Radial cytoarchitecture and patterns of cortical connectivity in autism

Functional connectivity in autism spectrum disorder evaluated using rs-fMRI and DKI

We evaluated functional connectivity (FC) in patients with adult autism spectrum disorder (ASD) using resting-state functional MRI (rs-fMRI) and diffusion kurtosis imaging (DKI). We acquired rs-fMRI data from 33 individuals with ASD and 33 healthy controls (HC) and DKI data from 18 individuals with ASD and 17 HC. ASD showed attenuated FC between the right frontal pole (FP) and the bilateral temporal fusiform cortex (TFusC) and enhanced FC between the right thalamus and the bilateral inferior division of lateral occipital cortex, and between the cerebellar vermis and the right occipital fusiform gyrus (OFusG) and the right lingual gyrus, compared with HC. ASD demonstrated increased axial kurtosis (AK) and mean kurtosis (MK) in white matter (WM) tracts, including the right anterior corona radiata (ACR), forceps minor (FM), and right superior longitudinal fasciculus (SLF). In ASD, there was also a significant negative correlation between MK and FC between the cerebellar vermis and the right OFusG in the corpus callosum, FM, right SLF and right ACR. Increased DKI metrics might represent neuroinflammation, increased complexity, or disrupted WM tissue integrity that alters long-distance connectivity. Nonetheless, protective or compensating adaptations of inflammation might lead to more abundant glial cells and cytokine activation effectively alleviating the degeneration of neurons, resulting in increased complexity. FC abnormality in ASD observed in rs-fMRI may be attributed to microstructural alterations of the commissural and long-range association tracts in WM as indicated by DKI.

Empirical mode decomposition of local field potential data from optogenetic experiments

Introduction

This study investigated the effects of cocaine administration and parvalbumin-type interneuron stimulation on local field potentials (LFPs) recorded in vivo from the medial prefrontal cortex (mPFC) of six mice using optogenetic tools.

Methods

The local network was subject to a brief 10 ms laser pulse, and the response was recorded for 2 s over 100 trials for each of the six subjects who showed stable coupling between the mPFC and the optrode. Due to the strong non-stationary and nonlinearity of the LFP, we used the adaptive, data-driven, Empirical Mode Decomposition (EMD) method to decompose the signal into orthogonal Intrinsic Mode Functions (IMFs).

Results

Through trial and error, we found that seven is the optimum number of orthogonal IMFs that overlaps with known frequency bands of brain activity. We found that the Index of Orthogonality (IO) of IMF amplitudes was close to zero. The Index of Energy Conservation (IEC) for each decomposition was close to unity, as expected for orthogonal decompositions. We found that the power density distribution vs. frequency follows a power law with an average scaling exponent of ~1.4 over the entire range of IMF frequencies 2-2,000 Hz.

Discussion

The scaling exponent is slightly smaller for cocaine than the control, suggesting that neural activity avalanches under cocaine have longer life spans and sizes.

Brain structural correlates of autistic traits across the diagnostic divide: A grey matter and white matter microstructure study

Autism Spectrum Disorders (ASD) are a set of neurodevelopmental conditions characterised by difficulties in social interaction and communication as well as stereotyped and restricted patterns of interest. Autistic traits exist in a continuum across the general population, whilst the extreme end of this distribution is diagnosed as clinical ASD. While many studies have investigated brain structure in autism using a case-control design, few have used a dimensional approach. To add to this growing body of literature, we investigated the structural brain correlates of autistic traits in a mixed sample of adult participants (25 ASD and 66 neurotypicals; age: 18-60 years). We examined the relationship between regional brain volumes (using voxel-based morphometry and surface-based morphometry) and white matter microstructure properties (using Diffusion Tensor Imaging) and autistic traits (using Autism Spectrum Quotient). Our findings show grey matter differences in regions including the orbitofrontal cortex and lingual gyrus, and suggestive evidence for white matter microstructure differences in tracts including the superior longitudinal fasciculus being related to higher autistic traits. These grey matter and white matter microstructure findings from our study are consistent with previous reports and support the brain structural differences in ASD. These findings provide further support for shared aetiology for autistic traits across the diagnostic divide.

Abnormal spatiotemporal expression pattern of progranulin and neurodevelopment impairment in VPA-induced ASD rat model

Some environmental risk factors have been proven to contribute to the etiology of autism spectrum disorder (ASD). Exposure to the antiepileptic drug valproic acid (VPA) during pregnancy significantly increases the risk of ASD in humans, and consequently is utilized as a validated animal model of ASD in rodents; however, the precise molecular and cellular mechanisms remain ill-defined. In the present study, we investigated the effect of prenatal VPA exposure on the spatiotemporal dynamics of Progranulin (PGRN) expression, neuronal apoptosis, synapse density, and AKT/GSK-3β pathway activation in the brains of VPA-exposed offspring. Results from behavioral tests were consistent with prior studies showing impaired sociability, restricted interests and increased repetitive behaviors in VPA rats at postnatal days 28-32. Our data also indicated that VPA exposure resulted in abnormal dynamics of PGRN expression in different brain regions at the different development stages. The temporal and spatial patterns of PGRN expression were consistent with the spatiotemporal regularity of abnormalities, which observed in apoptosis-related protein levels, neuron numbers, dendritic spine density, synapse-related protein levels, and AKT/GSK-3β phosphorylation in VPA rats. It suggests that prenatal VPA exposure may affect the spatiotemporal regularity of neuronal apoptosis and synaptic development/regression via interfering with the spatiotemporal process of PGRN expression and downstream AKT/GSK-3β pathway activation. This may be a potential mechanism of the abnormal neuroanatomical changes and ASD-like behaviors in VPA-induced ASD.

Atypical myelinogenesis and reduced axon caliber in the Scn1a variant model of Dravet syndrome: An electron microscopy pilot study of the developing and mature mouse corpus callosum

Dravet Syndrome (DS) is a genetic neurodevelopmental disease. Recurrent severe seizures begin in infancy and co-morbidities follow, including developmental delay, cognitive and behavioral dysfunction. A majority of DS patients have an SCN1A heterozygous gene mutation. This mutation causes a loss-of-function in inhibitory neurons, initiating seizure onset. We have investigated whether the sodium channelopathy may result in structural changes in the DS model independent of seizures. Morphometric analyses of axons within the corpus callosum were completed at P16 and P50 in Scn1a heterozygote KO male mice and their age-matched wild-type littermates. Trainable machine learning algorithms were used to examine electron microscopy images of ~400 myelinated axons per animal, per genotype, including myelinated axon cross-section area, frequency distribution and g-ratios. Pilot data for Scn1a heterozygote KO mice demonstrate the average axon caliber was reduced in developing and adult mice. Qualitative analysis also shows micro-features marking altered myelination at P16 in the DS model, with myelin out-folding and myelin debris within phagocytic cells. The data has indicated, in the absence of behavioral seizures, factors that governed a shift toward small calibre axons at P16 have persisted in adult Scn1a heterozygote KO corpus callosum. The pilot study provides a basis for future meta-analysis that will enable robust estimates of the effects of the sodium channelopathy on axon architecture. We propose that early therapeutic strategies in DS could help minimize the effect of sodium channelopathies, beyond the impact of overt seizures, and therefore achieve better long-term treatment outcomes.

