Superior temporal sulcus anatomical abnormalities in childhood autism: a voxel-based morphometry MRI study

Optimized attention-enhanced U-Net for autism detection and region localization in MRI

Autism spectrum disorder (ASD) is a neurodevelopmental condition that affects a child's cognitive and social skills, often diagnosed only after symptoms appear around age 2. Leveraging MRI for early ASD detection can improve intervention outcomes. This study proposes a framework for autism detection and region localization using an optimized deep learning approach with attention mechanisms. The pipeline includes MRI image collection, pre-processing (bias field correction, histogram equalization, artifact removal, and non-local mean filtering), and autism classification with a Symmetric Structured MobileNet with Attention Mechanism (SSM-AM). Enhanced by Refreshing Awareness-aided Election-Based Optimization (RA-EBO), SSM-AM achieves robust classification. Abnormality region localization utilizes a Multiscale Dilated Attention-based Adaptive U-Net (MDA-AUnet) further optimized by RA-EBO. Experimental results demonstrate that our proposed model outperforms existing methods, achieving an accuracy of 97.29%, sensitivity of 97.27%, specificity of 97.36%, and precision of 98.98%, significantly improving classification and localization performance. These results highlight the potential of our approach for early ASD diagnosis and targeted interventions. The datasets utilized for this work are publicly available at https://fcon_1000.projects.nitrc.org/indi/abide/.

Left-hemispheric atypicalities in the primary auditory cortex are associated with language comprehension and social skills in children with Autism Spectrum Disorder

Low-level auditory processing difficulties have been previously reported in children with Autism Spectrum Disorder (ASD), and some studies showed the relationship between these difficulties in the primary auditory cortex and language impairment in ASD. However, there is still a limited number of studies that comprehensively assess (i) amplitudes, latencies, and sensory gating effects in all early components of auditory processing (M50-M100-M200 complex) at the source level in magnetoencephalography with their relation to structural anatomy (gray matter volume, thickness, gyrification) (ii) and the association between brain metrics and clinical phenotype in the same group of children. To address this question, we used a standard paired-clicks paradigm in magnetoencephalography and brain morphometry analysis in children with and without ASD (NASD = 20, NTD = 20). First, the results revealed a reduction of M200 and altered M200 sensory gating effect in the left auditory cortex in children with ASD. Second, these alterations were related to lower language comprehension skills and higher autistic symptom severity. Finally, altered MEG responses were associated with gray matter thickness reduction as well as abnormal gyrification in the primary auditory cortex in ASD. The study revealed low-level functional and structural atypicalities in children with ASD and their relation to clinical phenotype.

Exploring the most discriminative brain structural abnormalities in ASD with multi-stage progressive feature refinement approach

Objective

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by increasing prevalence, diverse impairments, and unclear origins and mechanisms. To gain a better grasp of the origins of ASD, it is essential to identify the most distinctive structural brain abnormalities in individuals with ASD.

Methods

A Multi-Stage Progressive Feature Refinement Approach was employed to identify the most pivotal structural magnetic resonance imaging (MRI) features that distinguish individuals with ASD from typically developing (TD) individuals. The study included 175 individuals with ASD and 69 TD individuals, all aged between 7 and 18 years, matched in terms of age and gender. Both cortical and subcortical features were integrated, with a particular focus on hippocampal subfields.

Results

Out of 317 features, 9 had the most significant impact on distinguishing ASD from TD individuals. These structural features, which include a specific hippocampal subfield, are closely related to the brain areas associated with the reward system.

Conclusion

Structural irregularities in the reward system may play a crucial role in the pathophysiology of ASD, and specific hippocampal subfields may also contribute uniquely, warranting further investigation.

Disentangling the role of gray matter volume and concentration in autism spectrum disorder: A meta-analytic investigation of 25 years of voxel-based morphometry research

Despite over two decades of neuroimaging research, a unanimous definition of the pattern of structural variation associated with autism spectrum disorder (ASD) has yet to be found. One potential impeding issue could be the sometimes ambiguous use of measurements of variations in gray matter volume (GMV) or gray matter concentration (GMC). In fact, while both can be calculated using voxel-based morphometry analysis, these may reflect different underlying pathological mechanisms. We conducted a coordinate-based meta-analysis, keeping apart GMV and GMC studies of subjects with ASD. Results showed distinct and non-overlapping patterns for the two measures. GMV decreases were evident in the cerebellum, while GMC decreases were mainly found in the temporal and frontal regions. GMV increases were found in the parietal, temporal, and frontal brain regions, while GMC increases were observed in the anterior cingulate cortex and middle frontal gyrus. Age-stratified analyses suggested that such variations are dynamic across the ASD lifespan. The present findings emphasize the importance of considering GMV and GMC as distinct yet synergistic indices in autism research.

