and drug development toward breakthrough innovation based on the investigation of the comprehensive biological nature of aging individuals. The APMI movement is gaining momentum to systematically apply both systems neurophysiology and systems biology in exploratory translational neuroscience research on ND.

An altered scaffold for information processing: Cognitive control development in adolescents with autism

We investigated how cognitive neuroscientific studies during the last decade have advanced understanding of cognitive control from adolescence to young adulthood in individuals with autism spectrum disorder (ASD). To do so, we conducted a selective review of the larger structural, resting state, and diffusion imaging studies of brain regions and networks related to cognitive control that have been conducted since 2007 in individuals with ASD and typical development (TYP) ages 10 to 30 years that examined how these regions and networks support behavioral and task-based fMRI performance on tasks assessing cognitive control during this period. Longitudinal structural studies reveal overgrowth of the anterior cingulate (ACC) and slower white matter development in the parietal cortex in adolescents with ASD versus TYP. Cross-sectional studies of the salience, executive control and default mode resting state functional connectivity networks, which mediate cognitive control, demonstrate patterns of connectivity that differ from TYP through adolescence. Finally, white matter tracts underlying these control-related brain regions continue to show reduced diffusion properties compared to TYP. It is thus not surprising that cognitive control tasks performance improves less during adolescence in ASD versus TYP. This review illustrates that a cognitive neuroscientific approach produces insights about the mechanisms of persistent cognitive control deficits in individuals with ASD from adolescence into young adulthood not apparent with neuropsychological methods alone, and draws attention to the great need for longitudinal studies of this period in those with ASD. Further investigation of ACC and fronto-parietal neural circuits may help specify pathophysiology and treatment options.

Neurodevelopmental Hypothesis about the Etiology of Autism Spectrum Disorders

Previous models or hypotheses of autism spectral disorder (ASD) failed to take into full consideration the chronological and causal developmental trajectory, leading to the emergence of diverse phenotypes through a complex interaction between individual etiologies and environmental factors. Those phenotypes include persistent deficits in social communication and social interaction (criteria A in DSM-5), and restricted, repetitive patterns of behavior, interests, or activities (criteria B in DSM-5). In this article, we proposed a domain-general model that can explain criteria in DSM-5 based on the assumption that the same etiological mechanism would trigger the various phenotypes observed in different individuals with ASD. In the model, we assumed the following joint causes as the etiology of autism: (1) Hypoplasia of the pons in the brainstem, occurring immediately following neural tube closure; and (2) Deficiency in the GABA (γ-aminobutyric acid) developmental switch during the perinatal period. Microstructural abnormalities of the pons directly affect both the structural and functional development of the brain areas strongly connected to it, especially amygdala. The impairment of GABA switch could not only lead to the deterioration of inhibitory processing in the neural network, but could also cause abnormal cytoarchitecture. We introduced a perspective that atypical development in both brain structure and function can give full explanation of diverse phenotypes and pathogenetic mechanism of ASD. Finally, we discussed about neural mechanisms underlying the phenotypic characteristics of ASD that are not described in DSM-5 but should be considered as important foundation: sleep, global precedence, categorical perception, intelligence, interoception and motor control.

Annual Research Review: Understudied populations within the autism spectrum - current trends and future directions in neuroimaging research

BACKGROUND

Autism spectrum disorders (ASDs) are a heterogeneous group of neurodevelopmental conditions that vary in both etiology and phenotypic expression. Expressions of ASD characterized by a more severe phenotype, including autism with intellectual disability (ASD + ID), autism with a history of developmental regression (ASD + R), and minimally verbal autism (ASD + MV) are understudied generally, and especially in the domain of neuroimaging. However, neuroimaging methods are a potentially powerful tool for understanding the etiology of these ASD subtypes.

SCOPE AND METHODOLOGY

This review evaluates existing neuroimaging research on ASD + MV, ASD + ID, and ASD + R, identified by a search of the literature using the PubMed database, and discusses methodological, theoretical, and practical considerations for future research involving neuroimaging assessment of these populations.

FINDINGS

There is a paucity of neuroimaging research on ASD + ID, ASD + MV, and ASD + R, and what findings do exist are often contradictory, or so sparse as to be ungeneralizable. We suggest that while greater sample sizes and more studies are necessary, more important would be a paradigm shift toward multimodal (e.g. imaging genetics) approaches that allow for the characterization of heterogeneity within etiologically diverse samples.

