Partially enhanced thalamocortical functional connectivity in autism

Autistic-like behaviour and changes in thalamic cell numbers a rat model of valproic acid-induced autism; A behavioural and stereological study

The contribution of the thalamus to the development and behavioural changes in autism spectrum disorders (ASD), a neurodevelopmental syndrome, remains unclear. The aim of this study was to determine the changes in thalamic volume and cell number in the valproic acid (VPA)-induced ASD model using stereological methods and to clarify the relationship between thalamus and ASD-like behaviour. Ten pregnant rats were administered a single dose (600 mg/kg) of VPA intraperitoneally on G12.5 (VPA group), while five pregnant rats were injected with 5 ml saline (control group). Behavioural tests were performed to determine appropriate subjects and ASD-like behaviours. At P55, the brains of the subjects were removed. The sagittal sections were stained with cresyl violet and toluidine blue. The thalamic and hemispheric volumes with their ratios, the total number of thalamic cells, neurons and non-neuronal cells were calculated using stereological methods. Data were compared using a t-test and a Pearson correlation analysis was performed to examine the relationship between behaviour and stereological outcomes. VPA-treated rats had lower sociability and sociability indexes. There was no difference in social novelty preference and anxiety. The VPA group had larger hemispheric volume, lower thalamic volume, and fewer neurons. The highest percentage decrease was in non-neuronal cells. There was a moderate positive correlation between the number of non-neuronal cells and sociability, thalamic volume and the number of neurons as well as the time spent in the light box. The correlation between behaviour and stereological data suggests that the thalamus is associated with ASD-like behaviour.

Restoring thalamocortical circuit dysfunction by correcting HCN channelopathy in Shank3 mutant mice

Thalamocortical (TC) circuits are essential for sensory information processing. Clinical and preclinical studies of autism spectrum disorders (ASDs) have highlighted abnormal thalamic development and TC circuit dysfunction. However, mechanistic understanding of how TC dysfunction contributes to behavioral abnormalities in ASDs is limited. Here, our study on a Shank3 mouse model of ASD reveals TC neuron hyperexcitability with excessive burst firing and a temporal mismatch relationship with slow cortical rhythms during sleep. These TC electrophysiological alterations and the consequent sensory hypersensitivity and sleep fragmentation in Shank3 mutant mice are causally linked to HCN2 channelopathy. Restoring HCN2 function early in postnatal development via a viral approach or lamotrigine (LTG) ameliorates sensory and sleep problems. A retrospective case series also supports beneficial effects of LTG treatment on sensory behavior in ASD patients. Our study identifies a clinically relevant circuit mechanism and proposes a targeted molecular intervention for ASD-related behavioral impairments.

Atypical co-development of the thalamus and cortex in autism: Evidence from age-related white-gray contrast change

Recent studies have shown that white-gray contrast (WGC) of either cortical or subcortical gray matter provides for accurate predictions of age in typically developing (TD) children, and that, at least for the cortex, it changes differently with age in subjects with autism spectrum disorder (ASD) compared to their TD peers. Our previous study showed different patterns of contrast change between ASD and TD in sensorimotor and association cortices. While that study was confined to the cortex, we hypothesized that subcortical structures, particularly the thalamus, were involved in the observed cortical dichotomy between lower and higher processing. The current paper investigates that hypothesis using the WGC measures from the thalamus in addition to those from the cortex. We compared age-related WGC changes in the thalamus to those in the cortex. To capture the simultaneity of this change across the two structures, we devised a metric capturing the co-development of the thalamus and cortex (CoDevTC), proportional to the magnitude of cortical and thalamic age-related WGC change. We calculated this metric for each of the subjects in a large homogeneous sample taken from the Autism Brain Imaging Data Exchange (ABIDE) (N = 434). We used structural MRI data from the largest high-quality cross-sectional sample (NYU) as well as two other large high-quality sites, GU and OHSU, all three using Siemens 3T scanners. We observed that the co-development features in ASD and TD exhibit contrasting patterns; specifically, some higher-order thalamic nuclei, such as the lateral dorsal nucleus, exhibited reduction in codevelopment with most of the cortex in ASD compared to TD. Moreover, this difference in the CoDevTC pattern correlates with a number of behavioral measures across multiple cognitive and physiological domains. The results support previous notions of altered connectivity in autism, but add more specific evidence about the heterogeneity in thalamocortical development that elucidates the mechanisms underlying the clinical features of ASD.

Astrocytes in fragile X syndrome

Astrocytes have an important role in neuronal maturation and synapse function in the brain. The interplay between astrocytes and neurons is found to be altered in many neurodevelopmental disorders, including fragile X syndrome (FXS) that is the most common inherited cause of intellectual disability and autism spectrum disorder. Transcriptional, functional, and metabolic alterations in Fmr1 knockout mouse astrocytes, human FXS stem cell-derived astrocytes as well as in in vivo models suggest autonomous effects of astrocytes in the neurobiology of FXS. Abnormalities associated with FXS astrocytes include differentiation of central nervous system cell populations, maturation and regulation of synapses, and synaptic glutamate balance. Recently, FXS-specific changes were found more widely in astrocyte functioning, such as regulation of inflammatory pathways and maintenance of lipid homeostasis. Changes of FXS astrocytes impact the brain homeostasis and function both during development and in the adult brain and offer opportunities for novel types of approaches for intervention.

Neuroanatomical Alterations in the CNTNAP2 Mouse Model of Autism Spectrum Disorder

Autism spectrum disorder (ASD) is associated with neurodevelopmental alterations, including atypical forebrain cellular organization. Mutations in several ASD-related genes often result in cerebral cortical anomalies, such as the abnormal developmental migration of excitatory pyramidal cells and the malformation of inhibitory neuronal circuitry. Notably here, mutations in the CNTNAP2 gene result in ectopic superficial cortical neurons stalled in lower cortical layers and alterations to the balance of cortical excitation and inhibition. However, the broader circuit-level implications of these findings have not been previously investigated. Therefore, we assessed whether ectopic cortical neurons in CNTNAP2 mutant mice form aberrant connections with higher-order thalamic nuclei, potentially accounting for some autistic behaviors, such as repetitive and hyperactive behaviors. Furthermore, we assessed whether the development of parvalbumin-positive (PV) cortical interneurons and their specialized matrix support structures, called perineuronal nets (PNNs), were altered in these mutant mice. We found alterations in both ectopic neuronal connectivity and in the development of PNNs, PV neurons and PNNs enwrapping PV neurons in various sensory cortical regions and at different postnatal ages in the CNTNAP2 mutant mice, which likely lead to some of the cortical excitation/inhibition (E/I) imbalance associated with ASD. These findings suggest neuroanatomical alterations in cortical regions that underlie the emergence of ASD-related behaviors in this mouse model of the disorder.

Altered resting-state functional connectivity of the brain in children with autism spectrum disorder

Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders. Brain mapping has shown that functional brain connections are altered in autism. This study investigated the pattern of brain connection changes in autistic people compared to healthy people. This study aimed to analyze functional abnormalities within the brain due to ASD, using resting-state functional magnetic resonance imaging (fMRI). Resting-state functional magnetic resonance images of 26 individuals with ASD and 26 healthy controls were obtained from the Autism Brain Imaging Data Exchange (ABIDE) database. The DPARSF (data processing assistant for resting-state fMRI) toolbox was used for resting-state functional image processing, and features related to functional connections were extracted from these images. Then, the extracted features from both groups were compared using an Independent Two-Sample T Test, and the features with significant differences between the two groups were identified. Compared with healthy controls, individuals with ASD showed hyper-connectivity in the frontal lobe, anterior cingulum, parahippocampal, left precuneus, angular, caudate, superior temporal, and left pallidum, as well as hypo-connectivity in the precentral, left superior frontal, left middle orbitofrontal, right amygdala, and left posterior cingulum. Our findings show that abnormal functional connectivity exists in patients with ASD. This study makes an important advancement in our understanding of the abnormal neurocircuits causing autism.

