White matter and development in children with an autism spectrum disorder

Groups and Subgroups in Autism Spectrum Disorder (ASD) Considering an Advanced Integrative Model (AIM)

BACKGROUND

Autism spectrum disorder (ASD) is related to social communication difficulties, repetitive behaviors, and highly restricted interests beginning early in life. Currently, ASD is more diagnosed than in the past, and new models are needed. The Advanced Integrative Model (AIM) is a new model in which genes and concomitant medical problems to diagnosis (CMPD) and the impact of their rigorous and adequate treatment are considered.

METHODS

The role of a dynamic encephalopathy from which the individual response, susceptibilities in the brain and outside the brain, gut barrier and brain-blood-barrier permeabilities, and the plastic nature of the brain is proposed as a tool for diagnosis. The concomitant medical problems (CMP) are those at and outside the brain. The individual response to treatments of CMP is analyzed.

RESULTS

The AIM allows for classification into 3 main groups and 24 subgroups.

CONCLUSIONS

The groups and subgroups in ASD are obtained taking into account CMPD treatments and individual response.

Bridging Genetic Insights with Neuroimaging in Autism Spectrum Disorder-A Systematic Review

Autism Spectrum Disorder (ASD) is an early onset neurodevelopmental disorder characterized by impaired social interaction and communication, and repetitive patterns of behavior. Family studies show that ASD is highly heritable, and hundreds of genes have previously been implicated in the disorder; however, the etiology is still not fully clear. Brain imaging and electroencephalography (EEG) are key techniques that study alterations in brain structure and function. Combined with genetic analysis, these techniques have the potential to help in the clarification of the neurobiological mechanisms contributing to ASD and help in defining novel therapeutic targets. To further understand what is known today regarding the impact of genetic variants in the brain alterations observed in individuals with ASD, a systematic review was carried out using Pubmed and EBSCO databases and following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. This review shows that specific genetic variants and altered patterns of gene expression in individuals with ASD may have an effect on brain circuits associated with face processing and social cognition, and contribute to excitation-inhibition imbalances and to anomalies in brain volumes.

Whole-brain gray matter maturation trajectories associated with autistic traits from adolescence to early adulthood

A growing number of evidence supports a continued distribution of autistic traits in the general population. However, brain maturation trajectories of autistic traits as well as the influence of sex on these trajectories remain largely unknown. We investigated the association of autistic traits in the general population, with longitudinal gray matter (GM) maturation trajectories during the critical period of adolescence. We assessed 709 community-based adolescents (54.7% women) at age 14 and 22. After testing the effect of sex, we used whole-brain voxel-based morphometry to measure longitudinal GM volumes changes associated with autistic traits measured by the Social Responsiveness Scale (SRS) total and sub-scores. In women, we observed that the SRS was associated with slower GM volume decrease globally and in the left parahippocampus and middle temporal gyrus. The social communication sub-score correlated with slower GM volume decrease in the left parahippocampal, superior temporal gyrus, and pallidum; and the social cognition sub-score correlated with slower GM volume decrease in the left middle temporal gyrus, the right ventromedial prefrontal and orbitofrontal cortex. No longitudinal association was found in men. Autistic traits in young women were found to be associated with specific brain trajectories in regions of the social brain and the reward circuit known to be involved in Autism Spectrum Disorder. These findings support both the hypothesis of an earlier GM maturation associated with autistic traits in adolescence and of protective mechanisms in women. They advocate for further studies on brain trajectories associated with autistic traits in women.

EEG Correlates of Cognitive Functions in a Child with ASD and White Matter Signal Abnormalities: A Case Report with Two-and-a-Half-Year Follow-Up

This research aimed to examine the EEG correlates of different stimuli processing instances in a child with ASD and white matter signal abnormalities and to investigate their relationship to the results of behavioral tests. The prospective case study reports two and a half years of follow-up data from a child aged 38 to 66 months. Cognitive, speech-language, sensory, and EEG correlates of auditory-verbal and auditory-visual-verbal information processing were recorded during five test periods, and their mutual interrelation was analyzed. EEG findings revealed no functional theta frequency range redistribution in the frontal regions favoring the left hemisphere during speech processing. The results pointed to a positive linear trend in the relative theta frequency range and a negative linear trend in the relative alpha frequency range when listening to and watching the cartoon. There was a statistically significant correlation between EEG signals and behavioral test results. Based on the obtained results, it may be concluded that EEG signals and their association with the results of behavioral tests should be evaluated with certain restraints considering the characteristics of the stimuli during EEG recording.

The shared white matter developmental trajectory anomalies of attention-deficit/hyperactivity disorder and autism spectrum disorders: A meta-analysis of diffusion tensor imaging studies

Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) show common brain area abnormalities, which may contribute to the high shared co-occurrence symptoms and comorbidity of the two disorders. However, neuroanatomic anomalies in neurodevelopmental disorders may change over the course of development, and the developmental variation of these two disorders is unclear. Our study conducted a systematic literature search of PubMed, Web of Science, and EMBASE databases to identify disorder-shared abnormalities of white matter (WM) from childhood to adulthood in ADHD and ASD. 28 ADHD and 23 ASD datasets were included in this meta-analysis and were analysed by AES-SDM to detect differences in fractional anisotropy in patients compared to typically developing individuals. Our main findings reveal the variable WM developmental trajectories in ADHD and ASD respectively, and the two disorders showed overlapping corpus callosum tract abnormalities in their development from children to adults. Furthermore, the overlapping abnormalities of the corpus callosum tract increased with age, which may be related to their gradually increasing shared symptoms and comorbidity in these two disorders.

