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Postmortem studies have revealed increased density of excitatory synapses in the brains of individuals with autism spectrum disorder (ASD), with a putative link to aberrant mTOR-dependent synaptic pruning. ASD is also characterized by atypical macroscale functional connectivity as measured with resting-state fMRI (rsfMRI). These observations raise the question of whether excess of synapses causes aberrant functional connectivity in ASD. Using rsfMRI, electrophysiology and in silico modelling in Tsc2 haploinsufficient mice, we show that mTOR-dependent increased spine density is associated with ASD -like stereotypies and cortico-striatal hyperconnectivity. These deficits are completely rescued by pharmacological inhibition of mTOR. Notably, we further demonstrate that children with idiopathic ASD exhibit analogous cortical-striatal hyperconnectivity, and document that this connectivity fingerprint is enriched for ASD-dysregulated genes interacting with mTOR or Tsc2. Finally, we show that the identified transcriptomic signature is predominantly expressed in a subset of children with autism, thereby defining a segregable autism subtype. Our findings causally link mTOR-related synaptic pathology to large-scale network aberrations, revealing a unifying multi-scale framework that mechanistically reconciles developmental synaptopathy and functional hyperconnectivity in autism., Autism spectrum disorder (ASD) is characterised by synaptic surplus and atypical functional connectivity. Here, the authors show that synaptic pathology in Tsc2 haploinsufficient mice is associated with autism-like behavior and cortico-striatal hyperconnectivity, and that analogous functional hyperconnectivity signatures can be linked to mTOR-pathway dysfunction in subgroups of children with idiopathic ASD.

Understanding heterogeneity is an important goal on the path to precision medicine for autism spectrum disorders (ASD). We examined how cortical thickness (CT) in ASD can be parameterized as an individualized metric of atypicality relative to typically-developing (TD) age-related norms. Across a large sample (n = 870 per group) and wide age range (5–40 years), we applied normative modelling resulting in individualized whole-brain maps of age-related CT atypicality in ASD and isolating a small subgroup with highly age-atypical CT. Age-normed CT scores also highlights on-average differentiation, and associations with behavioural symptomatology that is separate from insights gleaned from traditional case-control approaches. This work showcases an individualized approach for understanding ASD heterogeneity that could potentially further prioritize work on a subset of individuals with cortical pathophysiology represented in age-related CT atypicality. Only a small subset of ASD individuals are actually highly atypical relative to age-norms. driving small on-average case-control differences., Richard Bethlehem et al. identify a subgroup of autism spectrum disorders (ASD) individuals with highly age-atypical cortical thickness using a normative modelling approach across a large cohort. This work highlights the importance of individualized approaches to gain insight into ASD heterogeneity.

Autism is a diagnostic label based on behavior. While the diagnostic criteria attempt to maximize clinical consensus, it also masks a wide degree of heterogeneity between and within individuals at multiple levels of analysis. Understanding this multi-level heterogeneity is of high clinical and translational importance. Here we present organizing principles to frame research examining multi-level heterogeneity in autism. Theoretical concepts such as ‘spectrum’ or ‘autisms’ reflect non-mutually exclusive explanations regarding continuous/dimensional or categorical/qualitative variation between and within individuals. However, common practices of small sample size studies and case–control models are suboptimal for tackling heterogeneity. Big data are an important ingredient for furthering our understanding of heterogeneity in autism. In addition to being ‘feature-rich’, big data should be both ‘broad’ (i.e., large sample size) and ‘deep’ (i.e., multiple levels of data collected on the same individuals). These characteristics increase the likelihood that the study results are more generalizable and facilitate evaluation of the utility of different models of heterogeneity. A model’s utility can be measured by its ability to explain clinically or mechanistically important phenomena, and also by explaining how variability manifests across different levels of analysis. The directionality for explaining variability across levels can be bottom-up or top-down, and should include the importance of development for characterizing changes within individuals. While progress can be made with ‘supervised’ models built upon a priori or theoretically predicted distinctions or dimensions of importance, it will become increasingly important to complement such work with unsupervised data-driven discoveries that leverage unknown and multivariate distinctions within big data. A better understanding of how to model heterogeneity between autistic people will facilitate progress towards precision medicine for symptoms that cause suffering, and person-centered support. 24 10 1435 1450

Social-communication (SC) and restricted repetitive behaviors (RRB) are autism diagnostic symptom domains. SC and RRB severity can markedly differ within and between individuals and may be underpinned by different neural circuitry and genetic mechanisms. Modeling SC-RRB balance could help identify how neural circuitry and genetic mechanisms map onto such phenotypic heterogeneity. Here, we developed a phenotypic stratification model that makes highly accurate (97–99%) out-of-sample SC = RRB, SC > RRB, and RRB > SC subtype predictions. Applying this model to resting state fMRI data from the EU-AIMS LEAP dataset (n = 509), we find that while the phenotypic subtypes share many commonalities in terms of intrinsic functional connectivity, they also show replicable differences within some networks compared to a typically-developing group (TD). Specifically, the somatomotor network is hypoconnected with perisylvian circuitry in SC > RRB and visual association circuitry in SC = RRB. The SC = RRB subtype show hyperconnectivity between medial motor and anterior salience circuitry. Genes that are highly expressed within these networks show a differential enrichment pattern with known autism-associated genes, indicating that such circuits are affected by differing autism-associated genomic mechanisms. These results suggest that SC-RRB imbalance subtypes share many commonalities, but also express subtle differences in functional neural circuitry and the genomic underpinnings behind such circuitry., Natasha Bertelsen et al. develop a computational model to categorize patients with autism spectrum disorder (ASD) into distinct subgroups, based on social-communicative or restricted repetitive behaviors. By integrating publicly available neuroimaging and genetic data, they report neural and molecular signatures in two of these subgroups, altogether highlighting subtle differences in neural circuitry and genomic networks that could underlie phenotypic differences among ASD patients.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that is accompanied by neurodevelopmental differences in regional cortical volume (CV), and a potential layer-specific pathology. Conventional measures of CV, however, do not indicate how volume is distributed across cortical layers. In a sample of 92 typically developing (TD) controls and 92 adult individuals with ASD (aged 18–52 years), we examined volumetric gradients by quantifying the degree to which CV is weighted from the pial to the white surface of the brain. Overall, the spatial distribution of Frustum Surface Ratio (FSR) followed the gyral and sulcal pattern of the cortex and approximated a bimodal Gaussian distribution caused by a linear mixture of vertices on gyri and sulci. Measures of FSR were highly correlated with vertex-wise estimates of mean curvature, sulcal depth, and pial surface area, although none of these features explained more than 76% variability in FSR on their own. Moreover, in ASD, we observed a pattern of predominant increases in the degree of FSR relative to TD controls, with an atypical neurodevelopmental trajectory. Our findings suggest a more outward-weighted gradient of CV in ASD, which may indicate a larger contribution of supragranular layers to regional differences in CV.

Excitation-inhibition (E:I) imbalance is theorized as an important pathophysiological mechanism in autism. Autism affects males more frequently than females and sex-related mechanisms (e.g., X-linked genes, androgen hormones) can influence E:I balance. This suggests that E:I imbalance may affect autism differently in males versus females. With a combination of in-silico modeling and in-vivo chemogenetic manipulations in mice, we first show that a time-series metric estimated from fMRI BOLD signal, the Hurst exponent (H), can be an index for underlying change in the synaptic E:I ratio. In autism we find that H is reduced, indicating increased excitation, in the medial prefrontal cortex (MPFC) of autistic males but not females. Increasingly intact MPFC H is also associated with heightened ability to behaviorally camouflage social-communicative difficulties, but only in autistic females. This work suggests that H in BOLD can index synaptic E:I ratio and that E:I imbalance affects autistic males and females differently.

