Both Hypo-Connectivity and Hyper-Connectivity of the Insular Subregions Associated With Severity in Children With Autism Spectrum Disorders

Insular functional connectivity in autistic and non-autistic development

BACKGROUND

There is evidence for altered interoceptive processing in individuals diagnosed with autism, compared to non-autistic individuals. At a neural level, functional and structural connectivity of interoceptive cortices may differ in autism, though developmental patterns of these differences are unclear as well as how these patterns may vary by subregion within the insular cortex. To better understand the roles of autism, age, and subregion in interoceptive connectivity patterns, we used a cross-sectional approach to examine interoceptive functional connectivity across individuals spanning a wide age range.

METHODS

N=59 autistic individuals (ages 7-54) and N=71 non-autistic individuals (ages 7-51) completed a resting-state functional magnetic resonance imaging scan. From these scans, we analyzed seed-based functional connectivity of insula subregions (posterior, middle, and anterior) by hemisphere. We analyzed associations with age, group, and interoceptive self-reported experiences, as measured in a subset of individuals who completed the Body Perception Questionnaire.

RESULTS

We found that with age, primary interoceptive cortex showed decreased functional coupling with subcortical regions such as the thalamus and increased coupling with multimodal parietal regions. Functional connectivity within key interoceptive areas was decreased in those with increased reported body awareness. Differences between the autistic and non-autistic groups were minimal, with a single finding of heightened connectivity in autism between left posterior insula and lateral occipital cortex.

CONCLUSIONS

These findings shed light on potential developmental shifts in how interoceptive processing is balanced between lower-order and higher-order areas. Further, they provide background for how autistic patterns of interoceptive processing may be considered relative to age.

Sex Differences in Spatiotemporal Consistency and Effective Connectivity of the Precuneus in Autism Spectrum Disorder

Autism spectrum disorder (ASD) has been reported to exhibit altered local functional consistency. However, previous studies mainly focused on male samples and explored the temporal consistency in the ASD brain ignoring the spatial consistency. In this study, FOur-dimensional Consistency of local neural Activities (FOCA) analysis was used to investigate the sex differences of local spatiotemporal consistency of spontaneous brain activity in ASD. This study used resting-state functional magnetic resonance imaging data from the Autism Brain Imaging Data Exchange database, including 64 males/64 females with ASD and 64 male/64 female neurotypical controls (NCs). Two-way analysis of variance was performed to ascertain diagnosis-by-sex interaction effects on whole brain FOCA maps. Moreover, granger causal analysis was used to investigate effective connectivity between the brain regions with interaction effects and the whole-brain in ASD. Significant diagnosis-by-sex interaction effects on FOCA were observed in the bilateral precuneus (PCUN), bilateral medial prefrontal cortex and right dorsolateral superior frontal gyrus. Specifically, FOCA was significantly increased in males with ASD but decreased in females with ASD in the PCUN compared with the sex-matched NC group. In addition, the lack of sex differences in the causal influences from the bilateral anterior cingulate cortex/medial prefrontal cortex to the PCUN was observed in ASD. Our results reveal altered sex differences in the spatiotemporal consistency of spontaneous brain activity and functional interaction of the anterior and posterior default mode network (DMN) in ASD, highlighting the critical role of the DMN in the sex heterogeneity of ASD.

Salience Network in Autism: preliminary results on functional connectivity analysis in resting state

The literature suggests that alterations in functional connectivity (FC) of the Salience Network (SN) may contribute to the manifestation of some clinical features of Autism Spectrum Disorder (ASD). The SN plays a key role in integrating external sensory information with internal emotional and bodily information. An atypical FC of this network could explain some symptomatic features of ASD such as difficulties in self-awareness and emotion processing and provide new insights into the neurobiological basis of autism. Using the Autism Brain Imaging Data Exchange II we investigated the resting-state FC of core regions of SN and its association with autism symptomatology in 29 individuals with ASD compared with 29 typically developing (TD) individuals. In ASD compared to TD individuals, seed-based connectivity analysis showed a reduced FC between the rostral prefrontal cortex and left cerebellum and an increased FC between the right supramarginal gyrus and the regions of the middle temporal gyrus and angular gyrus. Finally, we found that the clinical features of ASD are mainly associated with an atypical FC of the anterior insula and the involvement of dysfunctional mechanisms for emotional and social information processing. These findings expand the knowledge about the differences in the FC of SN between ASD and TD, highlighting atypical FC between structures that play key roles in social cognition and complex cognitive processes. Such anomalies could explain difficulties in processing salient stimuli, especially those of a socio-affective nature, with an impact on emotional and behavioral regulation.