Altered neural synchronization in response to 2 Hz amplitude-modulated tones in the auditory cortex of children with Autism Spectrum Disorder: An MEG study

OBJECTIVE

Some studies have hypothesized that atypical neural synchronization at the delta frequency band in the auditory cortex is associated with phonological and language skills in children with Autism Spectrum Disorder (ASD), but it is still poorly understood. This study investigated this neural activity and addressed the relationships between auditory response and behavioral measures of children with ASD.

METHODS

We used magnetoencephalography and individual brain models to investigate 2 Hz Auditory Steady-State Response (ASSR) in 20 primary-school-aged children with ASD and 20 age-matched typically developing (TD) controls.

RESULTS

First, we found a between-group difference in the localization of the auditory response, so as the topology of 2 Hz ASSR was more superior and posterior in TD children when comparing to children with ASD. Second, the power of 2 Hz ASSR was reduced in the ASD group. Finally, we observed a significant association between the amplitude of neural response and language skills in children with ASD.

CONCLUSIONS

The study provided the evidence of reduced neural response in children with ASD and its relation to language skills.

SIGNIFICANCE

These findings may inform future interventions targeting auditory and language impairments in ASD population.

Major depressive disorder and perceived social support: Moderated mediation model of security and brain dysfunction

Low social support increases the risk of Major depressive disorder (MDD), yet its effects on brain function are unclear. Thirty-two MDD patients with low social support, 52 with high social support, and 54 healthy controls were recruited. We investigated regional brain activity in MDD patients with low social support using resting-state functional Magnetic Resonance Imaging, employing measures such as degree centrality (DC), regional homogeneity, amplitude of low-frequency fluctuations, and fractional amplitude of low-frequency fluctuations. Abnormal regions identified in these analyses were selected as regions of interest for functional connectivity (FC) analysis. We then explored relationships among social support, brain dysfunction, MDD severity, and insecurity using partial correlation and moderated mediation models. Our findings reveal that MDD patients with low social support show decreased DC in the right superior temporal pole and right medial geniculate nucleus, coupled with increased FC between the right superior temporal pole and right inferior temporal gyrus, and the right supramarginal gyrus compared to those with high social support. Furthermore, the DC of the right medial geniculate nucleus positively correlates with social support, while the FC between the right superior temporal pole and right supramarginal gyrus negatively correlates with both social support and subjective support. Additionally, a moderated mediation model demonstrates that the FC between the right superior temporal pole and right supramarginal gyrus mediates the relationship between social support and depression severity, with security moderating this mediation. These findings underscore the impact of low social support on brain function and depression severity in MDD patients.

Intracortical myelin across laminae in adult individuals with 47,XXX: a 7 Tesla MRI study

47,XXX (Triple X syndrome) is a sex chromosome aneuploidy characterized by the presence of a supernumerary X chromosome in affected females and is associated with a variable cognitive, behavioral, and psychiatric phenotype. The effect of a supernumerary X chromosome in affected females on intracortical microstructure is currently unknown. Therefore, we conducted 7 Tesla structural MRI and compared T1 (ms), as a proxy for intracortical myelin (ICM), across laminae of 21 adult women with 47,XXX and 22 age-matched typically developing females using laminar analyses. Relationships between phenotypic traits and T1 values in 47,XXX were also investigated. Adults with 47,XXX showed higher bilateral T1 across supragranular laminae in the banks of the superior temporal sulcus, and in the right inferior temporal gyrus, suggesting decreases of ICM primarily within the temporal cortex in 47,XXX. Higher social functioning in 47,XXX was related to larger inferior temporal gyrus ICM content. Our findings indicate an effect of a supernumerary X chromosome in adult-aged women on ICM across supragranular laminae within the temporal cortex. These findings provide insight into the role of X chromosome dosage on ICM across laminae. Future research is warranted to further explore the functional significance of altered ICM across laminae in 47,XXX.