BACKGROUND: Interventions that promote mindfulness consistently show salutary effects on cognition and emotional wellbeing in adults, and more recently, in children and adolescents. However, we lack understanding of the neurobiological mechanisms underlying mindfulness in youth that should allow for more judicious application of these interventions in clinical and educational settings. METHODS: Using multi-echo multi-band fMRI, we examined dynamic (i.e., time-varying) and conventional static resting-state connectivity between core neurocognitive networks (i.e., salience/emotion, default mode, central executive) in 42 children and adolescents (ages 6-17). RESULTS: We found that trait mindfulness in youth relates to dynamic but not static resting-state connectivity. Specifically, more mindful youth transitioned more between brain states over the course of the scan, spent overall less time in a certain connectivity state, and showed a state-specific reduction in connectivity between salience/emotion and central executive networks. The number of state transitions mediated the link between higher mindfulness and lower anxiety, providing new insights into potential neural mechanisms underlying benefits of mindfulness on psychological health in youth. CONCLUSIONS: Our results provide new evidence that mindfulness in youth relates to functional neural dynamics and interactions between neurocognitive networks, over time. 336 211 218

In recent years the field of fMRI research has enjoyed expanded technical abilities related to resolution, as well as use across many fields of brain research. At the same time, the field has also dealt with uncertainty related to many known and unknown effects of artifact in fMRI data. In this review we discuss an emerging fMRI technology, called multi-echo (ME)-fMRI, which focuses on improving the fidelity and interpretability of fMRI. Where the essential problem of standard single-echo fMRI is the indeterminacy of sources of signals, whether BOLD or artifact, this is not the case for ME-fMRI. By acquiring multiple echo images per slice, the ME approach allows T2* decay to be modeled at every voxel at every time point. Since BOLD signals arise by changes in T2* over time, an fMRI experiment sampling the T2* signal decay can be analyzed to distinguish BOLD from artifact signal constituents. While the ME approach has a long history of use in theoretical and validation studies, modern MRI systems enable whole-brain multi-echo fMRI at high resolution. This review covers recent multi-echo fMRI acquisition methods, and the analysis steps for this data to make fMRI at once more principled, straightforward, and powerful. After a brief overview of history and theory, T2* modeling and applications will be discussed. These applications include T2* mapping and combining echoes from ME data to increase BOLD contrast and mitigate dropout artifacts. Next, the modeling of fMRI signal changes to detect signal origins in BOLD-related T2* versus artifact-related S0 changes will be reviewed. A focus is on the use of ME-fMRI data to extract and classify components from spatial ICA, called multi-echo ICA (ME-ICA). After describing how ME-fMRI and ME-ICA lead to a general model for analysis of fMRI signals, applications in animal and human imaging will be discussed. Applications include removing motion artifacts in resting state data at subject and group level. New imaging methods such as multi-band multi-echo fMRI and imaging at 7T are demonstrated throughout the review, and a practical analysis pipeline is described. The review culminates with evidence from recent studies of major boosts in statistical power from using multi-echo fMRI for detecting activation and connectivity in healthy individuals and patients with neuropsychiatric disease. In conclusion, the review shows evidence that the multi-echo approach expands the range of experiments that is practicable using fMRI. These findings suggest a compelling future role of the multi-echo approach in subject-level and clinical fMRI.; •An emerging fMRI technology, multi-echo (ME)-fMRI, makes fMRI more interpretable by enabling the detection of BOLD or artifact origins of acquired signals.•This review covers recent multi-echo fMRI acquisition methods, and the analysis steps for this data that make fMRI at once more principled, straightforward, and powerful.•After an overview of history and theory of ME-fMRI, T2* modeling and applications is discussed.•A focus is on the use of ME-fMRI data to extract and classify components from spatial ICA, called multi-echo ICA (ME-ICA).•New imaging methods such as multi-band multi-echo fMRI and imaging at 7T are demonstrated throughout the review, and a practical analysis pipeline is described. 154 59 80 ID: S1053811917302410; Accession Number: S1053811917302410; Author: Kundu, Prantik (a, ⁎); Author: Voon, Valerie (b); Author: Balchandani, Priti (a); Author: Lombardo, Michael V. (c); Author: Poser, Benedikt A. (d); Author: Bandettini, Peter A. (e); Affiliation: Departments of Radiology and Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Affiliation: Behavioral and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK; Affiliation: Department of Psychology and Center for Applied Neuroscience, University of Cyprus, Nicosia, Cyprus; Affiliation: Department of Cognitive Neuroscience, Maastricht University, Maastricht, NL, The Netherlands; Affiliation: Section on Functional Imaging Methods, National Institute of Mental Health, Bethesda, MD, USA; Topic: FMRI; Number of Pages: 22; Language: English

Summary Determining the best partition for a dataset can be a challenging task because of the lack of a priori information within an unsupervised learning framework and the absence of a unique clustering validation approach to evaluate clustering solutions. Here we present reval: a Python package that leverages stability-based relative clustering validation methods to select best clustering solutions as the ones that replicate, via supervised learning, on unseen subsets of data. The implementation of relative validation methods can contribute to the theory of clustering by fostering new approaches for the investigation of clustering results in different situations and for different data distributions. This work aims at contributing to this effort by implementing a package that works with multiple clustering and classification algorithms, hence allowing both the automation of the labeling process and the assessment of the stability of different clustering mechanisms., Highlights • Implementation of a stability-based relative validation technique for clustering • Best number of clusters selection for multiple tasks • Automation of stable clustering labels on new data via supervised learning • Complement or alternative to internal validation measures for clustering, The bigger picture reval is a Python package for stability-based relative clustering validation. It works with multiple clustering and classification algorithms, and as such, it enables the selection of best clustering solutions as the ones that replicate, via supervised learning, on unseen subsets of data. It is a tool that provides measures to evaluate clustering replicability and implements the automation of the labeling process. reval can be used as a complement or an alternative to internal validation measures, which highly rely on features inherent to a specific grouping solution, hindering the validation of replicable clusters., In the absence of labels that help categorize data, researchers rely on clustering algorithms to find meaningful partitions. Validating such partitions is a difficult task and widespread validation methods rely highly on the structure of the data at hand. This work presents a software implementation of a stability-based relative validation method for the selection of replicable stable solutions. It can be used with multiple clustering algorithms for different tasks, and it enables the automation of cluster labeling via classification methods.

Social visual engagement difficulties are hallmark early signs of autism (ASD) and are easily quantified using eye tracking methods. However, it is unclear how these difficulties are linked to atypical early functional brain organization in ASD. With resting state fMRI data in a large sample of ASD toddlers and other non-ASD comparison groups, we find ASD-related functional hypoconnnectivity between ‘social brain’ circuitry such as the default mode network (DMN) and visual and attention networks. An eye tracking-identified ASD subtype with pronounced early social visual engagement difficulties (GeoPref ASD) is characterized by marked DMN-occipito-temporal cortex (OTC) hypoconnectivity. Increased DMN-OTC hypoconnectivity is also related to increased severity of social-communication difficulties, but only in GeoPref ASD. Early and pronounced social-visual circuit hypoconnectivity is a key underlying neurobiological feature describing GeoPref ASD and may be critical for future social-communicative development and represent new treatment targets for early intervention in these individuals., eLife digest Many parents of children with autism spectrum disorder (ASD) spot the first signs when their child is still a toddler, by noticing that their child is less interested than other toddlers in people and in social play. These early differences in behavior can have long-term implications for brain development. The brains of toddlers with little interest in social stimuli will receive less social input than those of other toddlers. This will make it even harder for the brain to develop the circuits required to support social skills. But even among children with ASD, there are large differences in children's interest in the social world. One way of measuring these differences is to track eye movements. Lombardo et al. presented toddlers with and without ASD with images of moving colorful geometric shapes next to videos of dancing children. The majority of toddlers, including most of those with ASD, spent more time looking at the children than the shapes. But about 20% of the toddlers with ASD spent most of their time looking at the shapes. These toddlers also had the most severe social symptoms. To find out why, Lombardo et al. measured the toddlers' brain activity while they slept. During sleep, or when at rest, the brain shows stereotyped patterns of activity. Groups of brain regions that work together – such as those involved in vision – fire in synchrony. Lombardo et al. found that toddlers who preferred looking at shapes over people showed different patterns of brain activity while asleep compared to other children. In the toddlers who preferred shapes, brain networks involved in social skills were less likely to coordinate their activity with networks that support vision and attention. These findings suggest there may be multiple subtypes of ASD, with different symptoms resulting from different patterns of brain activity. At present, all children who receive a diagnosis of ASD receive much the same behavioral therapy. But in the future, studies of brain networks could allow children to receive more specific diagnoses. This could in turn lead to more effective and personalized treatments.

