Mapping the brain in autism. A voxel-based MRI study of volumetric differences and intercorrelations in autism

Age, Disease, and Their Interaction Effects on Intrinsic Connectivity of Children and Adolescents in Autism Spectrum Disorder Using Functional Connectomics

Brain connectivity analysis has provided crucial insights to pinpoint the differences between autistic and typically developing (TD) children during development. The aim of this study is to investigate the functional connectomics of autism spectrum disorder (ASD) versus TD and underpin the effects of development, disease, and their interactions on the observed atypical brain connectivity patterns. Resting-state functional magnetic resonance imaging (rs-fMRI) from the Autism Brain Imaging Data Exchange (ABIDE) data set, which is stratified into two cohorts: children (9-12 years) and adolescents (13-16 years), is used for the analysis. Differences in various graph theoretical network measures are calculated between ASD and TD in each group. Furthermore, two-factor analysis of variance test is used to study the effect of age, disease, and their interaction on the network measures and the network edges. Furthermore, the differences in connection strength between TD and ASD subjects are assessed using network-based statistics. The results showed that ASD exhibits increased functional integration at the expense of decreased functional segregation. In ASD adolescents, there is a significant decrease in modularity suggesting a less robust modular organization, and an increase in participation coefficient suggesting more random integration and widely distributed connection edges. Furthermore, there is significant hypoconnectivity observed in the adolescent group especially in the default mode network, while the children group shows both hyper- and hypoconnectivity. This study lends support to a model of global atypical connections and further identifies functional networks and areas that are independently affected by age, disease, and their interaction.

Clinical associations of maternal thyroid function with foetal brain development: Epidemiological interpretation and overview of available evidence

Thyroid hormone is an important regulator of early brain development, particularly during early stages of gestation during which foetal thyroid hormone availability depends on the maternal transfer of thyroid hormones. There is a wide range of experimental studies showing that low maternal thyroid hormone availability is associated with suboptimal brain development parameters. While few clinical studies have shown that overt maternal hypothyroidism is associated with lower child IQ, the question whether more subclinical changes in maternal thyroid function could also lead to suboptimal foetal brain development. In this review, we put the latter studies in perspective and discuss their interpretation from an epidemiological and clinical perspective. Furthermore, we extend this discussion to also include future perspective and identify important knowledge gaps in the field.

Reduced structural complexity of the right cerebellar cortex in male children with autism spectrum disorder

The cerebellum contains 80% of all neurons in the human brain and contributes prominently to implicit learning and predictive processing across motor, sensory, and cognitive domains. As morphological features of the cerebellum in atypically developing individuals remain unexplored in-vivo, this is the first study to use high-resolution 3D fractal analysis to estimate fractal dimension (FD), a measure of structural complexity of an object, of the left and right cerebellar cortex (automatically segmented from Magnetic Resonance Images using FreeSurfer), in male children with Autism Spectrum Disorders (ASD) (N = 20; mean age: 8.8 years old, range: 7.13-10.27) and sex, age, verbal-IQ, and cerebellar volume-matched typically developing (TD) boys (N = 18; mean age: 8.9 years old, range: 6.47-10.52). We focus on an age range within the 'middle and late childhood' period of brain development, between 6 and 12 years. A Mann-Whitney U test revealed a significant reduction in the FD of the right cerebellar cortex in ASD relative to TD boys (P = 0.0063, Bonferroni-corrected), indicating flatter and less regular surface protrusions in ASD relative to TD males. Consistent with the prediction that the cerebellum participates in implicit learning, those ASD boys with a higher (vs. lower) PIQ>VIQ difference showed higher, more normative complexity values, closer to TD children, providing new insight on our understanding of the neurological basis of differences in verbal and performance cognitive abilities that often characterize individuals with ASD.

Differences in Cortical Structure and Functional MRI Connectivity in High Functioning Autism

Autism spectrum disorders (ASD) represent a complex group of neurodevelopmental conditions characterized by deficits in communication and social behaviors. We examined the functional connectivity (FC) of the default mode network (DMN) and its relation to multimodal morphometry to investigate superregional, system-level alterations in a group of 22 adolescents and young adults with high-functioning autism compared to age-, and intelligence quotient-matched 29 healthy controls. The main findings were that ASD patients had gray matter (GM) reduction, decreased cortical thickness and larger cortical surface areas in several brain regions, including the cingulate, temporal lobes, and amygdala, as well as increased gyrification in regions associated with encoding visual memories and areas of the sensorimotor component of the DMN, more pronounced in the left hemisphere. Moreover, patients with ASD had decreased connectivity between the posterior cingulate cortex, and areas of the executive control component of the DMN and increased FC between the anteromedial prefrontal cortex and areas of the sensorimotor component of the DMN. Reduced cortical thickness in the right inferior frontal lobe correlated with higher social impairment according to the scores of the Autism Diagnostic Interview-Revised (ADI-R). Reduced cortical thickness in left frontal regions, as well as an increased cortical thickness in the right temporal pole and posterior cingulate, were associated with worse scores on the communication domain of the ADI-R. We found no association between scores on the restrictive and repetitive behaviors domain of ADI-R with structural measures or FC. The combination of these structural and connectivity abnormalities may help to explain some of the core behaviors in high-functioning ASD and need to be investigated further.

Crossing the divide: a longitudinal study of effective treatments for people with autism and attention deficit hyperactivity disorder across the lifespan

Background

Autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) frequently persist into adolescence and young adulthood. However, there are few clinical services that support those with these disorders through adulthood.

Objective

Our aim was to determine if clinical services meet the needs of people with ASD and ADHD, who are ‘at transition’ from childhood to adulthood.

Design

A longitudinal study of individuals with ASD and ADHD, the impact of services and treatments.

Methods

Our research methods included (1) interviewing > 180 affected individuals (and their families) with a confirmed diagnosis of ASD and/or ADHD, (2) screening for ASD and ADHD in approximately 1600 patients and (3) surveying general practitioner prescribing to 5651 ASD individuals across the UK. In addition, we tested the effectiveness of (1) new ASD diagnostic interview measures in 169 twins, 145 familes and 150 non-twins, (2) a magnetic resonance imaging-based diagnostic aid in 40 ASD individuals, (3) psychological treatments in 46 ASD individuals and (4) the feasability of e-learning in 28 clinicians.

Setting

NHS clinical services and prisons.

Participants

Focus – young people with ASD and ADHD as they ‘transition’ from childhood and adolescence into early adulthood.

Interventions

Testing the utility of diagnostic measures and services, web-based learning interventions, pharmacological prescribing and cognitive–behavioural treatments.

Main outcome measures

Symptom severity, service provision and met/unmet need.