Functional connectivity based machine learning approach for autism detection in young children using MEG signals

Objective.Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder, and identifying early autism biomarkers plays a vital role in improving detection and subsequent life outcomes. This study aims to reveal hidden biomarkers in the patterns of functional brain connectivity as recorded by the neuro-magnetic brain responses in children with ASD.Approach.We recorded resting-state magnetoencephalogram signals from thirty children with ASD (4-7 years) and thirty age and gender-matched typically developing (TD) children. We used a complex coherency-based functional connectivity analysis to understand the interactions between different brain regions of the neural system. The work characterizes the large-scale neural activity at different brain oscillations using functional connectivity analysis and assesses the classification performance of coherence-based (COH) measures for autism detection in young children. A comparative study has also been carried out on COH-based connectivity networks both region-wise and sensor-wise to understand frequency-band-specific connectivity patterns and their connections with autism symptomatology. We used artificial neural network (ANN) and support vector machine (SVM) classifiers in the machine learning framework with a five-fold CV technique.Main results.To classify ASD from TD children, the COH connectivity feature yields the highest classification accuracy of 91.66% in the high gamma (50-100 Hz) frequency band. In region-wise connectivity analysis, the second highest performance is in the delta band (1-4 Hz) after the gamma band. Combining the delta and gamma band features, we achieved a classification accuracy of 95.03% and 93.33% in the ANN and SVM classifiers, respectively. Using classification performance metrics and further statistical analysis, we show that ASD children demonstrate significant hyperconnectivity.Significance.Our findings support the weak central coherency theory in autism detection. Further, despite its lower complexity, we show that region-wise COH analysis outperforms the sensor-wise connectivity analysis. Altogether, these results demonstrate the functional brain connectivity patterns as an appropriate biomarker of autism in young children.

A convergent structure-function substrate of cognitive imbalances in autism

BACKGROUND

Autism spectrum disorder (ASD) is a common neurodevelopmental diagnosis showing substantial phenotypic heterogeneity. A leading example can be found in verbal and nonverbal cognitive skills, which vary from elevated to impaired compared with neurotypical individuals. Moreover, deficits in verbal profiles often coexist with normal or superior performance in the nonverbal domain.

METHODS

To study brain substrates underlying cognitive imbalance in ASD, we capitalized categorical and dimensional IQ profiling as well as multimodal neuroimaging.

RESULTS

IQ analyses revealed a marked verbal to nonverbal IQ imbalance in ASD across 2 datasets (Dataset-1: 155 ASD, 151 controls; Dataset-2: 270 ASD, 490 controls). Neuroimaging analysis in Dataset-1 revealed a structure-function substrate of cognitive imbalance, characterized by atypical cortical thickening and altered functional integration of language networks alongside sensory and higher cognitive areas.

CONCLUSION

Although verbal and nonverbal intelligence have been considered as specifiers unrelated to autism diagnosis, our results indicate that intelligence disparities are accentuated in ASD and reflected by a consistent structure-function substrate affecting multiple brain networks. Our findings motivate the incorporation of cognitive imbalances in future autism research, which may help to parse the phenotypic heterogeneity and inform intervention-oriented subtyping in ASD.

Increased resting-state thalamocortical functional connectivity in children and young adults with autism spectrum disorder

There is converging evidence that abnormal thalamocortical interactions contribute to attention deficits and sensory sensitivities in autism spectrum disorder (ASD). However, previous functional MRI studies of thalamocortical connectivity in ASD have produced inconsistent findings in terms of both the direction (hyper vs. hypoconnectivity) and location of group differences. This may reflect, in part, the confounding effects of head motion during scans. In the present study, we investigated resting-state thalamocortical functional connectivity in 8-25 year-olds with ASD and their typically developing (TD) peers. We used pre-scan training, on-line motion correction, and rigorous data quality assurance protocols to minimize motion confounds. ASD participants showed increased thalamic connectivity with temporal cortex relative to TD. Both groups showed similar age-related decreases in thalamic connectivity with occipital cortex, consistent with a process of circuit refinement. Findings of thalamocortical hyperconnectivity in ASD are consistent with other evidence that decreased thalamic inhibition leads to increase and less filtered sensory information reaching the cortex where it disrupts attention and contributes to sensory sensitivity. This literature motivates studies of mechanisms, functional consequences, and treatment of thalamocortical circuit dysfunction in ASD.

Catecholaminergic and cholinergic neuromodulation in autism spectrum disorder: A comparison to attention-deficit hyperactivity disorder

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder characterized by social impairments and restricted, repetitive behaviors. Treatment of ASD is notoriously difficult and might benefit from identification of underlying mechanisms that overlap with those disturbed in other developmental disorders, for which treatment options are more obvious. One example of the latter is attention-deficit hyperactivity disorder (ADHD), given the efficacy of especially stimulants in treatment of ADHD. Deficiencies in catecholaminergic systems [dopamine (DA), norepinephrine (NE)] in ADHD are obvious targets for stimulant treatment. Recent findings suggest that dysfunction in catecholaminergic systems may also be a factor in at least a subgroup of ASD. In this review we scrutinize the evidence for catecholaminergic mechanisms underlying ASD symptoms, and also include in this analysis a third classic ascending arousing system, the acetylcholinergic (ACh) network. We complement this with a comprehensive review of DA-, NE-, and ACh-targeted interventions in ASD, and an exploratory search for potential treatment-response predictors (biomarkers) in ASD, genetically or otherwise. Based on this review and analysis we propose that (1) stimulant treatment may be a viable option for an ASD subcategory, possibly defined by genetic subtyping; (2) cerebellar dysfunction is pronounced for a relatively small ADHD subgroup but much more common in ASD and in both cases may point toward NE- or ACh-directed intervention; (3) deficiency of the cortical salience network is sizable in subgroups of both disorders, and biomarkers such as eye blink rate and pupillometric data may predict the efficacy of targeting this underlying deficiency via DA, NE, or ACh in both ASD and ADHD.

Sleep Problems in Preschoolers With Autism Spectrum Disorder Are Associated With Sensory Sensitivities and Thalamocortical Overconnectivity

BACKGROUND

Projections between the thalamus and sensory cortices are established early in development and play an important role in regulating sleep as well as in relaying sensory information to the cortex. Atypical thalamocortical functional connectivity frequently observed in children with autism spectrum disorder (ASD) might therefore be linked to sensory and sleep problems common in ASD.

METHODS

Here, we investigated the relationship between auditory-thalamic functional connectivity measured during natural sleep functional magnetic resonance imaging, sleep problems, and sound sensitivities in 70 toddlers and preschoolers (1.5-5 years old) with ASD compared with a matched group of 46 typically developing children.

RESULTS

In children with ASD, sleep problems and sensory sensitivities were positively correlated, and increased sleep latency was associated with overconnectivity between the thalamus and auditory cortex in a subsample with high-quality magnetic resonance imaging data (n = 29). In addition, auditory cortex blood oxygen level-dependent signal amplitude was elevated in children with ASD, potentially reflecting reduced sensory gating or a lack of auditory habituation during natural sleep.

CONCLUSIONS

These findings indicate that atypical thalamocortical functional connectivity can be detected early in development and may play a crucial role in sleep problems and sensory sensitivities in ASD.