Although much research has been undertaken, the spatial patterns, developmental course, and sexual dimorphism of brain structure associated with autism remains enigmatic. One of the difficulties in investigating differences between the sexes in autism is the small sample sizes of available imaging datasets with mixed sex. Thus, the majority of the investigations have involved male samples, with females somewhat overlooked. This paper deploys machine learning on partial least squares feature extraction to reveal differences in regional brain structure between individuals with autism and typically developing participants. A four-class classification problem (sex and condition) is specified, with theoretical restrictions based on the evaluation of a novel upper bound in the resubstitution estimate. These conditions were imposed on the classifier complexity and feature space dimension to assure generalizable results from the training set to test samples. Accuracies above 80 % on gray and white matter tissues estimated from voxel-based morphometry (VBM) features are obtained in a sample of equal-sized high-functioning male and female adults with and without autism (N=120, n=30/group). The proposed learning machine revealed how autism is modulated by biological sex using a low-dimensional feature space extracted from VBM. In addition, a spatial overlap analysis on reference maps partially corroborated predictions of the "extreme male brain" theory of autism, in sexual dimorphic areas. 29 7

Autism spectrum disorder (ASD) has captured the attention of scientists, clinicians and the lay public because of its uncertain origins and striking clinical symptoms. A spectrum of candidate etiologies including evidence of genetic variants, present a perplexing picture of ASD origins. Furthermore, reliance on postmortem and other neurobiological evidence from older ASD cases limits understanding of its origins and early developmental processes. Arguably the least studied and understood period in ASD is prenatal and early postnatal, when ASD biology begins in a child. Missing, therefore, is what we call the ASD Living Biology. This is a conceptual and paradigm shift towards a focus on the abnormal prenatal processes underlying ASD within each individual. The concept emphasizes the specific need for foundational knowledge of a child’s development from abnormal prenatal beginnings to early clinical stages; and the ASD Living Biology paradigm seeks this knowledge by linking genetic and in vitro prenatal molecular, cellular and neural measurements with early in vivo postnatal molecular, neural and clinical presentation and progression in each ASD child. Within-child ASD Living Biology is a research concept we coin here that advocates the integration of that prenatal and postnatal information to generate individualized and group-level explanations, clinically useful prognoses, and effective treatments for ASD. Towards this effort, we review recent studies through the lens of ASD Living Biology. This view supports the theory of ASD as a progressive prenatal dysregulation of brain growth, spanning nearly all of prenatal life. ASD begins as early as the 1st and 2nd trimester with disruption of cell proliferation and differentiation in the brain. It continues with disruption of migration, laminar organization, cell growth, neurite outgrowth, synaptogenesis, receptor and neurotransmitter development, and assembly of functional neural networks. Among the most commonly reported high confidence ASD genes, 94% express during prenatal life and affect these developmental processes, with a majority affecting proliferation/differentiation and synapse development, potentially influenced by disrupted PI3K-AKT/RAS-ERK signaling. ASD toddler-derived cellular experiments show dysregulation of cell cycle, excess cell proliferation, reduced neuronal and synaptic maturation, and a 6-fold decrease in synchronized neural network activity. Such defects underlie atypical experience-dependent development of large-scale social and communication networks. Furthermore, variation in dysregulation of cell proliferation correlates with variation in a child’s brain growth, due to either ASD brain undergrowth with fewer and more functionally impaired neurons, or overgrowth with an excess of poorly synchronized neurons. It remains unclear how genetic factors cause these changes in ASD. Maternal immune activation (MIA) offers one possible non-genetic etiology, exhibiting a similar progression with increased proliferation and ASD-like neurodevelopmental defects and behavioral deficits. To address the prenatal and early postnatal molecular, cellular and anatomical changes in ASD, entirely new treatment concepts are needed. This also requires coordinated in vivo and in vitro ASD living biology research to unravel the heterogeneity in etiology, severity, developmental timing, and neural system distribution of disrupted development. We advocate that through an ASD living biology approach, relationships between prenatal stages, early-age postnatal brain growth and function, clinical presentation and progression, and treatment outcome may be defined at the individual level, thus enabling the development of precision medicine approaches with truly beneficial interventions.

BackgroundResting-state functional magnetic resonance imaging–based studies on functional connectivity in autism spectrum disorder (ASD) have generated inconsistent results. Interpretation of findings is further hampered by small samples and a focus on a limited number of networks, with networks underlying sensory processing being largely underexamined. We aimed to comprehensively characterize ASD-related alterations within and between 20 well-characterized resting-state networks using baseline data from the EU-AIMS (European Autism Interventions—A Multicentre Study for Developing New Medications) Longitudinal European Autism Project.MethodsResting-state functional magnetic resonance imaging data was available for 265 individuals with ASD (7.5–30.3 years; 73.2% male) and 218 typically developing individuals (6.9–29.8 years; 64.2% male), all with IQ > 70. We compared functional connectivity within 20 networks—obtained using independent component analysis—between the ASD and typically developing groups, and related functional connectivity within these networks to continuous (overall) autism trait severity scores derived from the Social Responsiveness Scale Second Edition across all participants. Furthermore, we investigated case-control differences and autism trait–related alterations in between-network connectivity.ResultsHigher autism traits were associated with increased connectivity within salience, medial motor, and orbitofrontal networks. However, we did not replicate previously reported case-control differences within these networks. The between-network analysis did reveal case-control differences showing on average 1) decreased connectivity of the visual association network with somatosensory, medial, and lateral motor networks, and 2) increased connectivity of the cerebellum with these sensory and motor networks in ASD compared with typically developing subjects.ConclusionsWe demonstrate ASD-related alterations in within- and between-network connectivity. The between-network alterations broadly affect connectivity between cerebellum, visual, and sensory-motor networks, potentially underlying impairments in multisensory and visual-motor integration frequently observed in ASD.

Prior work has revealed sex/gender-dependent autistic characteristics across behavioural and neural/biological domains. It remains unclear whether and how neural sex/gender differences are related to behavioural sex/gender differences in autism. Here, we examined whether atypical neural responses during mentalizing and self-representation are sex/gender-dependent in autistic adults and explored whether ‘camouflaging’ (acting as if behaviourally neurotypical) is associated with sex/gender-dependent neural responses. In total, N = 119 adults (33 typically developing males, 29 autistic males, 29 typically developing females and 28 autistic females) participated in a task-related functional magnetic resonance imaging paradigm to assess neural activation within right temporo-parietal junction and ventromedial prefrontal cortex during mentalizing and self-representation. Camouflaging in autism was quantified as the discrepancy between extrinsic behaviour in social–interpersonal contexts and intrinsic status. While autistic men showed hypoactive right temporo-parietal junction mentalizing and ventromedial prefrontal cortex self-representation responses compared to typically developing men, such neural responses in autistic women were not different from typically developing women. In autistic women only, increasing camouflaging was associated with heightened ventromedial prefrontal cortex self-representation response. There is a lack of impaired neural self-representation and mentalizing in autistic women compared to typically developing women. Camouflaging is heightened in autistic women and may relate to neural self-representation response. These results reveal brain-behaviour relations that help explain sex/gender-heterogeneity in social brain function in autism.

Background Histological evidence suggests that autism spectrum disorder (ASD) is accompanied by a reduced integrity of the grey-white matter boundary. This has also recently been confirmed by a structural neuroimaging study in vivo reporting significantly reduced grey-white matter tissue contrast (GWC) in adult individuals (18–42 years of age) with ASD relative to typically developing (TD) controls. However, it remains unknown whether the neuroanatomical differences in ASD at the grey-white matter boundary are stable across development or are age-dependent. Methods Here, we examined differences in the neurodevelopmental trajectories of GWC in a cross-sectional sample of 77 male ASD individuals and 76 typically developing (TD) controls across childhood and early adulthood (from 7 to 25 years). Results Using nested model comparisons, we first established that the developmental trajectory of GWC is complex in many regions across the cortex and includes linear and non-linear effects of age. Second, while ASD individuals have significantly reduced GWC overall, these differences are age-dependent and are most prominent during childhood (

The current study aimed to identify atypical neurophysiological activity associated with deficient affective processing in individuals with high callous-unemotional traits (CU). Fifty-six participants (M age = 20.52; 46% male) divided in two groups, differentiated on levels of CU traits, were invited to participate in the experimental phase of the study. Medial prefrontal cortex activity, measured with functional Near-Infrared Spectroscopy, and facial electro-myography activity were recorded during videos depicting violent, comedy and neutral scenes. Individuals high on CU traits showed similar medial prefrontal cortex oxygenated hemoglobin (HbO2) activity to positive and negative films, while the pre-frontal cortical responses of low CU individuals were more pronounced to positive than negative materials. High CU participants also showed reduced facial electromyography at the corrugator muscle in response to violent films, which was not differentiated from their responses to comedy films. These findings suggest that individuals high on CU traits show reduced but not absent (i.e., flat) affect to emotional material. Deficits in processing positive and negative valent material, measured with different neuro-physiological modalities, might be essential to understand CU traits. © 2015 Taylor & Francis. 11 1 72 87 J2: Soc. Neurosci.; Cited By :4; Export Date: 12 July 2017; Correspondence Address: Fanti, K.A.; Department of Psychology, University of Cyprus, P.O. Box 20537, Cyprus; email: kfanti@ucy.ac.cy