Results

People with ASD and ADHD have very significant unmet needs as they transition through adolescence and young adulthood. A major contributor to this is the presence of associated mental health symptoms. However, these are mostly undiagnosed (and untreated) by clinical services. Furthermore, the largest determinant of service provision was age and not severity of symptoms. We provide new tools to help diagnose both the core disorders and their associated symptoms. We also provide proof of concept for the effectiveness of simple psychological interventions to treat obsessional symptoms, the potential to run treatment trials in prisons and training interventions.

Limitations

Our findings only apply to clinical service settings.

Conclusions

As individuals ‘transition’ their contact with treatment and support services reduces significantly. Needs-led services are required, which can both identify individuals with the ‘core symptoms’ of ASD and ADHD and treat their residual symptoms and associated conditions.

Future work

To test our new diagnostic measures and treatment approaches in larger controlled trials.

Trial registration

Current Controlled Trials ISRCTN87114880.

Funding

The National Institute for Health Research Programme Grants for Applied Research programme.

Altered Whole-Brain Structural Covariance of the Hippocampal Subfields in Subcortical Vascular Mild Cognitive Impairment and Amnestic Mild Cognitive Impairment Patients

The hippocampus plays important roles in memory processing. However, the hippocampus is not a homogeneous structure, which consists of several subfields. The hippocampal subfields are differently affected by many neurodegenerative diseases, especially mild cognitive impairment (MCI). Amnestic mild cognitive impairment (aMCI) and subcortical vascular mild cognitive impairment (svMCI) are the two subtypes of MCI. aMCI is characterized by episodic memory loss, and svMCI is characterized by extensive white matter hyperintensities and multiple lacunar infarctions on magnetic resonance imaging. The primary cognitive impairment in svMCI is executive function, attention, and semantic memory. Some variations or disconnections within specific large-scale brain networks have been observed in aMCI and svMCI patients. The aim of this study was to investigate abnormalities in structural covariance networks (SCNs) between hippocampal subfields and the whole cerebral cortex in aMCI and svMCI patients, and whether these abnormalities are different between the two groups. Automated segmentation of hippocampal subfields was performed with FreeSurfer 5.3, and we selected five hippocampal subfields as the seeds of SCN analysis: CA1, CA2/3, CA4/dentate gyrus (DG), subiculum, and presubiculum. SCNs were constructed based on these hippocampal subfield seeds for each group. Significant correlations between hippocampal subfields, fusiform gyrus (FFG), and entorhinal cortex (ERC) in gray matter volume were found in each group. We also compared the differences in the strength of structural covariance between any two groups. In the aMCI group, compared to the normal controls (NC) group, we observed an increased association between the left CA1/CA4/DG/subiculum and the left temporal pole. Additionally, the hippocampal subfields (bilateral CA1, left CA2/3) significantly covaried with the orbitofrontal cortex in the svMCI group compared to the NC group. In the aMCI group compared to the svMCI group, we observed decreased association between hippocampal subfields and the right FFG, while we also observed an increased association between the bilateral subiculum/presubiculum and bilateral ERC. These findings provide new evidence that there is altered whole-brain structural covariance of the hippocampal subfields in svMCI and aMCI patients and provide insights to the pathological mechanisms of different MCI subtypes.

'Developmental Delay' Reconsidered: The Critical Role of Age-Dependent, Co-variant Development

In memory of Annette Karmiloff-Smith . This paper reviews recent neurobiological research reporting structural co-variance and temporal dependencies in age-dependent gene expression, parameters of cortical maturation, long range connectivity and interaction of the biological network with the environment. This research suggests that age by size trajectories of brain structures relate to functional properties more than absolute sizes. In line with these findings, recent behavioral studies of typically developing children whose language development was delayed reported long term consequences of such delays. As for neurodevelopmental disorders, disrupted developmental timing and slow acquisitional pace are hallmarks of these populations. It is argued that these behavioral and neuro-biological results highlight the need to commit to a developmental model which will reflect the fact that temporal dependencies overseeing structural co-variance among developmental components are major regulatory factors of typical development of the brain/mind network. Consequently, the concept of 'developmental delay' in developmental theorizing needs to be reconsidered.

Revisiting subcortical brain volume correlates of autism in the ABIDE dataset: effects of age and sex

BACKGROUND

Autism spectrum disorders (ASD) are characterized by substantial clinical, etiological and neurobiological heterogeneity. Despite this heterogeneity, previous imaging studies have highlighted the role of specific cortical and subcortical structures in ASD and have forwarded the notion of an ASD specific neuroanatomy in which abnormalities in brain structures are present that can be used for diagnostic classification approaches.

METHOD

A large (N = 859, 6-27 years, IQ 70-130) multi-center structural magnetic resonance imaging dataset was examined to specifically test ASD diagnostic effects regarding (sub)cortical volumes.

RESULTS

Despite the large sample size, we found virtually no main effects of ASD diagnosis. Yet, several significant two- and three-way interaction effects of diagnosis by age by gender were found.

CONCLUSION

The neuroanatomy of ASD does not exist, but is highly age and gender dependent. Implications for approaches of stratification of ASD into more homogeneous subtypes are discussed.

Brain structure in autism: a voxel-based morphometry analysis of the Autism Brain Imaging Database Exchange (ABIDE)

Increased brain volume is a consistent finding in young children with autism spectrum disorders (ASD); however, the regional specificity and developmental course of abnormal brain structure are less clear. Small sample sizes, particularly among voxel-based morphometry (VBM) investigations, likely contribute to this difficulty. Recently established large-scale neuroimaging data repositories have helped clarify the neuroanatomy of neuropsychiatric disorders such as schizophrenia and may prove useful in ASD. Structural brain images from the Autism Brain Imaging Database Exchange (ABIDE), which contains over 1100 participants, were analyzing using DARTEL VBM to investigate total brain and tissue volumes, and regional brain structure abnormalities in ASD. Two, overlapping cohorts were analyzed; an 'All Subjects' cohort (n = 833) that included all individuals with usable MRI data, and a 'Matched Samples' cohort (n = 600) comprised of ASD and TD individuals matched, within each site, on age and sex. Total brain and grey matter volumes were enlarged by approximately 1-2 % in ASD; however, the effect reached statistical significance in only the All Subjects cohort. Within the All Subjects cohort, VBM analysis revealed enlargement of the left anterior superior temporal gyrus in ASD. No significant regional changes were detected in the Matched Samples cohort. There was a non-significant reduction in the correlation between IQ and TBV in ASD compared to TD. Brain structure abnormalities in ASD individuals age 6 and older consists of a subtle increase in total brain volume due to enlargement of grey matter with little evidence of regionally specific effects.