Sensory-to-Cognitive Systems Integration Is Associated With Clinical Severity in Autism Spectrum Disorder

OBJECTIVE

Impaired multisensory integration in autism spectrum disorder (ASD) may arise from functional dysconnectivity among brain systems. Our study examines the functional connectivity integration between primary modal sensory regions and heteromodal processing cortex in ASD, and whether abnormalities in network integration relate to clinical severity.

METHOD

We studied a sample of 55 high-functioning ASD and 64 healthy control (HC) male children and adolescents (total n = 119, age range 7-18 years). Stepwise functional connectivity analysis (SFC) was applied to resting state functional magnetic resonance images (rsfMRI) to characterize the connectivity paths that link primary sensory cortices to higher-order brain cognitive functional circuits and to relate alterations in functional connectivity integration with three clinical scales: Social Communication Questionnaire, Social Responsiveness Scale, and Vineland Adaptive Behavior Scales.

RESULTS

HC displayed typical functional connectivity transitions from primary sensory systems to association areas, but the ASD group showed altered patterns of multimodal sensory integration to heteromodal systems. Specifically, compared to the HC group, the ASD group showed the following: (1) hyperconnectivity in the visual cortex at initial link step distances; (2) hyperconnectivity between sensory unimodal regions and regions of the default mode network; and (3) hypoconnectivity between sensory unimodal regions and areas of the fronto-parietal and attentional networks. These patterns of hyper- and hypoconnectivity were associated with increased clinical severity in ASD.

CONCLUSION

Networkwise reorganization in high-functioning ASD individuals affects strategic regions of unimodal-to-heteromodal cortical integration predicting clinical severity. In addition, SFC analysis appears to be a promising approach for studying the neural pathophysiology of multisensory integration deficits in ASD.

Dopamine receptor antagonists effects on low-dimensional attractors of local field potentials in optogenetic mice

The goal of this study was to investigate the effects of acute cocaine injection or dopamine (DA) receptor antagonists on the medial prefrontal cortex (mPFC) gamma oscillations and their relationship to short term neuroadaptation that may mediate addiction. For this purpose, optogenetically evoked local field potentials (LFPs) in response to a brief 10 ms laser light pulse were recorded from 17 mice. D1-like receptor antagonist SCH 23390 or D2-like receptor antagonist sulpiride, or both, were administered either before or after cocaine. A Euclidian distance-based dendrogram classifier separated the 100 trials for each animal in disjoint clusters. When baseline and DA receptor antagonists trials were combined in a single trial, a minimum of 20% overlap occurred in some dendrogram clusters, which suggests a possible common, invariant, dynamic mechanism shared by both baseline and DA receptor antagonists data. The delay-embedding method of neural activity reconstruction was performed using the correlation time and mutual information to determine the lag/correlation time of LFPs and false nearest neighbors to determine the embedding dimension. We found that DA receptor antagonists applied before cocaine cancels out the effect of cocaine and leaves the lag time distributions at baseline values. On the other hand, cocaine applied after DA receptor antagonists shifts the lag time distributions to longer durations, i.e. increase the correlation time of LFPs. Fourier analysis showed that a reasonable accurate decomposition of the LFP data can be obtained with a relatively small (less than ten) Fourier coefficients.

Atypical Local and Distal Patterns of Occipito-frontal Functional Connectivity are Related to Symptom Severity in Autism

Autism spectrum disorders (ASDs) are increasingly prevalent neurodevelopmental disorders characterized by sociocommunicative impairments. Growing consensus indicates that neurobehavioral abnormalities require explanation in terms of interconnected networks. Despite theoretical speculations about increased local and reduced distal connectivity, links between local and distal functional connectivity have not been systematically investigated in ASDs. Specifically, it remains open whether hypothesized local overconnectivity may reflect isolated versus overly integrative processing. Resting state functional MRI data from 57 children and adolescents with ASDs and 51 typically developing (TD) participants were included. In regional homogeneity (ReHo) analyses, pericalcarine visual cortex was found be locally overconnected (ASD > TD). Using this region as seed in whole-brain analyses, we observed overconnectivity in distal regions, specifically middle frontal gyri, for an ASD subgroup identified through k-means clustering. While in this subgroup local occipital to distal frontal overconnectivity was associated with greater symptom severity, a second subgroup showed the opposite pattern of connectivity and symptom severity correlations. Our findings suggest that increased local connectivity in ASDs is region-specific and may be partially associated with more integrative long-distance connectivity. Results also highlight the need to test for subtypes, as differential patterns of brain-behavior links were observed in two distinct subgroups of our ASD cohort.

Transient increased thalamic-sensory connectivity and decreased whole-brain dynamism in autism

Autism spectrum disorder (ASD) is a neurodevelopmental disorder associated with social communication deficits and restricted/repetitive behaviors and is characterized by large-scale atypical subcortical-cortical connectivity, including impaired resting-state functional connectivity between thalamic and sensory regions. Previous studies have typically focused on the abnormal static connectivity in ASD and overlooked potential valuable dynamic patterns in brain connectivity. However, resting-state brain connectivity is indeed highly dynamic, and abnormalities in dynamic brain connectivity have been widely identified in psychiatric disorders. In this study, we investigated the dynamic functional network connectivity (dFNC) between 51 intrinsic connectivity networks in 170 individuals with ASD and 195 age-matched typically developing (TD) controls using independent component analysis and a sliding window approach. A hard clustering state analysis and a fuzzy meta-state analysis were conducted respectively, for the exploration of local and global aberrant dynamic connectivity patterns in ASD. We examined the group difference in dFNC between thalamic and sensory networks in each functional state and group differences in four high-dimensional dynamic measures. The results showed that compared with TD controls, individuals with ASD show an increase in transient connectivity between hypothalamus/subthalamus and some sensory networks (right postcentral gyrus, bi paracentral lobule, and lingual gyrus) in certain functional states, and diminished global meta-state dynamics of the whole-brain functional network. In addition, these atypical dynamic patterns are significantly associated with autistic symptoms indexed by the Autism Diagnostic Observation Schedule. These converging results support and extend previous observations regarding hyperconnectivity between thalamic and sensory regions and stable whole-brain functional configuration in ASD. Dynamic brain connectivity may serve as a potential biomarker of ASD and further investigation of these dynamic patterns might help to advance our understanding of behavioral differences in this complex neurodevelopmental disorder.