Transcriptomic analysis of isolated and pooled human postmortem cerebellar Purkinje cells in autism spectrum disorders

At present, the neuronal mechanisms underlying the diagnosis of autism spectrum disorder (ASD) have not been established. However, studies from human postmortem ASD brains have consistently revealed disruptions in cerebellar circuitry, specifically reductions in Purkinje cell (PC) number and size. Alterations in cerebellar circuitry would have important implications for information processing within the cerebellum and affect a wide range of human motor and non-motor behaviors. Laser capture microdissection was performed to obtain pure PC populations from a cohort of postmortem control and ASD cases and transcriptional profiles were compared. The 427 differentially expressed genes were enriched for gene ontology biological processes related to developmental organization/connectivity, extracellular matrix organization, calcium ion response, immune function and PC signaling alterations. Given the complexity of PCs and their far-ranging roles in response to sensory stimuli and motor function regulation, understanding transcriptional differences in this subset of cerebellar cells in ASD may inform on convergent pathways that impact neuronal function.

Alpha connectivity and inhibitory control in adults with autism spectrum disorder

BACKGROUND

Individuals with autism spectrum disorder (ASD) often report difficulties with inhibition in everyday life. During inhibition tasks, adults with ASD show reduced activation of and connectivity between brain areas implicated in inhibition, suggesting impairments in inhibitory control at the neural level. Our study further investigated these differences by using magnetoencephalography (MEG) to examine the frequency band(s) in which functional connectivity underlying response inhibition occurs, as brain functions are frequency specific, and whether connectivity in certain frequency bands differs between adults with and without ASD.

METHODS

We analysed MEG data from 40 adults with ASD (27 males; 26.94 ± 6.08 years old) and 39 control adults (27 males; 27.29 ± 5.94 years old) who performed a Go/No-go task. The task involved two blocks with different proportions of No-go trials: Inhibition (25% No-go) and Vigilance (75% No-go). We compared whole-brain connectivity in the two groups during correct No-go trials in the Inhibition vs. Vigilance blocks between 0 and 400 ms.

RESULTS

Despite comparable performance on the Go/No-go task, adults with ASD showed reduced connectivity compared to controls in the alpha band (8-14 Hz) in a network with a main hub in the right inferior frontal gyrus. Decreased connectivity in this network predicted more self-reported difficulties on a measure of inhibition in everyday life.

LIMITATIONS

Measures of everyday inhibitory control were not available for all participants, so this relationship between reduced network connectivity and inhibitory control abilities may not be necessarily representative of all adults with ASD or the larger ASD population. Further research with independent samples of adults with ASD, including those with a wider range of cognitive abilities, would be valuable.

CONCLUSIONS

Our findings demonstrate reduced functional brain connectivity during response inhibition in adults with ASD. As alpha-band synchrony has been linked to top-down control mechanisms, we propose that the lack of alpha synchrony observed in our ASD group may reflect difficulties in suppressing task-irrelevant information, interfering with inhibition in real-life situations.

Age-related differences in white matter diffusion measures in autism spectrum condition

BACKGROUND

Autism spectrum condition (ASC) is accompanied by developmental differences in brain anatomy and connectivity. White matter differences in ASC have been widely studied with diffusion imaging but results are heterogeneous and vary across the age range of study participants and varying methodological approaches. To characterize the neurodevelopmental trajectory of white matter maturation, it is necessary to examine a broad age range of individuals on the autism spectrum and typically developing controls, and investigate age × group interactions.

METHODS

Here, we employed a spatially unbiased tract-based spatial statistics (TBSS) approach to examine age-related differences in white matter connectivity in a sample of 41 individuals with ASC, and 41 matched controls between 7-17 years of age.

RESULTS

We found significant age-related differences between the ASC and control group in widespread brain regions. This included age-related differences in the uncinate fasciculus, corticospinal tract, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, anterior thalamic radiation, superior longitudinal fasciculus and forceps major. Measures of fractional anisotropy (FA) were significantly positively associated with age in both groups. However, this relationship was significantly stronger in the ASC group relative to controls. Measures of radial diffusivity (RD) were significantly negatively associated with age in both groups, but this relationship was significantly stronger in the ASC group relative to controls.

LIMITATIONS

The generalisability of our findings is limited by the restriction of the sample to right-handed males with an IQ > 70. Furthermore, a longitudinal design would be required to fully investigate maturational processes across this age group.

CONCLUSIONS

Taken together, our findings suggest that autistic males have an altered trajectory of white matter maturation relative to controls. Future longitudinal analyses are required to further characterize the extent and time course of these differences.

Deviation from normative brain development is associated with symptom severity in autism spectrum disorder

Background

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition. The degree to which the brain development in ASD deviates from typical brain development, and how this deviation relates to observed behavioral outcomes at the individual level are not well-studied. We hypothesize that the degree of deviation from typical brain development of an individual with ASD would relate to observed symptom severity.

Methods

The developmental changes in anatomical (cortical thickness, surface area, and volume) and diffusion metrics (fractional anisotropy and apparent diffusion coefficient) were compared between a sample of ASD (n = 247) and typically developing children (TDC) (n = 220) aged 6-25. Machine learning was used to predict age (brain age) from these metrics in the TDC sample, to define a normative model of brain development. This model was then used to compute brain age in the ASD sample. The difference between chronological age and brain age was considered a developmental deviation index (DDI), which was then correlated with ASD symptom severity.