The Cerebellar Involvement in Autism Spectrum Disorders: From the Social Brain to Mouse Models

Autism spectrum disorders (ASD) are pervasive neurodevelopmental disorders that include a variety of forms and clinical phenotypes. This heterogeneity complicates the clinical and experimental approaches to ASD etiology and pathophysiology. To date, a unifying theory of these diseases is still missing. Nevertheless, the intense work of researchers and clinicians in the last decades has identified some ASD hallmarks and the primary brain areas involved. Not surprisingly, the areas that are part of the so-called “social brain”, and those strictly connected to them, were found to be crucial, such as the prefrontal cortex, amygdala, hippocampus, limbic system, and dopaminergic pathways. With the recent acknowledgment of the cerebellar contribution to cognitive functions and the social brain, its involvement in ASD has become unmistakable, though its extent is still to be elucidated. In most cases, significant advances were made possible by recent technological developments in structural/functional assessment of the human brain and by using mouse models of ASD. Mouse models are an invaluable tool to get insights into the molecular and cellular counterparts of the disease, acting on the specific genetic background generating ASD-like phenotype. Given the multifaceted nature of ASD and related studies, it is often difficult to navigate the literature and limit the huge content to specific questions. This review fulfills the need for an organized, clear, and state-of-the-art perspective on cerebellar involvement in ASD, from its connections to the social brain areas (which are the primary sites of ASD impairments) to the use of monogenic mouse models.

The mirror neuron system compensates for amygdala dysfunction - associated social deficits in individuals with higher autistic traits

The amygdala is a core node in the social brain which exhibits structural and functional abnormalities in Autism spectrum disorder and there is evidence that the mirror neuron system (MNS) can functionally compensate for impaired emotion processing following amygdala lesions. In the current study, we employed an fMRI paradigm in 241 subjects investigating MNS and amygdala responses to observation, imagination and imitation of dynamic facial expressions and whether these differed in individuals with higher (n = 77) as opposed to lower (n = 79) autistic traits. Results indicated that individuals with higher compared to lower autistic traits showed worse recognition memory for fearful faces, smaller real-life social networks, and decreased left basolateral amygdala (BLA) responses to imitation. Additionally, functional connectivity between the left BLA and the left inferior frontal gyrus (IFG) as well as some other MNS regions was increased in individuals with higher autistic traits, especially during imitation of fearful expressions. The left BLA-IFG connectivity significantly moderated the autistic group differences on recognition memory for fearful faces, indicating that increased amygdala-MNS connectivity could diminish the social behavioral differences between higher and lower autistic trait groups. Overall, findings demonstrate decreased imitation-related amygdala activity in individuals with higher autistic traits in the context of increased amygdala-MNS connectivity which may functionally compensate for amygdala dysfunction and social deficits. Training targeting the MNS may capitalize on this compensatory mechanism for therapeutic benefits in Autism spectrum disorder.

Differences in subcortico-cortical interactions identified from connectome and microcircuit models in autism

The pathophysiology of autism has been suggested to involve a combination of both macroscale connectome miswiring and microcircuit anomalies. Here, we combine connectome-wide manifold learning with biophysical simulation models to understand associations between global network perturbations and microcircuit dysfunctions in autism. We studied neuroimaging and phenotypic data in 47 individuals with autism and 37 typically developing controls obtained from the Autism Brain Imaging Data Exchange initiative. Our analysis establishes significant differences in structural connectome organization in individuals with autism relative to controls, with strong between-group effects in low-level somatosensory regions and moderate effects in high-level association cortices. Computational models reveal that the degree of macroscale anomalies is related to atypical increases of recurrent excitation/inhibition, as well as subcortical inputs into cortical microcircuits, especially in sensory and motor areas. Transcriptomic association analysis based on postmortem datasets identifies genes expressed in cortical and thalamic areas from childhood to young adulthood. Finally, supervised machine learning finds that the macroscale perturbations are associated with symptom severity scores on the Autism Diagnostic Observation Schedule. Together, our analyses suggest that atypical subcortico-cortical interactions are associated with both microcircuit and macroscale connectome differences in autism.

Hyperconnectivity of social brain networks in autism during action-intention judgment

Deficits in social communication in autism spectrum disorder (ASD) have been documented using neuroimaging techniques such as functional MRI over the past decade. More recently, functional connectivity MRI has revealed altered connectivity in face processing, mentalizing, and mirroring brain networks, networks involved in the social brain in ASD. However, to our knowledge, previous studies have not examined these three networks concurrently. The purpose of the current study was to investigate the functional connectivity of the face processing, mentalizing, and mirroring networks (within each network and across networks) in ASD during an action-intention task in which participants were asked to determine the means and intention of a model's actions. We examined: a) within-network connectivity of each network using an ROI-to-ROI analysis; b) connectivity of each network hub to the rest of the brain using a seed-to-voxel analysis; c) the between-network connectivity of each network hub using ROI-to-ROI analysis; and d) brain-behavior relationships by correlating autism symptoms with brain connectivity. Task-fMRI data were used from 21 participants with ASD and 20 typically developing participants. The ASD group consistently showed significantly greater connectivity between networks and between hub regions to the rest of the brain. Hyperconnectivity in ASD may entail more and widespread resource utilization for accomplishing action-intention judgment.

Widespread Disrupted White Matter Microstructure in Autism Spectrum Disorders

Autism Spectrum Disorders (ASDs) are characterised by impaired social communication and restricted repetitive behaviours. Researchers posit that these core features may be underpinned by disrupted structural connectivity. A tract based spatial statistical analysis of diffusion MRI data was performed to investigate white matter organisation (an indication of structural connectivity) in a well-defined cohort of 45 ASD and 45 age and IQ matched control participants. Aberrant structural connectivity characterised by reduced fractional anisotropy was observed in several fiber pathways in ASD relative to controls. Disrupted white matter organisation was associated with social deficits and restricted repetitive behaviours in ASD. Abnormal structural connectivity is apparent in ASD and may be linked to the core behavioural features of the disorder.

Reciprocal White Matter Changes Associated With Copy Number Variation at 15q11.2 BP1-BP2: A Diffusion Tensor Imaging Study

BACKGROUND

The 15q11.2 BP1-BP2 cytogenetic region has been associated with learning and motor delays, autism, and schizophrenia. This region includes a gene that codes for the cytoplasmic FMR1 interacting protein 1 (CYFIP1). The CYFIP1 protein is involved in actin cytoskeletal dynamics and interacts with the fragile X mental retardation protein. Absence of fragile X mental retardation protein causes fragile X syndrome. Because abnormal white matter microstructure has been reported in both fragile X syndrome and psychiatric disorders, we looked at the impact of 15q11.2 BP1-BP2 dosage on white matter microstructure.

METHODS

Combining a brain-wide voxel-based approach and a regional-based analysis, we analyzed diffusion tensor imaging data from healthy individuals with the deletion (n = 30), healthy individuals with the reciprocal duplication (n = 27), and IQ-matched control subjects with no large copy number variants (n = 19), recruited from a large genotyped population sample.

RESULTS

We found global mirror effects (deletion > control > duplication) on fractional anisotropy. The deletion group showed widespread increased fractional anisotropy when compared with duplication. Regional analyses revealed a greater effect size in the posterior limb of the internal capsule and a tendency for decreased fractional anisotropy in duplication.

CONCLUSIONS

These results show a reciprocal effect of 15q11.2 BP1-BP2 on white matter microstructure, suggesting that reciprocal chromosomal imbalances may lead to opposite changes in brain structure. Findings in the deletion overlap with previous white matter differences reported in fragile X syndrome patients, suggesting common pathogenic mechanisms derived from disruptions of cytoplasmic CYFIP1-fragile X mental retardation protein complexes. Our data begin to identify specific components of the 15q11.2 BP1-BP2 phenotype and neurobiological mechanisms of potential relevance to the increased risk for disorder.