Maternal immune activation (MIA) via infection during pregnancy is known to increase risk for autism spectrum disorder (ASD). However, it is unclear how MIA disrupts fetal brain gene expression in ways that may explain this increased risk. Here we examine how MIA dysregulates rat fetal brain gene expression (at a time point analogous to the end of the first trimester of human gestation) in ways relevant to ASD-associated pathophysiology. MIA downregulates expression of ASD-associated genes, with the largest enrichments in genes known to harbor rare highly penetrant mutations. MIA also downregulates expression of many genes also known to be persistently downregulated in the ASD cortex later in life and which are canonically known for roles in affecting prenatally late developmental processes at the synapse. Transcriptional and translational programs that are downstream targets of highly ASD-penetrant FMR1 and CHD8 genes are also heavily affected by MIA. MIA strongly upregulates expression of a large number of genes involved in translation initiation, cell cycle, DNA damage and proteolysis processes that affect multiple key neural developmental functions. Upregulation of translation initiation is common to and preserved in gene network structure with the ASD cortical transcriptome throughout life and has downstream impact on cell cycle processes. The cap-dependent translation initiation gene, EIF4E, is one of the most MIA-dysregulated of all ASD-associated genes and targeted network analyses demonstrate prominent MIA-induced transcriptional dysregulation of mTOR and EIF4E-dependent signaling. This dysregulation of translation initiation via alteration of the Tsc2–mTor–Eif4e axis was further validated across MIA rodent models. MIA may confer increased risk for ASD by dysregulating key aspects of fetal brain gene expression that are highly relevant to pathophysiology affecting ASD.Molecular Psychiatry advance online publication, 21 March 2017; doi:10.1038/mp.2017.15. © 2017 The Author(s) Cited By :1; Export Date: 17 July 2017; Article in Press

Early-onset neurodevelopmental conditions (e.g., autism) affect males more frequently than females. Androgens may play a role in this male-bias by sex-differentially impacting early prenatal brain development, particularly neural circuits that later develop specialized roles in social cognition. Here, we find that increasing prenatal testosterone in humans is associated with later reduction of functional connectivity between social brain default mode (DMN) subsystems in adolescent males, but has no effect in females. Since testosterone can work directly via the androgen receptor (AR) or indirectly via the estrogen receptor through aromatase conversion to estradiol, we further examined how a potent non-aromatizable androgen, dihydrotestosterone (DHT), acts via the AR to influence gene expression in human neural stem cells (hNSC)—particularly for genes of high-relevance for DMN circuitry. DHT dysregulates a number of genes enriched for syndromic causes of autism and intellectual disability and for genes that in later development are expressed in anatomical patterns that highly correspond to the cortical midline DMN subsystem. DMN-related and DHT-affected genes (e.g., MEF2C) are involved in a number of synaptic processes, many of which impact excitation-inhibition balance. Androgens have male-specific prenatal influence over social brain circuitry in humans and may be relevant towards explaining some component of male-bias in early-onset neurodevelopmental conditions. 1 14

Sex differences in the human brain are of interest for many reasons: for example, there are sex differences in the observed prevalence of psychiatric 28 8 2959 2975

Background The EU-AIMS Longitudinal European Autism Project (LEAP) is to date the largest multi-centre, multi-disciplinary observational study on biomarkers for autism spectrum disorder (ASD). The current paper describes the clinical characteristics of the LEAP cohort and examines age, sex and IQ differences in ASD core symptoms and common co-occurring psychiatric symptoms. A companion paper describes the overall design and experimental protocol and outlines the strategy to identify stratification biomarkers. Methods From six research centres in four European countries, we recruited 437 children and adults with ASD and 300 controls between the ages of 6 and 30 years with IQs varying between 50 and 148. We conducted in-depth clinical characterisation including a wide range of observational, interview and questionnaire measures of the ASD phenotype, as well as co-occurring psychiatric symptoms. Results The cohort showed heterogeneity in ASD symptom presentation, with only minimal to moderate site differences on core clinical and cognitive measures. On both parent-report interview and questionnaire measures, ASD symptom severity was lower in adults compared to children and adolescents. The precise pattern of differences varied across measures, but there was some evidence of both lower social symptoms and lower repetitive behaviour severity in adults. Males had higher ASD symptom scores than females on clinician-rated and parent interview diagnostic measures but not on parent-reported dimensional measures of ASD symptoms. In contrast, self-reported ASD symptom severity was higher in adults compared to adolescents, and in adult females compared to males. Higher scores on ASD symptom measures were moderately associated with lower IQ. Both inattentive and hyperactive/impulsive ADHD symptoms were lower in adults than in children and adolescents, and males with ASD had higher levels of inattentive and hyperactive/impulsive ADHD symptoms than females. Conclusions The established phenotypic heterogeneity in ASD is well captured in the LEAP cohort. Variation both in core ASD symptom severity and in commonly co-occurring psychiatric symptoms were systematically associated with sex, age and IQ. The pattern of ASD symptom differences with age and sex also varied by whether these were clinician ratings or parent- or self-reported which has important implications for establishing stratification biomarkers and for their potential use as outcome measures in clinical trials. Electronic supplementary material The online version of this article (doi:10.1186/s13229-017-0145-9) contains supplementary material, which is available to authorized users.

BackgroundAutism spectrum disorders (ASD) are etiologically heterogeneous and complex. Functional genomics work has begun to identify a diverse array of dysregulated transcriptomic programs (e.g., synaptic, immune, cell cycle, DNA damage, WNT signaling, cortical patterning and differentiation) potentially involved in ASD brain abnormalities during childhood and adulthood. However, it remains unclear whether such diverse dysregulated pathways are independent of each other or instead reflect coordinated hierarchical systems-level pathology.MethodsTwo ASD cortical transcriptome datasets were re-analyzed using consensus weighted gene co-expression network analysis (WGCNA) to identify common coexpression modules across datasets. Linear mixed-effect models and Bayesian replication statistics were used to identify replicable differentially expressed modules. Eigengene network analysis was then utilized to identify between-group differences in how co-expression modules interact and cluster into hierarchical meta-modular organization. Protein-protein interaction analyses were also used to determine whether dysregulated co-expression modules show enhanced interactions.ResultsWe find replicable evidence for 10 gene co-expression modules that are differentially expressed in ASD cortex. Rather than being independent non-interacting sources of pathology, these dysregulated co-expression modules work in synergy and physically interact at the protein level. These systems-level transcriptional signals are characterized by downregulation of synaptic processes coordinated with upregulation of immune/inflammation, response to other organism, catabolism, viral processes, translation, protein targeting and localization, cell proliferation, and vasculature development. Hierarchical organization of meta-modules (clusters of highly correlated modules) is also highly affected in ASD.ConclusionsThese findings highlight that dysregulation of the ASD cortical transcriptome is characterized by the dysregulation of multiple coordinated transcriptional programs producing synergistic systems-level effects that cannot be fully appreciated by studying the individual component biological processes in isolation.

IMPORTANCE Autism spectrum disorder (ASD) is 2 to 5 times more common in male individuals than in female individuals. While the male preponderant prevalence of ASD might partially be explained by sex differences in clinical symptoms, etiological models suggest that the biological male phenotype carries a higher intrinsic risk for ASD than the female phenotype. To our knowledge, this hypothesis has never been tested directly, and the neurobiological mechanisms that modulate ASD risk in male individuals and female individuals remain elusive. OBJECTIVES To examine the probability of ASD as a function of normative sex-related phenotypic diversity in brain structure and to identify the patterns of sex-related neuroanatomical variability associated with low or high probability of ASD. DESIGN, SETTING, AND PARTICIPANTS This study examined a cross-sectional sample of 98 right-handed, high-functioning adults with ASD and 98 matched neurotypical control individuals aged 18 to 42 years. A multivariate probabilistic classification approach was used to develop a predictive model of biological sex based on cortical thickness measures assessed via magnetic resonance imaging in neurotypical controls. This normative model was subsequently applied to individuals with ASD. The study dates were June 2005 to October 2009, and this analysis was conducted between June 2015 and July 2016. MAIN OUTCOMES AND MEASURES Sample and population ASD probability estimates as a function of normative sex-related diversity in brain structure, as well as neuroanatomical patterns associated with low or high ASD probability in male individuals and female individuals. RESULTS Among the 98 individuals with ASD, 49 were male and 49 female, with a mean (SD) age of 26.88 (7.18) years. Among the 98 controls, 51 were male and 47 female, with a mean (SD) age of 27.39 (6.44) years. The sample probability of ASD increased significantly with predictive probabilities for the male neuroanatomical brain phenotype. For example, biological female individuals with a more male-typic pattern of brain anatomy were significantly (ie, 3 times) more likely to have ASD than biological female individuals with a characteristically female brain phenotype (P =.72 vs.24, respectively; χ1 2= 20.26; P