Results

Machine learning model trained on all five metrics accurately predicted age in the TDC (r = 0.88) and the ASD (r = 0.85) samples, with dominant contributions to the model from the diffusion metrics. Within the ASD group, the DDI derived from fractional anisotropy was correlated with ASD symptom severity (r = - 0.2), such that individuals with the most advanced brain age showing the lowest severity, and individuals with the most delayed brain age showing the highest severity.

Limitations

This work investigated only linear relationships between five specific brain metrics and only one measure of ASD symptom severity in a limited age range. Reported effect sizes are moderate. Further work is needed to investigate developmental differences in other age ranges, other aspects of behavior, other neurobiological measures, and in an independent sample before results can be clinically applicable.

Conclusions

Findings demonstrate that the degree of deviation from typical brain development relates to ASD symptom severity, partially accounting for the observed heterogeneity in ASD. Our approach enables characterization of each individual with reference to normative brain development and identification of distinct developmental subtypes, facilitating a better understanding of developmental heterogeneity in ASD.

Maternal stress in Shank3ex4-9 mice increases pup-directed care and alters brain white matter in male offspring

Gene-environment interactions contribute to the risk for Autism Spectrum Disorder (ASD). Among environmental factors, prenatal exposure to stress may increase the risk for ASD. To examine if there is an interaction between exposure to maternal stress and reduced dosage or loss of Shank3, wild-type (WT), heterozygous (HET) and homozygous (HOM) female mice carrying a deletion of exons four through nine of Shank3 (Shank3^ex4-9) were exposed to chronic unpredictable mild stress (CUMS) from prior to conception throughout gestation. This study examined maternal care of these dams and the white matter microstructure in the brains of their adult male offspring. Overall, our findings suggest that maternal exposure to CUMS increased pup-directed care for dams of all three genotypes. Compared to WT and HET dams, HOM dams also exhibited increased maternal care behaviors with increased time spent in the nest and reduced cage exploration, regardless of exposure to CUMS. Diffusion tensor imaging showed higher mean fractional anisotropy in the hippocampal stratum radiatum of WT and HOM male offspring from dams exposed to CUMS and HOM offspring from unexposed dams, compared to WT male offspring from unexposed dams. These data support that CUMS in Shank3-mutant dams results in subtle maternal care alterations and long-lasting changes in the white matter of the hippocampus of their offspring.

Brain Connectivity Reflected in Electroencephalogram Coherence in Individuals With Autism: A Meta-Analysis

INTRODUCTION

Many theories have been proposed about the etiology of autism. One is related to brain connectivity in patients with autism. Several studies have reported brain connectivity changes in autism disease. This study was performed on Electroencephalogram (EEG) studies that evaluated patients with autism, using functional brain connectivity, and compared them with typically-developing individuals.

METHODS

Three scientific databases of ScienceDirect, Medline (PubMed), and BioMed Central were systematically searched through their online search engines. Comprehensive Meta-analysis software analyzed the obtained data.

RESULTS

The systematic search led to 10 papers, in which EEG coherence was used to obtain the brain connectivity of people with autism. To determine the effect size, Cohen's d parameter was used. In the first meta-analysis, the study of the maximum effect size was considered, and all significant effect sizes were evaluated in the second meta-analysis. The effect size was assessed using a random-effects model in both meta-analyses. The results of the first meta-analysis indicated that heterogeneity was not present among the studies (Q=13.345, P>0.1). The evaluation of all effect sizes in the second meta-analysis showed a significant lack of homogeneity among the studies (Q=56.984, P=0.0001).

CONCLUSION

On the whole, autism was found to be related to neural connectivity, and the present research showed the difference in the EEG coherence of people with autism and healthy people. These conclusions require further studies with more extensive data, considering different brain regions, and novel analysis techniques for assessing brain connectivity.

Metabolic profiling in children with autism spectrum disorder with and without mental regression: preliminary results from a cross-sectional case-control study

INTRODUCTION

It is challenging to establish the mechanisms involved in the variety of well-defined clinical phenotypes in autism spectrum disorder (ASD) and the pathways involved in their pathogeneses.

OBJECTIVES

The aim of the present study was to evaluate the metabolomic profiles of children with ASD subclassified by mental regression (AR) phenotype and with no regression (ANR).

METHODS

The present study was a cross-sectional case-control study. Thirty children aged 2-6 years with ASD were included: 15 with ANR and 15 with AR. In addition, a control group of 30 normally developing children was selected and matched to the ASD group by sex and age. Plasma samples were analyzed with a metabolomics single platform methodology based on liquid chromatography-mass spectrometry. Univariate and multivariate analysis, including orthogonal partial least squares-discriminant analysis modeling and Shared-and-Unique-Structures plots, were performed using MetaboAnalyst 4.0 and SIMCA-P 15. The primary endpoint was the metabolic signature profiling among healthy children and autistic children and their subgroups.

RESULTS

Metabolomic profiles of 30 healthy children, 15 ANR and 15 AR were compared. Several differences between healthy children and children with ASD were detected, involving mainly amino acid, lipid and nicotinamide metabolism. Furthermore, we report subtle differences between the ANR and AR groups.

CONCLUSIONS

In this study, we report, for the first time, the plasmatic metabolomic profiles of children with ASD, including two different phenotypes based on mental regression status. The use of a liquid chromatography-mass spectrometry platform approach for metabolomics in ASD children using plasma appears to be very efficient and adds further support to previous findings in urine. Furthermore, the present study documents several changes related to amino acid, NAD⁺ and lipid metabolism that, in some cases, such as arginine and glutamate pathway alterations, seem to be associated with the AR phenotype. Further targeted analyses are needed in a larger cohort to validate the results presented herein.