Using resting state functional MRI to build a personalized autism diagnosis system

Autism spectrum disorder (ASD) is a neuro-developmental disorder associated with social impairments, communication difficulties, and restricted and repetitive behaviors. Yet, there is no confirmed cause identified for ASD. Studying the functional connectivity of the brain is an emerging technique used in diagnosing and understanding ASD. In this study, we obtained the resting state functional MRI data of 283 subjects from the National Database of Autism Research (NDAR). An automated autism diagnosis system was built using the data from NDAR. The proposed system is machine learning based. Power spectral densities (PSDs) of time courses corresponding to the spatial activation areas are used as input features, feeds them to a stacked autoencoder then builds a classifier using probabilistic support vector machines. Over the used dataset, around 90% of sensitivity, specificity and accuracy was achieved by our machine learning system. Moreover, the system generalization ability was checked over two different prevalence values, one for the general population and the other for the of high risk population, and the system proved to be very generalizable, especially among the population of high risk. The proposed system generates a full personalized report for each subject, along with identifying the global differences between ASD and typically developed (TD) subjects and its ability to diagnose autism. It shows the impacted areas and the severity of implications. From the clinical aspect, this report is considered very valuable as it helps in both predicting and understanding behavior of autistic subjects. Moreover, it helps in designing a plan for personalized treatment per each individual subject. The proposed work is taking a step towards achieving personalized medicine in autism which is the ultimate goal of our group's research efforts in this area.

Cocaine-Induced Changes in Low-Dimensional Attractors of Local Field Potentials in Optogenetic Mice

Optogenetically evoked local field potential (LFP) recorded from the medial prefrontal cortex (mPFC) of mice during basal conditions and following a systemic cocaine administration were analyzed. Blue light stimuli were delivered to mPFC through a fiber optic every 2 s and each trial was repeated 100 times. As in the previous study, we used a surrogate data method to check that nonlinearity was present in the experimental LFPs and only used the last 1.5 s of steady activity to measure the LFPs phase resetting induced by the brief 10 ms light stimulus. We found that the steady dynamics of the mPFC in response to light stimuli could be reconstructed in a three-dimensional phase space with topologically similar "8"-shaped attractors across different animals. Therefore, cocaine did not change the complexity of the recorded nonlinear data compared to the control case. The phase space of the reconstructed attractor is determined by the LFP time series and its temporally shifted versions by a multiple of some lag time. We also compared the change in the attractor shape between cocaine-injected and control using (1) dendrogram clustering and (2) Frechet distance. We found about 20% overlap between control and cocaine trials when classified using dendrogram method, which suggest that it may be possible to describe mathematically both data sets with the same model and slightly different model parameters. We also found that the lag times are about three times shorter for cocaine trials compared to control. As a result, although the phase space trajectories for control and cocaine may look similar, their dynamics is significantly different.

Multi-modal imaging investigation of anterior cingulate cortex cytoarchitecture in neurodevelopment

Multi-modal imaging may improve our understanding of the relationship between cortical morphology and cytoarchitecture. To this end we integrated the analyses of several magnetic resonance imaging (MRI) and spectroscopy (MRS) metrics within the anterior cingulate cortex (ACC). Considering the ACCs role in neurodevelopmental disorders, we also investigated the association between neuropsychiatric symptoms and the various metrics. T1 and diffusion-weighted MRI and ¹H-MRS (ACC voxel) data along with phenotypic information were acquired from children (8-12 years) with various neurodevelopmental disorders (n=95) and healthy controls (n=50). From within the MRS voxel mean diffusivity (MD) of the grey matter fraction, intrinsic curvature (IC) of the surface and concentrations of creatine, choline, glutamate, N-acetylaspartate and myo-inositol were extracted. Linear models were used to investigate if the neurochemicals predicted MD and IC or if MD predicted IC. Finally, measures of various symptom severities were included to determine the influence of symptoms of neurodevelopmental disorders. All five neurochemicals inversely predicted MD (all p_uncorrected<0.04, β=0.23-0.36). There was no association between IC and MD or IC and the neurochemicals (all p>0.05). Severity of autism symptoms related positively to MD (p_uncorrected=0.002, β=0.39). Our findings support the notion that the neurochemicals relate to cytoarchitecture within the cortex. Additionally, we showed that autism symptoms across participants relate to the ACC cytoarchitecture.

Changes in intrinsic local connectivity after reading intervention in children with autism

Most of the existing behavioral and cognitive intervention programs in autism spectrum disorders (ASD) have not been tested at the neurobiological level, thus falling short of finding quantifiable neurobiological changes underlying behavioral improvement. The current study takes a translational neuroimaging approach to test the impact of a structured visual imagery-based reading intervention on improving reading comprehension and assessing its underlying local neural circuitry. Behavioral and resting state functional MRI (rs-fMRI) data were collected from children with ASD who were randomly assigned to an Experimental group (ASD-EXP; n=14) and a Wait-list control group (ASD-WLC; n=14). Participants went through an established reading intervention training program (Visualizing and Verbalizing for language comprehension and thinking or V/V; 4-h per day, 10-weeks, 200h of face-to-face instruction). Local functional connectivity was examined using a connection density approach from graph theory focusing on brain areas considered part of the Reading Network. The main results are as follows: (I) the ASD-EXP group showed significant improvement, compared to the ASD-WLC group, in their reading comprehension ability evidenced from change in comprehension scores; (II) the ASD-EXP group showed increased local brain connectivity in Reading Network regions compared to the ASD-WLC group post-intervention; (III) intervention-related changes in local brain connectivity were observed in the ASD-EXP from pre to post-intervention; and (IV) improvement in language comprehension significantly predicted changes in local connectivity. The findings of this study provide novel insights into brain plasticity in children with developmental disorders using targeted intervention programs.

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.

Is Synaesthesia More Prevalent in Autism Spectrum Conditions? Only Where There Is Prodigious Talent

Savant syndrome is a condition where prodigious talent co-occurs with developmental difficulties such as autism spectrum conditions (ASC). To better understand savant skills, we previously proposed a link with synaesthesia: that savant syndrome may arise in ASC individuals who also happen to have synaesthesia. A second, unrelated claim is that people with autism may have higher rates of synaesthesia. Here we ask whether synaesthesia is indeed found more often in autism per se, or only in cases where autism co-occurs with savant skills. People with autism in previous studies when tested for synaesthesia were not differentiated into those with and without savant abilities. Here we tested three groups: people with autism who also have savant skills (), people with autism without savant skills (), and controls without autism (). We used a validated test to diagnose grapheme–colour synaesthesia. Results show a significantly higher prevalence of synaesthesia in people with ASC, but only those who also have savant skills. This suggests that synaesthesia in autism is linked to those with savant abilities rather than autism per se. We discuss the role of synaesthesia in the development of prodigious talent.