Atypical alpha band microstates produced during eyes-closed resting state EEG in autism

Electroencephalogram (EEG) microstates, which represent quasi-stable patterns of scalp topography, are a promising tool that has the temporal resolution to study atypical spatial and temporal networks in autism spectrum disorder (ASD). While current literature suggests microstates are atypical in ASD, their clinical utility, i.e., relationship with the core behavioural characteristics of ASD, is not fully understood. The aim of this study was to examine microstate parameters in ASD, and examine the relationship between these parameters and core behavioural characteristics in ASD. We compared duration, occurrence, coverage, global explained variance percentage, global field power and spatial correlation of EEG microstates between autistic and neurotypical (NT) adults. Modified k-means cluster analysis was used on eyes-closed, resting state EEG from 30 ASD (10 females, 28.97 ± 9.34 years) and 30 age-equated NT (13 females, 29.33 ± 8.88 years) adults. Five optimal microstates, A to E, were selected to best represent the data. Five microstate maps explaining 80.44% of the NT and 78.44% of the ASD data were found. The ASD group was found to have atypical parameters of microstate A, C, D, and E. Of note, all parameters of microstate C in the ASD group were found to be significantly less than NT. While parameters of microstate D, and E were also found to significantly correlate with subscales of the Ritvo Autism Asperger Diagnostic Scale - Revised (RAADS-R), these findings did not survive a Bonferroni Correction. These findings, in combination with previous findings, highlight the potential clinical utility of EEG microstates and indicate their potential value as a neurophysiologic marker that can be further studied.

Autism-associated brain differences can be observed in utero using MRI

Developmental changes that occur before birth are thought to be associated with the development of autism spectrum disorders. Identifying anatomical predictors of early brain development may contribute to our understanding of the neurobiology of autism spectrum disorders and allow for earlier and more effective identification and treatment of autism spectrum disorders. In this study, we used retrospective clinical brain magnetic resonance imaging data from fetuses who were diagnosed with autism spectrum disorders later in life (prospective autism spectrum disorders) in order to identify the earliest magnetic resonance imaging-based regional volumetric biomarkers. Our results showed that magnetic resonance imaging-based autism spectrum disorder biomarkers can be found as early as in the fetal period and suggested that the increased volume of the insular cortex may be the most promising magnetic resonance imaging-based fetal biomarker for the future emergence of autism spectrum disorders, along with some additional, potentially useful changes in regional volumes and hemispheric asymmetries.

The Dynamical Biomarkers in Functional Connectivity of Autism Spectrum Disorder Based on Dynamic Graph Embedding

Autism spectrum disorder (ASD) is a neurological and developmental disorder and its early diagnosis is a challenging task. The dynamic brain network (DBN) offers a wealth of information for the diagnosis and treatment of ASD. Mining the spatio-temporal characteristics of DBN is critical for finding dynamic communication across brain regions and, ultimately, identifying the ASD diagnostic biomarker. We proposed the dgEmbed-KNN and the Aggregation-SVM diagnostic models, which use the spatio-temporal information from DBN and interactive information among brain regions represented by dynamic graph embedding. The classification accuracies show that dgEmbed-KNN model performs slightly better than traditional machine learning and deep learning methods, while the Aggregation-SVM model has a very good capacity to diagnose ASD using aggregation brain network connections as features. We discovered over- and under-connections in ASD at the level of dynamic connections, involving brain regions of the postcentral gyrus, the insula, the cerebellum, the caudate nucleus, and the temporal pole. We also found abnormal dynamic interactions associated with ASD within/between the functional subnetworks, including default mode network, visual network, auditory network and saliency network. These can provide potential DBN biomarkers for ASD identification.