Environmental Enrichment Therapy for Autism: Outcomes with Increased Access

We have previously shown in two randomized clinical trials that environmental enrichment is capable of ameliorating symptoms of autism spectrum disorder (ASD), and in the present study, we determined whether this therapy could be effective under real-world circumstances. 1,002 children were given daily Sensory Enrichment Therapy, by their parents, using personalized therapy instructions given over the Internet. Parents were asked to assess the symptoms of their child every 2 weeks for up to 7 months. An intention-to-treat analysis showed significant overall gains for a wide range of symptoms in these children, including learning, memory, anxiety, attention span, motor skills, eating, sleeping, sensory processing, self-awareness, communication, social skills, and mood/autism behaviors. The children of compliant caregivers were more likely to experience a significant improvement in their symptoms. The treatment was effective across a wide age range and there was equal progress reported for males and females, for USA and international subjects, for those who paid and those who did not pay for the therapy, and for individuals at all levels of initial symptom severity. Environmental enrichment, delivered via an online system, therefore appears to be an effective, low-cost means of treating the symptoms of ASD.

Biochemistry of the cingulate cortex in autism: An MR spectroscopy study

Neuroimaging studies have uncovered structural and functional alterations in the cingulate cortex in individuals with autism spectrum disorders (ASD). Such abnormalities may underlie neurochemical imbalance. In order to characterize the neurochemical profile, the current study examined the concentration of brain metabolites in dorsal ACC (dACC) and posterior cingulate cortex (PCC) in high-functioning adults with ASD. Twenty high-functioning adults with ASD and 20 age-and-IQ-matched typically developing (TD) peers participated in this Proton magnetic resonance spectroscopy (1H-MRS) study. LCModel was used in analyzing the spectra to measure the levels of N-Acetyl aspartate (NAA), choline (Cho), creatine (Cr), and glutamate/glutamine (Glx) in dACC and PCC. Groups were compared using means for the ratio of each metabolite to their respective Cr levels as well as on absolute internal-water-referenced measures of each metabolite. There was a significant increase in Cho in PCC for ASD adults, with a marginal increase in dACC. A reduction in NAA/Cr in dACC was found in ASD participants, compared to their TD peers. No significant differences in Glx/Cr or Cho/Cr were found in dACC. There were no statistically significant group differences in the absolute concentration of NAA, Cr, Glx, or NAA/Cr, Cho/Cr, and Glx/Cr in the PCC. Differences in the metabolic properties of dACC compared to PCC were also found. Results of this study provide evidence for possible cellular and metabolic differences in the dACC and PCC in adults with ASD. This may suggest neuronal dysfunction in these regions and may contribute to the neuropathology of ASD. Autism Res 2016, 9: 643-657. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

Diffusion tensor imaging reveals no white matter impairments among adults with autism spectrum disorder

Abnormalities within white matter (WM) have been identified in autism spectrum disorder (ASD). Although there is some support for greater neurobiological deficits among females with ASD, there is little research investigating sex differences in WM in ASD. We used diffusion tensor imaging (DTI) to investigate WM aberration in 25 adults with high-functioning ASD and 24 age-, sex- and IQ-matched controls. Tract-based spatial statistics (TBSS) was used to explore differences in WM in major tract bundles. The effects of biological sex were also investigated. TBSS revealed no differences in fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), or axial diffusivity (AD) between groups. There were no effects of biological sex. We consider whether methodological differences between past studies have contributed to the highly heterogeneous findings in the literature. Finally, we suggest that, among a high-functioning sample of adults with ASD, differences in WM microstructure may not be related to clinical impairment.

Development of the uncinate fasciculus: Implications for theory and developmental disorders

The uncinate fasciculus (UF) is a long-range white matter tract that connects limbic regions in the temporal lobe to the frontal lobe. The UF is one of the latest developing tracts, and continues maturing into the third decade of life. As such, individual differences in the maturational profile of the UF may serve to explain differences in behavior. Indeed, atypical macrostructure and microstructure of the UF have been reported in numerous studies of individuals with developmental and psychiatric disorders such as social deprivation and maltreatment, autism spectrum disorders, conduct disorder, risk taking, and substance abuse. The present review evaluates what we currently know about the UF's developmental trajectory and reviews the literature relating UF abnormalities to specific disorders. Additionally, we take a dimensional approach and critically examine symptoms and behavioral impairments that have been demonstrated to cluster with UF aberrations, in an effort to relate these impairments to our speculations regarding the functionality of the UF. We suggest that developmental disorders with core problems relating to memory retrieval, reward and valuation computation, and impulsive decision making may be linked to aberrations in uncinate microstructure.