Neuroanatomical and neurofunctional markers of social cognition in autism spectrum disorder

Social impairments in autism spectrum disorder (ASD), a hallmark feature of its diagnosis, may underlie specific neural signatures that can aid in differentiating between those with and without ASD. To assess common and consistent patterns of differences in brain responses underlying social cognition in ASD, this study applied an activation likelihood estimation (ALE) meta-analysis to results from 50 neuroimaging studies of social cognition in children and adults with ASD. In addition, the group ALE clusters of activation obtained from this was used as a social brain mask to perform surface-based cortical morphometry (SBM) in an empirical structural MRI dataset collected from 55 ASD and 60 typically developing (TD) control participants. Overall, the ALE meta-analysis revealed consistent differences in activation in the posterior superior temporal sulcus at the temporoparietal junction, middle frontal gyrus, fusiform face area (FFA), inferior frontal gyrus (IFG), amygdala, insula, and cingulate cortex between ASD and TD individuals. SBM analysis showed alterations in the thickness, volume, and surface area in individuals with ASD in STS, insula, and FFA. Increased cortical thickness was found in individuals with ASD, the IFG. The results of this study provide functional and anatomical bases of social cognition abnormalities in ASD by identifying common signatures from a large pool of neuroimaging studies. These findings provide new insights into the quest for a neuroimaging-based marker for ASD. Hum Brain Mapp 37:3957-3978, 2016. © 2016 Wiley Periodicals, Inc.

A Study of the Correlation between VEP and Clinical Severity in Children with Autism Spectrum Disorder

Visual evoked potential (VEP) is a technique used to assess the brain's electrical response to visual stimuli. The aims of this study were to examine neural transmission within the visual pathway through VEP testing in preschool children with autism spectrum disorder (ASD) and compare it to age-matched controls, as well as search for a correlation between the VEP parameters and the symptoms of ASD. Participants were composed of ASD children (9 males) and typically developing children (8 males and 4 females), aged between 3 and 5 years. Checkerboards were chosen as the pattern-reversal VEP. The clinical severity of ASD was assessed using the Autism Treatment Evaluation Checklist (ATEC) and the Vineland Adaptive Behavior Scales 2nd edition (VABS-II). Our findings demonstrated that children with ASD had significantly longer N145 latency compared to the controls. A longer N145 latency correlated with a higher score of ATEC within the sensory/cognitive awareness subdomain. In addition, a slower N145 response was also associated with a lower VABS-II score within the socialization domain. The correlation between longer VEP latency and abnormal behaviors in children with ASD suggests a delayed neural communication within other neural circuits, apart from the visual pathway. These lines of evidence support the possibility of using VEP, along with clinical parameters, for the assessment of ASD severity.

Structural Covariance of Sensory Networks, the Cerebellum, and Amygdala in Autism Spectrum Disorder

Sensory dysfunction is a core symptom of autism spectrum disorder (ASD), and abnormalities with sensory responsivity and processing can be extremely debilitating to ASD patients and their families. However, relatively little is known about the underlying neuroanatomical and neurophysiological factors that lead to sensory abnormalities in ASD. Investigation into these aspects of ASD could lead to significant advancements in our general knowledge about ASD, as well as provide targets for treatment and inform diagnostic procedures. Thus, the current study aimed to measure the covariation of volumes of brain structures (i.e., structural magnetic resonance imaging) that may be involved in abnormal sensory processing, in order to infer connectivity of these brain regions. Specifically, we quantified the structural covariation of sensory-related cerebral cortical structures, in addition to the cerebellum and amygdala by computing partial correlations between the structural volumes of these structures. These analyses were performed in participants with ASD (n = 36), as well as typically developing peers (n = 32). Results showed decreased structural covariation between sensory-related cortical structures, especially between the left and right cerebral hemispheres, in participants with ASD. In contrast, these same participants presented with increased structural covariation of structures in the right cerebral hemisphere. Additionally, sensory-related cerebral structures exhibited decreased structural covariation with functionally identified cerebellar networks. Also, the left amygdala showed significantly increased structural covariation with cerebral structures related to visual processing. Taken together, these results may suggest several patterns of altered connectivity both within and between cerebral cortices and other brain structures that may be related to sensory processing.

Cerebellar anatomical alterations and attention to eyes in autism

The cerebellum is implicated in social cognition and is likely to be involved in the pathophysiology of autism spectrum disorder (ASD). The goal of our study was to explore cerebellar morphology in adults with ASD and its relationship to eye contact, as measured by fixation time allocated on the eye region using an eye-tracking device. Two-hundred ninety-four subjects with ASD and controls were included in our study and underwent a structural magnetic resonance imaging scan. Global segmentation and cortical parcellation of the cerebellum were performed. A sub-sample of 59 subjects underwent an eye tracking protocol in order to measure the fixation time allocated to the eye region. We did not observe any difference in global cerebellar volumes between ASD patients and controls; however, regional analyses found a decrease of the volume of the right anterior cerebellum in subjects with ASD compared to controls. There were significant correlations between fixation time on eyes and the volumes of the vermis and Crus I. Our results suggest that cerebellar morphology may be related to eye avoidance and reduced social attention. Eye tracking may be a promising neuro-anatomically based stratifying biomarker of ASD.

Gray matter abnormalities in pediatric autism spectrum disorder: a meta-analysis with signed differential mapping

The gray matter abnormalities revealed by magnetic resonance imaging are inconsistent, especially in pediatric individuals with autism spectrum disorder (ASD) (age < 18 years old), a phenomenon possibly related to the core pathophysiology of ASD. The purpose of our meta-analysis was to identify and map the specific gray matter abnormalities in pediatric ASD individuals thereby exploring the potential effects of clinical and demographic characteristics of these gray matter changes. A systematic search was conducted to identify voxel-based morphometry studies in pediatric individuals with ASD. The effect-size signed differential mapping method was used to quantitatively estimate the regional gray matter abnormalities in pediatric ASD individuals. Meta-regression was used to examine the associations among age, gender, intelligence quotient, symptom severity and gray matter changes. Fifteen studies including 364 pediatric individuals with ASD (male = 282, age = 10.3 ± 4.4 years) and 377 healthy controls (male = 289, age = 10.5 ± 4.2 years) were included. Pediatric ASD individuals showed significant gray matter increases in the right angular gyrus, left superior and middle frontal gyrus, left precuneus, left inferior occipital gyrus and right inferior temporal gyrus, most of which involving the default mode network, and decreases in the left cerebellum and left postcentral gyrus. The meta-regression analysis showed that the repetitive behavior scores of the Autism Diagnostic Interview-Revised were positively associated with increased gray matter volumes in the right angular gyrus. Increased rather than decreased gray matter volume, especially involving the angular gyrus and prefrontal cortex may be the core pathophysiology in the early course of ASD.