Gray matter asymmetry alterations in children and adolescents with comorbid autism spectrum disorder and attention-deficit/hyperactivity disorder

Despite the high coexistence of autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) (ASD + ADHD), the underlying neurobiological basis of this disorder remains unclear. Altered brain structural asymmetries have been verified in ASD and ADHD, respectively, making brain asymmetry a candidate for characterizing this coexisting disorder. Here, we measured the gray matter (GM) volume asymmetry in ASD + ADHD versus ASD without ADHD (ASD-only), ADHD without ASD (ADHD-only), and typically developing controls (TDc). High-resolution T1-weighted data from 48 ASD + ADHD, 63 ASD-only, 32 ADHD-only, and 211 matched TDc were included in our study. We also assessed brain-behavior relationships and the effects of age on GM asymmetry. We found that there were both shared and disorder-specific GM volume asymmetry alterations in ASD + ADHD, ASD-only, and ADHD-only compared with TDc. This finding demonstrates that ASD + ADHD is neither an endophenocopy nor an additive pathology of ASD and ADHD, but an entirely different neuroanatomical pathology. In addition, ASD + ADHD displayed altered GM volume asymmetries in the prefrontal regions responsible for executive function and theory of mind compared with ASD-only. We also found significant effects of age on GM asymmetry. The present study may provide structural insights into the neural basis of ASD + ADHD.

Embracing neurodiversity in doll play: Investigating neural and language correlates of doll play in a neurodiverse sample

Doll play may provide opportunities for children to rehearse social interactions, even when playing alone. Previous research has found that the posterior superior temporal sulcus (pSTS) was more engaged when children played with dolls alone, compared to playing with tablet games alone. Children's use of internal state language (ISL) about others was also associated with pSTS activity. As differences in social cognition are frequently observed in autistic people, we were interested in the brain and language correlates of doll play in children with varying levels of autistic traits. We investigated children's (N = 57, mean age = 6.72, SD = 1.53) use of ISL and their pSTS brain activity using functional near-infrared spectroscopy (fNIRS) as they played with dolls and tablet games, both alone and with a social partner. We also investigated whether there were any effects of autistic traits using the parent-report Autism Spectrum Quotient-Children's Version (AQ-Child). We found that the left pSTS was engaged more as children played with dolls or a tablet with a partner, and when playing with dolls alone, compared to when playing with a tablet alone. Relations between language and neural correlates of social processing were distinct based on the degree of autistic traits. For children with fewer autistic traits, greater pSTS activity was associated with using ISL about others. For children with more autistic traits, greater pSTS activity was associated with experimenter talk during solo play. These divergent pathways highlight the importance of embracing neurodiversity in children's play patterns to best support their development through play.

Early autism diagnosis based on path signature and Siamese unsupervised feature compressor

Autism spectrum disorder has been emerging as a growing public health threat. Early diagnosis of autism spectrum disorder is crucial for timely, effective intervention and treatment. However, conventional diagnosis methods based on communications and behavioral patterns are unreliable for children younger than 2 years of age. Given evidences of neurodevelopmental abnormalities in autism spectrum disorder infants, we resort to a novel deep learning-based method to extract key features from the inherently scarce, class-imbalanced, and heterogeneous structural MR images for early autism diagnosis. Specifically, we propose a Siamese verification framework to extend the scarce data, and an unsupervised compressor to alleviate data imbalance by extracting key features. We also proposed weight constraints to cope with sample heterogeneity by giving different samples different voting weights during validation, and used Path Signature to unravel meaningful developmental features from the two-time point data longitudinally. We further extracted machine learning focused brain regions for autism diagnosis. Extensive experiments have shown that our method performed well under practical scenarios, transcending existing machine learning methods and providing anatomical insights for autism early diagnosis.

A multimodal interface for speech perception: the role of the left superior temporal sulcus in social cognition and autism

Multimodal integration is crucial for human interaction, in particular for social communication, which relies on integrating information from various sensory modalities. Recently a third visual pathway specialized in social perception was proposed, which includes the right superior temporal sulcus (STS) playing a key role in processing socially relevant cues and high-level social perception. Importantly, it has also recently been proposed that the left STS contributes to audiovisual integration of speech processing. In this article, we propose that brain areas along the right STS that support multimodal integration for social perception and cognition can be considered homologs to those in the left, language-dominant hemisphere, sustaining multimodal integration of speech and semantic concepts fundamental for social communication. Emphasizing the significance of the left STS in multimodal integration and associated processes such as multimodal attention to socially relevant stimuli, we underscore its potential relevance in comprehending neurodevelopmental conditions characterized by challenges in social communication such as autism spectrum disorder (ASD). Further research into this left lateral processing stream holds the promise of enhancing our understanding of social communication in both typical development and ASD, which may lead to more effective interventions that could improve the quality of life for individuals with atypical neurodevelopment.