Brain MR diffusion tensor imaging in Kennedy's disease

INTRODUCTION

Kennedy's disease (KD) is a progressive degenerative disorder affecting lower motor neurons. We investigated the correlation between disease severity and whole brain white matter microstructure, including upper motor neuron tracts, by using diffusion-tensor imaging (DTI) in eight patients with KD in whom disease severity was evaluated using the Amyotrophic Lateral Sclerosis Functional Rating Scale (ALSFRS).

METHODS

From DTI acquisitions we obtained maps of fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (L1) and radial diffusivities (L2, L3). We then employed tract-based spatial statistics (TBSS) to investigate within-patient correlations of DTI invariants with ALSFRS and disease duration (DD).

RESULTS

We found a significant correlation between low ALSFRS and 1) low FA values in association commissural and projection fibers, and 2) high L3 values in commissural tracts and fronto-parietal white matter. Additionally, we found a significant association between longer DD and 1) low FA in the genu and body of corpus callosum, association fibers and midbrain and 2) high L1 in projection and association tracts.

CONCLUSIONS

The associations between clinical variables and white matter microstructural changes in areas thought to be spared by the disease process support the hypothesis of a multisystem involvement in the complex pathogenic mechanisms responsible for the clinical disability of these patients.

Shared Brain Connectivity Issues, Symptoms, and Comorbidities in Autism Spectrum Disorder, Attention Deficit/Hyperactivity Disorder, and Tourette Syndrome

The prevalence of neurodevelopmental disorders, including autism spectrum disorder (ASD), attention deficit/hyperactivity disorder (ADHD), and Tourette syndrome (TS), has increased over the past two decades. Currently, about one in six children in the United States is diagnosed as having a neurodevelopmental disorder. Evidence suggests that ASD, ADHD, and TS have similar neuropathology, which includes long-range underconnectivity and short-range overconnectivity. They also share similar symptomatology with considerable overlap in their core and associated symptoms and a frequent overlap in their comorbid conditions. Consequently, it is apparent that ASD, ADHD, and TS diagnoses belong to a broader spectrum of neurodevelopmental illness. Biologically, long-range underconnectivity and short-range overconnectivity are plausibly related to neuronal insult (e.g., neurotoxicity, neuroinflammation, excitotoxicity, sustained microglial activation, proinflammatory cytokines, toxic exposure, and oxidative stress). Therefore, these disorders may a share a similar etiology. The main purpose of this review is to critically examine the evidence that ASD, ADHD, and TS belong to a broader spectrum of neurodevelopmental illness, an abnormal connectivity spectrum disorder, which results from neural long-range underconnectivity and short-range overconnectivity. The review also discusses the possible reasons for these neuropathological connectivity findings. In addition, this review examines the role and issue of axonal injury and regeneration in order to better understand the neuropathophysiological interplay between short- and long-range axons in connectivity issues.

Linked alterations in gray and white matter morphology in adults with high-functioning autism spectrum disorder: a multimodal brain imaging study

Growing evidence suggests that a broad range of behavioral anomalies in people with autism spectrum disorder (ASD) can be linked with morphological and functional alterations in the brain. However, the neuroanatomical underpinnings of ASD have been investigated using either structural magnetic resonance imaging (MRI) or diffusion tensor imaging (DTI), and the relationships between abnormalities revealed by these two modalities remain unclear. This study applied a multimodal data-fusion method, known as linked independent component analysis (ICA), to a set of structural MRI and DTI data acquired from 46 adult males with ASD and 46 matched controls in order to elucidate associations between different aspects of atypical neuroanatomy of ASD. Linked ICA identified two composite components that showed significant between-group differences, one of which was significantly correlated with age. In the other component, participants with ASD showed decreased gray matter (GM) volumes in multiple regions, including the bilateral fusiform gyri, bilateral orbitofrontal cortices, and bilateral pre- and post-central gyri. These GM changes were linked with a pattern of decreased fractional anisotropy (FA) in several white matter tracts, such as the bilateral inferior longitudinal fasciculi, bilateral inferior fronto-occipital fasciculi, and bilateral corticospinal tracts. Furthermore, unimodal analysis for DTI data revealed significant reductions of FA along with increased mean diffusivity in those tracts for ASD, providing further evidence of disrupted anatomical connectivity. Taken together, our findings suggest that, in ASD, alterations in different aspects of brain morphology may co-occur in specific brain networks, providing a comprehensive view for understanding the neuroanatomy of this disorder.