Neural processing of biological motion in autism: An investigation of brain activity and effective connectivity

The superior temporal sulcus (STS) forms a key region for social information processing and disruptions of its function have been associated with socio-communicative impairments characteristic of autism spectrum disorders (ASD). Task-based fMRI was applied in 15 adults with ASD and 15 matched typical-controls (TC) to explore differences in activity and effective connectivity of STS while discriminating either 'intact' versus 'scrambled' biological motion point light displays (explicit processing) or responding to a color-change while the 'intact' versus 'scrambled' nature of the stimulus was irrelevant for the task (implicit processing). STS responded stronger to 'intact' than 'scrambled' stimuli in both groups, indicating that the basic encoding of 'biological' versus 'non-biological' motion seems to be intact in ASD. Only in the TC-group however, explicit attention to the biological motion content induced an augmentation of STS-activity, which was not observed in the ASD-group. Overall, these findings suggest an inadequacy to recruit STS upon task demand in ASD, rather than a generalized alteration in STS neural processing. The importance of attention orienting for recruiting relevant neural resources was further underlined by the observation that connectivity between STS and medial prefrontal cortex (mPFC), a key region in attention regulation, effectively modulated STS-recruitment in the ASD-group.

Altered neurite morphology and cholinergic function of induced pluripotent stem cell-derived neurons from a patient with Kleefstra syndrome and autism

The aim of the present study was to establish an in vitro Kleefstra syndrome (KS) disease model using the human induced pluripotent stem cell (hiPSC) technology. Previously, an autism spectrum disorder (ASD) patient with Kleefstra syndrome (KS-ASD) carrying a deleterious premature termination codon mutation in the EHMT1 gene was identified. Patient specific hiPSCs generated from peripheral blood mononuclear cells of the KS-ASD patient were differentiated into post-mitotic cortical neurons. Lower levels of EHMT1 mRNA as well as protein expression were confirmed in these cells. Morphological analysis on neuronal cells differentiated from the KS-ASD patient-derived hiPSC clones showed significantly shorter neurites and reduced arborization compared to cells generated from healthy controls. Moreover, density of dendritic protrusions of neuronal cells derived from KS-ASD hiPSCs was lower than that of control cells. Synaptic connections and spontaneous neuronal activity measured by live cell calcium imaging could be detected after 5 weeks of differentiation, when KS-ASD cells exhibited higher sensitivity of calcium responses to acetylcholine stimulation indicating a lower nicotinic cholinergic tone at baseline condition in KS-ASD cells. In addition, gene expression profiling of differentiated neuronal cells from the KS-ASD patient revealed higher expression of proliferation-related genes and lower mRNA levels of genes involved in neuronal maturation and migration. Our data demonstrate anomalous neuronal morphology, functional activity and gene expression in KS-ASD patient-specific hiPSC-derived neuronal cultures, which offers an in vitro system that contributes to a better understanding of KS and potentially other neurodevelopmental disorders including ASD.

Graph theoretical approaches towards understanding differences in frontoparietal and default mode networks in Autism

Autism Spectrum Disorder is a complex developmental disorder affecting 1 in 68 children in the United States. While the prevalence may be on the rise, we currently lack a firm understanding of the etiology of the disease, and diagnosis is made purely on behavioral observation and informant report. As one method to improve our understanding of the disease, the current study took a systems-level approach by assessing the causal interactions among the frontoparietal and default mode networks using structural covariance of a large Autism dataset. Although preliminary, we report diffuse yet subtle changes throughout these networks when comparing age and sex matched controls to ASD patients.

The connectomes of males and females with autism spectrum disorder have significantly different white matter connectivity densities

Autism spectrum disorder (ASD) encompasses a set of neurodevelopmental conditions whose striking sex-related disparity (with an estimated male-to-female ratio of 4:1) remains unknown. Here we use magnetic resonance imaging (MRI) and diffusion weighted imaging (DWI) to identify the brain structure correlates of the sex-by-ASD diagnosis interaction in a carefully selected cohort of 110 ASD patients (55 females) and 83 typically-developing (TD) subjects (40 females). The interaction was found to be predicated primarily upon white matter connectivity density innervating, bilaterally, the lateral aspect of the temporal lobe, the temporo-parieto-occipital junction and the medial parietal lobe. By contrast, regional gray matter (GM) thickness and volume are not found to modulate this interaction significantly. When interpreted in the context of previous studies, our findings add considerable weight to three long-standing hypotheses according to which the sex disparity of ASD incidence is (A) due to WM connectivity rather than to GM differences, (B) modulated to a large extent by temporoparietal connectivity, and (C) accompanied by brain function differences driven by these effects. Our results contribute substantially to the task of unraveling the biological mechanisms giving rise to the sex disparity in ASD incidence, whose clinical implications are significant.

Anomalous gray matter structural networks in recent onset post-traumatic stress disorder

Alterations of the topological organization of abnormal regions or network-level structural aberrations are still poorly understood for post-traumatic stress disorder (PTSD). Herein, we investigated brain structural networks in recent-onset PTSD patients, all affected by the coalmine-flood disaster. Cortical networks were studied in recent onset PTSD patients (n = 15) and matched healthy controls (n = 25). Cortical networks were constructed by thresholding correlation matrices of 150 regions and quantified using graph theoretical approaches. Contributions of high-degree nodes, and regional and global network measures, including degree and betweenness, were studied. Compared with healthy controls, PTSD patients showed altered quantitative values in global network properties, characterized by shorter path length and higher clustering. Moreover, PTSD patients exhibited decreased connectivity in the right lingual gyrus, parahippocampal gyrus, left supramarginal gyrus, parahippocampal gyrus, bilateral superior and inferior frontal gyrus, superior frontal gyrus, and posterior cingulate gyrus. Nodal centrality decreased predominantly in the occipital regions (lingual gyrus) and default-mode regions, while increased correlations and centralities were observed in the medial temporal lobe and posterior cingulate cortex. PTSD-related networks exhibited a less efficient organization and regional connectivity. According to these findings, we conclude that regional connections involving fear-processing and re-experiential-processing cortex may play a role in maintaining or adapting to PTSD pathology.

Candidate Biomarkers in Children with Autism Spectrum Disorder: A Review of MRI Studies

Searching for effective biomarkers is one of the most challenging tasks in the research field of Autism Spectrum Disorder (ASD). Magnetic resonance imaging (MRI) provides a non-invasive and powerful tool for investigating changes in the structure, function, maturation, connectivity, and metabolism of the brain of children with ASD. Here, we review the more recent MRI studies in young children with ASD, aiming to provide candidate biomarkers for the diagnosis of childhood ASD. The review covers structural imaging methods, diffusion tensor imaging, resting-state functional MRI, and magnetic resonance spectroscopy. Future advances in neuroimaging techniques, as well as cross-disciplinary studies and large-scale collaborations will be needed for an integrated approach linking neuroimaging, genetics, and phenotypic data to allow the discovery of new, effective biomarkers.

Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls

Neuroimaging-based single subject prediction of brain disorders has gained increasing attention in recent years. Using a variety of neuroimaging modalities such as structural, functional and diffusion MRI, along with machine learning techniques, hundreds of studies have been carried out for accurate classification of patients with heterogeneous mental and neurodegenerative disorders such as schizophrenia and Alzheimer's disease. More than 500 studies have been published during the past quarter century on single subject prediction focused on a multiple brain disorders. In the first part of this study, we provide a survey of more than 200 reports in this field with a focus on schizophrenia, mild cognitive impairment (MCI), Alzheimer's disease (AD), depressive disorders, autism spectrum disease (ASD) and attention-deficit hyperactivity disorder (ADHD). Detailed information about those studies such as sample size, type and number of extracted features and reported accuracy are summarized and discussed. To our knowledge, this is by far the most comprehensive review of neuroimaging-based single subject prediction of brain disorders. In the second part, we present our opinion on major pitfalls of those studies from a machine learning point of view. Common biases are discussed and suggestions are provided. Moreover, emerging trends such as decentralized data sharing, multimodal brain imaging, differential diagnosis, disease subtype classification and deep learning are also discussed. Based on this survey, there is extensive evidence showing the great potential of neuroimaging data for single subject prediction of various disorders. However, the main bottleneck of this exciting field is still the limited sample size, which could be potentially addressed by modern data sharing models such as the ones discussed in this paper. Emerging big data technologies and advanced data-intensive machine learning methodologies such as deep learning have coincided with an increasing need for accurate, robust and generalizable single subject prediction of brain disorders during an exciting time. In this report, we survey the past and offer some opinions regarding the road ahead.

Multivariate characterization of white matter heterogeneity in autism spectrum disorder

The complexity and heterogeneity of neuroimaging findings in individuals with autism spectrum disorder has suggested that many of the underlying alterations are subtle and involve many brain regions and networks. The ability to account for multivariate brain features and identify neuroimaging measures that can be used to characterize individual variation have thus become increasingly important for interpreting and understanding the neurobiological mechanisms of autism. In the present study, we utilize the Mahalanobis distance, a multidimensional counterpart of the Euclidean distance, as an informative index to characterize individual brain variation and deviation in autism. Longitudinal diffusion tensor imaging data from 149 participants (92 diagnosed with autism spectrum disorder and 57 typically developing controls) between 3.1 and 36.83 years of age were acquired over a roughly 10-year period and used to construct the Mahalanobis distance from regional measures of white matter microstructure. Mahalanobis distances were significantly greater and more variable in the autistic individuals as compared to control participants, demonstrating increased atypicalities and variation in the group of individuals diagnosed with autism spectrum disorder. Distributions of multivariate measures were also found to provide greater discrimination and more sensitive delineation between autistic and typically developing individuals than conventional univariate measures, while also being significantly associated with observed traits of the autism group. These results help substantiate autism as a truly heterogeneous neurodevelopmental disorder, while also suggesting that collectively considering neuroimaging measures from multiple brain regions provides improved insight into the diversity of brain measures in autism that is not observed when considering the same regions separately. Distinguishing multidimensional brain relationships may thus be informative for identifying neuroimaging-based phenotypes, as well as help elucidate underlying neural mechanisms of brain variation in autism spectrum disorders.

Neuroanatomy and Neuropathology of Autism Spectrum Disorder in Humans

Autism spectrum disorder (ASD) is a lifelong heterogeneous neurodevelopmental condition that is associated with differences in brain anatomy and connectivity. Yet, the molecular and cellular mechanisms that underpin the atypical developmental of the brain in ASD remain poorly understood. Here, we review the findings of in vivo neuroimaging studies examining the time course of atypical brain development in ASD and relate the different neurodevelopmental stages that are atypical in ASD to the known neurobiological mechanisms that drive the maturation of the typically developing brain. In particular, we focus on the notion of 'early brain overgrowth' in ASD, which may lead to differences in the formation of the brain's micro- and macro-circuitry. Moreover, we attempt to link the in vivo reports describing differences in brain anatomy and connectivity on the macroscopic level to the increasing number of post-mortem studies examining the neural architecture of the brain in ASD on the microscopic level. In addition, we discuss future directions and outstanding questions in this particular field of research and highlight the need for establishing the link between micro- and macro-pathology in the same set of individuals with ASD based on advances in genetic, molecular and imaging techniques. In combination, these may proof to be invaluable for patient stratification and the development of novel pharmacotherapies in the future.

Decreased Left Caudate Volume Is Associated with Increased Severity of Autistic-Like Symptoms in a Cohort of ADHD Patients and Their Unaffected Siblings

Autism spectrum disorder (ASD) symptoms frequently occur in individuals with attention-deficit/hyperactivity disorder (ADHD). While there is evidence that both ADHD and ASD have differential structural brain correlates, knowledge of the structural brain profile of individuals with ADHD with raised ASD symptoms is limited. The presence of ASD-like symptoms was measured by the Children's Social Behavior Questionnaire (CSBQ) in a sample of typically developing controls (n = 154), participants with ADHD (n = 239), and their unaffected siblings (n = 144) between the ages of 8 and 29. Structural magnetic resonance imaging (MRI) correlates of ASD ratings were analysed by studying the relationship between ASD ratings and grey matter volumes using mixed effects models which controlled for ADHD symptom count and total brain volume. ASD ratings were significantly elevated in participants with ADHD relative to controls and unaffected siblings. For the entire group (participants with ADHD, unaffected siblings and TD controls), mixed effect models revealed that the left caudate nucleus volume was negatively correlated with ASD ratings (t = 2.83; P = 0.005). The current findings are consistent with the role of the caudate nucleus in executive function, including the selection of goals based on the evaluation of action outcomes and the use of social reward to update reward representations. There is a specific volumetric profile associated with subclinical ASD-like symptoms in participants with ADHD, unaffected siblings and controls with the caudate nucleus and globus pallidus being of critical importance in predicting the level of ASD-like symptoms in all three groups.

Brain gray matter alterations and associated demographic profiles in adults with autism spectrum disorder: A meta-analysis of voxel-based morphometry studies

BACKGROUND

There is increasing evidence that children with autism spectrum disorder are accompanied by specific anatomical alterations. However, the anatomical abnormalities in adults with autism spectrum disorder are poorly understood. This study was aimed to identify the neuroanatomical substrates underlying the pathophysiology of adults with autism spectrum disorder. We also investigated the relationship between neuroanatomical alterations and clinical and demographic characteristics.

METHODS

A total of 13 datasets were enrolled, of which 12 studies compared whole-brain differences of 382 adult patients with autism and 393 healthy control subjects. We conducted a meta-analysis to quantitatively estimate regional gray matter volume abnormalities in individuals with autism using the effect-size signed differential mapping.

RESULTS

The voxel-wise meta-analysis revealed that relative to controls, adults with autism spectrum disorder had significantly increased gray matter volume in the middle temporal gyrus, superior temporal gyrus, postcentral gyrus and parahippocampal gyrus, and reduced gray matter volume in the anterior cingulate cortex and cerebellum. Variations in gray matter volume were significantly associated with the mean age and mean total IQ score of the patients, as well as with the percentage of male patients with autism.