Autism spectrum disorder in the scope of tactile processing

Sensory processing abnormalities are among the most common behavioral phenotypes seen in autism spectrum disorder (ASD), typically characterized by either over- or under-responsiveness to stimulation. In this review, we focus on tactile processing dysfunction in ASD. We firstly review clinical studies wherein sensitivity to tactile stimuli has traditionally been assessed by self-, parent- and experimenter-reports. We also discuss recent investigations using psychophysical paradigms that gauge individual tactile thresholds. These more experimentally rigorous studies allow for more objective assessments of tactile abnormalities in ASD. However, little is understood about the neurobiological mechanisms underlying these abnormalities, or the link between tactile abnormalities and ASD symptoms. Neurobiological research that has been conducted has pointed toward dysfunction in the excitation/inhibition balance of the central nervous system of those with ASD. This review covers recent efforts that have investigated tactile dysfunction in ASD from clinical and behavioral perspectives, and some of the efforts to link these to neurobiology. On the whole, findings are inconsistent, which can be ascribed to the subjectivity of clinical assessments, the heterogeneity of ASD cohorts, and the diversity of tactile sensitivity measures. Future endeavors into understanding tactile processing differences in ASD will greatly benefit from controlled experiments driven by neurobiological hypotheses.

From High Intellectual Potential to Asperger Syndrome: Evidence for Differences and a Fundamental Overlap-A Systematic Review

Background: An increasing number of clinicians point to similar clinical features between some children with High Intellectual Potential (HIP or "Giftedness" = Total IQ > 2 SD), and children with Autism Spectrum Disorder (ASD) without intellectual or language delay, formerly diagnosed with Asperger Syndrome. Some of these common features are social interaction impairments, special interests, and in some cases high-verbal abilities. The aim of this article is to determine whether these similarities exist at more fundamental levels, other than clinical, and to explore the literature in order to provide empirical support for an overlap between ASD and HIP. Method: First, comparative studies between ASD and HIP children were sought. Because of a lack of data, the respective characteristics of ASD and HIP subjects were explored by a cross-sectional review of different areas of research. Emphasis was placed on psychometric and cognitive evaluations, experimental and developmental assessments, and neurobiological research, following a "bottom-up" procedure. Results: This review highlights the existence of similarities in the neurocognitive, developmental and neurobiological domains between these profiles, which require further study. In addition, the conclusions of several studies show that there are differences between HIP children with a homogeneous Intellectual Quotient profile and children with a heterogeneous Intellectual Quotient profile. Conclusion: HIP seems to cover different developmental profiles, one of which might share features with ASD. A new line of investigation providing a possible starting-point for future research is proposed. Its implications, interesting from both clinical and research perspectives, are discussed.

Brain oscillations and connectivity in autism spectrum disorders (ASD): new approaches to methodology, measurement and modelling

Although atypical social behaviour remains a key characterisation of ASD, the presence of sensory and perceptual abnormalities has been given a more central role in recent classification changes. An understanding of the origins of such aberrations could thus prove a fruitful focus for ASD research. Early neurocognitive models of ASD suggested that the study of high frequency activity in the brain as a measure of cortical connectivity might provide the key to understanding the neural correlates of sensory and perceptual deviations in ASD. As our review shows, the findings from subsequent research have been inconsistent, with a lack of agreement about the nature of any high frequency disturbances in ASD brains. Based on the application of new techniques using more sophisticated measures of brain synchronisation, direction of information flow, and invoking the coupling between high and low frequency bands, we propose a framework which could reconcile apparently conflicting findings in this area and would be consistent both with emerging neurocognitive models of autism and with the heterogeneity of the condition.

Reduced Volume of the Arcuate Fasciculus in Adults with High-Functioning Autism Spectrum Conditions

Atypical language is a fundamental feature of autism spectrum conditions (ASC), but few studies have examined the structural integrity of the arcuate fasciculus, the major white matter tract connecting frontal and temporal language regions, which is usually implicated as the main transfer route used in processing linguistic information by the brain. Abnormalities in the arcuate have been reported in young children with ASC, mostly in low-functioning or non-verbal individuals, but little is known regarding the structural properties of the arcuate in adults with ASC or, in particular, in individuals with ASC who have intact language, such as those with high-functioning autism or Asperger syndrome. We used probabilistic tractography of diffusion-weighted imaging to isolate and scrutinize the arcuate in a mixed-gender sample of 18 high-functioning adults with ASC (17 Asperger syndrome) and 14 age- and IQ-matched typically developing controls. Arcuate volume was significantly reduced bilaterally with clearest differences in the right hemisphere. This finding remained significant in an analysis of all male participants alone. Volumetric reduction in the arcuate was significantly correlated with the severity of autistic symptoms as measured by the Autism-Spectrum Quotient. These data reveal that structural differences are present even in high-functioning adults with ASC, who presented with no clinically manifest language deficits and had no reported developmental language delay. Arcuate structural integrity may be useful as an index of ASC severity and thus as a predictor and biomarker for ASC. Implications for future research are discussed.

Diffusion Tensor Imaging Provides Evidence of Possible Axonal Overconnectivity in Frontal Lobes in Autism Spectrum Disorder Toddlers

BACKGROUND

Theories of brain abnormality in autism spectrum disorder (ASD) have focused on underconnectivity as an explanation for social, language, and behavioral deficits but are based mainly on studies of older autistic children and adults.

METHODS

In 94 ASD and typical toddlers ages 1 to 4 years, we examined the microstructure (indexed by fractional anisotropy) and volume of axon pathways using in vivo diffusion tensor imaging of fronto-frontal, fronto-temporal, fronto-striatal, and fronto-amygdala axon pathways, as well as posterior contrast tracts. Differences between ASD and typical toddlers in the nature of the relationship of age to these measures were tested.

RESULTS

Frontal tracts in ASD toddlers displayed abnormal age-related changes with greater fractional anisotropy and volume than normal at younger ages but an overall slower than typical apparent rate of continued development across the span of years. Posterior cortical contrast tracts had few significant abnormalities.

CONCLUSIONS

Frontal fiber tracts displayed deviant early development and age-related changes that could underlie impaired brain functioning and impact social and communication behaviors in ASD.

Epilepsy and Autism

Epilepsy and autistic spectrum disorder frequently coexist in the same individual. Electroencephalogram (EEG) epileptiform activity is also present at a substantially higher rate in children with autism than normally developing children. As with epilepsy, there are a multitude of genetic and environmental factors that can result in autistic spectrum disorder. There is growing consensus from both animal and clinical studies that autism is a disorder of aberrant connectivity. As measured with functional magnetic resonance imaging (MRI) and EEG, the brain in autistic spectrum disorder may be under- or overconnected or have a mixture of over- and underconnectivity. In the case of comorbid epilepsy and autism, an imbalance of the excitatory/inhibitory (E/I) ratio in selected regions of the brain may drive overconnectivity. Understanding the mechanism by which altered connectivity in individuals with comorbid epilepsy and autistic spectrum disorder results in the behaviors specific to the autistic spectrum disorder remains a challenge.