Autism affects males more than females, giving rise to the idea that the influence of steroid hormones on early fetal brain development may be one important early biological risk factor. Utilizing the Danish Historic Birth Cohort and Danish Psychiatric Central Register, we identified all amniotic fluid samples of males born between 1993 and 1999 who later received ICD-10 (International Classification of Diseases, 10th Revision) diagnoses of autism, Asperger syndrome or PDD-NOS (pervasive developmental disorder not otherwise specified) (n=128) compared with matched typically developing controls. Concentration levels of Δ4 sex steroids (progesterone, 17α-hydroxy-progesterone, androstenedione and testosterone) and cortisol were measured with liquid chromatography tandem mass spectrometry. All hormones were positively associated with each other and principal component analysis confirmed that one generalized latent steroidogenic factor was driving much of the variation in the data. The autism group showed elevations across all hormones on this latent generalized steroidogenic factor (Cohen's d=0.37, P=0.0009) and this elevation was uniform across ICD-10 diagnostic label. These results provide the first direct evidence of elevated fetal steroidogenic activity in autism. Such elevations may be important as epigenetic fetal programming mechanisms and may interact with other important pathophysiological factors in autism. © 2015 Macmillan Publishers Limited. 20 3 369 376 Cited By :73; Export Date: 17 July 2017

Autism is a set of heterogeneous neurodevelopmental conditions, characterised by early-onset difficulties in social communication and unusually restricted, repetitive behaviour and interests. The worldwide population prevalence is about 1%. Autism affects more male than female individuals, and comorbidity is common (>70% have concurrent conditions). Individuals with autism have atypical cognitive profiles, such as impaired social cognition and social perception, executive dysfunction, and atypical perceptual and information processing. These profiles are underpinned by atypical neural development at the systems level. Genetics has a key role in the aetiology of autism, in conjunction with developmentally early environmental factors. Large-effect rare mutations and small-effect common variants contribute to risk. Assessment needs to be multidisciplinary and developmental, and early detection is essential for early intervention. Early comprehensive and targeted behavioural interventions can improve social communication and reduce anxiety and aggression. Drugs can reduce comorbid symptoms, but do not directly improve social communication. Creation of a supportive environment that accepts and respects that the individual is different is crucial. 383 9920 896 910 Cited By :288; Export Date: 17 July 2017

This review examines the role of hormones in the development of social and nonsocial cognition and the brain. Research findings from human studies designed to elucidate the effects of both prenatal and postnatal exposure to hormones in children and young adults are summarized. Effects are found to be both time and dose dependent, with exposure to abnormal hormone levels having a limited impact outside the "critical window" in development. Particular attention is given to the role of prenatal hormone exposure, which appears to be vital for early organization of the brain. In later life, measurements of circulating hormone levels and the administration of testosterone and oxytocin are found to predict behavior, but the effect is thought to be one of "activation" or "fine-tuning" of the early organization of the brain. Possible directions for valuable future research are discussed. © 2013 Springer-Verlag Berlin Heidelberg. 465 5 557 571 Cited By :59; Export Date: 17 July 2017

Autism spectrum conditions (ASC) are more prevalent in males than females. The biological basis of this difference remains unclear. It has been postulated that one of the primary causes of ASC is a partial disconnection of the frontal lobe from higher-order association areas during development (that is, a frontal 'disconnection syndrome'). Therefore, in the current study we investigated whether frontal connectivity differs between males and females with ASC. We recruited 98 adults with a confirmed highfunctioning ASC diagnosis (61 males: aged 18-41 years; 37 females: aged 18-37 years) and 115 neurotypical controls (61 males: aged 18-45 years; 54 females: aged 18-52 years). Current ASC symptoms were evaluated using the Autism Diagnostic Observation Schedule (ADOS). Diffusion tensor imaging was performed and fractional anisotropy (FA) maps were created. Mean FA values were determined for five frontal fiber bundles and two non-frontal fiber tracts. Between-group differences in mean tract FA, as well as sex-by-diagnosis interactions were assessed. Additional analyses including ADOS scores informed us on the influence of current ASC symptom severity on frontal connectivity. We found that males with ASC had higher scores of current symptom severity than females, and had significantly lower mean FA values for all but one tract compared to controls. No differences were found between females with or without ASC. Significant sex-by-diagnosis effects were limited to the frontal tracts. Taking current ASC symptom severity scores into account did not alter the findings, although the observed power for these analyses varied. We suggest these findings of frontal connectivity abnormalities in males with ASC, but not in females with ASC, have the potential to inform us on some of the sex differences reported in the behavioral phenotype of ASC. 7 e1090 e1090 PT: J

Atypical cortical organization and reduced integrity of the gray-white matter boundary have been reported by postmortem studies in individuals with autism spectrum disorder (ASD). However, there are no in vivo studies that examine these particular features of cortical organization in ASD. Hence, we used structural magnetic resonance imaging to examine differences in tissue contrast between gray and white matter in 98 adults with ASD and 98 typically developing controls, to test the hypothesis that individuals with ASD have significantly reduced tissue contrast. More specifically, we examined contrast as a percentage between gray and white matter tissue signal intensities (GWPC) sampled at the gray-white matter boundary, and across different cortical layers. We found that individuals with ASD had significantly reduced GWPC in several clusters throughout the cortex (cluster, P < 0.05). As expected, these reductions were greatest when tissue intensities were sampled close to gray-white matter interface, which indicates a less distinct gray-white matter boundary in ASD. Our in vivo findings of reduced GWPC in ASD are therefore consistent with prior postmortem findings of a less well-defined gray-white matter boundary in ASD. Taken together, these results indicate that GWPC might be utilized as an in vivo proxy measure of atypical cortical microstructural organization in future studies. 27 2 877 887 PT: J

Oxytocin may influence various human behaviors and the connectivity across subcortical and cortical networks. Previous oxytocin studies are male biased and often constrained by task-based inferences. Here, we investigate the impact of oxytocin on resting-state connectivity between subcortical and cortical networks in women. We collected resting-state functional magnetic resonance imaging (fMRI) data on 26 typically developing women 40 min following intranasal oxytocin administration using a double-blind placebo-controlled crossover design. Independent components analysis (ICA) was applied to examine connectivity between networks. An independent analysis of oxytocin receptor (OXTR) gene expression in human subcortical and cortical areas was carried out to determine plausibility of direct oxytocin effects on OXTR. In women, OXTR was highly expressed in striatal and other subcortical regions, but showed modest expression in cortical areas. Oxytocin increased connectivity between corticostriatal circuitry typically involved in reward, emotion, social communication, language and pain processing. This effect was 1.39 standard deviations above the null effect of no difference between oxytocin and placebo. This oxytocin-related effect on corticostriatal connectivity covaried with autistic traits, such that oxytocin-related increase in connectivity was stronger in individuals with higher autistic traits. In sum, oxytocin strengthened corticostriatal connectivity in women, particularly with cortical networks that are involved in social-communicative, motivational and affective processes. This effect may be important for future work on neurological and psychiatric conditions (for example, autism), particularly through highlighting how oxytocin may operate differently for subsets of individuals. 7 e1099 e1099 PT: J

Neuroimaging studies have reported structural and physiological differences that could help understand the causes and development of Autism Spectrum Disorder (ASD). Many of them rely on multisite designs, with the recruitment of larger samples increasing statistical power. However, recent large-scale studies have put some findings into question, considering the results to be strongly dependent on the database used, and demonstrating the substantial heterogeneity within this clinically defined category. One major source of variance may be the acquisition of the data in multiple centres. In this work we analysed the differences found in the multisite, multi-modal neuroimaging database from the UK Medical Research Council Autism Imaging Multicentre Study (MRC AIMS) in terms of both diagnosis and acquisition sites. Since the dissimilarities between sites were higher than between diagnostic groups, we developed a technique called Significance Weighted Principal Component Analysis (SWPCA) to reduce the undesired intensity variance due to acquisition site and to increase the statistical power in detecting group differences. After eliminating site-related variance, statistically significant group differences were found, including Broca's area and the temporo-parietal junction. However, discriminative power was not sufficient to classify diagnostic groups, yielding accuracies results close to random. Our work supports recent claims that ASD is a highly heterogeneous condition that is difficult to globally characterize by neuroimaging, and therefore different (and more homogenous) subgroups should be defined to obtain a deeper understanding of ASD. Hum Brain Mapp 38:1208–1223, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc. 38 3 1208 1223 Export Date: 17 July 2017