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Structural alterations of gray (GM) and white matter (WM) in ASD were investigated.

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Linked independent component analysis was used for multimodal data analysis.

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Alterations of GM and WM in ASD co-occurred in cognitive and affective networks.

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Results reveal an integrative view of multiple aspects of structural changes in ASD.

Increased left hemisphere impairment in high-functioning autism: a tract based spatial statistics study

There is evidence emerging from Diffusion Tensor Imaging (DTI) research that autism spectrum disorders (ASD) are associated with greater impairment in the left hemisphere. Although this has been quantified with volumetric region of interest analyses, it has yet to be tested with white matter integrity analysis. In the present study, tract based spatial statistics was used to contrast white matter integrity of 12 participants with high-functioning autism or Aspergers syndrome (HFA/AS) with 12 typically developing individuals. Fractional Anisotropy (FA) was examined, in addition to axial, radial and mean diffusivity (AD, RD and MD). In the left hemisphere, participants with HFA/AS demonstrated significantly reduced FA in predominantly thalamic and fronto-parietal pathways and increased RD. Symmetry analyses confirmed that in the HFA/AS group, WM disturbance was significantly greater in the left compared to right hemisphere. These findings contribute to a growing body of literature suggestive of reduced FA in ASD, and provide preliminary evidence for RD impairments in the left hemisphere.

Altered white matter connectivity as a neural substrate for social impairment in Autism Spectrum Disorder

BACKGROUND

Autism Spectrum Disorder (ASD) symptoms have been hypothesized to result from altered brain connectivity. The 'disconnectivity' hypothesis has been used to explain characteristic impairments in socio-emotional function, observed clinically in ASD. Here, we review the evidence for impaired white matter connectivity as a neural substrate for socio-emotional dysfunction in ASD. A review of diffusion tensor imaging (DTI) studies, and focused discussion of relevant post-mortem, structural, and functional neuroimaging studies, is provided.

METHODS

Studies were identified using a sensitive search strategy in MEDLINE, Embase and PsycINFO article databases using the OvidSP database interface. Search terms included database subject headings for the concepts of pervasive developmental disorders, and DTI. Seventy-two published DTI studies examining white matter microstructure in ASD were reviewed. A comprehensive discussion of DTI studies that examined white matter tracts linking socio-emotional structures is presented.

RESULTS

Several DTI studies reported microstructural differences indicative of developmental alterations in white matter organization, and potentially myelination, in ASD. Altered structure within long-range white matter tracts linking socio-emotional processing regions was implicated. While alterations of the uncinate fasciculus and frontal and temporal thalamic projections have been associated with social symptoms in ASD, few studies examined association of tract microstructure with core impairment in this disorder.

CONCLUSIONS

The uncinate fasciculus and frontal and temporal thalamic projections mediate limbic connectivity and integrate structures responsible for complex socio-emotional functioning. Impaired development of limbic connectivity may represent one neural substrate contributing to ASD social impairments. Future efforts to further elucidate the nature of atypical white matter development, and its relationship to core symptoms, may offer new insights into etiological mechanisms contributing to ASD impairments and uncover novel opportunities for targeted intervention.

Reduction in retinal nerve fiber layer thickness in young adults with autism spectrum disorders

Recent years have seen an increase in the use of retinal nerve fiber layer (RNFL) evaluation as an easy-to-use, reproducible, proxy-measure of brain structural abnormalities. Here, we evaluated RNFL thickness in a group of subjects with high functioning autism (HFA) or with Asperger Syndrome (AS) to its potential as a tool to study autism pathophysiology. All subjects underwent high-resolution spectral domain optical coherence tomography to evaluate RNFL thickness. HFA subjects presented with reduced global RNFL thickness compared both to AS subjects and controls. AS subjects showed a reduced nasal quadrant RNFL thickness compared to controls. Verbal-IQ/performance-IQ discrepancy correlated with RNFL thickness. Our data suggest that RNFL evaluation could help in the development of biological markers of autism pathophysiology.