Mesial temporal lobe and memory function in autism spectrum disorder: an exploration of volumetric findings

Studies have shown that individuals with autism spectrum disorder (ASD) tend to perform significantly below typical developing individuals on standardized measures of memory, even when not significantly different on measures of IQ. The current study sought to examine within ASD whether anatomical correlates of memory performance differed between those with average-to-above-average IQ (AIQ group) and those with low-average to borderline ability (LIQ group) as well as in relations to typically developing comparisons (TDC). Using automated volumetric analyses, we examined regional volume of classic memory areas including the hippocampus, parahippocampal gyrus, entorhinal cortex, and amygdala in an all-male sample AIQ (n = 38) and LIQ (n = 18) individuals with ASD along with 30 typically developing comparisons (TDC). Memory performance was assessed using the Test of Memory and Learning (TOMAL) compared among the groups and then correlated with regional brain volumes. Analyses revealed group differences on almost all facets of memory and learning as assessed by the various subtests of the TOMAL. The three groups did not differ on any region of interest (ROI) memory-related brain volumes. However, significant size-memory function interactions were observed. Negative correlations were found between the volume of the amygdala and composite, verbal, and delayed memory indices for the LIQ ASD group, indicating larger volume related to poorer performance. Implications for general memory functioning and dysfunctional neural connectivity in ASD are discussed.

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

Background

While there is increasing evidence of altered brain connectivity in autism, the degree and direction of these alterations in connectivity and their uniqueness to autism has not been established. The aim of the present study was to compare connectivity in children with autism to that of typically developing controls and children with developmental delay without autism.

Methods

We assessed EEG spectral power, coherence, phase lag, Pearson and partial correlations, and epileptiform activity during the awake, slow wave sleep, and REM sleep states in 137 children aged 2 to 6 years with autism (n = 87), developmental delay without autism (n = 21), or typical development (n = 29).

Findings

We found that brain connectivity, as measured by coherence, phase lag, and Pearson and partial correlations distinguished children with autism from both neurotypical and developmentally delayed children. In general, children with autism had increased coherence which was most prominent during slow wave sleep.

Interpretation

Functional connectivity is distinctly different in children with autism compared to samples with typical development and developmental delay without autism. Differences in connectivity in autism are state and region related. In this study, children with autism were characterized by a dynamically evolving pattern of altered connectivity.

•

We used EEG to examine the connectivity in young children in awake, rapid eye movement, and slow wave sleep (SWS) states.

•

Differences in coherence between the autism group and the other groups were maximal during SWS.

•

Sleep may be the most sensitive time to measure differences in neuro-development before they are observable in behavior.

Shared mechanisms underlie normal healthy sleep and normal brain development. Therefore, we suspect that differences in the way that the brain is behaving during sleep have the potential to tell us about what might be developing incorrectly in people with neurodevelopmental disorders. In addition, sleep evaluations of children allow us to filter out waking distractions, so that we are truly measuring the brain working offline. For instance, the differences in the way the brain was connected that we observed between our three study groups were by far the most notable during slow wave sleep. This finding highlights the importance of taking the state of the brain into account when commenting on the ‘connectedness’ of the brain as a potential biomarker for neurodevelopmental disorders. Future attempts to classify developmental disorders by using differences in connectivity must take into account brain state, whether awake or asleep as well as developmental stage.

Semi-Metric Topology of the Human Connectome: Sensitivity and Specificity to Autism and Major Depressive Disorder

Introduction

The human functional connectome is a graphical representation, consisting of nodes connected by edges, of the inter-relationships of blood oxygenation-level dependent (BOLD) time-series measured by MRI from regions encompassing the cerebral cortices and, often, the cerebellum. Semi-metric analysis of the weighted, undirected connectome distinguishes an edge as either direct (metric), such that there is no alternative path that is accumulatively stronger, or indirect (semi-metric), where one or more alternative paths exist that have greater strength than the direct edge. The sensitivity and specificity of this method of analysis is illustrated by two case-control analyses with independent, matched groups of adolescents with autism spectrum conditions (ASC) and major depressive disorder (MDD).

Results

Significance differences in the global percentage of semi-metric edges was observed in both groups, with increases in ASC and decreases in MDD relative to controls. Furthermore, MDD was associated with regional differences in left frontal and temporal lobes, the right limbic system and cerebellum. In contrast, ASC had a broadly increased percentage of semi-metric edges with a more generalised distribution of effects and some areas of reduction. In summary, MDD was characterised by localised, large reductions in the percentage of semi-metric edges, whilst ASC is characterised by more generalised, subtle increases. These differences were corroborated in greater detail by inspection of the semi-metric backbone for each group; that is, the sub-graph of semi-metric edges present in >90% of participants, and by nodal degree differences in the semi-metric connectome.

Conclusion

These encouraging results, in what we believe is the first application of semi-metric analysis to neuroimaging data, raise confidence in the methodology as potentially capable of detection and characterisation of a range of neurodevelopmental and psychiatric disorders.

Increased Functional Connectivity Between Subcortical and Cortical Resting-State Networks in Autism Spectrum Disorder

IMPORTANCE

Individuals with autism spectrum disorder (ASD) exhibit severe difficulties in social interaction, motor coordination, behavioral flexibility, and atypical sensory processing, with considerable interindividual variability. This heterogeneous set of symptoms recently led to investigating the presence of abnormalities in the interaction across large-scale brain networks. To date, studies have focused either on constrained sets of brain regions or whole-brain analysis, rather than focusing on the interaction between brain networks.

OBJECTIVES

To compare the intrinsic functional connectivity between brain networks in a large sample of individuals with ASD and typically developing control subjects and to estimate to what extent group differences would predict autistic traits and reflect different developmental trajectories.

DESIGN, SETTING, AND PARTICIPANTS

We studied 166 male individuals (mean age, 17.6 years; age range, 7-50 years) diagnosed as having DSM-IV-TR autism or Asperger syndrome and 193 typical developing male individuals (mean age, 16.9 years; age range, 6.5-39.4 years) using resting-state functional magnetic resonance imaging (MRI). Participants were matched for age, IQ, head motion, and eye status (open or closed) in the MRI scanner. We analyzed data from the Autism Brain Imaging Data Exchange (ABIDE), an aggregated MRI data set from 17 centers, made public in August 2012.

MAIN OUTCOMES AND MEASURES

We estimated correlations between time courses of brain networks extracted using a data-driven method (independent component analysis). Subsequently, we associated estimates of interaction strength between networks with age and autistic traits indexed by the Social Responsiveness Scale.