Insular function in autism: Update and future directions in neuroimaging and interventions

The insular cortex, hidden within the lateral sulcus of the human brain, participates in a range of cognitive, affective, and sensory functions. Autism spectrum disorder (ASD), a neurodevelopmental condition affecting all of these functional domains, has increasingly been linked with atypical activation and connectivity of the insular cortices. Here we review the latest research linking atypical insular function to a range of behaviors characteristic of ASD, with an emphasis on neuroimaging findings in the domains of social cognition and executive function. We summarize some of the recent work linking the insula to interventions in autism, including oxytocin-based pharmacological treatments and music therapy. We suggest that future directions likely to yield significant insights into insular pathology in ASD include the analysis of the dynamics of this brain region. We also conclude that more basic research is necessary on the use of oxytocin pharmacotherapy, and larger studies addressing participant heterogeneity are needed on the use of music therapy in ASD. Long-term studies are needed to ascertain sustained effects of these interventions.

Altered resting-state dynamics in autism spectrum disorder: Causal to the social impairment?

Autism spectrum disorder (ASD) is characterized by profound impairments in social abilities and by restricted interests and repetitive behaviors. Much work in the past decade has been dedicated to understanding the brain-bases of ASD, and in the context of resting-state functional connectivity fMRI in high-functioning adolescents and adults, the field has established a set of reliable findings: decreased cortico-cortical interactions among brain regions thought to be engaged in social processing, along with a simultaneous increase in thalamo-cortical and striato-cortical interactions. However, few studies have attempted to manipulate these altered patterns, leading to the question of whether such patterns are actually causally involved in producing the corresponding behavioral impairments. We discuss a few such recent attempts in the domains of fMRI neurofeedback and overt social interaction during scanning, and we conclude that the evidence of causal involvement is somewhat mixed. We highlight the potential role of the thalamus and striatum in ASD and emphasize the need for studies that directly compare scanning during multiple cognitive states in addition to the resting-state.

Overt social interaction and resting state in young adult males with autism: core and contextual neural features

Conversation is an important and ubiquitous social behaviour. Individuals with autism spectrum disorder (autism) without intellectual disability often have normal structural language abilities but deficits in social aspects of communication like pragmatics, prosody, and eye contact. Previous studies of resting state activity suggest that intrinsic connections among neural circuits involved with social processing are disrupted in autism, but to date no neuroimaging study has examined neural activity during the most commonplace yet challenging social task: spontaneous conversation. Here we used functional MRI to scan autistic males (n = 19) without intellectual disability and age- and IQ-matched typically developing control subjects (n = 20) while they engaged in a total of 193 face-to-face interactions. Participants completed two kinds of tasks: conversation, which had high social demand, and repetition, which had low social demand. Autistic individuals showed abnormally increased task-driven interregional temporal correlation relative to controls, especially among social processing regions and during high social demand. Furthermore, these increased correlations were associated with parent ratings of participants' social impairments. These results were then compared with previously-acquired resting state data (56 autism, 62 control subjects). While some interregional correlation levels varied by task or rest context, others were strikingly similar across both task and rest, namely increased correlation among the thalamus, dorsal and ventral striatum, somatomotor, temporal and prefrontal cortex in the autistic individuals, relative to the control groups. These results suggest a basic distinction. Autistic cortico-cortical interactions vary by context, tending to increase relative to controls during task and decrease during test. In contrast, striato- and thalamocortical relationships with socially engaged brain regions are increased in both task and rest, and may be core to the condition of autism.

Aberrant "deep connectivity" in autism: A cortico-subcortical functional connectivity magnetic resonance imaging study

The number of studies examining functional brain networks in Autism Spectrum Disorder (ASD) has risen over the last decade and has characterized ASD as a disorder of altered brain connectivity. However, these studies have focused largely on cortical structures, and only a few studies have examined cortico-subcortical connectivity in regions like thalamus and basal ganglia in ASD. The goal of this study was to characterize the functional connectivity between cortex and subcortical regions in ASD using the Autism Brain Imaging Data Exchange (ABIDE-II). Resting-state functional magnetic resonance imaging data were used from 168 typically developing (TD) and 138 ASD participants across different sites from the ABIDE II dataset. Functional connectivity of basal ganglia and thalamus to unimodal and supramodal networks was examined in this study. Overconnectivity (ASD > TD) was found between unimodal (except for medial visual network) and subcortical regions, and underconnectivity (TD > ASD) was found between supramodal (except for default mode and dorsal attention networks) and subcortical regions; positive correlations between ASD phenotype and unimodal-subcortical connectivity were found and negative ones with supramodal-subcortical connectivity. These findings suggest that brain networks heavily involved in sensory processing had higher connectivity with subcortical regions, whereas those involved in higher-order thinking showed decreased connectivity in ASD. In addition, brain-behavior correlations indicated a relationship between ASD phenotype and connectivity. Thus, differences in cortico-subcortical connectivity may have a significant impact on basic and higher-order cognitive processes in ASD. Autism Res 2019, 12: 384-400 © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: This study focused on examining the functional connectivity (synchronization of brain activity across regions) of two types of brain networks (unimodal and supramodal) with subcortical areas (thalamus and basal ganglia) in children, adolescents, and adults with autism spectrum disorder (ASD) and how this relates to ASD phenotype. ASD participants showed overconnectivity in unimodal networks and underconnectivity in supramodal networks. These findings provide new insights into cortico-subcortical connections between basic sensory and high-order cognitive processes.

Functional MRI connectivity of children with autism and low verbal and cognitive performance

Background

Functional neuroimaging research in autism spectrum disorder has reported patterns of decreased long-range, within-network, and interhemispheric connectivity. Research has also reported increased corticostriatal connectivity and between-network connectivity for default and attentional networks. Past studies have excluded individuals with autism and low verbal and cognitive performance (LVCP), so connectivity in individuals more significantly affected with autism has not yet been studied. This represents a critical gap in our understanding of brain function across the autism spectrum.

Methods

Using behavioral support procedures adapted from Nordahl, et al. (J Neurodev Disord 8:20–20, 2016), we completed non-sedated structural and functional MRI scans of 56 children ages 7–17, including LVCP children (n = 17, mean IQ = 54), children with autism and higher performance (HVCP, n = 20, mean IQ = 106), and neurotypical children (NT, n = 19, mean IQ = 111). Preparation included detailed intake questionnaires, video modeling, behavioral and anxiety reduction techniques, active noise-canceling headphones, and in-scan presentation of the Inscapes movie paradigm from Vanderwal et al. (Neuroimage 122:222–32, 2015). A high temporal resolution multiband echoplanar fMRI protocol analyzed motion-free time series data, extracted from concatenated volumes to mitigate the influence of motion artifact. All participants had > 200 volumes of motion-free fMRI scanning. Analyses were corrected for multiple comparisons.

Results

LVCP showed decreased within-network connectivity in default, salience, auditory, and frontoparietal networks (LVCP < HVCP) and decreased interhemispheric connectivity (LVCP < HVCP=NT). Between-network connectivity was higher for LVCP than NT between default and dorsal attention and frontoparietal networks. Lower IQ was associated with decreased connectivity within the default network and increased connectivity between default and dorsal attention networks.

Conclusions

This study demonstrates that with moderate levels of support, including readily available techniques, information about brain similarities and differences in LVCP individuals can be further studied. This initial study suggested decreased network segmentation and integration in LVCP individuals. Further imaging studies of LVCP individuals with larger samples will add to understanding of origins and effects of autism on brain function and behavior.

Electronic supplementary material

The online version of this article (10.1186/s13229-018-0248-y) contains supplementary material, which is available to authorized users.