Altered microstructural connectivity of the superior cerebellar peduncle is related to motor dysfunction in children with autistic spectrum disorders

Many studies have reported motor impairments in autistic spectrum disorders (ASD). However, the brain mechanism underlying motor impairment in ASD remains unclear. Recent neuroimaging studies have suggested that underconnectivity between the cerebellum and other brain regions contributes to the features of ASD. In this study, we investigated the microstructural integrity of the cerebellar pathways, including the superior, middle, and inferior cerebellar peduncles, of children with and without ASD by using diffusion tensor imaging (DTI) tractography to determine whether the microstructural integrity of the cerebellar pathways is related to motor function in children with ASD. Thirteen children with ASD and 11 age-, gender-, handedness-, and IQ-matched typically developing (TD) controls were enrolled in this study. DTI outcome measurements, such as fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD), for the cerebellar pathways were calculated. The Movement Assessment Battery for Children 2 (M-ABC 2) was used for assessing motor functions. There were no significant differences between the two groups in RD. However, compared to the TD subjects, patients with ASD had a significantly lower FA in the right superior cerebellar peduncle and lower AD in the left superior cerebellar peduncle, in addition to a significantly lower score in ball skills and the total test score of M-ABC 2. There was a significant positive correlation between the total test score of M-ABC 2 and FA in the right superior cerebellar peduncle in the ASD group. These findings suggest that the altered microstructural integrity of the superior cerebellar peduncle may be related to motor impairment in ASD.

Recommendations for early diagnosis and intervention in autism spectrum disorders: an Italian-Israeli consensus conference

On April 2013 experts in the field of autism from Italy and Israel convened in Jerusalem to discuss and finalize clinical recommendations for early diagnosis and intervention in Autism Spectrum Disorders (ASDs). In this paper, we summarize the results of this Italian-Israeli consensus conference. ASDs constitute a class of severe and heterogeneous neurodevelopmental conditions caused by atypical brain development beginning during early prenatal life, reflecting many genetic, neurobiological and environmental influences. The first clinical signs of ASDs begin to be evident in children between 12 and 18 months of age, often after a period of relatively typical postnatal development. Recent longitudinal studies reveal substantial diversity in developmental trajectories through childhood and adolescence. Some intervention approaches have been demonstrated to be effective in improving core symptoms of ASDs, even if the heterogeneity and developmental nature of the disorder make it implausible that only one specific treatment will be best for all children with ASDs. More randomized control trials (RCTs) on early intervention are needed to identify the most effective strategies and provide the most efficient allocation of resources during the critical early intervention time period. Future research should focus on linking biological phenotypes with specific genotypes, thus establishing a foundation for the development of diagnostic screening tools and individualization of treatments.

Altered neural connectivity in excitatory and inhibitory cortical circuits in autism

Converging evidence from diverse studies suggests that atypical brain connectivity in autism affects in distinct ways short- and long-range cortical pathways, disrupting neural communication and the balance of excitation and inhibition. This hypothesis is based mostly on functional non-invasive studies that show atypical synchronization and connectivity patterns between cortical areas in children and adults with autism. Indirect methods to study the course and integrity of major brain pathways at low resolution show changes in fractional anisotropy (FA) or diffusivity of the white matter in autism. Findings in post-mortem brains of adults with autism provide evidence of changes in the fine structure of axons below prefrontal cortices, which communicate over short- or long-range pathways with other cortices and subcortical structures. Here we focus on evidence of cellular and axon features that likely underlie the changes in short- and long-range communication in autism. We review recent findings of changes in the shape, thickness, and volume of brain areas, cytoarchitecture, neuronal morphology, cellular elements, and structural and neurochemical features of individual axons in the white matter, where pathology is evident even in gross images. We relate cellular and molecular features to imaging and genetic studies that highlight a variety of polymorphisms and epigenetic factors that primarily affect neurite growth and synapse formation and function in autism. We report preliminary findings of changes in autism in the ratio of distinct types of inhibitory neurons in prefrontal cortex, known to shape network dynamics and the balance of excitation and inhibition. Finally we present a model that synthesizes diverse findings by relating them to developmental events, with a goal to identify common processes that perturb development in autism and affect neural communication, reflected in altered patterns of attention, social interactions, and language.