CONCLUSION

These findings confirmed that the neuroanatomical alterations in the fronto-temporal cortices, limbic system and cerebellum in adult individuals with autism were different from the children and young adolescent's autism. The effects of demographic characteristics on the brain morphological changes allow us to further clarify the neurobiological mechanisms and developmental trajectory in adult population with autism spectrum disorder.

Relationship Between Cortical Gyrification, White Matter Connectivity, and Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition, which is accompanied by differences in gray matter neuroanatomy and white matter connectivity. However, it is unknown whether these differences are linked or reflect independent aetiologies. Using a multimodal neuroimaging approach, we therefore examined 51 male adults with ASD and 48 neurotypical controls to investigate the relationship between gray matter local gyrification (lGI) and white matter diffusivity in associated fiber tracts. First, ASD individuals had a significant increase in gyrification around the left pre- and post-central gyrus. Second, white matter fiber tracts originating and/or terminating in the cluster of increased lGI had a significant increase in axial diffusivity. This increase in diffusivity was predominantly observed in tracts in close proximity to the cortical sheet. Last, we demonstrate that the increase in lGI was significantly correlated with increased diffusivity of short tracts. This relationship was not significantly modulated by a main effect of group (i.e., ASD), which was more closely associated with gray matter gyrification than white matter diffusivity. Our findings suggest that differences in gray matter neuroanatomy and white matter connectivity are closely linked, and may reflect common rather than distinct aetiological pathways.

Frontal networks in adults with autism spectrum disorder

It has been postulated that autism spectrum disorder is underpinned by an 'atypical connectivity' involving higher-order association brain regions. To test this hypothesis in a large cohort of adults with autism spectrum disorder we compared the white matter networks of 61 adult males with autism spectrum disorder and 61 neurotypical controls, using two complementary approaches to diffusion tensor magnetic resonance imaging. First, we applied tract-based spatial statistics, a 'whole brain' non-hypothesis driven method, to identify differences in white matter networks in adults with autism spectrum disorder. Following this we used a tract-specific analysis, based on tractography, to carry out a more detailed analysis of individual tracts identified by tract-based spatial statistics. Finally, within the autism spectrum disorder group, we studied the relationship between diffusion measures and autistic symptom severity. Tract-based spatial statistics revealed that autism spectrum disorder was associated with significantly reduced fractional anisotropy in regions that included frontal lobe pathways. Tractography analysis of these specific pathways showed increased mean and perpendicular diffusivity, and reduced number of streamlines in the anterior and long segments of the arcuate fasciculus, cingulum and uncinate--predominantly in the left hemisphere. Abnormalities were also evident in the anterior portions of the corpus callosum connecting left and right frontal lobes. The degree of microstructural alteration of the arcuate and uncinate fasciculi was associated with severity of symptoms in language and social reciprocity in childhood. Our results indicated that autism spectrum disorder is a developmental condition associated with abnormal connectivity of the frontal lobes. Furthermore our findings showed that male adults with autism spectrum disorder have regional differences in brain anatomy, which correlate with specific aspects of autistic symptoms. Overall these results suggest that autism spectrum disorder is a condition linked to aberrant developmental trajectories of the frontal networks that persist in adult life.

Persistence of megalencephaly in a subgroup of young boys with autism spectrum disorder

A recurring finding in autism spectrum disorder research is that head and brain growth is disproportionate to body growth in early childhood. Nordahl et al. (2011) demonstrated that this occurs in approximately 15% of boys with autism. While the literature suggests that brain growth normalizes at older ages, this has never been evaluated in a longitudinal study. The current study evaluated head circumference and total cerebral volume in 129 male children with autism and 49 age-matched, typically developing controls. We determined whether 3-year-old boys with brain size disproportionate to height (which we call disproportionate megalencephaly) demonstrated an abnormal trajectory of head growth from birth and whether they maintained an enlarged brain at 5 years of age. Findings were based on longitudinal, structural MRI data collected around 3, 4, and 5 years of age and head circumference data from medical records. At 3 years of age, 19 boys with autism had enlarged brains while 110 had brain sizes in the normal range. Boys with disproportionate megalencephaly had greater total cerebral, gray matter, and white matter volumes from 3-5 years compared to boys with autism and normal sized brains and typically developing boys, but no differences in body size. While head circumference did not differ between groups at birth, it was significantly greater in the disproportionate megalencephaly group by around 2 years. These data suggest that there is a subgroup of boys with autism who have brains disproportionate to body size and that this continues until at least 5 years of age. Autism Res 2016, 9: 1169-1182. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Studying Autism Spectrum Disorder with Structural and Diffusion Magnetic Resonance Imaging: A Survey

Magnetic resonance imaging (MRI) modalities have emerged as powerful means that facilitate non-invasive clinical diagnostics of various diseases and abnormalities since their inception in the 1980s. Multiple MRI modalities, such as different types of the sMRI and DTI, have been employed to investigate facets of ASD in order to better understand this complex syndrome. This paper reviews recent applications of structural magnetic resonance imaging (sMRI) and diffusion tensor imaging (DTI), to study autism spectrum disorder (ASD). Main reported findings are sometimes contradictory due to different age ranges, hardware protocols, population types, numbers of participants, and image analysis parameters. The primary anatomical structures, such as amygdalae, cerebrum, and cerebellum, associated with clinical-pathological correlates of ASD are highlighted through successive life stages, from infancy to adulthood. This survey demonstrates the absence of consistent pathology in the brains of autistic children and lack of research investigations in patients under 2 years of age in the literature. The known publications also emphasize advances in data acquisition and analysis, as well as significance of multimodal approaches that combine resting-state, task-evoked, and sMRI measures. Initial results obtained with the sMRI and DTI show good promise toward the early and non-invasive ASD diagnostics.

Neuroanatomical variation in autism spectrum disorder: A comprehensive review

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by impairments in socialization, communication, and behavior. Many investigators have described the anatomical abnormalities in autistic brains, in an attempt to correlate them with the manifestations of ASD. Herein, we reviewed all the available literature about the neuroanatomical findings in ASD available via "PubMed" and "Google Scholar." References found in review articles were also searched manually. There was substantial discrepancy throughout the literature regarding the reported presence and significance of neuroanatomical findings in ASD, and this is thoroughly discussed in the present review.

Similarly Expanded Bilateral Temporal Lobe Volumes in Female and Male Children With Autism Spectrum Disorder

BACKGROUND

Autism spectrum disorder (ASD) is more prevalent in male than female individuals. Very few studies have examined sex modulations of brain anatomical differences between individuals with ASD and typically developing (TD) individuals, especially in children. The current study aimed to identify sex-dependent and/or sex-independent neuroanatomical mechanisms underlying ASD.