Adenosine Actions on Oligodendroglia and Myelination in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is the most commonly diagnosed neurodevelopmental disorder. Independent of neuronal dysfunction, ASD and its associated comorbidities have been linked to hypomyelination and oligodendroglial dysfunction. Additionally, the neuromodulator adenosine has been shown to affect certain ASD comorbidities and symptoms, such as epilepsy, impairment of cognitive function, and anxiety. Adenosine is both directly and indirectly responsible for regulating the development of oligodendroglia and myelination through its interaction with, and modulation of, several neurotransmitters, including glutamate, dopamine, and serotonin. In this review, we will focus on the recent discoveries in adenosine interaction with physiological and pathophysiological activities of oligodendroglia and myelination, as well as ASD-related aspects of adenosine actions on neuroprotection and neuroinflammation. Moreover, we will discuss the potential therapeutic value and clinical approaches of adenosine manipulation against hypomyelination in ASD.

Functional connectivity in ASD: Atypical pathways in brain networks supporting action observation and joint attention

Autism Spectrum Disorder (ASD) is a developmental disorder characterized by impaired social communication, including attending to and interpreting social cues, initiating and responding to joint attention, and engaging in abstract social cognitive reasoning. Current studies emphasize a underconnectivity in ASD, particularly for brain systems that support abstract social reasoning and introspective thought. Here, we evaluate intrinsic connectivity in children with ASD, targeting brain systems that support the developmental precursors to social reasoning, namely perception of social cues and joint attention. Using resting state fMRI made available through the Autism Brain Imaging Data Exchange (ABIDE), we compute functional connectivity within and between nodes in the action observation, attention and social cognitive networks in children and adolescents with ASD. We also compare connectivity strength to observational assessments that explicitly evaluate severity of ASD on two distinct subdomains using the ADOS-Revised schedule: social affective (SA) and restricted, repetitive behaviors (RRB). Compared to age-matched controls, children with ASD have decreased functional connectivity in a number of connections in the action observation network, particularly in the lateral occipital cortex (LOTC) and fusiform gyrus (FG). Distinct patterns of connections were also correlated with symptom severity on the two subdomains of the ADOS. ADOS-SA severity most strongly correlated with connectivity to the left TPJ, while ADOS-RRB severity correlated with connectivity to the dMPFC. We conclude that atypical connectivity in the action observation system may underlie some of the more complex deficits in social cognitive systems in ASD.

Brain dynamics in ASD during movie-watching show idiosyncratic functional integration and segregation

To refine our understanding of autism spectrum disorders (ASD), studies of the brain in dynamic, multimodal and ecological experimental settings are required. One way to achieve this is to compare the neural responses of ASD and typically developing (TD) individuals when viewing a naturalistic movie, but the temporal complexity of the stimulus hampers this task, and the presence of intrinsic functional connectivity (FC) may overshadow movie‐driven fluctuations. Here, we detected inter‐subject functional correlation (ISFC) transients to disentangle movie‐induced functional changes from underlying resting‐state activity while probing FC dynamically. When considering the number of significant ISFC excursions triggered by the movie across the brain, connections between remote functional modules were more heterogeneously engaged in the ASD population. Dynamically tracking the temporal profiles of those ISFC changes and tying them to specific movie subparts, this idiosyncrasy in ASD responses was then shown to involve functional integration and segregation mechanisms such as response inhibition, background suppression, or multisensory integration, while low‐level visual processing was spared. Through the application of a new framework for the study of dynamic experimental paradigms, our results reveal a temporally localized idiosyncrasy in ASD responses, specific to short‐lived episodes of long‐range functional interplays.

Longitudinal development of thalamic and internal capsule microstructure in autism spectrum disorder

The thalamus is a key sensorimotor relay area that is implicated in autism spectrum disorder (ASD). However, it is unknown how the thalamus and white-matter structures that contain thalamo-cortical fiber connections (e.g., the internal capsule) develop from childhood into adulthood and whether this microstructure relates to basic motor challenges in ASD. We used diffusion weighted imaging in a cohort-sequential design to assess longitudinal development of the thalamus, and posterior- and anterior-limbs of the internal capsule (PLIC and ALIC, respectively) in 89 males with ASD and 56 males with typical development (3-41 years; all verbal). Our results showed that the group with ASD exhibited different developmental trajectories of microstructure in all regions, demonstrating childhood group differences that appeared to approach and, in some cases, surpass the typically developing group in adolescence and adulthood. The PLIC (but not ALIC nor thalamus) mediated the relation between age and finger-tapping speed in both groups. Yet, the gap in finger-tapping speed appeared to widen at the same time that the between-group gap in the PLIC appeared to narrow. Overall, these results suggest that childhood group differences in microstructure of the thalamus and PLIC become less robust in adolescence and adulthood. Further, finger-tapping speed appears to be mediated by the PLIC in both groups, but group differences in motor speed that widen during adolescence and adulthood suggest that factors beyond the microstructure of the thalamus and internal capsule may contribute to atypical motor profiles in ASD. Autism Res 2018, 11: 450-462. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

LAY SUMMARY

Microstructure of the thalamus, a key sensory and motor brain area, appears to develop differently in individuals with autism spectrum disorder (ASD). Microstructure is important because it informs us of the density and organization of different brain tissues. During childhood, thalamic microstructure was distinct in the ASD group compared to the typically developing group. However, these group differences appeared to narrow with age, suggesting that the thalamus continues to dynamically change in ASD into adulthood.

Indices of repetitive behaviour are correlated with patterns of intrinsic functional connectivity in youth with autism spectrum disorder

The purpose of the current study was to examine how repetitive behaviour in Autism Spectrum Disorder (ASD) is related to intrinsic functional connectivity patterns in a number of large-scale, neural networks. Resting-state fMRI scans from thirty subjects with ASD and thirty-two age-matched, typically developing control subjects were analysed. Seed-to-voxel and ROI-to-ROI functional connectivity analyses were used to examine resting-state connectivity in a number of cortical and subcortical neural networks. Bivariate correlation analysis was performed to examine the relationship between repetitive behaviour scores from the Repetitive Behaviour Scale - Revised and intrinsic functional connectivity in ASD subjects. Compared to control subjects, ASD subjects displayed marked over-connectivity of the thalamus with several cortical sensory processing areas, as well as over-connectivity of the basal ganglia with somatosensory and motor cortices. Within the ASD group, significant correlations were found between functional connectivity patterns and total RBS-R scores as well as one principal component analysis-derived score from the RBS-R. These results suggest that thalamocortical resting-state connectivity is altered in individuals with ASD, and that resting-state functional connectivity is associated with ASD symptomatology.

A proton MR spectroscopy study of the thalamus in twins with autism spectrum disorder

Multiple lines of research have reported thalamic abnormalities in individuals with autism spectrum disorder (ASD) that are associated with social communication impairments (SCI), restricted and repetitive behaviors (RRB), or sensory processing abnormalities (SPA). Thus, the thalamus may represent a common neurobiological structure that is shared across symptom domains in ASD. Same-sex monozygotic (MZ) and dizygotic (DZ) twin pairs with and without ASD underwent cognitive/behavioral evaluation and magnetic resonance imaging to assess the thalamus. Neurometabolites were measured with 1H magnetic resonance spectroscopy (MRS) utilizing a multi-voxel PRESS sequence and were referenced to creatine+phosphocreatine (tCr). N-acetyl aspartate (NAA), a marker of neuronal integrity, was reduced in twins with ASD (n=47) compared to typically-developing (TD) controls (n=33), and this finding was confirmed in a sub-sample of co-twins discordant for ASD (n=11). NAA in the thalamus was correlated to a similar extent with SCI, RRB, and SPA, such that reduced neuronal integrity was associated with greater symptom severity. Glutamate+glutamine (Glx) was also reduced in affected versus unaffected co-twins. Additionally, NAA and Glx appeared to be primarily genetically-mediated, based on comparisons between MZ and DZ twin pairs. Thus, thalamic abnormalities may be influenced by genetic susceptibility for ASD but are likely not domain-specific.