Diffusion tensor imaging in SPG11- and SPG4-linked hereditary spastic paraplegia

The aim of this study was to identify potential diagnostic markers of Hereditary Spastic Paraplegia (HSP). We investigated the white matter features of spastic gait (SPG)11- and SPG4-linked HSP, using diffusion tensor imaging performed with a 3-Tesla (3T) scanner. We examined four patients with SPG11 mutations, three with SPG4 mutations, and 26 healthy controls. We obtained maps of fractional anisotropy (FA) and mean diffusivity (MD), which we analyzed through both region of interest -based approach and tract-based spatial statistics (TBSS). Compared with healthy controls, SPG11 patients presented increased MD and decreased FA in the semioval centers, frontal and peritrigonal white matter, posterior limb of the internal capsule, and throughout the corpus callosum. Similar alterations were seen in the SPG4 patients at the levels of the semioval centers, the posterior limb of the internal capsule, the left cerebral pedicle, the genu and trunk of the corpus callosum, and the peritrigonal white matter on the left. No MD or FA alterations were observed in the cerebellar white matter. In a direct comparison, white matter alterations were more pronounced and widespread in HSP-SPG11 than in HSP-SPG4 patients. Joint TBSS analysis of all three groups confirmed significant widespread alterations of FA and MD values in the supratentorial white matter. This noninvasive study documented the presence of altered diffusivity in white matter in both forms of HSP, which could represent an important diagnostic marker of HSP. The association of reduced FA and increased MD in this patient population supports the interpretation of HPG as a neurodegenerative disorder.

Cerebral diffusion tensor MR tractography in tuberous sclerosis complex: correlation with neurologic severity and tract-based spatial statistical analysis

BACKGROUND AND PURPOSE

The neurologic significance of residual cerebral white matter tracts, identified on diffusion tensor tractography, has not been well studied in tuberous sclerosis complex. We aimed to correlate the quantity of reconstructed white matter tracts with the degree of neurologic impairment of subjects with the use of DTI and determined differences in white matter integrity between patients with tuberous sclerosis complex and controls with the use of voxelwise analysis.

MATERIALS AND METHODS

In this case-control study, 16 patients with tuberous sclerosis complex and 12 control subjects underwent DTI. Major white matter tracts, comprising bilateral PF and CF, were reconstructed and assessed for quantity, represented by NOP and NOF. A neurologic severity score, based on the presence of developmental disability, seizure, autism, and other neuropsychiatric disorders, was calculated for each subject. We then correlated this score with white matter quantity. Voxelwise tract-based spatial statistics was used to determine differences in FA, axial, and radial diffusivity values between the tuberous sclerosis complex group and the control subjects.

RESULTS

NOP and NOF of CF, bilateral PF, and MWT in the tuberous sclerosis complex group were all significantly lower than those in the control subjects (P < .05). The neurologic severity score was moderately negatively correlated with NOF and NOP regarding CF (r = -.70; r = -.75), bilateral PF (r = -.66; r = -.68), and MWT (r = -.71; r = -.74). Tract-based spatial statistics revealed that patients with tuberous sclerosis complex showed a widespread reduction (P < .05) in FA and axial diffusivity in most cerebral white matter regions.

CONCLUSIONS

Patients with tuberous sclerosis complex with reduced residual white matter were neurologically more severely affected. Tract-based spatial statistics revealed decreased FA and axial diffusivity of the cerebral white matter in the tuberous sclerosis complex group, suggesting reduced axonal integrity.

Concordance of white matter and gray matter abnormalities in autism spectrum disorders: a voxel-based meta-analysis study

There are at least two fundamental unanswered questions in the literature on autism spectrum disorders (ASD): Are abnormalities in white (WM) and gray matter (GM) consistent with one another? Are WM morphometric alterations consistent with alterations in the GM of regions connected by these abnormal WM bundles and vice versa? The aim of this work is to bridge this gap. After selecting voxel-based morphometry and diffusion tensor imaging studies comparing autistic and normally developing groups of subjects, we conducted an activation likelihood estimation (ALE) meta-analysis to estimate consistent brain alterations in ASD. Multidimensional scaling was used to test the similarity of the results. The ALE results were then analyzed to identify the regions of concordance between GM and WM areas. We found statistically significant topological relationships between GM and WM abnormalities in ASD. The most numerous were negative concordances, found bilaterally but with a higher prevalence in the right hemisphere. Positive concordances were found in the left hemisphere. Discordances reflected the spatial distribution of negative concordances. Thus, a different hemispheric contribution emerged, possibly related to pathogenetic factors affecting the right hemisphere during early developmental stages. Besides, WM fiber tracts linking the brain structures involved in social cognition showed abnormalities, and most of them had a negative concordance with the connected GM regions. We interpreted the results in terms of altered brain networks and their role in the pervasive symptoms dramatically impairing communication and social skills in ASD patients.