METHODS

Magnetic resonance imaging data were acquired from the Autism Brain Imaging Data Exchange. A 2 (diagnosis) × 2 (sex) design was used. Subjects whose ages were between 6 and 20 years were included for analysis, with matched full-scale IQ between groups for each dataset. The resulting effective numbers of subjects were 36 female subjects with ASD, 54 TD female subjects, 182 male subjects with ASD, and 172 TD male subjects. Twenty independent gray matter (GM) and 20 white matter (WM) volume sources were estimated using source-based morphometry.

RESULTS

Among all the independent GM and WM sources, none of them showed a significant diagnosis by sex interaction. One GM source of the bilateral inferior and middle temporal lobe showed a significantly larger volume in ASD than TD individuals and in male than in female subjects. This diagnosis effect was age sensitive and was present only in participants between 8 and 14 years of age.

CONCLUSIONS

Only sex-independent, large-scale neuroanatomical alterations could be observed in children with ASD. The directionality of bilateral temporal GM alterations was in line with the prediction of the extreme male brain hypothesis, supporting the view that similar neurobiological mechanisms may drive sexual dimorphism and the onset of ASD.

Independence of Hot and Cold Executive Function Deficits in High-Functioning Adults with Autism Spectrum Disorder

Individuals with autistic spectrum disorder (ASD) display diverse deficits in social, cognitive and behavioral functioning. To date, there has been mixed findings on the profile of executive function deficits for high-functioning adults (IQ > 70) with ASD. A conceptual distinction is commonly made between "cold" and "hot" executive functions. Cold executive functions refer to mechanistic higher-order cognitive operations (e.g., working memory), whereas hot executive functions entail cognitive abilities supported by emotional awareness and social perception (e.g., social cognition). This study aimed to determine the independence of deficits in hot and cold executive functions for high-functioning adults with ASD. Forty-two adults with ASD (64% male, aged 18-66 years) and 40 age and gender matched controls were administered The Awareness of Social Inference Test (TASIT; emotion recognition and social inference), Letter Number Sequencing (working memory) and Hayling Sentence Completion Test (response initiation and suppression). Between-group analyses identified that the ASD group performed significantly worse than matched controls on all measures of cold and hot executive functions (d = 0.54 - 1.5). Hierarchical multiple regression analyses revealed that the ASD sample performed more poorly on emotion recognition and social inference tasks than matched controls after controlling for cold executive functions and employment status. The findings also indicated that the ability to recognize emotions and make social inferences was supported by working memory and response initiation and suppression processes. Overall, this study supports the distinction between hot and cold executive function impairments for adults with ASD. Moreover, it advances understanding of higher-order impairments underlying social interaction difficulties for this population which, in turn, may assist with diagnosis and inform intervention programs.

Diagnosis of Autism Spectrum Disorders Using Temporally Distinct Resting-State Functional Connectivity Networks

INTRODUCTION

Resting-state functional magnetic resonance imaging (R-fMRI) is dynamic in nature as neural activities constantly change over the time and are dominated by repeating brief activations and deactivations involving many brain regions. Each region participates in multiple brain functions and is part of various functionally distinct but spatially overlapping networks. Functional connectivity computed as correlations over the entire time series always overlooks interregion interactions that often occur repeatedly and dynamically in time, limiting its application to disease diagnosis.

AIMS

We develop a novel framework that uses short-time activation patterns of brain connectivity to better detect subtle disease-induced disruptions of brain connectivity. A clustering algorithm is first used to temporally decompose R-fMRI time series into distinct clusters with similar spatial distribution of neural activity based on the assumption that functionally distinct networks should be largely temporally distinct as brain states do not simultaneously coexist in general. A Pearson correlation-based functional connectivity network is then constructed for each cluster to allow for better exploration of spatiotemporal dynamics of individual neural activity. To reduce significant intersubject variability and to remove possible spurious connections, we use a group-constrained sparse regression model to construct a backbone sparse network for each cluster and use it to weight the corresponding Pearson correlation network.

RESULTS

The proposed method outperforms the conventional static, temporally dependent fully connected correlation-based networks by at least 7% on a publicly available autism dataset. We were able to reproduce similar results using data from other centers.

CONCLUSIONS

By combining the advantages of temporal independence and group-constrained sparse regression, our method improves autism diagnosis.

Age-associated changes in rich-club organisation in autistic and neurotypical human brains

Macroscopic structural networks in the human brain have a rich-club architecture comprising both highly inter-connected central regions and sparsely connected peripheral regions. Recent studies show that disruption of this functionally efficient organisation is associated with several psychiatric disorders. However, despite increasing attention to this network property, whether age-associated changes in rich-club organisation occur during human adolescence remains unclear. Here, analysing a publicly shared diffusion tensor imaging dataset, we found that, during adolescence, brains of typically developing (TD) individuals showed increases in rich-club organisation and inferred network functionality, whereas individuals with autism spectrum disorders (ASD) did not. These differences between TD and ASD groups were statistically significant for both structural and functional properties. Moreover, this typical age-related changes in rich-club organisation were characterised by progressive involvement of the right anterior insula. In contrast, in ASD individuals, did not show typical increases in grey matter volume, and this relative anatomical immaturity was correlated with the severity of ASD social symptoms. These results provide evidence that rich-club architecture is one of the bases of functionally efficient brain networks underpinning complex cognitive functions in adult human brains. Furthermore, our findings suggest that immature rich-club organisation might be associated with some neurodevelopmental disorders.

Cerebro-cerebellar Resting-State Functional Connectivity in Children and Adolescents with Autism Spectrum Disorder

BACKGROUND

The cerebellum plays important roles in sensori-motor and supramodal cognitive functions. Cellular, volumetric, and functional abnormalities of the cerebellum have been found in autism spectrum disorders (ASD), but no comprehensive investigation of cerebro-cerebellar connectivity in ASD is available.

METHODS

We used resting-state functional connectivity magnetic resonance imaging in 56 children and adolescents (28 subjects with ASD, 28 typically developing subjects) 8-17 years old. Partial and total correlation analyses were performed for unilateral regions of interest (ROIs), distinguished in two broad domains as sensori-motor (premotor/primary motor, somatosensory, superior temporal, and occipital) and supramodal (prefrontal, posterior parietal, and inferior and middle temporal).

RESULTS

There were three main findings: 1) Total correlation analyses showed predominant cerebro-cerebellar functional overconnectivity in the ASD group; 2) partial correlation analyses that emphasized domain specificity (sensori-motor vs. supramodal) indicated a pattern of robustly increased connectivity in the ASD group (compared with the typically developing group) for sensori-motor ROIs but predominantly reduced connectivity for supramodal ROIs; and 3) this atypical pattern of connectivity was supported by significantly increased noncanonical connections (between sensori-motor cerebral and supramodal cerebellar ROIs and vice versa) in the ASD group.

CONCLUSIONS

Our findings indicate that sensori-motor intrinsic functional connectivity is atypically increased in ASD, at the expense of connectivity supporting cerebellar participation in supramodal cognition.