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

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

Children with ASD show links between aberrant sound processing, social symptoms, and atypical auditory interhemispheric and thalamocortical functional connectivity

Autism spectrum disorder (ASD) is a complex and prevalent neurodevelopmental disorder characterized by social and communicative deficits, as well as repetitive behaviors and atypical sensitivity to sensory stimulation. Alterations in network connectivity are widely recognized, but their interplay with social and sensory symptoms remains largely unclear. Here, functional magnetic resonance imaging and diagnostic and behavioral assessments were used in a cohort of children and adolescents with ASD (n=40) and matched typically developing (TD, n=38) controls to examine the relation between auditory processing, interhemispheric and thalamocortical network connectivity, and social-behavioral symptom severity. We found that atypical processing of sounds was related to social, cognitive, and communicative impairments. Additionally, severity of sensory processing deficits and lower verbal IQ were related to reduced interhemispheric connectivity of auditory cortices in ASD. Increased connectivity between the thalamus and auditory cortex in ASD, however, was associated with reduced cognitive and behavioral symptomatology, suggesting that thalamocortical overconnectivity might reflect a compensatory mechanism in ASD. These findings provide novel evidence for links between auditory sensory deficits and impairments in social interaction and communication.

Temporal fractal analysis of the rs-BOLD signal identifies brain abnormalities in autism spectrum disorder

Background

Brain connectivity in autism spectrum disorders (ASD) has proven difficult to characterize due to the heterogeneous nature of the spectrum. Connectivity in the brain occurs in a complex, multilevel and multi-temporal manner, driving the fluctuations observed in local oxygen demand. These fluctuations can be characterized as fractals, as they auto-correlate at different time scales. In this study, we propose a model-free complexity analysis based on the fractal dimension of the rs-BOLD signal, acquired with magnetic resonance imaging. The fractal dimension can be interpreted as measure of signal complexity and connectivity. Previous studies have suggested that reduction in signal complexity can be associated with disease. Therefore, we hypothesized that a detectable difference in rs-BOLD signal complexity could be observed between ASD patients and Controls.

Methods and findings

Anatomical and functional data from fifty-five subjects with ASD (12.7 ± 2.4 y/o) and 55 age-matched (14.1 ± 3.1 y/o) healthy controls were accessed through the NITRC database and the ABIDE project. Subjects were scanned using a 3T GE Signa MRI and a 32-channel RF-coil. Axial FSPGR-3D images were used to prescribe rs-BOLD (TE/TR = 30/2000ms) where 300 time points were acquired. Motion correction was performed on the functional data and anatomical and functional images were aligned and spatially warped to the N27 standard brain atlas. Fractal analysis, performed on a grey matter mask, was done by estimating the Hurst exponent in the frequency domain using a power spectral density approach and refining the estimation in the time domain with de-trended fluctuation analysis and signal summation conversion methods. Voxel-wise fractal dimension (FD) was calculated for every subject in the control group and in the ASD group to create ROI-based Z-scores for the ASD patients. Voxel-wise validation of FD normality across controls was confirmed, and non-Gaussian voxels were eliminated from subsequent analysis. To maintain a 95% confidence level, only regions where Z-score values were at least 2 standard deviations away from the mean (i.e. where |Z| > 2.0) were included in the analysis. We found that the main regions, where signal complexity significantly decreased among ASD patients, were the amygdala (p = 0.001), the vermis (p = 0.02), the basal ganglia (p = 0.01) and the hippocampus (p = 0.02). No regions reported significant increase in signal complexity in this study. Our findings were correlated with ADIR and ADOS assessment tools, reporting the highest correlation with the ADOS metrics.

Conclusions

Brain connectivity is best modeled as a complex system. Therefore, a measure of complexity as the fractal dimension of fluctuations in brain oxygen demand and utilization could provide important information about connectivity issues in ASD. Moreover, this technique can be used in the characterization of a single subject, with respect to controls, without the need for group analysis. Our novel approach provides an ideal avenue for personalized diagnostics, thus providing unique patient specific assessment that could help in individualizing treatments.

Altered Developmental Expression of the Astrocyte-Secreted Factors Hevin and SPARC in the Fragile X Mouse Model

Astrocyte dysfunction has been indicated in many neurodevelopmental disorders, including Fragile X Syndrome (FXS). FXS is caused by a deficiency in fragile X mental retardation protein (FMRP). FMRP regulates the translation of numerous mRNAs and its loss disturbs the composition of proteins important for dendritic spine and synapse development. Here, we investigated whether the astrocyte-derived factors hevin and SPARC, known to regulate excitatory synapse development, have altered expression in FXS. Specifically, we analyzed the expression of these factors in wild-type (WT) mice and in fragile X mental retardation 1 (Fmr1) knock-out (KO) mice that lack FMRP expression. Samples were collected from the developing cortex and hippocampus (regions of dendritic spine abnormalities in FXS) of Fmr1 KO and WT pups. Hevin and SPARC showed altered expression patterns in Fmr1 KO mice compared to WT, in a brain-region specific manner. In cortical tissue, we found a transient increase in the level of hevin in postnatal day (P)14 Fmr1 KO mice, compared to WT. Additionally, there were modest decreases in Fmr1 KO cortical levels of SPARC at P7 and P14. In the hippocampus, hevin expression was much lower in P7 Fmr1 KO mice than in WT. At P14, hippocampal hevin levels were similar between genotypes, and by P21 Fmr1 KO hevin expression surpassed WT levels. These findings imply aberrant astrocyte signaling in FXS and suggest that the altered expression of hevin and SPARC contributes to abnormal synaptic development in FXS.

Disordered cortical connectivity underlies the executive function deficits in children with autism spectrum disorders

The present study examined the executive function and cortical connectivity of children with autism spectrum disorders (ASD) and investigated whether the executive function deficits exhibited by these children were differentially affected and associated with the cortical connectivity. The present study compared high-functioning (HFA) and low-functioning (LFA) children with typically developing children (TDC) on their executive functions as measured by the Hong Kong List Learning Test, D2 Test of Concentration, Five Point Test, Children's Color Trail Test, Tower of California Test, and Go/No-Go task and neural connectivity as measured by theta coherence in the distributed fronto-parietal network. Thirty-eight children with ASD (19 HFA and 19 LFA) and 28 TDC children, aged 8-17 years, participated voluntarily in the study. The results on executive function showed that the LFA group demonstrated the poorest performance as exhibited by their Executive Composite and individual executive function scores, while the TDC group exhibited the highest. These results have extended the findings of previous studies in demonstrating that HFA and LFA children have significant differences in their degree of executive function deficits. The results on neural connectivity also showed that children with ASD demonstrated a different pattern of electroencephalography (EEG) coherence from TDC children, as demonstrated by the significantly elevated theta coherence in the fronto-parietal network, and that the severity of executive dysfunction between high- and low-functioning children with ASD was found to be associated with the disordered neural connectivity in these children.