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.

Relating anatomical and social connectivity: white matter microstructure predicts emotional empathy

Understanding cues to the internal states of others involves a widely distributed network of brain regions. Although white matter (WM) connections are likely crucial for communication between these regions, the role of anatomical connectivity in empathic processing remains unexplored. The present study tested for a relationship between anatomical connectivity and empathy by assessing the WM microstructural correlates of affective empathy, which promotes interpersonal understanding through emotional reactions, and cognitive empathy, which does so via perspective taking. Associations between fractional anisotropy (FA) and the emotional (empathic concern, EC) and cognitive (perspective taking, PT) dimensions of empathy as assessed by the Interpersonal Reactivity Index were examined. EC was positively associated with FA in tracts providing communicative pathways within the limbic system, between perception and action-related regions, and between perception and affect-related regions, independently of individual differences in age, gender, and other dimensions of interpersonal reactivity. These findings provide a neuroanatomical basis for the rapid, privileged processing of emotional sensory information and the automatic elicitation of responses to the affective displays of others.

Autism spectrum disorder: does neuroimaging support the DSM-5 proposal for a symptom dyad? A systematic review of functional magnetic resonance imaging and diffusion tensor imaging studies

A systematic review of 208 studies comprising functional magnetic resonance imaging and diffusion tensor imaging data in patients with 'autism spectrum disorder' (ASD) was conducted, in order to determine whether these data support the forthcoming DSM-5 proposal of a social communication and behavioral symptom dyad. Studies consistently reported abnormal function and structure of fronto-temporal and limbic networks with social and pragmatic language deficits, of temporo-parieto-occipital networks with syntactic-semantic language deficits, and of fronto-striato-cerebellar networks with repetitive behaviors and restricted interests in ASD patients. Therefore, this review partially supports the DSM-5 proposal for the ASD dyad.

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.

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.

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.

White matter and development in children with an autism spectrum disorder

Recent research suggests that brain development follows an abnormal trajectory in children with autism spectrum disorders (ASD). The current study examined changes in diffusivity with age within defined white matter tracts in a group of typically developing children and a group of children with an ASD, aged 6 to 14 years. Age by group interactions were observed for frontal, long distant, interhemispheric and posterior tracts, for longitudinal, radial and mean diffusivity, but not for fractional anisotropy. In all cases, these measures of diffusivity decreased with age in the typically developing group, but showed little or no change in the ASD group. This supports the hypothesis of an abnormal developmental trajectory of white matter in this population, which could have profound effects on the development of neural connectivity and contribute to atypical cognitive development in children with ASD.

Abnormal white matter integrity in young children with autism

This study investigated white matter integrity in young children with autism using diffusion tensor imaging (DTI). Twenty-two children with autism, mean age 3:2 years, and 32 controls, mean age 3:4 years, participated in the study. Tract-based spatial statistics (TBSS) revealed white matter abnormalities in several distinct clusters within the genu and body of the corpus callosum (CC), left superior longitudinal fasciculus (SLF) and right and left cingulum (Cg). TBSS-VOIs analysis was performed in the clusters where differences in fractional anisotropy (FA) were detected to investigate the relationship between changes in FA and diffusivity indices. In all VOIs, increase in FA was caused by a decrease in radial diffusivity (Dr), while no changes in axial diffusivity (Da) or mean diffusivity (MD) were observed. Tractography analysis was applied to further study the CC, SLF, and Cg. Witelson parcellation scheme was used for the CC. Significant increase in FA was seen in children with autism in the mid-body of the CC as well as in the left Cg. It is suggested that such abnormal white matter integrity in young children with autism may adversely affect connectivity between different brain regions and may be linked to some of the behavioral impairments apparent in autism.

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.