RESULTS

Relative to typically developing control participants, individuals with ASD showed increased functional connectivity between primary sensory networks and subcortical networks (thalamus and basal ganglia) (all t ≥ 3.13, P < .001 corrected). The strength of such connections was associated with the severity of autistic traits in the ASD group (all r ≥ 0.21, P < .0067 corrected). In addition, subcortico-cortical interaction decreased with age in the entire sample (all r ≤ -0.09, P < .012 corrected), although this association was significant only in typically developing participants (all r ≤ -0.13, P < .009 corrected).

CONCLUSIONS AND RELEVANCE

Our results showing ASD-related impairment in the interaction between primary sensory cortices and subcortical regions suggest that the sensory processes they subserve abnormally influence brain information processing in individuals with ASD. This might contribute to the occurrence of hyposensitivity or hypersensitivity and of difficulties in top-down regulation of behavior.

Structural MRI biomarkers of shared pathogenesis in autism spectrum disorder and epilepsy

Etiological factors that contribute to a high comorbidity between autism spectrum disorder (ASD) and epilepsy are the subject of much debate. Does epilepsy cause ASD or are there common underlying brain abnormalities that increase the risk of developing both disorders? This review summarizes evidence from quantitative MRI studies to suggest that abnormalities of brain structure are not necessarily the consequence of ASD and epilepsy but are antecedent to disease expression. Abnormal gray and white matter volumes are present prior to onset of ASD and evident at the time of onset in pediatric epilepsy. Aberrant brain growth trajectories are also common in both disorders, as evidenced by blunted gray matter maturation and white matter maturation. Although the etiological factors that explain these abnormalities are unclear, high heritability estimates for gray matter volume and white matter microstructure demonstrate that genetic factors assert a strong influence on brain structure. In addition, histopathological studies of ASD and epilepsy brain tissue reveal elevated rates of malformations of cortical development (MCDs), such as focal cortical dysplasia and heterotopias, which supports disruption of neuronal migration as a contributing factor. Although MCDs are not always visible on MRI with conventional radiological analysis, quantitative MRI detection methods show high sensitivity to subtle malformations in epilepsy and can be potentially applied to MCD detection in ASD. Such an approach is critical for establishing quantitative neuroanatomic endophenotypes that can be used in genetic research. In the context of emerging drug treatments for seizures and autism symptoms, such as rapamycin and rapalogs, in vivo neuroimaging markers of subtle structural brain abnormalities could improve sample stratification in human clinical trials and potentially extend the range of patients that might benefit from treatment. This article is part of a Special Issue entitled "Autism and Epilepsy".

Atypical functional brain connectivity during rest in autism spectrum disorders

OBJECTIVE

Connectivity atypicalities in autism spectrum disorders (ASD) have been extensively proposed. The default mode network (DMN) is critical in this study, given the insight it provides for long-distance connectivity, and the importance of regions in this network for introspection and social emotion processing, areas affected in ASD. However, study of this network has largely been limited to adults; research earlier in development is lacking. The objective of this study was to examine DMN connectivity in children/adolescents with ASD.

METHODS

A total of 115 children/adolescents, aged 6 to 17 years (71 males with ASD and 44 group age-matched TD males) were included in these analyses. We examined group differences in (1) functional connectivity between the posterior cingulate cortex and regions across the brain, (2) connectivity within the DMN as a function of age and intelligence quotient (IQ), and (3) the association between DMN connectivity and empathic accuracy.

RESULTS

Individuals with ASD, relative to controls, showed either stronger or weaker connectivity between the posterior cingulate cortex (PCC) and DMN regions, depending on the region, but also showed stronger connectivity with non-DMN regions. A significant group-by-age interaction was observed in functional connectivity between the PCC and medial prefrontal cortex; connectivity increased with age in controls, but decreased in individuals with ASD. No effects of IQ were found. There was a significant group difference in the relation between DMN connectivity and empathic accuracy.

INTERPRETATION

Differences in functional connectivity may suggest the presence of neural atypicalities that impact the development of typical connectivity in ASD. In addition to affecting DMN dynamics, these atypicalities may also impact social-cognitive abilities.

Anterior insular cortex regulation in autism spectrum disorders

Autism spectrum disorders (ASDs) comprise a heterogeneous set of neurodevelopmental disorders characterized by dramatic impairments of interpersonal behavior, communication, and empathy. Recent neuroimaging studies suggested that ASD are disorders characterized by widespread abnormalities involving distributed brain network, though clear evidence of differences in large-scale brain network interactions underlying the cognitive and behavioral symptoms of ASD are still lacking. Consistent findings of anterior insula cortex hypoactivation and dysconnectivity during tasks related to emotional and social processing indicates its dysfunctional role in ASD. In parallel, increasing evidence showed that successful control of anterior insula activity can be attained using real-time fMRI paradigms. More importantly, successful regulation of this region was associated with changes in behavior and brain connectivity in both healthy individuals and psychiatric patients. Building on these results we here propose and discuss the use of real-time fMRI neurofeedback in ASD aiming at improving emotional and social behavior.

Abnormalities in the zinc-metalloprotease-BDNF axis may contribute to megalencephaly and cortical hyperconnectivity in young autism spectrum disorder patients

Whereas aberrant brain connectivity is likely the core pathology of autism-spectrum disorder (ASD), studies do not agree as to whether hypo- or hyper-connectivity is the main underlying problem. Recent functional imaging studies have shown that, in most young ASD patients, cerebral cortical regions appear hyperconnected, and cortical thickness/brain size is increased. Collectively, these findings indicate that developing ASD brains may exist in an altered neurotrophic milieu. Consistently, some ASD patients, as well as some animal models of ASD, show increased levels of brain-derived neurotrophic factor (BDNF). However, how BDNF is upregulated in ASD is unknown. To address this question, we propose the novel hypothesis that a putative zinc-metalloprotease-BDNF (ZMB) axis in the forebrain plays a pivotal role in the development of hyperconnectivity and megalencephaly in ASD. We have previously demonstrated that extracellular zinc at micromolar concentrations can rapidly increase BDNF levels and phosphorylate the receptor tyrosine kinase TrkB via the activation of metalloproteases. The role of metalloproteases in ASD is still uncertain, but in fragile X syndrome, a monogenic disease with an autistic phenotype, the levels of MMP are increased. Early exposure to lipopolysaccharides (LPS) and other MMP activators such as organic mercurials also have been implicated in ASD pathogenesis. The resultant increases in BDNF levels at synapses, especially those involved in the zinc-containing, associative glutamatergic system may produce abnormal brain circuit development. Various genetic mutations that lead to ASD are also known to affect BDNF signaling: some down-regulate, and others up-regulate it. We hypothesize that, although both up- and down-regulation of BDNF may induce autism symptoms, only BDNF up-regulation is associated with the hyperconnectivity and large brain size observed in most young idiopathic ASD patients. To test this hypothesis, we propose to examine the ZMB axis in animal models of ASD. Synaptic zinc can be examined by fluorescence zinc staining. MMP activation can be measured by in situ zymography and Western blot analysis. Finally, regional levels of BDNF can be measured. Validating this hypothesis may shed light on the central pathogenic mechanism of ASD and aid in the identification of useful biomarkers and the development of preventive/therapeutic strategies.