Different aberrant mentalizing networks in males and females with autism spectrum disorders: Evidence from resting-state functional magnetic resonance imaging

Previous studies have found that individuals with autism spectrum disorders show impairments in mentalizing processes and aberrant brain activity compared with typically developing participants. However, the findings are mainly from male participants and the aberrant effects in autism spectrum disorder females and sex differences are still unclear. To address these issues, this study analyzed intrinsic functional connectivity of mentalizing regions using resting-state functional magnetic resonance imaging data of 48 autism spectrum disorder males and females and 48 typically developing participants in autism brain imaging data exchange. Whole-brain analyses showed that autism spectrum disorder males had hyperconnectivity in functional connectivity of the bilateral temporal-parietal junction, whereas autism spectrum disorder females showed hypoconnectivity in functional connectivity of the medial prefrontal cortex, precuneus, and right temporal-parietal junction. Interaction between sex and autism was found in both short- and long-distance functional connectivity effects, confirming that autism spectrum disorder males showed overconnectivity, while autism spectrum disorder females showed underconnectivity. Furthermore, a regression analysis revealed that in autism spectrum disorder, males and females demonstrated different relations between the functional connectivity effects of the mentalizing regions and the core autism spectrum disorder deficits. These results suggest sex differences in the mentalizing network in autism spectrum disorder individuals. Future work is needed to examine how sex interacts with other factors such as age and the sex differences during mentalizing task performance.

Mutations in Human Accelerated Regions Disrupt Cognition and Social Behavior

Comparative analyses have identified genomic regions potentially involved in human evolution but do not directly assess function. Human accelerated regions (HARs) represent conserved genomic loci with elevated divergence in humans. If some HARs regulate human-specific social and behavioral traits, then mutations would likely impact cognitive and social disorders. Strikingly, rare biallelic point mutations-identified by whole-genome and targeted "HAR-ome" sequencing-showed a significant excess in individuals with ASD whose parents share common ancestry compared to familial controls, suggesting a contribution in 5% of consanguineous ASD cases. Using chromatin interaction sequencing, massively parallel reporter assays (MPRA), and transgenic mice, we identified disease-linked, biallelic HAR mutations in active enhancers for CUX1, PTBP2, GPC4, CDKL5, and other genes implicated in neural function, ASD, or both. Our data provide genetic evidence that specific HARs are essential for normal development, consistent with suggestions that their evolutionary changes may have altered social and/or cognitive behavior. PAPERCLIP.

Basal ganglia impairments in autism spectrum disorder are related to abnormal signal gating to prefrontal cortex

Research on the biological basis of autism spectrum disorder has yielded a list of brain abnormalities that are arguably as diverse as the set of behavioral symptoms that characterize the disorder. Among these are patterns of abnormal cortical connectivity and abnormal basal ganglia development. In attempts to integrate the existing literature, the current paper tests the hypothesis that impairments in the basal ganglia's function to flexibly select and route task-relevant neural signals to the prefrontal cortex underpins patterns of abnormal synchronization between the prefrontal cortex and other cortical processing centers observed in individuals with autism spectrum disorder (ASD). We tested this hypothesis using a Dynamic Causal Modeling analysis of neuroimaging data collected from 16 individuals with ASD (mean age=25.3 years; 6 female) and 17 age- and IQ-matched neurotypical controls (mean age=25.6, 6 female), who performed a Go/No-Go test of executive functioning. Consistent with the hypothesis tested, a random-effects Bayesian model selection procedure determined that a model of network connectivity in which basal ganglia activation modulated connectivity between the prefrontal cortex and other key cortical processing centers best fit the data of both neurotypicals and individuals with ASD. Follow-up analyses suggested that the largest group differences were observed for modulation of connectivity between prefrontal cortex and the sensory input region in the occipital lobe [t(31)=2.03, p=0.025]. Specifically, basal ganglia activation was associated with a small decrease in synchronization between the occipital region and prefrontal cortical regions in controls; however, in individuals with ASD, basal ganglia activation resulted in increased synchronization between the occipital region and the prefrontal cortex. We propose that this increased synchronization may reflect a failure in basal ganglia signal gating mechanisms, resulting in a non-selective copying of signals to prefrontal cortex. Such a failure to prioritize and filter signals to the prefrontal cortex could result in the pervasive impairments in cognitive flexibility and executive functioning that characterize autism spectrum disorder, and may offer a mechanistic explanation of some of the observed abnormalities in patterns of cortical synchronization in ASD.

Resting State Functional Connectivity MRI among Spectral MEG Current Sources in Children on the Autism Spectrum

Social and communicative impairments are among the core symptoms of autism spectrum disorders (ASD), and a great deal of evidence supports the notion that these impairments are associated with aberrant functioning and connectivity of various cortical networks. The present study explored the links between sources of MEG amplitude in various frequency bands and functional connectivity MRI in the resting state. The goal of combining these modalities was to use sources of neural oscillatory activity, measured with MEG, as functionally relevant seed regions for a more traditional pairwise fMRI connectivity analysis. We performed a seed-based connectivity analysis on resting state fMRI data, using seed regions derived from frequency-specific amplitude sources in resting state MEG data in the same nine subjects with ASD (10–17 years of age). We then compared fMRI connectivity among these MEG-source-derived regions between participants with autism and typically developing, age-matched controls. We used a source modeling technique designed for MEG data to detect significant amplitude sources in six frequency bands: delta (2–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), beta (12–30 Hz), low gamma (30–60 Hz), and high gamma (60–120 Hz). MEG-derived source maps for each participant were co-registered in standard MNI space, and group-level source maps were obtained for each frequency. For each frequency band, the 10 largest clusters resulting from these t-tests were used as regions of interest (ROIs) for the fMRI functional connectivity analysis. Pairwise BOLD signal correlations were obtained between each pair of these ROIs for each frequency band. Each pairwise correlation was compared between the ASD and TD groups using t-tests. We also constrained these pairwise correlations to known network structures, resulting in a follow-up set of correlation matrices specific to each network we considered. Frequency-specific MEG sources had distinct patterns of fMRI resting state functional connectivity in the ASD group, but perhaps the most significant was a finding of hypoconnectivity between many sources of low and high gamma activity. These novel findings suggest that in ASD there are differences in functionally defined networks as shown in previous fMRI studies, as well as between sets of regions defined by magnetoencephalographic neural oscillatory activity.

Altered Onset Response Dynamics in Somatosensory Processing in Autism Spectrum Disorder

Abnormalities in cortical connectivity and evoked responses have been extensively documented in autism spectrum disorder (ASD). However, specific signatures of these cortical abnormalities remain elusive, with data pointing toward abnormal patterns of both increased and reduced response amplitudes and functional connectivity. We have previously proposed, using magnetoencephalography (MEG) data, that apparent inconsistencies in prior studies could be reconciled if functional connectivity in ASD was reduced in the feedback (top-down) direction, but increased in the feedforward (bottom-up) direction. Here, we continue this line of investigation by assessing abnormalities restricted to the onset, feedforward inputs driven, component of the response to vibrotactile stimuli in somatosensory cortex in ASD. Using a novel method that measures the spatio-temporal divergence of cortical activation, we found that relative to typically developing participants, the ASD group was characterized by an increase in the initial onset component of the cortical response, and a faster spread of local activity. Given the early time window, the results could be interpreted as increased thalamocortical feedforward connectivity in ASD, and offer a plausible mechanism for the previously observed increased response variability in ASD, as well as for the commonly observed behaviorally measured tactile processing abnormalities associated with the disorder.

The Disrupted Connectivity Hypothesis of Autism Spectrum Disorders: Time for the Next Phase in Research

During the past decade, the disrupted connectivity theory has generated considerable interest as a pathophysiological model for autism spectrum disorders (ASD). This theory postulates that deficiencies in the way the brain coordinates and synchronizes activity amongst different regions may account for the clinical symptoms of ASD. This review critically examines the current structural and functional connectivity data in ASD and evaluates unresolved assumptions and gaps in knowledge that limit the interpretation of these data. Collectively, studies very often show group alterations in what are thought of as measures of cerebral connectivity, though the patterns of findings vary considerably. We argue that there are three principle needs in this research agenda. First, further basic research is needed to understand the links between measures commonly used (DTI, fMRI, EEG) and other (histological, computational) levels of analysis. Second, speculated causes of inconsistencies in the literature (age, clinical heterogeneity) demand studies that directly evaluate these interpretations. Finally, the field needs well-specified mechanistic models of altered cerebral communication in ASD whose predictions can be tested on multiple levels of analyses.