Impaired structural connectivity of socio-emotional circuits in autism spectrum disorders: a diffusion tensor imaging study

Background

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.

Methods/Principal Findings

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.

Conclusions/Significance

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.

Functional annotation of genes overlapping copy number variants in autistic patients: focus on axon pathfinding

We have used Gene Ontology (GO) and pathway analyses to uncover the common functions associated to the genes overlapping Copy Number Variants (CNVs) in autistic patients. Our source of data were four published studies [1-4]. We first applied a two-step enrichment strategy for autism-specific genes. We fished out from the four mentioned studies a list of 2928 genes overall overlapping 328 CNVs in patients and we first selected a sub-group of 2044 genes after excluding those ones that are also involved in CNVs reported in the Database of Genomic Variants (enrichment step 1). We then selected from the step 1-enriched list a sub-group of 514 genes each of which was found to be deleted or duplicated in at least two patients (enrichment step 2). The number of statistically significant processes and pathways identified by the Database for Annotation, Visualization and Integrated Discovery and Ingenuity Pathways Analysis softwares with the step 2-enriched list was significantly higher compared to the step 1-enriched list. In addition, statistically significant GO terms, biofunctions and pathways related to nervous system development and function were exclusively identified by the step 2-enriched list of genes. Interestingly, 21 genes were associated to axon growth and pathfinding. The latter genes and other ones associated to nervous system in this study represent a new set of autism candidate genes deserving further investigation. In summary, our results suggest that the autism’s “connectivity genes” in some patients affect very early phases of neurodevelopment, i.e., earlier than synaptogenesis.

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.

Structural and functional magnetic resonance imaging of autism spectrum disorders

The neurobiology of autism spectrum disorders (ASDs) has become increasingly understood since the advent of magnetic resonance imaging (MRI). Initial observations of an above-average head circumference were supported by structural MRI studies that found evidence of increased total brain volume and early rapid brain overgrowth in affected individuals. Subsequent research revealed consistent abnormalities in cortical gray and white matter volume in ASDs. The structural integrity and orientation of white matter have been further elucidated via diffusion tensor imaging methods. The emergence of functional MRI techniques led to an enhanced understanding of the neural circuitry of ASDs, demonstrating areas of dysfunctional cortical activation and atypical cortical specialization. These studies have provided evidence of underconnectivity in distributed cortical networks integral to the core impairments associated with ASDs. Abnormalities in the default-mode network during the resting state have also been identified. Overall, structural and functional MRI research has generated important insights into the neurobiology of ASDs. Additional research is needed to further delineate the underlying brain basis of this constellation of disorders.

Tract-specific analyses of diffusion tensor imaging show widespread white matter compromise in autism spectrum disorder

BACKGROUND

Previous diffusion tensor imaging (DTI) studies have shown white matter compromise in children and adults with autism spectrum disorder (ASD), which may relate to reduced connectivity and impaired function of distributed networks. However, tract-specific evidence remains limited in ASD. We applied tract-based spatial statistics (TBSS) for an unbiased whole-brain quantitative estimation of the fractional anisotropy (FA), mean diffusion (MD) and axial and radial diffusion of the white matter tracts in children and adolescents with ASD.

METHODS

DTI was performed in 26 ASD and 24 typically developing (TD) participants, aged 9-20 years. Groups were matched for age and IQ. Each participant's aligned FA, MD and axial and radial diffusion data were projected onto the mean FA skeleton representing the centers of all tracts and the resulting data fed into voxelwise group statistics.

RESULTS

TBSS revealed decreased FA and increased MD and radial diffusion in the ASD group compared to the TD group in the corpus callosum, anterior and posterior limbs of the internal capsule, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, superior longitudinal fasciculus, cingulum, anterior thalamic radiation, and corticospinal tract. No single site with inverse effects (increased FA, reduced MD or radial diffusion in the ASD group) was detected. In clusters of significant group difference, age was positively correlated with FA and negatively correlated with MD and radial diffusion in the TD, but not the ASD group.

CONCLUSIONS

Our findings reveal white matter compromise affecting numerous tracts in children and adolescents with ASD. Slightly varying patterns of diffusion abnormalities detected for some tracts may suggest tract-specific patterns of white matter abnormalities associated with ASD. Age-dependent effects further show that maturational changes (increasing FA, decreasing MD and radial diffusion with age) are diminished in ASD from school-age childhood into young adulthood.