Is functional brain connectivity atypical in autism? A systematic review of EEG and MEG studies

BACKGROUND

Although it is well recognized that autism is associated with altered patterns of over- and under-connectivity, specifics are still a matter of debate. Little has been done so far to synthesize available literature using whole-brain electroencephalography (EEG) and magnetoencephalography (MEG) recordings.

OBJECTIVES

1) To systematically review the literature on EEG/MEG functional and effective connectivity in autism spectrum disorder (ASD), 2) to synthesize and critically appraise findings related with the hypothesis that ASD is characterized by long-range underconnectivity and local overconnectivity, and 3) to provide, based on the literature, an analysis of tentative factors that are likely to mediate association between ASD and atypical connectivity (e.g., development, topography, lateralization).

METHODS

Literature reviews were done using PubMed and PsychInfo databases. Abstracts were screened, and only relevant articles were analyzed based on the objectives of this paper. Special attention was paid to the methodological characteristics that could have created variability in outcomes reported between studies.

RESULTS

Our synthesis provides relatively strong support for long-range underconnectivity in ASD, whereas the status of local connectivity remains unclear. This observation was also mirrored by a similar relationship with lower frequencies being often associated with underconnectivity and higher frequencies being associated with both under- and over-connectivity. Putting together these observations, we propose that ASD is characterized by a general trend toward an under-expression of lower-band wide-spread integrative processes compensated by more focal, higher-frequency, locally specialized, and segregated processes. Further investigation is, however, needed to corroborate the conclusion and its generalizability across different tasks. Of note, abnormal lateralization in ASD, specifically an elevated left-over-right EEG and MEG functional connectivity ratio, has been also reported consistently across studies.

CONCLUSIONS

The large variability in study samples and methodology makes a systematic quantitative analysis (i.e. meta-analysis) of this body of research impossible. Nevertheless, a general trend supporting the hypothesis of long-range functional underconnectivity can be observed. Further research is necessary to more confidently determine the status of the hypothesis of short-range overconnectivity. Frequency-band specific patterns and their relationships with known symptoms of autism also need to be further clarified.

An In vivo Multi-Modal Structural Template for Neonatal Piglets Using High Angular Resolution and Population-Based Whole-Brain Tractography

An increasing number of applications use the postnatal piglet model in neuroimaging studies, however, these are based primarily on T1 weighted image templates. There is a growing need for a multimodal structural brain template for a comprehensive depiction of the piglet brain, particularly given the growing applications of diffusion weighted imaging for characterizing tissue microstructures and white matter organization. In this study, we present the first multimodal piglet structural brain template which includes a T1 weighted image with tissue segmentation probability maps, diffusion weighted metric templates with multiple diffusivity maps, and population-based whole-brain fiber tracts for postnatal piglets. These maps provide information about the integrity of white matter that is not available in T1 images alone. The availability of this diffusion weighted metric template will contribute to the structural imaging analysis of the postnatal piglet brain, especially models that are designed for the study of white matter diseases. Furthermore, the population-based whole-brain fiber tracts permit researchers to visualize the white matter connections in the piglet brain across subjects, guiding the delineation of a specific white matter region for structural analysis where current diffusion data is lacking. Researchers are able to augment the tracts by merging tracts from their own data to the population-based fiber tracts and thus improve the confidence of the population-wise fiber distribution.

Potential serum biomarkers from a metabolomics study of autism

BACKGROUND

Early detection and diagnosis are very important for autism. Current diagnosis of autism relies mainly on some observational questionnaires and interview tools that may involve a great variability. We performed a metabolomics analysis of serum to identify potential biomarkers for the early diagnosis and clinical evaluation of autism.

METHODS

We analyzed a discovery cohort of patients with autism and participants without autism in the Chinese Han population using ultra-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry (UPLC/Q-TOF MS/MS) to detect metabolic changes in serum associated with autism. The potential metabolite candidates for biomarkers were individually validated in an additional independent cohort of cases and controls. We built a multiple logistic regression model to evaluate the validated biomarkers.

RESULTS

We included 73 patients and 63 controls in the discovery cohort and 100 cases and 100 controls in the validation cohort. Metabolomic analysis of serum in the discovery stage identified 17 metabolites, 11 of which were validated in an independent cohort. A multiple logistic regression model built on the 11 validated metabolites fit well in both cohorts. The model consistently showed that autism was associated with 2 particular metabolites: sphingosine 1-phosphate and docosahexaenoic acid.

LIMITATIONS

While autism is diagnosed predominantly in boys, we were unable to perform the analysis by sex owing to difficulty recruiting enough female patients. Other limitations include the need to perform test-retest assessment within the same individual and the relatively small sample size.

CONCLUSION

Two metabolites have potential as biomarkers for the clinical diagnosis and evaluation of autism.

Developmental differences in intra-individual variability in children with ADHD and ASD

BACKGROUND

Intra-individual variability reflects temporal variation within an individual's performance on a cognitive task. Children with developmental disorders, such as ADHD and ASD show increased levels of intra-individual variability. In typical development, intra-individual variability decreases sharply between the ages 6 and 20. The tight link between intra-individual variability and age has led to the suggestion that it may be marker of neural development. As there is accumulating evidence that ADHD and ASD are characterised by atypical neurodevelopmental trajectories, we set out to explore developmental changes in intra-individual variability in subjects with ADHD and ASD.