Developmental changes in electrophysiological properties of auditory cortical neurons in the Cntnap2 knockout rat

Disruptions in the CNTNAP2 gene are known to cause language impairments and symptoms associated with autism spectrum disorder (ASD). Importantly, knocking out this gene in rodents results in ASD-like symptoms that include auditory processing deficits. This study used in vitro patch-clamp electrophysiology to examine developmental alterations in auditory cortex pyramidal neurons of Cntnap2-/- rats, hypothesizing that CNTNAP2 is essential for maintaining intrinsic neuronal properties and synaptic wiring in the developing auditory cortex. Whole cell patch-clamp recordings were conducted in wildtype and Cntnap2-/- littermates at three postnatal age ranges (P8-12, P18-21, and P70-90). Consistent changes across age were seen in all measures of intrinsic membrane properties and spontaneous synaptic input. Intrinsic cell properties such as action potential half-widths, rheobase, and action-potential firing frequencies were different between wildtype and Cntnap2-/- rats predominantly during the juvenile stage (P18-21), whereas adult Cntnap2-/- rats showed higher frequencies of spontaneous and mini postsynaptic currents (sPSCs; mPSCs), with lower sPSC amplitudes. These results indicate that intrinsic cell properties are altered in Cntnap2-/- rats during the juvenile age, leading to a hyperexcitable phenotype during this stage of synaptic remodeling and refinement. Although intrinsic properties eventually normalize by reaching adulthood, changes in synaptic input, potentially caused by the differences in intrinsic membrane properties, seem to manifest in the adult age and are presumably responsible for the hyperreactive behavioral phenotype. In conjunction with a previous study, the present results also indicate a large influence of breeding scheme, i.e., pre- or postnatal environment, on the impact of Cntnap2 on cellular physiology.NEW & NOTEWORTHY This study shows that neurons in the auditory cortex of Cntnap2 knockout rats are hyperexcitable only during the juvenile age, whereas resulting changes in synaptic input persist in the adult. In conjunction with a previous study, the present results indicate that it is not the genes alone, but also the influence of pre- and postnatal environment, that shape neuronal function, highlighting the importance of early intervention in neurodevelopmental disorders.

Integration of structural MRI and epigenetic analyses hint at linked cellular defects of the subventricular zone and insular cortex in autism: Findings from a case study

Introduction

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social interaction, communication and repetitive, restrictive behaviors, features supported by cortical activity. Given the importance of the subventricular zone (SVZ) of the lateral ventrical to cortical development, we compared molecular, cellular, and structural differences in the SVZ and linked cortical regions in specimens of ASD cases and sex and age-matched unaffected brain.

Methods

We used magnetic resonance imaging (MRI) and diffusion tractography on ex vivo postmortem brain samples, which we further analyzed by Whole Genome Bisulfite Sequencing (WGBS), Flow Cytometry, and RT qPCR.

Results

Through MRI, we observed decreased tractography pathways from the dorsal SVZ, increased pathways from the posterior ventral SVZ to the insular cortex, and variable cortical thickness within the insular cortex in ASD diagnosed case relative to unaffected controls. Long-range tractography pathways from and to the insula were also reduced in the ASD case. FACS-based cell sorting revealed an increased population of proliferating cells in the SVZ of ASD case relative to the unaffected control. Targeted qPCR assays of SVZ tissue demonstrated significantly reduced expression levels of genes involved in differentiation and migration of neurons in ASD relative to the control counterpart. Finally, using genome-wide DNA methylation analyses, we identified 19 genes relevant to neurological development, function, and disease, 7 of which have not previously been described in ASD, that were significantly differentially methylated in autistic SVZ and insula specimens.

Conclusion

These findings suggest a hypothesis that epigenetic changes during neurodevelopment alter the trajectory of proliferation, migration, and differentiation in the SVZ, impacting cortical structure and function and resulting in ASD phenotypes.

Gabrb3 is required for the functional integration of pyramidal neuron subtypes in the somatosensory cortex

Dysfunction of gamma-aminobutyric acid (GABA)ergic circuits is strongly associated with neurodevelopmental disorders. However, it is unclear how genetic predispositions impact circuit assembly. Using in vivo two-photon and widefield calcium imaging in developing mice, we show that Gabrb3, a gene strongly associated with autism spectrum disorder (ASD) and Angelman syndrome (AS), is enriched in contralaterally projecting pyramidal neurons and is required for inhibitory function. We report that Gabrb3 ablation leads to a developmental decrease in GABAergic synapses, increased local network synchrony, and long-lasting enhancement in functional connectivity of contralateral-but not ipsilateral-pyramidal neuron subtypes. In addition, Gabrb3 deletion leads to increased cortical response to tactile stimulation at neonatal stages. Using human transcriptomics and neuroimaging datasets from ASD subjects, we show that the spatial distribution of GABRB3 expression correlates with atypical connectivity in these subjects. Our studies reveal a requirement for Gabrb3 during the emergence of interhemispheric circuits for sensory processing.