Background Fine motor skill impairments are common in autism spectrum disorder (ASD), significantly affecting quality of life. Sensory inputs reaching the primary motor cortex (M1) from the somatosensory cortex (S1) are likely involved in fine motor skill and specifically motor learning. However, the role of these connections has not been directly investigated in humans. This study aimed to investigate, for the first time, the role of the S1-M1 connections in healthy subjects in vivo and whether microstructural alterations are associated with motor impairment in ASD. Methods Sixty right-handed neurotypical adult men aged 18 to 45 years, and 60 right-handed age- and sex-matched subjects diagnosed with ASD underwent fine motor skill assessment and scanning with diffusion tensor imaging (DTI). The streamlines of the hand region connecting S1-M1 of the motor-sensory homunculus were virtually dissected using TrackVis, and diffusion properties were extracted. The face/tongue region connections were used as control tracts. Results The ASD group displayed lower motor performances and altered DTI measurements of the hand-region connection. Behavioral performance correlated with hand-region DTI measures in both groups, but not with the face/tongue connections, indicating anatomical specificity. There was a left-hemisphere association of motor ability in the control group and an atypical rightward shift in the ASD group. Conclusions These findings suggest that direct interaction between S1 and M1 may contribute to the human ability to precisely interact with and manipulate the environment. Because electrophysiological evidence indicates that these connections may underpin long-term potentiation in M1, our findings may lead to novel therapeutic treatments for motor skill disorders. © 2016 Society of Biological Psychiatry 81 3 211 219 Export Date: 17 July 2017

The male preponderance in autism prevalence has brought together the disparate topics of sex/gender and autism research. Two directions of neuroimaging studies on the relationships between sex/gender and autism may inform male-specific risk mechanisms and female-specific protective mechanisms of autism. First, we review how sex/gender moderates autism-related brain changes and how this informs general models of autism etiology. Better-powered human neuroimaging studies suggest that the brain characteristics of autism are qualitatively, rather than simply quantitatively, different between males and females. However, age and comorbidities might substantially moderate the pattern of differences. Second, we review how the relationship between autism-related brain changes (separately in males and females) and normative brain sex/gender differences informs specific etiological–developmental mechanisms. Both human and animal studies converge to indicate that the brain characteristics of autism are partly associated with normative brain sex/gender differences, suggesting convergence or overlap between the mechanisms leading to and modifying the development of autism and the mechanisms underlying sex differentiation and/or gender socialization. Future animal work needs to investigate sex differences in rodent mutants modeling autism-relevant genes and environmental exposures. Future human work needs to address the substantial phenotypic and etiological heterogeneity of autism and to focus on longitudinal neuroimaging studies (from early development) on the developmental trajectories of sex/gender-differential neural characteristics of autism. Combining animal and human work links up the causal chain from etiological factors, brain and physical development, to phenotypes. These together help delineate the different roles of sex and gender in relation to risk vs. protective mechanisms. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc. 95 01-Feb 380 397 Cited By :3; Export Date: 17 July 2017

Background: Sex differences are present in many neuropsychiatric conditions that affect emotion and approach-avoidance behavior. One potential mechanism underlying such observations is testosterone in early development. Although much is known about the effects of testosterone in adolescence and adulthood, little is known in humans about how testosterone in fetal development influences later neural sensitivity to valenced facial cues and approach-avoidance behavioral tendencies. Methods: With functional magnetic resonance imaging we scanned 25 8-11-year-old children while viewing happy, fear, neutral, or scrambled faces. Fetal testosterone (FT) was measured via amniotic fluid sampled between 13 and 20 weeks gestation. Behavioral approach-avoidance tendencies were measured via parental report on the Sensitivity to Punishment and Sensitivity to Rewards questionnaire. Results: Increasing FT predicted enhanced selectivity for positive compared with negatively valenced facial cues in reward-related regions such as caudate, putamen, and nucleus accumbens but not the amygdala. Statistical mediation analyses showed that increasing FT predicts increased behavioral approach tendencies by biasing caudate, putamen, and nucleus accumbens but not amygdala to be more responsive to positive compared with negatively valenced cues. In contrast, FT was not predictive of behavioral avoidance tendencies, either through direct or neurally mediated paths. Conclusions: This work suggests that testosterone in humans acts as a fetal programming mechanism on the reward system and influences behavioral approach tendencies later in life. As a mechanism influencing atypical development, FT might be important across a range of neuropsychiatric conditions that asymmetrically affect the sexes, the reward system, emotion processing, and approach behavior. © 2012 Society of Biological Psychiatry. 72 10 839 847 Cited By :48; Export Date: 17 July 2017

In nonhuman species, testosterone is known to have permanent organizing effects early in life that predict later expression of sex differences in brain and behavior. However, in humans, it is still unknown whether such mechanisms have organizing effects on neural sexual dimorphism. In human males, we show that variation in fetal testosterone (FT) predicts later local gray matter volume of specific brain regions in a direction that is congruent with sexual dimorphism observed in a large independent sample of age-matched males and females from the NIH Pediatric MRI Data Repository. Right temporoparietal junction/posterior superior temporal sulcus (RTPJ/pSTS), planum temporale/parietal operculum (PT/PO), and posterior lateral orbitofrontal cortex (plOFC) had local gray matter volume that was both sexually dimorphic and predicted in a congruent direction by FT. That is, gray matter volume in RTPJ/pSTS was greater for males compared to females and was positively predicted by FT. Conversely, gray matter volume in PT/PO and plOFC was greater in females compared to males and was negatively predicted by FT. Subregions of both amygdala and hypothalamus were also sexually dimorphic in the direction of Male > Female, but were not predicted by FT. However, FT positively predicted gray matter volume of a non-sexually dimorphic subregion of the amygdala. These results bridge a long-standing gap between human and nonhuman species by showing that FT acts as an organizing mechanism for the development of regional sexual dimorphism in the human brain. © 2012 the authors. 32 2 674 680 Cited By :126; Export Date: 17 July 2017

Empirical investigations of the relation of frontal lobe function to self-evaluation have mostly examined the evaluation of abstract qualities in relation to self versus other people. The present research furthers our understanding of frontal lobe involvement in self-evaluation by examining two processes that have not been widely studied by neuroscientists: on-line self-evaluations and correction of systematic judgment errors that influence self-evaluation. Although people evaluate their abstract qualities, it is equally important that perform on-line evaluations to assess the success of their behavior in a particular situation. In addition, self-evaluations of task performance are sometimes overconfident because of systematic judgment errors. What role do the neural regions associated with abstract self-evaluations and decision bias play in on-line evaluation and self-evaluation bias? In this fMRI study, self-evaluation in two reasoning tasks was examined; one elicited overconfident self-evaluations of performance because of salient but misleading aspects of the task and the other was free from misleading aspects. Medial PFC (mPFC), a region associated with self-referential processing, was generally involved in on-line self-evaluations but not specific to accurate or overconfident evaluation. Orbitofrontal cortex (OFC) activity, a region associated with accurate nonsocial judgment, negatively predicted individual differences in overconfidence and was negatively associated with confidence level for incorrect trials. © 2009 Massachusetts Institute of Technology. 22 9 2108 2119 Cited By :52; Export Date: 17 July 2017

People with autism spectrum conditions (ASC) have difficulties with mentalizing, empathy, and narrative comprehension. A new test of social and narrative cognition, the Moral Dilemmas Film Task, was developed to probe individuals' spontaneous understanding of naturalistic film scenes. Twenty-eight individuals with ASC and 28 neurotypical controls, matched for age, sex, and IQ, watched four short emotionally charged film clips each depicting a moral dilemma, and were asked to write about what they had seen. Individuals with ASC produced significantly shorter film-based narratives and showed a smaller bias for mental states over objects in their narratives than controls. A significant correlation was found between verbal IQ and the level of mentalizing in film narratives for the ASC group, but not the control group, while the reverse pattern was found with a measure of self-reported cognitive and affective empathy. These results suggest that to the extent that both groups succeed in viewing moral dilemmas in terms of mental content, they do so in different ways, with individuals with ASC using verbal scaffolding to increase their ability to draw meaning from social scenes. The well-established empathy deficit in ASC extends to spontaneous interpretation of moral dilemmas. This new film task has the potential to assay different aspects of how the social world is represented differently in ASC, including during moral comprehension. © 2009 International Society for Autism Research, Wiley Periodicals, Inc. 2 3 148 156 Cited By :22; Export Date: 17 July 2017

The striatum plays a key role in many cognitive and emotional processes, and displays an intricate pattern of connectivity with cortical and subcortical structures. Invasive tracing work in rats and non-human primates demonstrates that the striatum can be segregated into subregions based on similar clustering of input and output fibers. In contrast, the human striatum is typically segregated according to local anatomical landmarks without considering natural boundaries formed by functional/anatomical networks. Here, we used non-invasive magnetic resonance (MR) imaging in young, healthy adults to define subregions of the human striatum based on volume correlations with other subcortical and cortical structures. We present three methods to delineate anatomical volumetric correlations based on gray matter content estimated from T1-weighted MR images. We observed both consistencies with and divergences from invasive tracing work in animals, suggesting that magnetic resonance imaging (MRI)-based covariance likely does not correspond to direct anatomical connections, although it might index other forms of connectivity or tissue type similarity. These novel approaches may be useful in understanding connectivity of other regions, and changes in connectivity in patient or ageing populations. © The Authors (2008). 27 6 1534 1546 Cited By :16; Export Date: 17 July 2017