Susceptibility to distraction in autism spectrum disorder: probing the integrity of oscillatory alpha-band suppression mechanisms

When attention is directed to one information stream over another, the brain can be configured in advance to selectively process the relevant stream and suppress potentially distracting inputs. One key mechanism of suppression is through the deployment of anticipatory alpha-band (~10 Hz) oscillatory activity, with greater alpha-band power observed in cortical regions that will ultimately process the distracting stream. Atypical attention has been implicated in autism spectrum disorder (ASD), including greater interference by distracting task-irrelevant inputs. Here we tested the integrity of these alpha-band mechanisms in ASD using an intersensory attention task. Electroencephalography (EEG) was recorded while participants were cued on a trial-by-trial basis to selectively deploy attention to the visual or auditory modality in anticipation of a target within the cued modality. Whereas typically developing (TD) children showed the predicted alpha-band modulation, with increased alpha-band power over parieto-occipital scalp when attention was deployed to the auditory compared with the visual modality, this differential pattern was entirely absent at the group level in the ASD cohort. Further, only the ASD group showed impaired performance due to the presence of task-irrelevant sensory information. These data suggest that impaired modulation of alpha-band activity plays a role in increased distraction from extraneous sensory inputs in ASD.

Network-based analysis reveals stronger local diffusion-based connectivity and different correlations with oral language skills in brains of children with high functioning autism spectrum disorders

Neuroimaging has uncovered both long-range and short-range connectivity abnormalities in the brains of individuals with autism spectrum disorders (ASD). However, the precise connectivity abnormalities and the relationship between these abnormalities and cognition and ASD symptoms have been inconsistent across studies. Indeed, studies find both increases and decreases in connectivity, suggesting that connectivity changes in the ASD brain are not merely due to abnormalities in specific connections, but rather, due to changes in the structure of the network in which the brain areas interact (i.e., network topology). In this study, we examined the differences in the network topology between high-functioning ASD patients and age and gender matched typically developing (TD) controls. After quantitatively characterizing the whole-brain connectivity network using diffusion tensor imaging (DTI) data, we searched for brain regions with different connectivity between ASD and TD. A measure of oral language ability was then correlated with the connectivity changes to determine the functional significance of such changes. Whole-brain connectivity measures demonstrated greater local connectivity and shorter path length in ASD as compared to TD. Stronger local connectivity was found in ASD, especially in regions such as the left superior parietal lobule, the precuneus and angular gyrus, and the right supramarginal gyrus. The relationship between oral language ability and local connectivity within these regions was significantly different between ASD and TD. Stronger local connectivity was associated with better performance in ASD and poorer performance in TD. This study supports the notion that increased local connectivity is compensatory for supporting cognitive function in ASD.

Is synesthesia more common in patients with Asperger syndrome?

There is increasing evidence from case reports that synesthesia is more common in individuals with autism spectrum conditions (ASC). Further, genes related to synesthesia have also been found to be linked to ASC and, similar to synaesthetes, individuals with ASC show altered brain connectivity and unusual brain activation during sensory processing. However, up to now a systematic investigation of whether synesthesia is more common in ASC patients is missing. The aim of the current pilot study was to test this hypothesis by investigating a group of patients diagnosed with Asperger Syndrome (AS) using questionnaires and standard consistency tests in order to classify them as grapheme-color synaesthetes. The results indicate that there are indeed many more grapheme-color synaesthetes among AS patients. This finding is discussed in relation to different theories regarding the development of synesthesia as well as altered sensory processing in autism.

Age, plasticity, and homeostasis in childhood brain disorders

It has been widely accepted that the younger the age and/or immaturity of the organism, the greater the brain plasticity, the young age plasticity privilege. This paper examines the relation of a young age to plasticity, reviewing human pediatric brain disorders, as well as selected animal models, human developmental and adult brain disorder studies. As well, we review developmental and childhood acquired disorders that involve a failure of regulatory homeostasis. Our core arguments are as follows:

Local functional overconnectivity in posterior brain regions is associated with symptom severity in autism spectrum disorders

Although growing evidence indicates atypical long-distance connectivity in autism spectrum disorder (ASD), much less is known about local connectivity, despite conjectures that local overconnectivity may be causally involved in the disorder. Using functional connectivity MRI and graph theory, we found that local functional connectivity was atypically increased in adolescents with ASD in temporo-occipital regions bilaterally. Posterior overconnectivity was found to be associated with higher ASD symptom severity, whereas an ASD subsample with low severity showed frontal underconnectivity. The findings suggest links between symptomatology and local connectivity, which vary within the autism spectrum.

Approaches to local connectivity in autism using resting state functional connectivity MRI

While the literature on aberrant long-distance connectivity in autism spectrum disorder (ASD) has grown fast over the past decade, little is known about local connectivity. We used regional homogeneity and local density approaches at different spatial scales to examine local connectivity in 29 children and adolescents with ASD and 29 matched typically developing participants, using resting state functional magnetic resonance imaging data. Across a total of 12 analysis pipelines, the gross pattern of between-group findings was overall stable, with local overconnectivity in the ASD group in occipital and posterior temporal regions and underconnectivity in middle/posterior cingulate, and medial prefrontal regions. This general pattern was confirmed in secondary analyses for low-motion subsamples (n = 20 per group), in which time series segments with >0.25 mm head motion were censored, as well as in an analysis including global signal regression. Local overconnectivity in visual regions appears consistent with preference for local over global visual processing previously reported in ASD, whereas cingulate and medial frontal underconnectivity may relate to aberrant function within the default mode network.

White matter impairment in the speech network of individuals with autism spectrum disorder

Impairments in language and communication are core features of Autism Spectrum Disorder (ASD), and a substantial percentage of children with ASD do not develop speech. ASD is often characterized as a disorder of brain connectivity, and a number of studies have identified white matter impairments in affected individuals. The current study investigated white matter integrity in the speech network of high-functioning adults with ASD. Diffusion tensor imaging (DTI) scans were collected from 18 participants with ASD and 18 neurotypical participants. Probabilistic tractography was used to estimate the connection strength between ventral premotor cortex (vPMC), a cortical region responsible for speech motor planning, and five other cortical regions in the network of areas involved in speech production. We found a weaker connection between the left vPMC and the supplementary motor area in the ASD group. This pathway has been hypothesized to underlie the initiation of speech motor programs. Our results indicate that a key pathway in the speech production network is impaired in ASD, and that this impairment can occur even in the presence of normal language abilities. Therapies that result in normalization of this pathway may hold particular promise for improving speech output in ASD.

•

We used diffusion tensor imaging to measure white matter (WM) tracts in autism.

•

Autistic participants were high-functioning individuals with normal language skills.