METHOD

We used propensity score matching to match a cross-sectional sample of children with ADHD, ASD and control subjects (N = 405, aged 6-19 years old) for age, IQ and gender. We used ex-Gaussian distribution parameters to characterise intra-individual variability on fast responses (sigma) and slow responses (tau).

RESULT

Results showed that there was a similar decrease in mean response times with age across groups, and an interaction between age and group for measures of variability, where there was a much lower rate of change in the variability parameters (sigma and tau) for subjects with ASD compared with the other two groups. Subjects with ADHD had higher intra-individual variability, reflected by both sigma and tau, but the rate of decrease in variability with age was similar to that of the controls.

CONCLUSION

These results suggest that subjects with ADHD, ASD and controls differ in the rate at which intra-individual variability decreases during development, and support the idea that intra-individual variability may be a marker of neural development, mimicking the neurodevelopmental changes in these disorders.

The autism puzzle: Diffuse but not pervasive neuroanatomical abnormalities in children with ASD

Autism Spectrum Disorder (ASD) is a clinically diagnosed, heterogeneous, neurodevelopmental condition, whose underlying causes have yet to be fully determined. A variety of studies have investigated either cortical, subcortical, or cerebellar anatomy in ASD, but none have conducted a complete examination of all neuroanatomical parameters on a single, large cohort. The current study provides a comprehensive examination of brain development of children with ASD between the ages of 4 and 18 years who are carefully matched for age and sex with typically developing controls at a ratio of one-to-two. Two hundred and ten magnetic resonance images were examined from 138 Control (116 males and 22 females) and 72 participants with ASD (61 males and 11 females). Cortical segmentation into 78 brain-regions and 81,924 vertices was conducted with CIVET which facilitated a region-of-interest- (ROI-) and vertex-based analysis, respectively. Volumes for the cerebellum, hippocampus, striatum, pallidum, and thalamus and many associated subregions were derived using the MAGeT Brain algorithm. The study reveals cortical, subcortical and cerebellar differences between ASD and Control group participants. Diagnosis, diagnosis-by-age, and diagnosis-by-sex interaction effects were found to significantly impact total brain volume but not total surface area or mean cortical thickness of the ASD participants. Localized (vertex-based) analysis of cortical thickness revealed no significant group differences, even when age, age-range, and sex were used as covariates. Nonetheless, the region-based cortical thickness analysis did reveal regional changes in the left orbitofrontal cortex and left posterior cingulate gyrus, both of which showed reduced age-related cortical thinning in ASD. Our finding of region-based differences without significant vertex-based results likely indicates non-focal effects spanning the entirety of these regions. The hippocampi, thalamus, and globus pallidus, were smaller in volume relative to total cerebrum in the ASD participants. Various sub-structures showed an interaction of diagnosis-by-age, diagnosis-by-sex, and diagnosis-by-age-range, in the case where age was divided into childhood (age < 12) and adolescence (12 < age < 18). This is the most comprehensive imaging-based neuro-anatomical pediatric and adolescent ASD study to date. These data highlight the neurodevelopmental differences between typically developing children and those with ASD, and support aspects of the hypothesis of abnormal neuro-developmental trajectory of the brain in ASD.

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Thorough analysis of neuroanatomical patterns in children and adolescents with ASD

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Cortical, subcortical, and cerebellar development is assessed.

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Total brain volume is smaller in males with ASD compared with Controls.

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Cortical thickness in ASD does not decrease between childhood and adulthood.

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Hippocampi, thalamus, globus pallidus and cerebellum are relatively smaller in ASD.

Neurophysiological indices of atypical auditory processing and multisensory integration are associated with symptom severity in autism

Atypical processing and integration of sensory inputs are hypothesized to play a role in unusual sensory reactions and social-cognitive deficits in autism spectrum disorder (ASD). Reports on the relationship between objective metrics of sensory processing and clinical symptoms, however, are surprisingly sparse. Here we examined the relationship between neurophysiological assays of sensory processing and (1) autism severity and (2) sensory sensitivities, in individuals with ASD aged 6-17. Multiple linear regression indicated significant associations between neural markers of auditory processing and multisensory integration, and autism severity. No such relationships were apparent for clinical measures of visual/auditory sensitivities. These data support that aberrant early sensory processing contributes to autism symptoms, and reveal the potential of electrophysiology to objectively subtype autism.

EEG hyper-connectivity in high-risk infants is associated with later autism

Background

It has been previously reported that structural and functional brain connectivity in individuals with autism spectrum disorders (ASD) is atypical and may vary with age. However, to date, no measures of functional connectivity measured within the first 2 years have specifically associated with a later ASD diagnosis.

Methods

In the present study, we analyzed functional brain connectivity in 14-month-old infants at high and low familial risk for ASD using electroencephalography (EEG). EEG was recorded while infants attended to videos. Connectivity was assessed using debiased weighted phase lag index (dbWPLI). At 36 months, the high-risk infants were assessed for symptoms of ASD.

Results

As a group, high-risk infants who were later diagnosed with ASD demonstrated elevated phase-lagged alpha-range connectivity as compared to both low-risk infants and high-risk infants who did not go on to ASD. Hyper-connectivity was most prominent over frontal and central areas. The degree of hyper-connectivity at 14 months strongly correlated with the severity of restricted and repetitive behaviors in participants with ASD at 3 years. These effects were not attributable to differences in behavior during the EEG session or to differences in spectral power.