Individuals affected by autism spectrum conditions (ASC) are considerably heterogeneous. Novel approaches are needed to parse this heterogeneity to enhance precision in clinical and translational research. Applying a clustering approach taken from genomics and systems biology on two large independent cognitive datasets of adults with and without ASC (n = 694; n = 249), we find replicable evidence for 5 discrete ASC subgroups that are highly differentiated in item-level performance on an explicit mentalizing task tapping ability to read complex emotion and mental states from the eye region of the face (Reading the Mind in the Eyes Test; RMET). Three subgroups comprising 45-62% of ASC adults show evidence for large impairments (Cohen's d = -1.03 to -11.21), while other subgroups are effectively unimpaired. These findings delineate robust natural subdivisions within the ASC population that may allow for more individualized inferences and accelerate research towards precision medicine goals. © The Author(s) 2016. 6 Cited By :3; Export Date: 17 July 2017

In humans, both language and fine motor skills are associated with left-hemisphere specialization, whereas visuospatial skills are associated with right-hemisphere specialization. Individuals with autism spectrum conditions (ASC) show a profile of deficits and strengths that involves these lateralized cognitive functions. Here we test the hypothesis that regions implicated in these functions are atypically rightward lateralized in individuals with ASC and, that such atypicality is associated with functional performance. Participants included 67 male, right-handed adults with ASC and 69 age- and IQ-matched neurotypical males. We assessed group differences in structural asymmetries in cortical regions of interest with voxel-based analysis of grey matter volumes, followed by correlational analyses with measures of language, motor and visuospatial skills. We found stronger rightward lateralization within the inferior parietal lobule and reduced leftward lateralization extending along the auditory cortex comprising the planum temporale, Heschl's gyrus, posterior supramarginal gyrus, and parietal operculum, which was more pronounced in ASC individuals with delayed language onset compared to those without. Planned correlational analyses showed that for individuals with ASC, reduced leftward asymmetry in the auditory region was associated with more childhood social reciprocity difficulties. We conclude that atypical cerebral structural asymmetry is a potential candidate neurophenotype of ASC. © 2015 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc. 37 1 230 253 Cited By :9; Export Date: 17 July 2017

Alexithymia refers to pronounced difficulty in identifying and describing one's own emotions and is associated with an externally oriented focus of thinking. Alexithymia is known to be much more common in adults with autism spectrum disorders (ASD) compared with the typically developing (TD) adult population. However, we know very little about alexithymia in young children with ASD and advancing our understanding of this topic may be of critical clinical and translational importance. Here, we present the first study to examine alexithymia in children with ASD. We find that alexithymia is substantially elevated in ASD on both self- and parent-report measures. Despite both measures being sensitive to on-average group differentiation, we find no evidence of correlation between such measures, indicating that children and their parents may be using different sources of information. Parent-rated alexithymia is also associated with increasing levels of autistic traits. Discrepancy between self and other alexithymia ratings are also associated with autistic traits, but only in ASD. These results underscore the idea that assessing alexithymia in ASD at younger ages may help identify important subgroups that have particular difficulties in the domain of emotion processing. Autism Res 2016, 9: 773–780. © 2015 International Society for Autism Research, Wiley Periodicals, Inc. © 2015 International Society for Autism Research, Wiley Periodicals, Inc. 9 7 773 780 Cited By :4; Export Date: 17 July 2017

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. © The Author 2016. 26 7 3297 3309 Cited By :2; Export Date: 17 July 2017

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. © 2016 The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. 139 2 616 630 Cited By :7; Export Date: 17 July 2017

Autism spectrum disorder (ASD) is one of the most common neurodevelopmental disorders, but effective medical treatments for the core symptoms of the disorder are still lacking. According to the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5), the core symptoms of ASD comprise deficits in social communication and interaction, and repetitive and restricted behaviours, which include sensory abnormalities. Novel genetic and preclinical approaches now provide unprecedented opportunities to identify the underpinning pathophysiological mechanisms and aetiology-based treatment targets, as discussed in a Review article by Ghosh et al. (Drug discovery for autism spectrum disorder: challenges and opportunities. Nat. Rev. Drug Discov. 12, 777–790 (2013)1. This has led to more interest from the pharmaceutical industry in an area in which the overall risk of failure is seen as very high because key parameters of drug efficiency are not yet established and the regulatory environment is uncertain. For example, industry has recently invested in several pre-competitive projects, such as the European Union (EU) Innovative Medicines Initiative (IMI)-brokered public–private partnership EU-AIMS (European Autism Interventions — A Multicentre Study for Developing New Medications)2. 15 1 70 73 PT: J

Autism (ASD) is vastly heterogeneous, particularly in early language development. While ASD language trajectories in the first years of life are highly unstable, by early childhood these trajectories stabilize and arepredictive of longer-term outcome. Early neural substrates that predict/precede such outcomes are largely unknown, but could have considerable translational and clinical impact. Pre-diagnosis fMRI response to speech in ASD toddlers with relatively good language outcome was highly similar to non-ASD comparison groups and robustly recruited language-sensitive superior temporal cortices. In contrast, language-sensitive superior temporal cortices were hypoactive in ASD toddlers with poor language outcome. Brain-behavioral relationships were atypically reversed in ASD, and a multimodal combination of pre-diagnostic clinical behavioral measures and speech-related fMRI response showed the most promise as an ASD prognosis classifier. Thus, before ASD diagnoses and outcome become clinically clear, distinct functional neuroimaging phenotypes are already present that can shed insight on an ASD toddler's later outcome. © 2015 Elsevier Inc. 86 2 567 577 Cited By :26; Export Date: 17 July 2017

Autism spectrum disorders (ASD) are a group of neurodevelopmental conditions characterized by atypical structural and functional brain connectivity. Complex network analysis has been mainly used to describe altered network-level organization for functional systems and white matter tracts in ASD. However, atypical functional and structural connectivity are likely to be also linked to abnormal development of the correlated structure of cortical gray matter. Such covariations of gray matter are particularly well suited to the investigation of the complex cortical pathology of ASD, which is not confined to isolated brain regions but instead acts at the systems level. In this study, we examined network centrality properties of gray matter networks in adults with ASD (n = 84) and neurotypical controls (n = 84) using graph theoretical analysis. We derived a structural covariance network for each group using interregional correlation matrices of cortical volumes extracted from a surface-based parcellation scheme containing 68 cortical regions. Differences between groups in closeness network centrality measures were evaluated using permutation testing. We identified several brain regions in the medial frontal, parietal and temporo-occipital cortices with reductions in closeness centrality in ASD compared to controls. We also found an association between an increased number of autistic traits and reduced centrality of visual nodes in neurotypicals. Our study shows that ASD are accompanied by atypical organization of structural covariance networks by means of a decreased centrality of regions relevant for social and sensorimotor processing. These findings provide further evidence for the altered network-level connectivity model of ASD. © 2015 Elsevier Ltd. 69 142 149 Cited By :2; Export Date: 17 July 2017

Importance: The identification of genomic signatures that aid early identification of individuals at risk for autism spectrum disorder (ASD) in the toddler period remains a major challenge because of the genetic and phenotypic heterogeneity of the disorder. Generally, ASD is not diagnosed before the fourth to fifth birthday.Objective: To apply a functional genomic approach to identify a biologically relevant signature with promising performance in the diagnostic classification of infants and toddlers with ASD.Design, Setting, And Participants: Proof-of-principle study of leukocyte RNA expression levels from 2 independent cohorts of children aged 1 to 4 years (142 discovery participants and 73 replication participants) using Illumina microarrays. Coexpression analysis of differentially expressed genes between Discovery ASD and control toddlers were used to define gene modules and eigengenes used in a diagnostic classification analysis. Independent validation of the classifier performance was tested on the replication cohort. Pathway enrichment and protein-protein interaction analyses were used to confirm biological relevance of the functional networks in the classifier. Participant recruitment occurred in general pediatric clinics and community settings. Male infants and toddlers (age range, 1-4 years) were enrolled in the study. Recruitment criteria followed the 1-YearWell-Baby Check-Up Approach. Diagnostic judgment followed DSM-IV-TR and Autism Diagnostic Observation Schedule criteria for autism. Participants with ASD were compared with control groups composed of typically developing toddlers as well as toddlers with global developmental or language delay.Main Outcomes And Measures: Logistic regression and receiver operating characteristic curve analysis were used in a classification test to establish the accuracy, specificity, and sensitivity of the module-based classifier.Results: Our signature of differentially coexpressed genes was enriched in translation and immune/inflammation functions and produced 83%accuracy. In an independent test with approximately half of the sample and a different microarray, the diagnostic classification of ASD vs control samples was 75%accurate. Consistent with its ASD specificity, our signature did not distinguish toddlers with global developmental or language delay from typically developing toddlers (62%accuracy).Conclusions And Relevance: This proof-of-principle study demonstrated that genomic biomarkers with very good sensitivity and specificity for boys with ASD in general pediatric settings can be identified. It also showed that a blood-based clinical test for at-risk male infants and toddlers could be refined and routinely implemented in pediatric diagnostic settings. © 2015 American Medical Association. All rights reserved. 72 4 386 394 Cited By :21; Export Date: 17 July 2017