Atypical effective connectivity of thalamo-cortical circuits in autism spectrum disorder

Autism spectrum disorder (ASD) is a neurodevelopment disorder characterized by atypical connectivity within and across multiple brain systems. We aimed to explore information transmission from the sensory periphery to information processing centers of the brain across thalamo-cortical circuits in ASD. A large multicenter dataset from the autism brain imaging data exchange was utilized. A thalamus template derived from the Automatic Anatomic Labeling atlas was subdivided into six subregions corresponding to six cortical regions using a "winner-takes-all" strategy. Granger causality analysis (GCA) was then applied to calculate effective connectivity from subregions of the thalamus to the corresponding cortical regions. Results demonstrate reduced effective connectivity from the thalamus to left prefrontal cortex (P = 0.023), right posterior parietal cortex (P = 0.03), and bilateral temporal cortex (left: P = 0.014; right: P = 0.015) in ASD compared with healthy control (HC) participants. The GCA values of the thalamus-bilateral temporal cortex connections were significantly negatively correlated with communication scores as assessed by the autism diagnostic observation schedule in the ASD group (left: P = 0.037; right: P = 0.007). Age-related analyses showed that the strengths of the thalamus-bilateral temporal cortex connections were significantly positively correlated with age in the HC group (left: P = 0.013; right: P = 0.016), but not in the ASD group (left: P = 0.506; right: P = 0.219). These results demonstrate impaired thalamo-cortical information transmission in ASD and suggest that atypical development of thalamus-temporal cortex connections may relate to communication deficits in the disorder. Autism Res 2016, 9: 1183-1190. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Multivariate classification of autism spectrum disorder using frequency-specific resting-state functional connectivity--A multi-center study

BACKGROUND

Resting-state functional magnetic resonance imaging studies examining low frequency fluctuations (0.01-0.08 Hz) have revealed atypical whole brain functional connectivity patterns in adolescents with autism spectrum disorder (ASD), and these atypical patterns can be used to discriminate individuals with ASD from controls. However, at present it is unknown whether functional connectivity at specific frequency bands can be used to discriminate individuals with ASD from controls, and whether relationships with symptom severity are stronger in specific frequency bands.

METHODS

We selected 240 adolescent subjects (12-18 years old, 112 with autism spectrum disorder (101/11, males/females) and 128 healthy controls (104/24, males/females)) from 6 separate international sites in the Autism Brain Imaging Data Exchange database. Whole brain functional connectivity networks were constructed in the Slow-5 (0.01-0.027 Hz) and Slow-4 (0.027-0.073 Hz) frequency bands, which were then used as classification features.

RESULTS

An accuracy of 79.17% (p<0.001) was obtained using support vector machine. Most of the discriminative features were concentrated on the Slow-4 band. In the Slow-4 band, atypical connections between the default mode network, fronto-parietal network and cingulo-opercular network were detected. A significant correlation was found between social and communication deficits as measured by the ADOS in individuals with ASD and the classification scores based on connectivity between the default mode network and the cingulo-opercular network. Connections of the thalamus were of the highest classification weight in the Slow-4 band.

CONCLUSIONS

Our findings provide preliminary evidence for frequency-specific whole brain functional connectivity indices that may eventually be used to aid detection of ASD.

Characteristics of Brains in Autism Spectrum Disorder: Structure, Function and Connectivity across the Lifespan

Autism spectrum disorder (ASD) is a highly prevalent neurodevelopmental disorder characterized by impaired social communication and restricted and repetitive behaviors (RRBs). Over the past decade, neuroimaging studies have provided considerable insights underlying neurobiological mechanisms of ASD. In this review, we introduce recent findings from brain imaging studies to characterize the brains of ASD across the human lifespan. Results of structural Magnetic Resonance Imaging (MRI) studies dealing with total brain volume, regional brain structure and cortical area are summarized. Using task-based functional MRI (fMRI), many studies have shown dysfunctional activation in critical areas of social communication and RRBs. We also describe several data to show abnormal connectivity in the ASD brains. Finally, we suggest the possible strategies to study ASD brains in the future.

Regional specificity of aberrant thalamocortical connectivity in autism

Preliminary evidence suggests aberrant (mostly reduced) thalamocortical (TC) connectivity in autism spectrum disorder (ASD), but despite the crucial role of thalamus in sensorimotor functions and its extensive connectivity with cerebral cortex, relevant evidence remains limited. We performed a comprehensive investigation of region-specific TC connectivity in ASD. Resting-state functional MRI and diffusion tensor imaging (DTI) data were acquired for 60 children and adolescents with ASD (ages 7-17 years) and 45 age, sex, and IQ-matched typically developing (TD) participants. We examined intrinsic functional connectivity (iFC) and anatomical connectivity (probabilistic tractography) with thalamus, using 68 unilateral cerebral cortical regions of interest (ROIs). For frontal and parietal lobes, iFC was atypically reduced in the ASD group for supramodal association cortices, but was increased for cingulate gyri and motor cortex. Temporal iFC was characterized by overconnectivity for auditory cortices, but underconnectivity for amygdalae. Occipital iFC was broadly reduced in the ASD group. DTI indices (such as increased radial diffusion) for regions with group differences in iFC further indicated compromised anatomical connectivity, especially for frontal ROIs, in the ASD group. Our findings highlight the regional specificity of aberrant TC connectivity in ASD. Their overall pattern can be largely accounted for by functional overconnectivity with limbic and sensorimotor regions, but underconnectivity with supramodal association cortices. This could be related to comparatively early maturation of limbic and sensorimotor regions in the context of early overgrowth in ASD, at the expense of TC connectivity with later maturing cortical regions.

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.

Robust disruptions in electroencephalogram cortical oscillations and large-scale functional networks in autism

BACKGROUND

Autism spectrum disorders (ASD) are increasingly prevalent and have a significant impact on the lives of patients and their families. Currently, the diagnosis is determined by clinical judgment and no definitive physiological biomarker for ASD exists. Quantitative biomarkers obtainable from clinical neuroimaging data - such as the scalp electroencephalogram (EEG) - would provide an important aid to clinicians in the diagnosis of ASD. The interpretation of prior studies in this area has been limited by mixed results and the lack of validation procedures. Here we use retrospective clinical data from a well-characterized population of children with ASD to evaluate the rhythms and coupling patterns present in the EEG to develop and validate an electrophysiological biomarker of ASD.

METHODS

EEG data were acquired from a population of ASD (n = 27) and control (n = 55) children 4-8 years old. Data were divided into training (n = 13 ASD, n = 24 control) and validation (n = 14 ASD, n = 31 control) groups. Evaluation of spectral and functional network properties in the first group of patients motivated three biomarkers that were computed in the second group of age-matched patients for validation.

RESULTS

Three biomarkers of ASD were identified in the first patient group: (1) reduced posterior/anterior power ratio in the alpha frequency range (8-14 Hz), which we label the "peak alpha ratio", (2) reduced global density in functional networks, and (3) a reduction in the mean connectivity strength of a subset of functional network edges. Of these three biomarkers, the first and third were validated in a second group of patients. Using the two validated biomarkers, we were able to classify ASD subjects with 83 % sensitivity and 68 % specificity in a post-hoc analysis.

CONCLUSIONS

This study demonstrates that clinical EEG can provide quantitative biomarkers to assist diagnosis of autism. These results corroborate the general finding that ASD subjects have decreased alpha power gradients and network connectivities compared to control subjects. In addition, this study demonstrates the necessity of using statistical techniques to validate EEG biomarkers identified using exploratory methods.