Conclusions

The results suggest that early hyper-connectivity in the alpha frequency range is an important feature of the ASD neurophysiological phenotype.

Electronic supplementary material

The online version of this article (doi:10.1186/1866-1955-6-40) contains supplementary material, which is available to authorized users.

Reduced beta connectivity during emotional face processing in adolescents with autism

Background

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impairments in social cognition. The biological basis of deficits in social cognition in ASD, and their difficulty in processing emotional face information in particular, remains unclear. Atypical communication within and between brain regions has been reported in ASD. Interregional phase-locking is a neurophysiological mechanism mediating communication among brain areas and is understood to support cognitive functions. In the present study we investigated interregional magnetoencephalographic phase synchronization during the perception of emotional faces in adolescents with ASD.

Methods

A total of 22 adolescents with ASD (18 males, mean age =14.2 ± 1.15 years, 22 right-handed) with mild to no cognitive delay and 17 healthy controls (14 males, mean age =14.4 ± 0.33 years, 16 right-handed) performed an implicit emotional processing task requiring perception of happy, angry and neutral faces while we recorded neuromagnetic signals. The faces were presented rapidly (80 ms duration) to the left or right of a central fixation cross and participants responded to a scrambled pattern that was presented concurrently on the opposite side of the fixation point. Task-dependent interregional phase-locking was calculated among source-resolved brain regions.

Results

Task-dependent increases in interregional beta synchronization were observed. Beta-band interregional phase-locking in adolescents with ASD was reduced, relative to controls, during the perception of angry faces in a distributed network involving the right fusiform gyrus and insula. No significant group differences were found for happy or neutral faces, or other analyzed frequency ranges. Significant reductions in task-dependent beta connectivity strength, clustering and eigenvector centrality (all P <0.001) in the right insula were found in adolescents with ASD, relative to controls.

Conclusions

Reduced beta synchronization may reflect inadequate recruitment of task-relevant networks during emotional face processing in ASD. The right insula, specifically, was a hub of reduced functional connectivity and may play a prominent role in the inability to effectively extract emotional information from faces. These findings suggest that functional disconnection in brain networks mediating emotional processes may contribute to deficits in social cognition in this population.

Electronic supplementary material

The online version of this article (doi:10.1186/2040-2392-5-51) contains supplementary material, which is available to authorized users.

A diffusion-tensor-based white matter atlas for rhesus macaques

Atlases of key white matter (WM) structures in humans are widely available, and are very useful for region of interest (ROI)-based analyses of WM properties. There are histology-based atlases of cortical areas in the rhesus macaque, but none currently of specific WM structures. Since ROI-based analysis of WM pathways is also useful in studies using rhesus diffusion tensor imaging (DTI) data, we have here created an atlas based on a publicly available DTI-based template of young rhesus macaques. The atlas was constructed to mimic the structure of an existing human atlas that is widely used, making results translatable between species. Parcellations were carefully hand-drawn on a principle-direction color-coded fractional anisotropy image of the population template. The resulting atlas can be used as a reference to which registration of individual rhesus data can be performed for the purpose of white-matter parcellation. Alternatively, specific ROIs from the atlas may be warped into individual space to be used in ROI-based group analyses. This atlas will be made publicly available so that it may be used as a resource for DTI studies of rhesus macaques.

Neural substrates of numerosity estimation in autism

Visual skills, including numerosity estimation are reported to be superior in autism spectrum disorders (ASD). This phenomenon is attributed to individuals with ASD processing local features, rather than the Gestalt. We examined the neural correlates of numerosity estimation in adults with and without ASD, to disentangle perceptual atypicalities from numerosity processing. Fourteen adults with ASD and matched typically developed (TD) controls estimated the number of dots (80-150) arranged either randomly (local information) or in meaningful patterns (global information) while brain activity was recorded with magnetoencephalography (MEG). Behavioral results showed no significant group difference in the errors of estimation. However, numerical estimation in ASD was more variable across numerosities than TD and was not affected by the global arrangement of the dots. At 80-120 ms, MEG analyses revealed early significant differences (TD > ASD) in source amplitudes in visual areas, followed from 120 to 400 ms by group differences in temporal, and then parietal regions. After 400 ms, a source was found in the superior frontal gyrus in TD only. Activation in temporal areas was differently sensitive to the global arrangement of dots in TD and ASD. MEG data show that individuals with autism exhibit widespread functional abnormalities. Differences in temporal regions could be linked to atypical global perception. Occipital followed by parietal and frontal differences might be driven by abnormalities in the processing and conversion of visual input into a number-selective neural code and complex cognitive decisional stages. These results suggest overlapping atypicalities in sensory, perceptual and number-related processing during numerosity estimation in ASD.

Reduced beta band connectivity during number estimation in autism

Recent evidence suggests that disruption of integrative processes in sensation and perception may play a critical role in cognitive and behavioural atypicalities characteristic of ASD. In line with this, ASD is associated with altered structural and functional brain connectivity and atypical patterns of inter-regional communication which have been proposed to contribute to cognitive difficulties prevalent in this group. The present MEG study used atlas-guided source space analysis of inter-regional phase synchronization in ASD participants, as well as matched typically developing controls, during a dot number estimation task. This task included stimuli with globally integrated forms (animal shapes) as well as randomly-shaped stimuli which lacked a coherent global pattern. Early task-dependent increases in inter-regional phase synchrony in theta, alpha and beta frequency bands were observed. Reduced long-range beta-band phase synchronization was found in participants with ASD at 70-145 ms during presentation of globally coherent dot patterns. This early reduction in task-dependent inter-regional connectivity encompassed numerous areas including occipital, parietal, temporal, and frontal lobe regions. These results provide the first evidence for inter-regional phase synchronization during numerosity estimation, as well as its alteration in ASD, and suggest that problems with communication among brain areas may contribute to difficulties with integrative processes relevant to extraction of meaningful 'Gestalt' features in this population.