•

WM between left supplementary motor and premotor areas is impaired in autism.

•

This tract is believed to be involved in the initiation of speech articulation.

•

Speech production may be impaired in the absence of language deficits in autism.

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

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

Abnormalities in fronto-striatal connectivity within language networks relate to differences in grey-matter heterogeneity in Asperger syndrome

Asperger syndrome (AS) is an Autism Spectrum Disorder (ASD) characterised by qualitative impairment in the development of emotional and social skills with relative preservation of general intellectual abilities, including verbal language. People with AS may nevertheless show atypical language, including rate and frequency of speech production. We previously observed that abnormalities in grey matter homogeneity (measured with texture analysis of structural MR images) in AS individuals when compared with controls are also correlated with the volume of caudate nucleus. Here, we tested a prediction that these distributed abnormalities in grey matter compromise the functional integrity of brain networks supporting verbal communication skills. We therefore measured the functional connectivity between caudate nucleus and cortex during a functional neuroimaging study of language generation (verbal fluency), applying psycho-physiological interaction (PPI) methods to test specifically for differences attributable to grey matter heterogeneity in AS participants. Furthermore, we used dynamic causal modelling (DCM) to characterise the causal directionality of these differences in interregional connectivity during word production. Our results revealed a diagnosis-dependent influence of grey matter heterogeneity on the functional connectivity of the caudate nuclei with right insula/inferior frontal gyrus and anterior cingulate, respectively with the left superior frontal gyrus and right precuneus. Moreover, causal modelling of interactions between inferior frontal gyri, caudate and precuneus, revealed a reliance on bottom-up (stimulus-driven) connections in AS participants that contrasted with a dominance of top-down (cognitive control) connections from prefrontal cortex observed in control participants. These results provide detailed support for previously hypothesised central disconnectivity in ASD and specify discrete brain network targets for diagnosis and therapy in ASD.

•

We used MRI techniques to assess the connectivity in language networks in AS.

•

Grey-matter heterogeneity of MR images correlated with volume of caudate in AS.

•

Hence, caudate nuclei were used as seed ROIs in connectivity analyses: PPI, DCM.

•

Grey-matter heterogeneity differently tuned caudate connectivity in AS, controls.

•

DCM of language circuitry featured bottom-up models in AS and top-down in controls.

Developmental heterochrony and the evolution of autistic perception, cognition and behavior

BACKGROUND

Autism is usually conceptualized as a disorder or disease that involves fundamentally abnormal neurodevelopment. In the present work, the hypothesis that a suite of core autism-related traits may commonly represent simple delays or non-completion of typical childhood developmental trajectories is evaluated.

DISCUSSION

A comprehensive review of the literature indicates that, with regard to the four phenotypes of (1) restricted interests and repetitive behavior, (2) short-range and long-range structural and functional brain connectivity, (3) global and local visual perception and processing, and (4) the presence of absolute pitch, the differences between autistic individuals and typically developing individuals closely parallel the differences between younger and older children.

SUMMARY

The results of this study are concordant with a model of 'developmental heterochrony', and suggest that evolutionary extension of child development along the human lineage has potentiated and structured genetic risk for autism and the expression of autistic perception, cognition and behavior.

Task-related functional connectivity in autism spectrum conditions: an EEG study using wavelet transform coherence

BACKGROUND

Autism Spectrum Conditions (ASC) are a set of pervasive neurodevelopmental conditions characterized by a wide range of lifelong signs and symptoms. Recent explanatory models of autism propose abnormal neural connectivity and are supported by studies showing decreased interhemispheric coherence in individuals with ASC. The first aim of this study was to test the hypothesis of reduced interhemispheric coherence in ASC, and secondly to investigate specific effects of task performance on interhemispheric coherence in ASC.

METHODS

We analyzed electroencephalography (EEG) data from 15 participants with ASC and 15 typical controls, using Wavelet Transform Coherence (WTC) to calculate interhemispheric coherence during face and chair matching tasks, for EEG frequencies from 5 to 40 Hz and during the first 400 ms post-stimulus onset.

RESULTS

Results demonstrate a reduction of interhemispheric coherence in the ASC group, relative to the control group, in both tasks and for all electrode pairs studied. For both tasks, group differences were generally observed after around 150 ms and at frequencies lower than 13 Hz. Regarding within-group task comparisons, while the control group presented differences in interhemispheric coherence between faces and chairs tasks at various electrode pairs (FT7-FT8, TP7-TP8, P7-P8), such differences were only seen for one electrode pair in the ASC group (T7-T8). No significant differences in EEG power spectra were observed between groups.

CONCLUSIONS

Interhemispheric coherence is reduced in people with ASC, in a time and frequency specific manner, during visual perception and categorization of both social and inanimate stimuli and this reduction in coherence is widely dispersed across the brain.Results of within-group task comparisons may reflect an impairment in task differentiation in people with ASC relative to typically developing individuals.Overall, the results of this research support the value of WTC in examining the time-frequency microstructure of task-related interhemispheric EEG coherence in people with ASC.

Task-related functional connectivity in autism spectrum conditions: an EEG study using wavelet transform coherence

Background

Autism Spectrum Conditions (ASC) are a set of pervasive neurodevelopmental conditions characterized by a wide range of lifelong signs and symptoms. Recent explanatory models of autism propose abnormal neural connectivity and are supported by studies showing decreased interhemispheric coherence in individuals with ASC. The first aim of this study was to test the hypothesis of reduced interhemispheric coherence in ASC, and secondly to investigate specific effects of task performance on interhemispheric coherence in ASC.

Methods

We analyzed electroencephalography (EEG) data from 15 participants with ASC and 15 typical controls, using Wavelet Transform Coherence (WTC) to calculate interhemispheric coherence during face and chair matching tasks, for EEG frequencies from 5 to 40 Hz and during the first 400 ms post-stimulus onset.

Results

Results demonstrate a reduction of interhemispheric coherence in the ASC group, relative to the control group, in both tasks and for all electrode pairs studied. For both tasks, group differences were generally observed after around 150 ms and at frequencies lower than 13 Hz. Regarding within-group task comparisons, while the control group presented differences in interhemispheric coherence between faces and chairs tasks at various electrode pairs (FT7-FT8, TP7-TP8, P7-P8), such differences were only seen for one electrode pair in the ASC group (T7-T8). No significant differences in EEG power spectra were observed between groups.

Conclusions

Interhemispheric coherence is reduced in people with ASC, in a time and frequency specific manner, during visual perception and categorization of both social and inanimate stimuli and this reduction in coherence is widely dispersed across the brain.

Results of within-group task comparisons may reflect an impairment in task differentiation in people with ASC relative to typically developing individuals.

Overall, the results of this research support the value of WTC in examining the time-frequency microstructure of task-related interhemispheric EEG coherence in people with ASC.

Diffusion tensor imaging in autism spectrum disorder: a review

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