Continuous high-frequency deep brain stimulation of the anterior insula modulates autism-like behavior in a valproic acid-induced rat model

BACKGROUND

Until now, the treatment of patients with autism spectrum disorder (ASD) remain a difficult problem. The insula is involved in empathy and sensorimotor integration, which are often impaired in individuals with ASD. Deep brain stimulation, modulating neuronal activity in specific brain circuits, has recently been considered as a promising intervention for neuropsychiatric disorders. Valproic acid (VPA) is a potential teratogenic agent, and prenatal exposure can cause autism-like symptoms including repetitive behaviors and defective sociability. Herein, we investigated the effects of continuous high-frequency deep brain stimulation in the anterior insula of rats exposed to VPA and explored cognitive functions, behavior, and molecular proteins connected to autism spectrum disorder.

METHODS

VPA-exposed offspring were bilaterally implanted with electrodes in the anterior insula (Day 0) with a recovery period of 1 week. (Day 0-7). High-frequency deep brain stimulation was applied from days 11 to 29. Three behavioral tests, including three-chamber social interaction test, were performed on days 7, 13, 18, 25 and 36, and several rats were used for analysis of immediate early genes and proteomic after deep brain stimulation intervention. Meanwhile, animals were subjected to a 20 day spatial learning and cognitive rigidity test using IntelliCage on day 11.

RESULTS

Deep brain stimulation improved the sociability and social novelty preference at day 18 prior to those at day 13, and the improvement has reached the upper limit compared to day 25. As for repetitive/stereotypic-like behavior, self- grooming time were reduced at day 18 and reached the upper limit, and the numbers of burried marbles were reduced at day 13 prior to those at day 18 and day 25. The improvements of sociability and social novelty preference were persistent after the stimulation had ceased. Spatial learning ability and cognitive rigidity were unaffected. We identified 35 proteins in the anterior insula, some of which were intimately linked to autism, and their expression levels were reversed upon administration of deep brain stimulation.

CONCLUSIONS

Autism-like behavior was ameliorated and autism-related proteins were reversed in the insula by deep brain stimulation intervention, these findings reveal that the insula may be a potential target for DBS in the treatment of autism, which provide a theoretical basis for its clinical application., although future studies are still warranted.

Hypoconnectivity between anterior insula and amygdala associates with future vulnerabilities in social development in a neurodiverse sample of neonates

Altered resting state functional connectivity (FC) involving the anterior insula (aINS), a key node in the salience network, has been reported consistently in autism. Here we examined, for the first time, FC between the aINS and the whole brain in a sample of full-term, postmenstrual age (PMA) matched neonates (mean 44.0 weeks, SD = 1.5) who due to family history have high likelihood (HL) for developing autism (n = 12) and in controls (n = 41) without family history of autism (low likelihood, LL). Behaviors associated with autism were evaluated between 12 and 18 months (M = 17.3 months, SD = 2.5) in a subsample (25/53) of participants using the First Year Inventory (FYI). Compared to LL controls, HL neonates showed hypoconnectivity between left aINS and left amygdala. Lower connectivity between the two nodes was associated with higher FYI risk scores in the social domain (r(25) = -0.561, p = .003) and this association remained robust when maternal mental health factors were considered. Considering that a subsample of LL participants (n = 14/41) underwent brain imaging during the fetal period at PMA 31 and 34 weeks, in an exploratory analysis, we evaluated prospectively development of the LaINS-Lamy connectivity and found that the two areas strongly coactivate throughout the third trimester of pregnancy. The study identifies left lateralized anterior insula-amygdala connectivity as a potential target of further investigation into neural circuitry that enhances likelihood of future onset of social behaviors associated with autism during neonatal and potentially prenatal periods.