Neuromagnetic vistas into typical and atypical development of frontal lobe functions

The frontal lobes are involved in many higher-order cognitive functions such as social cognition executive functions and language and speech. These functions are complex and follow a prolonged developmental course from childhood through to early adulthood. Magnetoencephalography (MEG) is ideal for the study of development of these functions, due to its combination of temporal and spatial resolution which allows the determination of age-related changes in both neural timing and location. There are several challenges for MEG developmental studies: to design tasks appropriate to capture the neurodevelopmental trajectory of these cognitive functions, and to develop appropriate analysis strategies to capture various aspects of neuromagnetic frontal lobe activity. Here, we review our MEG research on social and executive functions, and speech in typically developing children and in two clinical groups – children with autism spectrum disorder and children born very preterm. The studies include facial emotional processing, inhibition, visual short-term memory, speech production, and resting-state networks. We present data from event-related analyses as well as on oscillations and connectivity analyses and review their contributions to understanding frontal lobe cognitive development. We also discuss the challenges of testing young children in the MEG and the development of age-appropriate technologies and paradigms.

Coordinated Information Generation and Mental Flexibility: Large-Scale Network Disruption in Children with Autism

Autism spectrum disorder (ASD) includes deficits in social cognition, communication, and executive function. Recent neuroimaging studies suggest that ASD disrupts the structural and functional organization of brain networks and, presumably, how they generate information. Here, we relate deficits in an aspect of cognitive control to network-level disturbances in information processing. We recorded magnetoencephalography while children with ASD and typically developing controls performed a set-shifting task designed to test mental flexibility. We used multiscale entropy (MSE) to estimate the rate at which information was generated in a set of sources distributed across the brain. Multivariate partial least-squares analysis revealed 2 distributed networks, operating at fast and slow time scales, that respond completely differently to set shifting in ASD compared with control children, indicating disrupted temporal organization within these networks. Moreover, when typically developing children engaged these networks, they achieved faster reaction times. When children with ASD engaged these networks, there was no improvement in performance, suggesting that the networks were ineffective in children with ASD. Our data demonstrate that the coordination and temporal organization of large-scale neural assemblies during the performance of cognitive control tasks is disrupted in children with ASD, contributing to executive function deficits in this group.

Using quantitative and analytic EEG methods in the understanding of connectivity in autism spectrum disorders: a theory of mixed over- and under-connectivity

Neuroimaging technologies and research has shown that autism is largely a disorder of neuronal connectivity. While advanced work is being done with fMRI, MRI-DTI, SPECT and other forms of structural and functional connectivity analyses, the use of EEG for these purposes is of additional great utility. Cantor et al. (1986) were the first to examine the utility of pairwise coherence measures for depicting connectivity impairments in autism. Since that time research has shown a combination of mixed over and under-connectivity that is at the heart of the primary symptoms of this multifaceted disorder. Nevertheless, there is reason to believe that these simplistic pairwise measurements under represent the true and quite complicated picture of connectivity anomalies in these persons. We have presented three different forms of multivariate connectivity analysis with increasing levels of sophistication (including one based on principle components analysis, sLORETA source coherence, and Granger causality) to present a hypothesis that more advanced statistical approaches to EEG coherence analysis may provide more detailed and accurate information than pairwise measurements. A single case study is examined with findings from MR-DTI, pairwise and coherence and these three forms of multivariate coherence analysis. In this case pairwise coherences did not resemble structural connectivity, whereas multivariate measures did. The possible advantages and disadvantages of different techniques are discussed. Future work in this area will be important to determine the validity and utility of these techniques.

Abnormal cingulum bundle development in autism: a probabilistic tractography study

There is now considerable evidence that white matter abnormalities play a role in the neurobiology of autism. Little research has been directed, however, at understanding (a) typical white matter development in autism and how this relates to neurocognitive impairments observed in the disorder. In this study we used probabilistic tractography to identify the cingulum bundle in 21 adolescents and young adults with Autism Spectrum Disorder (ASD), and 21 age- and sex-matched healthy volunteers. We investigated group differences in the relationships between age and fractional anisotropy, a putative measure of white matter integrity, within the cingulum bundle. Moreover, in a preliminary investigation, we examined the relationship between cingulum fractional anisotropy and executive functioning using the Behavior Rating Inventory of Executive Function (BRIEF). The ASD participants demonstrated significantly lower fractional anisotropy within the cingulum bundle compared to the typically developing volunteers. There was a significant group-by-age interaction such that the ASD group did not show the typical age-associated increases in fractional anisotropy observed among healthy individuals. Moreover, lower fractional anisotropy within the cingulum bundle was associated with worse BRIEF behavioral regulation index scores in the ASD group. The current findings implicate a dysregulation in cingulum bundle white matter development occurring in late adolescence and early adulthood in ASD, and suggest that greater disturbances in this trajectory are associated with executive dysfunction in ASD.