Unveiling the development of human voice perception: Neurobiological mechanisms and pathophysiology

The human voice is a critical stimulus for the auditory system that promotes social connection, informs the listener about identity and emotion, and acts as the carrier for spoken language. Research on voice processing in adults has informed our understanding of the unique status of the human voice in the mature auditory cortex and provided potential explanations for mechanisms that underly voice selectivity and identity processing. There is evidence that voice perception undergoes developmental change starting in infancy and extending through early adolescence. While even young infants recognize the voice of their mother, there is an apparent protracted course of development to reach adult-like selectivity for human voice over other sound categories and recognition of other talkers by voice. Gaps in the literature do not allow for an exact mapping of this trajectory or an adequate description of how voice processing and its neural underpinnings abilities evolve. This review provides a comprehensive account of developmental voice processing research published to date and discusses how this evidence fits with and contributes to current theoretical models proposed in the adult literature. We discuss how factors such as cognitive development, neural plasticity, perceptual narrowing, and language acquisition may contribute to the development of voice processing and its investigation in children. We also review evidence of voice processing abilities in premature birth, autism spectrum disorder, and phonagnosia to examine where and how deviations from the typical trajectory of development may manifest.

Preliminary observations on the associations between sensory processing abnormalities and event-related potentials in adults with autism spectrum disorder

Aim

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is thought to involve a variety of neurophysiological characteristics. Event-related potentials (ERPs) reflect cognitive functions in the brain's cognitive processing. In this study, we investigated differences in P300 and N100 of ERPs between ASD and typically developing groups and focused on the relationship between the components of ERPs and measures of autistic traits and sensory processing characteristics.

Methods

ERPs were measured in 96 subjects in the ASD group and 62 subjects in the age- and sex-adjusted typically developing group. Correlations between each component and the scores of the Autism-Spectrum Quotient Japanese version (AQ-J) and the Adolescent and Adult Sensory Profile (AASP) were also evaluated.

Results

The ASD group showed a significant decrease in the amplitude of N100 at C3. Furthermore, a negative correlation was found between lower amplitude at C3 of N100 and low registered sensory scores in both groups.

Conclusion

Our findings imply that the N100 amplitude at C3 could be a potential indicator for examining the neurophysiological traits of ASD; however, these results should be interpreted with caution due to their preliminary nature. These tentative insights into sensory processing anomalies may be discernible in specific subsets of the ASD population, providing a foundation for future investigative pathways.

Social Brain Perspectives on the Social and Evolutionary Neuroscience of Human Language

Human language and social cognition are two key disciplines that have traditionally been studied as separate domains. Nonetheless, an emerging view suggests an alternative perspective. Drawing on the theoretical underpinnings of the social brain hypothesis (thesis of the evolution of brain size and intelligence), the social complexity hypothesis (thesis of the evolution of communication), and empirical research from comparative animal behavior, human social behavior, language acquisition in children, social cognitive neuroscience, and the cognitive neuroscience of language, it is argued that social cognition and language are two significantly interconnected capacities of the human species. Here, evidence in support of this view reviews (1) recent developmental studies on language learning in infants and young children, pointing to the important crucial benefits associated with social stimulation for youngsters, including the quality and quantity of incoming linguistic information, dyadic infant/child-to-parent non-verbal and verbal interactions, and other important social cues integral for facilitating language learning and social bonding; (2) studies of the adult human brain, suggesting a high degree of specialization for sociolinguistic information processing, memory retrieval, and comprehension, suggesting that the function of these neural areas may connect social cognition with language and social bonding; (3) developmental deficits in language and social cognition, including autism spectrum disorder (ASD), illustrating a unique developmental profile, further linking language, social cognition, and social bonding; and (4) neural biomarkers that may help to identify early developmental disorders of language and social cognition. In effect, the social brain and social complexity hypotheses may jointly help to describe how neurotypical children and adults acquire language, why autistic children and adults exhibit simultaneous deficits in language and social cognition, and why nonhuman primates and other organisms with significant computational capacities cannot learn language. But perhaps most critically, the following article argues that this and related research will allow scientists to generate a holistic profile and deeper understanding of the healthy adult social brain while developing more innovative and effective diagnoses, prognoses, and treatments for maladies and deficits also associated with the social brain.