Translational Magnetic Resonance Imaging in Autism Spectrum Disorder From the Mouse Model to Human

Autism spectrum disorder (ASD) is a heterogeneous syndrome characterized by behavioral features such as impaired social communication, repetitive behavior patterns, and a lack of interest in novel objects. A multimodal neuroimaging using magnetic resonance imaging (MRI) in patients with ASD shows highly heterogeneous abnormalities in function and structure in the brain associated with specific behavioral features. To elucidate the mechanism of ASD, several ASD mouse models have been generated, by focusing on some of the ASD risk genes. A specific behavioral feature of an ASD mouse model is caused by an altered gene expression or a modification of a gene product. Using these mouse models, a high field preclinical MRI enables us to non-invasively investigate the neuronal mechanism of the altered brain function associated with the behavior and ASD risk genes. Thus, MRI is a promising translational approach to bridge the gap between mice and humans. This review presents the evidence for multimodal MRI, including functional MRI (fMRI), diffusion tensor imaging (DTI), and volumetric analysis, in ASD mouse models and in patients with ASD and discusses the future directions for the translational study of ASD.

Identifying Boys With Autism Spectrum Disorder Based on Whole-Brain Resting-State Interregional Functional Connections Using a Boruta-Based Support Vector Machine Approach

An increasing number of resting-state functional magnetic resonance neuroimaging (R-fMRI) studies have used functional connections as discriminative features for machine learning to identify patients with brain diseases. However, it remains unclear which functional connections could serve as highly discriminative features to realize the classification of autism spectrum disorder (ASD). The aim of this study was to find ASD-related functional connectivity patterns and examine whether these patterns had the potential to provide neuroimaging-based information to clinically assist with the diagnosis of ASD by means of machine learning. We investigated the whole-brain interregional functional connections derived from R-fMRI. Data were acquired from 48 boys with ASD and 50 typically developing age-matched controls at NYU Langone Medical Center from the publicly available Autism Brain Imaging Data Exchange I (ABIDE I) dataset; the ASD-related functional connections identified by the Boruta algorithm were used as the features of support vector machine (SVM) to distinguish patients with ASD from typically developing controls (TDC); a permutation test was performed to assess the classification performance. Approximately, 92.9% of participants were correctly classified by a combined SVM and leave-one-out cross-validation (LOOCV) approach, wherein 95.8% of patients with ASD were correctly identified. The default mode network (DMN) exhibited a relatively high network degree and discriminative power. Eight important brain regions showed a high discriminative power, including the posterior cingulate cortex (PCC) and the ventrolateral prefrontal cortex (vlPFC). Significant correlations were found between the classification scores of several functional connections and ASD symptoms (p < 0.05). This study highlights the important role of DMN in ASD identification. Interregional functional connections might provide useful information for the clinical diagnosis of ASD.

Resting state electroencephalography microstates in autism spectrum disorder: A mini-review

Atypical spatial organization and temporal characteristics, found via resting state electroencephalography (EEG) microstate analysis, have been associated with psychiatric disorders but these temporal and spatial parameters are less known in autism spectrum disorder (ASD). EEG microstates reflect a short time period of stable scalp potential topography. These canonical microstates (i.e., A, B, C, and D) and more are identified by their unique topographic map, mean duration, fraction of time covered, frequency of occurrence and global explained variance percentage; a measure of how well topographical maps represent EEG data. We reviewed the current literature for resting state microstate analysis in ASD and identified eight publications. This current review indicates there is significant alterations in microstate parameters in ASD populations as compared to typically developing (TD) populations. Microstate parameters were also found to change in relation to specific cognitive processes. However, as microstate parameters are found to be changed by cognitive states, the differently acquired data (e.g., eyes closed or open) resting state EEG are likely to produce disparate results. We also review the current understanding of EEG sources of microstates and the underlying brain networks.

Revisiting Nonlinear Functional Brain Co-activations: Directed, Dynamic, and Delayed

The center stage of neuro-imaging is currently occupied by studies of functional correlations between brain regions. These correlations define the brain functional networks, which are the most frequently used framework to represent and interpret a variety of experimental findings. In the previous study, we first demonstrated that the relatively stronger blood oxygenated level dependent (BOLD) activations contain most of the information relevant to understand functional connectivity, and subsequent work confirmed that a large compression of the original signals can be obtained without significant loss of information. In this study, we revisit the correlation properties of these epochs to define a measure of nonlinear dynamic directed functional connectivity (nldFC) across regions of interest. We show that the proposed metric provides at once, without extensive numerical complications, directed information of the functional correlations, as well as a measure of temporal lags across regions, overall offering a different and complementary perspective in the analysis of brain co-activation patterns. In this study, we provide further details for the computations of these measures and for a proof of concept based on replicating existing results from an Autistic Syndrome database, and discuss the main features and advantages of the proposed strategy for the study of brain functional correlations.