Increased prefrontal and parietal cortical thickness does not correlate with anhedonia in patients with untreated first-episode major depressive disorders

Cerebral morphological abnormalities in major depressive disorder (MDD) may be modulated by antidepressant treatment and course of illness in chronic medicated patients. The present study examined cortical thickness in patients with untreated first-episode MDD to elucidate the early pathophysiology of this illness. Here, we examined cortical thickness in patients with first-episode MDD (N=27) and healthy controls (N=27) using an automated surface-based method (in FreeSurfer). By assessing the correlation between caudate volume and cortical thickness at each vertex on the cortical surface, a caudate-cortical network was obtained for each group. Subsequent analysis was performed to assess the effect of anhedonia by the Temporal Experience of Pleasure Scale. We observed increased cortical thickness at the right orbital frontal cortex and the left inferior parietal gyrus in MDD patients compared with healthy controls. Furthermore, morphometric correlational analysis using cortical thickness measurement revealed increased caudate-cortical connectivity in the bilateral superior parietal gyrus in MDD patients. All changes were not related to anhedonia. These preliminary findings may reflect disorder manifestation close to illness onset and may provide insight into the early neurobiology of MDD.

[Formula: see text]Current knowledge on motor disorders in children with autism spectrum disorder (ASD)

Motor symptomatology in autism is currently poorly understood, and still not included in the autism spectrum disorder (ASD) diagnostic criteria, although some studies suggest the presence of motor disturbances in this syndrome. We provide here a literature review on early motor symptoms in autism, focusing on studies on psychomotor issues (tone, postural control, manual dexterity, handedness, praxis). The approach adopted in research to study altered motor behaviors is generally global and there is no detailed semiology of the motor or neuromotor disorders observed in people with ASD. This global approach does not enable understanding of the neuro-developmental mechanisms involved in ASD. Identification of clinical neuro-psychomotor profiles in reference to a standard would help to better understand the origin and the nature of the disorders encountered in ASD, and would thus give new directions for treatment.

Cognitive set shifting deficits and their relationship to repetitive behaviors in autism spectrum disorder

The neurocognitive impairments associated with restricted and repetitive behaviors (RRBs) in autism spectrum disorder (ASD) are not yet clear. Prior studies indicate that individuals with ASD show reduced cognitive flexibility, which could reflect difficulty shifting from a previously learned response pattern or a failure to maintain a new response set. We examined different error types on a test of set-shifting completed by 60 individuals with ASD and 55 age- and nonverbal IQ-matched controls. Individuals with ASD were able to initially shift sets, but they exhibited difficulty maintaining new response sets. Difficulty with set maintenance was related to increased severity of RRBs. General difficulty maintaining new response sets and a heightened tendency to revert to old preferences may contribute to RRBs.

The emerging picture of autism spectrum disorder: genetics and pathology

Autism spectrum disorder (ASD) is defined by impaired social interaction and communication accompanied by stereotyped behaviors and restricted interests. Although ASD is common, its genetic and clinical features are highly heterogeneous. A number of recent breakthroughs have dramatically advanced our understanding of ASD from the standpoint of human genetics and neuropathology. These studies highlight the period of fetal development and the processes of chromatin structure, synaptic function, and neuron-glial signaling. The initial efforts to systematically integrate findings of multiple levels of genomic data and studies of mouse models have yielded new clues regarding ASD pathophysiology. This early work points to an emerging convergence of disease mechanisms in this complex and etiologically heterogeneous disorder.

EEG biofeedback for autism spectrum disorder: a commentary on Kouijzer et al. (2013)

Research conducted by Kouijzer et al. (Appl Psychophysiol Biofeedback 38(1):17-28, 2013) compared the effects of skin conductance biofeedback and EEG-biofeedback on patients with autistic spectrum disorders to determine their relative efficacy. While they found a difference between treatment and control groups, there was no significant difference on many variables between the two treatment groups. From this, the increase in symptom alleviation from autistic spectrum disorder was attributed to non-specific factors surrounding the study. We now offer alternative explanations for their findings and propose different options for future studies. We hypothesize that the location and type of neurofeedback used adversely impacted the findings. We speculate that had they used a form of EEG-biofeedback that can combat deficiencies in connectivity and also trained the areas of the brain most affected by autism, there may have then been a significant difference between the effectiveness of EEG-biofeedback versus skin conductance biofeedback.

MRI Surface-Based Brain Morphometry in Egyptian Autistic and Typically Developing Children

OBJECTIVES

The verbal abilities of autistic children differ from those of typically developing ones and they also differ among autistic children themselves. Neuroanatomical changes and an abnormal organization of functional networks are expected to accompany such a neurodevelopmental disorder. The aim of this study was to delineate the brain neuroanatomical changes in Egyptian children with autism and to compare them with previous studies in order to add more insight into the global brain imaging deviations linked to autism.

PATIENTS AND METHODS

Twenty-five autistic children and 25 typically developing children underwent MRI. Further analysis was performed using surface-based morphometry to obtain cortical thickness, brain volume, and cortical complexity.

RESULTS

MRI analysis results revealed significantly greater cortical thickness, cortical complexity, and gray matter volume in the autistic as compared to the control group. On the other hand, the white matter volume was significantly smaller.

CONCLUSION

These findings generally align with findings in previous studies, except for occasional differences.

Modeling a model: Mouse genetics, 22q11.2 Deletion Syndrome, and disorders of cortical circuit development

Understanding the developmental etiology of autistic spectrum disorders, attention deficit/hyperactivity disorder and schizophrenia remains a major challenge for establishing new diagnostic and therapeutic approaches to these common, difficult-to-treat diseases that compromise neural circuits in the cerebral cortex. One aspect of this challenge is the breadth and overlap of ASD, ADHD, and SCZ deficits; another is the complexity of mutations associated with each, and a third is the difficulty of analyzing disrupted development in at-risk or affected human fetuses. The identification of distinct genetic syndromes that include behavioral deficits similar to those in ASD, ADHC and SCZ provides a critical starting point for meeting this challenge. We summarize clinical and behavioral impairments in children and adults with one such genetic syndrome, the 22q11.2 Deletion Syndrome, routinely called 22q11DS, caused by micro-deletions of between 1.5 and 3.0 MB on human chromosome 22. Among many syndromic features, including cardiovascular and craniofacial anomalies, 22q11DS patients have a high incidence of brain structural, functional, and behavioral deficits that reflect cerebral cortical dysfunction and fall within the spectrum that defines ASD, ADHD, and SCZ. We show that developmental pathogenesis underlying this apparent genetic "model" syndrome in patients can be defined and analyzed mechanistically using genomically accurate mouse models of the deletion that causes 22q11DS. We conclude that "modeling a model", in this case 22q11DS as a model for idiopathic ASD, ADHD and SCZ, as well as other behavioral disorders like anxiety frequently seen in 22q11DS patients, in genetically engineered mice provides a foundation for understanding the causes and improving diagnosis and therapy for these disorders of cortical circuit development.