A comparison of neuroimaging findings in childhood onset schizophrenia and autism spectrum disorder: a review of the literature

BACKGROUND

Autism spectrum disorder (ASD) and childhood onset schizophrenia (COS) are pediatric neurodevelopmental disorders associated with significant morbidity. Both conditions are thought to share an underlying genetic architecture. A comparison of neuroimaging findings across ASD and COS with a focus on altered neurodevelopmental trajectories can shed light on potential clinical biomarkers and may highlight an underlying etiopathogenesis.

METHODS

A comprehensive review of the medical literature was conducted to summarize neuroimaging data with respect to both conditions in terms of structural imaging (including volumetric analysis, cortical thickness and morphology, and region of interest studies), white matter analysis (include volumetric analysis and diffusion tensor imaging) and functional connectivity.

RESULTS

In ASD, a pattern of early brain overgrowth in the first few years of life is followed by dysmaturation in adolescence. Functional analyses have suggested impaired long-range connectivity as well as increased local and/or subcortical connectivity in this condition. In COS, deficits in cerebral volume, cortical thickness, and white matter maturation seem most pronounced in childhood and adolescence, and may level off in adulthood. Deficits in local connectivity, with increased long-range connectivity have been proposed, in keeping with exaggerated cortical thinning.

CONCLUSION

The neuroimaging literature supports a neurodevelopmental origin of both ASD and COS and provides evidence for dynamic changes in both conditions that vary across space and time in the developing brain. Looking forward, imaging studies which capture the early post natal period, which are longitudinal and prospective, and which maximize the signal to noise ratio across heterogeneous conditions will be required to translate research findings into a clinical environment.

Reduced Theta Connectivity during Set-Shifting in Children with Autism

Autism spectrum disorder (ASD) is a characterized by deficits in social cognition and executive function. An area of particular difficulty for children with ASD is cognitive flexibility, such as the ability to shift between attentional or response sets. The biological basis of such deficits remains poorly understood, although atypical development of structural and functional brain connectivity have been reported in ASD, suggesting that disruptions of normal patterns of inter-regional communication may contribute to cognitive problems in this group. The present magnetoencephalography study measured inter-regional phase synchronization while children with ASD and typically developing matched controls (6–14 years of age) performed a set-shifting task. Reduced theta-band phase synchronization was observed in children with ASD during extradimensional set-shifting. This reduction in task-dependent inter-regional connectivity encompassed numerous areas including multiple frontal lobe regions, and indicates that problems with communication among brain areas may contribute to difficulties with executive function in ASD.

Neuropsychological investigation of motor impairments in autism

It is unclear how standardized neuropsychological measures of motor function relate to brain volumes of motor regions in autism spectrum disorder (ASD). An all-male sample composed of 59 ASD and 30 controls (ages 5-33 years) completed three measures of motor function: strength of grip (SOG), finger tapping test (FTT), and grooved pegboard test (GPT). Likewise, all participants underwent magnetic resonance imaging with region of interest (ROI) volumes obtained to include the following regions: motor cortex (precentral gyrus), somatosensory cortex (postcentral gyrus), thalamus, basal ganglia, cerebellum, and caudal middle frontal gyrus. These traditional neuropsychological measures of motor function are assumed to differ in motor complexity, with GPT requiring the most followed by FTT and SOG. Performance by ASD participants on the GPT and FTT differed significantly from that of controls, with the largest effect size differences observed on the more complex GPT task. Differences on the SOG task between the two groups were nonsignificant. Since more complex motor tasks tap more complex networks, poorer GPT performance by those with ASD may reflect less efficient motor networks. There was no gross pathology observed in classic motor areas of the brain in ASD, as ROI volumes did not differ, but FTT was negatively related to motor cortex volume in ASD. The results suggest a hierarchical motor disruption in ASD, with difficulties evident only in more complex tasks as well as a potential anomalous size-function relation in motor cortex in ASD.

Functional and structural connectivity of frontostriatal circuitry in Autism Spectrum Disorder

Abnormalities in frontostriatal circuitry potentially underlie the two core deficits in Autism Spectrum Disorder (ASD); social interaction and communication difficulties and restricted interests and repetitive behaviors. Whilst a few studies have examined connectivity within this circuitry in ASD, no previous study has examined both functional and structural connectivity within the same population. The present study provides the first exploration of both functional and structural frontostriatal connectivity in ASD. Twenty-eight right-handed Caucasian male ASD (17.28 ± 3.57 years) and 27 right-handed male, age and IQ matched controls (17.15 ± 3.64 years) took part in the study. Resting state functional connectivity was carried out on 21 ASD and control participants, and tractography was carried out on 22 ASD and 24 control participants, after excluding subjects for excessive motion and poor data quality. Functional connectivity analysis was carried out between the frontal cortex and striatum after which tractography was performed between regions that showed significant group differences in functional connectivity. The ASD group showed increased functional connectivity between regions in the frontal cortex [anterior cingulate cortex (ACC), middle frontal gyrus (MFG), paracingulate gyrus (Pcg) and orbitofrontal cortex (OFC)], and striatum [nucleus accumbens (NAcc) and caudate]. Increased functional connectivity between ACC and caudate was associated with deactivation to social rewards in the caudate, as previously reported in the same participants. Greater connectivity between the right MFG and caudate was associated with higher restricted interests and repetitive behaviors and connectivity between the bilateral Pcg and NAcc, and the right OFC and NAcc, was negatively associated with social and communicative deficits. Although tracts were reliably constructed for each subject, there were no group differences in structural connectivity. Results are in keeping with previously reported increased corticostriatal functional connectivity in ASD.