Aberrant Effective Connectivity of the Ventral Putamen in Boys With Attention-Deficit/Hyperactivity Disorder

OBJECTIVE

The connectivity alterations in the putamen were found in revealing the neural correlates of attention-deficit/hyperactivity disorder (ADHD), but whether the effective connectivity of the putamen is atypical in ADHD remains unclear. Investigating this abnormality contributes to describing the neural circuit of ADHD at the level of macrostructural organization.

METHODS

Data were acquired from thirty-two boys with ADHD and fifty-two matched typically developing controls (TDC) from Peking University (Peking) dataset deposited at the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) platform. We examined the effective connectivity of the putamen using Granger causality analysis (GCA) and then determined whether these connections could differentiate ADHD from TDC.

RESULTS

Compared with TDC, the ADHD group showed decreased effective connectivity from the left ventral rostral putamen (VRP) to left calcarine (CAL), right medial part of the superior frontal gyrus, left orbital part of superior frontal gyrus and left middle occipital gyrus (MOG). Increased effective connectivity from the left inferior occipital gyrus and right lingual gyrus to left VRP was also found in ADHD. The result of the classification accuracy showed that 72.3% of participants were correctly classified using support vector machine. Moreover, GCA values from the left VRP to left CAL and left MOG were significantly correlated with hyper/impulsive scores of patients with ADHD.

CONCLUSION

The findings may help extend our understanding of the ADHD-related neural loops.

Functional Networks Abnormalities in Autism Spectrum Disorder: Age-Related Hypo and Hyper Connectivity

Autism spectrum disorder (ASD) is a developmental disorder characterized by defects in social interaction. The past functional connectivity studies using resting-state fMRI have found both patterns of hypo-connectivity and hyper-connectivity in ASD and proposed the age as an important factor on functional connectivity disorders. However, this influence is not clearly characterized yet. Previous studies have often examined the functional connectivity disorders in particular brain regions in an age group or a mixture of age groups. The present study compares whole-brain within-connectivity and between-connectivity between ASD individuals and typically developing (TD) controls in three age groups including children (< 11 years), adolescents (11-18 years), and adults (> 18 years), each comprising 21 ASD individuals and 21 TD controls. The age groups were matched for age, Full IQ, and gender. Independent component analysis and dual regression were used to investigate within-connectivity. The full and partial correlations between ICs were used to investigate between-connectivity. Examination of the within-connectivity showed hyper-connectivity, especially in cerebellum and brainstem in ASD children but both hyper/hypo connectivity in adolescents and ASD adults. In ASD children, difference in the between-connectivity among default mode network (DMN), salience-executive network and fronto-parietal network were observed. There was also a negative correlation between DMN and temporal network. Full correlation comparison between ASD adolescents and TD individuals showed significant differences between cerebellum and DMN. Our results supported just the hyper-connectivity in childhood, but both hypo and hyper-connectivity after childhood and hypothesized that abnormal resting connections in ASD exist in the regions of the brain known to be involved in social cognition.

Underconnectivity Between Visual and Salience Networks and Links With Sensory Abnormalities in Autism Spectrum Disorders

OBJECTIVE

The anterior insular cortex (AI), which is a part of the salience network, is critically involved in visual awareness, multisensory perception, and social and emotional processing, among other functions. In children and adolescents with autism spectrum disorders (ASDs), evidence has suggested aberrant functional connectivity (FC) of AI compared with typically developing peers. While recent studies have primarily focused on the functional connections between salience and social networks, much less is known about connectivity between AI and primary sensory regions, including visual areas, and how these patterns may be linked to autism symptomatology.

METHOD

The current investigation implemented functional magnetic resonance imaging to examine resting-state FC patterns of salience and visual networks in children and adolescents with ASDs compared with typically developing controls, and to relate them to behavioral measures.

RESULTS

Functional underconnectivity was found in the ASD group between left AI and bilateral visual cortices. Moreover, in an ASD subgroup with more atypical visual sensory profiles, FC was positively correlated with abnormal social motivational responsivity.

CONCLUSION

Findings of reduced FC between salience and visual networks in ASDs potentially indicate deficient selection of salient information. Moreover, in children and adolescents with ASDs who show strongly atypical visual sensory profiles, connectivity at seemingly more neurotypical levels may be paradoxically associated with greater impairment of social motivation.