BackgroundIncreasing evidence suggests that autism is associated with abnormal white-matter (WM) anatomy and impaired brain ‘connectivity’. While myelin plays a critical role in synchronized brain communication, its aetiological role in autistic symptoms has only been indirectly addressed by WM volumetric, relaxometry and diffusion tensor imaging studies. A potentially more specific measure of myelin content, termed myelin water fraction (MWF), could provide improved sensitivity to myelin alteration in autism.MethodWe performed a cross-sectional imaging study that compared 14 individuals with autism and 14 age- and IQ-matched controls. T1 relaxation times (T1), T2 relaxation times (T2) and MWF values were compared between autistic subjects, diagnosed using the Autism Diagnostic Interview – Revised (ADI-R), with current symptoms assessed using the Autism Diagnostic Observation Schedule (ADOS) and typical healthy controls. Correlations between T1, T2 and MWF values with clinical measures [ADI-R, ADOS, and the Autism Quotient (AQ)] were also assessed.ResultsIndividuals with autism showed widespread WM T1 and MWF differences compared to typical controls. Within autistic individuals, worse current social interaction skill as measured by the ADOS was related to reduced MWF although not T1. No significant differences or correlations with symptoms were observed with respect to T2.ConclusionsAutistic individuals have significantly lower global MWF and higher T1, suggesting widespread alteration in tissue microstructure and biochemistry. Areas of difference, including thalamic projections, cerebellum and cingulum, have previously been implicated in the disorder; however, this is the first study to specifically indicate myelin alteration in these regions.

Autism spectrum disorders (ASD) are a group of conditions that show abnormalities in the neuroanatomy of multiple brain regions. The variability in the development of intelligence and language among individuals on the autism spectrum has long been acknowledged, but it remains unknown whether these differences impact on the neuropathology of ASD. In this study, we aimed to compare associations between surface-based regional brain measures and general intelligence (IQ) scores in ASD individuals with and without a history of language delay. We included 64 ASD adults of normal intelligence (37 without a history of language delay and 27 with a history of language delay and 80 neurotypicals). Regions with a significant association between verbal and nonverbal IQ and measures of cortical thickness (CT), surface area, and cortical volume were first identified in the combined sample of individuals with ASD and controls. Thicker dorsal frontal and temporal cortices, and thinner lateral orbital frontal and parieto-occipital cortices were associated with greater and lower verbal IQ scores, respectively. Correlations between cortical volume and verbal IQ were observed in similar regions as revealed by the CT analysis. A significant difference between ASD individuals with and without a history of language delay in the association between CT and verbal IQ was evident in the parieto-occipital region. These results indicate that ASD subgroups defined on the basis of differential language trajectories in childhood can have different associations between verbal IQ and brain measures in adulthood despite achieving similar levels of cognitive performance. © 2015 International Society for Autism Research, Wiley Periodicals, Inc. 8 5 556 566 Cited By :2; Export Date: 17 July 2017

The "Reading the Mind in the Eyes" test (Eyes test) is an advanced test of theory of mind. Typical sex difference has been reported (i.e., female advantage). Individuals with autism show more difficulty than do typically developing individuals, yet it remains unclear how this is modulated by sex, as females with autism have been under-represented. Here in a large, non-male-biased sample we test for the effects of sex, diagnosis, and their interaction. The Eyes test (revised version) was administered online to 395 adults with autism (178 males, 217 females) and 320 control adults (152 males, 168 females). Two-way ANOVA showed a significant sex-by-diagnosis interaction in total correct score (F(1,711) = 5.090, p = 0.024, νp2 = 0.007) arising from a significant sex difference between control males and females (p < 0.001, Cohen's d = 0.47), and an absence of a sex difference between males and females with autism (p = 0.907, d = 0.01); significant case-control differences were observed across sexes, with effect sizes of d = 0.35 in males and d = 0.69 in females. Group-difference patterns fit with the extreme-male-brain (EMB) theory predictions. Eyes test-Empathy Quotient and Eyes test-Autism Spectrum Quotient correlations were significant only in females with autism (r = 0.35, r = -0.32, respectively), but not in the other 3 groups. Support vector machine (SVM) classification based on response pattern across all 36 items classified autism diagnosis with a relatively higher accuracy for females (72.2%) than males (65.8%). Nevertheless, an SVM model trained within one sex generalized equally well when applied to the other sex. Performance on the Eyes test is a sex-independent phenotypic characteristic of adults with autism, reflecting sex-common social difficulties, and provides support for the EMB theory predictions for both males and females. Performance of females with autism differed from same-sex controls more than did that of males with autism. Females with autism also showed stronger coherence between self-reported dispositional traits and Eyes test performance than all other groups. Copyright © 2015 Baron-Cohen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 10 8 Cited By :17; Export Date: 17 July 2017

Autism spectrum conditions (ASC) are characterised by deficits in understanding and expressing emotions and are frequently accompanied by alexithymia, a difficulty in understanding and expressing emotion words. Words are differentially represented in the brain according to their semantic category and these difficulties in ASC predict reduced activation to emotion-related words in limbic structures crucial for affective processing. Semantic theories view ‘emotion actions’ as critical for learning the semantic relationship between a word and the emotion it describes, such that emotion words typically activate the cortical motor systems involved in expressing emotion actions such as facial expressions. As ASC are also characterised by motor deficits and atypical brain structure and function in these regions, motor structures would also be expected to show reduced activation during emotion-semantic processing. Here we used event-related fMRI to compare passive processing of emotion words in comparison to abstract verbs and animal names in typically-developing controls and individuals with ASC. Relatively reduced brain activation in ASC for emotion words, but not matched control words, was found in motor areas and cingulate cortex specifically. The degree of activation evoked by emotion words in the motor system was also associated with the extent of autistic traits as revealed by the Autism Spectrum Quotient. We suggest that hypoactivation of motor and limbic regions for emotion word processing may underlie difficulties in processing emotional language in ASC. The role that sensorimotor systems and their connections might play in the affective and social-communication difficulties in ASC is discussed., Highlights • Motor and limbic cortices are typically activated by emotion words. • In ASC, activity in these key regions is reduced for this word type specifically. • Hypoactivity does not appear in brain regions unrelated to emotion word processing. • ASC motor systems' hypoactivity to emotion words correlates with symptomatology. • Motor deficits may help explain emotion processing problems and other ASC symptoms.

Autism spectrum conditions (autism) affect ~1% of the population and are characterized by deficits in social communication. Oxytocin has been widely reported to affect social-communicative function and its neural underpinnings. Here we report the first evidence that intranasal oxytocin administration improves a core problem that individuals with autism have in using eye contact appropriately in real-world social settings. A randomized double-blind, placebo-controlled, within-subjects design is used to examine how intranasal administration of 24 IU of oxytocin affects gaze behavior for 32 adult males with autism and 34 controls in a real-time interaction with a researcher. This interactive paradigm bypasses many of the limitations encountered with conventional static or computer-based stimuli. Eye movements are recorded using eye tracking, providing an objective measurement of looking patterns. The measure is shown to be sensitive to the reduced eye contact commonly reported in autism, with the autism group spending less time looking to the eye region of the face than controls. Oxytocin administration selectively enhanced gaze to the eyes in both the autism and control groups (transformed mean eye-fixation difference per second = 0.082; 95% CI:0.025-0.14, P = 0.006). Within the autism group, oxytocin has the most effect on fixation duration in individuals with impaired levels of eye contact at baseline (Cohen's d = 0.86). These findings demonstrate that the potential benefits of oxytocin in autism extend to a realtime interaction, providing evidence of a therapeutic effect in a key aspect of social communication. 5 2 Cited By :42; Export Date: 17 July 2017