Specific Functional Connectivity Patterns of Middle Temporal Gyrus Subregions in Children and Adults with Autism Spectrum Disorder

As one of the key regions in the "social brain" network, the middle temporal gyrus (MTG) has been widely reported to be associated with autism spectrum disorder (ASD), but there have been contradictory results in terms of whether it shows hyperconnectivity or hypoconnectivity. Delineating roles of MTG at the subregional level may eliminate the observed inconsistencies and provide a new avenue to reveal the neurophysiologic mechanism of ASD. Thus, we first performed connectivity-based parcellation using the BrainMap database to identify fine-grained functional topography of the MTG. Then, the MTG subregions were used to investigate differences in the functional connectivity in children and adults with ASD using two data sets from Autism Brain Imaging Data Exchange database. Four distinct subregions in the human left and right MTG were identified, including the anterior MTG (aMTG), middle-anterior MTG (maMTG), middle-posterior MTG, and posterior MTG (pMTG). The bilateral pMTG was more vulnerable in both children and adults with ASD than in the typically developing (TD) group, mainly showing hypoconnectivity with different brain regions. In addition, the bilateral aMTG and right maMTG also showed altered functional connectivity in adults with ASD compared to the TD group. Moreover, all these altered MTG subregions were mainly associated with social cognition and language, as revealed by functional characterization. Further correlation analyses also showed trends of association between altered connectivity of the left aMTG and the Autism Diagnostic Observation Schedule scores in adults with ASD. Together, these results suggest a potential objective way to explore sub-regional differences associated with such disorders. Autism Res 2020, 13: 410-422. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Four distinct subregions in the human left and right middle temporal gyrus (MTG) were identified, including the anterior MTG (aMTG), middle-anterior MTG (maMTG), middle-posterior MTG, and posterior MTG (pMTG). The bilateral pMTG was more vulnerable in both children and adults with autism spectrum disorder (ASD) than in the typically developing (TD) group, mainly showing hypoconnectivity with different brain regions. In addition, the bilateral aMTG and right maMTG also showed altered functional connectivity in adults with ASD compared to the TD group. Moreover, all these altered MTG subregions were mainly associated with social cognition and language, as revealed by functional characterization. Further correlation analyses also showed trends of association between altered connectivity of the left aMTG and the Autism Diagnostic Observation Schedule scores in adults with ASD.

Altered Connectivity Between Cerebellum, Visual, and Sensory-Motor Networks in Autism Spectrum Disorder: Results from the EU-AIMS Longitudinal European Autism Project

BACKGROUND

Resting-state functional magnetic resonance imaging-based studies on functional connectivity in autism spectrum disorder (ASD) have generated inconsistent results. Interpretation of findings is further hampered by small samples and a focus on a limited number of networks, with networks underlying sensory processing being largely underexamined. We aimed to comprehensively characterize ASD-related alterations within and between 20 well-characterized resting-state networks using baseline data from the EU-AIMS (European Autism Interventions-A Multicentre Study for Developing New Medications) Longitudinal European Autism Project.

METHODS

Resting-state functional magnetic resonance imaging data was available for 265 individuals with ASD (7.5-30.3 years; 73.2% male) and 218 typically developing individuals (6.9-29.8 years; 64.2% male), all with IQ > 70. We compared functional connectivity within 20 networks-obtained using independent component analysis-between the ASD and typically developing groups, and related functional connectivity within these networks to continuous (overall) autism trait severity scores derived from the Social Responsiveness Scale Second Edition across all participants. Furthermore, we investigated case-control differences and autism trait-related alterations in between-network connectivity.

RESULTS

Higher autism traits were associated with increased connectivity within salience, medial motor, and orbitofrontal networks. However, we did not replicate previously reported case-control differences within these networks. The between-network analysis did reveal case-control differences showing on average 1) decreased connectivity of the visual association network with somatosensory, medial, and lateral motor networks, and 2) increased connectivity of the cerebellum with these sensory and motor networks in ASD compared with typically developing subjects.

CONCLUSIONS

We demonstrate ASD-related alterations in within- and between-network connectivity. The between-network alterations broadly affect connectivity between cerebellum, visual, and sensory-motor networks, potentially underlying impairments in multisensory and visual-motor integration frequently observed in ASD.