Neural correlates of audiovisual narrative speech perception in children and adults on the autism spectrum: A functional magnetic resonance imaging study

Autistic individuals show substantially reduced benefit from observing visual articulations during audiovisual speech perception, a multisensory integration deficit that is particularly relevant to social communication. This has mostly been studied using simple syllabic or word-level stimuli and it remains unclear how altered lower-level multisensory integration translates to the processing of more complex natural multisensory stimulus environments in autism. Here, functional neuroimaging was used to examine neural correlates of audiovisual gain (AV-gain) in 41 autistic individuals to those of 41 age-matched non-autistic controls when presented with a complex audiovisual narrative. Participants were presented with continuous narration of a story in auditory-alone, visual-alone, and both synchronous and asynchronous audiovisual speech conditions. We hypothesized that previously identified differences in audiovisual speech processing in autism would be characterized by activation differences in brain regions well known to be associated with audiovisual enhancement in neurotypicals. However, our results did not provide evidence for altered processing of auditory alone, visual alone, audiovisual conditions or AV- gain in regions associated with the respective task when comparing activation patterns between groups. Instead, we found that autistic individuals responded with higher activations in mostly frontal regions where the activation to the experimental conditions was below baseline (de-activations) in the control group. These frontal effects were observed in both unisensory and audiovisual conditions, suggesting that these altered activations were not specific to multisensory processing but reflective of more general mechanisms such as an altered disengagement of Default Mode Network processes during the observation of the language stimulus across conditions.

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

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

Inhibitory dysfunction and social processing difficulties in autism: A comprehensive narrative review

The primary inhibitory neurotransmitter γ-aminobutyric acid (GABA) has a prominent role in regulating neural development and function, with disruption to GABAergic signalling linked to behavioural phenotypes associated with neurodevelopmental disorders, particularly autism. Such neurochemical disruption, likely resulting from diverse genetic and molecular mechanisms, particularly during early development, can subsequently affect the cellular balance of excitation and inhibition in neuronal circuits, which may account for the social processing difficulties observed in autism and related conditions. This comprehensive narrative review integrates diverse streams of research from several disciplines, including molecular neurobiology, genetics, epigenetics, and systems neuroscience. In so doing it aims to elucidate the relevance of inhibitory dysfunction to autism, with specific focus on social processing difficulties that represent a core feature of this disorder. Many of the social processing difficulties experienced in autism have been linked to higher levels of the excitatory neurotransmitter glutamate and/or lower levels of inhibitory GABA. While current therapeutic options for social difficulties in autism are largely limited to behavioural interventions, this review highlights the psychopharmacological studies that explore the utility of GABA modulation in alleviating such difficulties.

Towards a comprehensive approach to mentalization-based treatment for children with autism: integrating attachment, neurosciences, and mentalizing

Autism spectrum disorder (ASD) is diagnosed based on socio-communicative difficulties, which are believed to result from deficits in mentalizing, mainly evidenced by alterations in recognizing and responding to the mental states of others. In recent years, efforts have been made to develop mentalization-based treatment (MBT) models for this population. These models focus on enhancing individuals' ability to understand and reflect on their own mental states, as well as those of others. However, MBT approaches for people with ASD are limited by their existing theoretical background, which lacks a strong foundation grounded in neuroscience-based evidence properly integrated with attachment, and mentalizing. These are crucial aspects for understanding psychological processes in autism, and as such, they play a pivotal role in shaping the development of tailored and effective therapeutic strategies for this specific population. In this paper we review evidence related to the neurobiological, interpersonal, and psychological dimensions of autism and their implications for mentalizing processes. We also review previous mentalization-based frameworks on the psychosis continuum to provide a comprehensive understanding of attachment, neurobiology, and mentalization domains in therapeutic approaches for autism. After presenting a synthesis of the literature, we offer a set of clinical strategies for the work with children with autism. Finally, we provide recommendations to advance the field towards more robust models that can serve as a basis for evidence-based therapeutic strategies.

APPlications of amyloid-β precursor protein metabolites in macrocephaly and autism spectrum disorder

Metabolites of the Amyloid-β precursor protein (APP) proteolysis may underlie brain overgrowth in Autism Spectrum Disorder (ASD). We have found elevated APP metabolites (total APP, secreted (s) APPα, and α-secretase adamalysins in the plasma and brain tissue of children with ASD). In this review, we highlight several lines of evidence supporting APP metabolites' potential contribution to macrocephaly in ASD. First, APP appears early in corticogenesis, placing APP in a prime position to accelerate growth in neurons and glia. APP metabolites are upregulated in neuroinflammation, another potential contributor to excessive brain growth in ASD. APP metabolites appear to directly affect translational signaling pathways, which have been linked to single gene forms of syndromic ASD (Fragile X Syndrome, PTEN, Tuberous Sclerosis Complex). Finally, APP metabolites, and microRNA, which regulates APP expression, may contribute to ASD brain overgrowth, particularly increased white matter, through ERK receptor activation on the PI3K/Akt/mTOR/Rho GTPase pathway, favoring myelination.

White and gray matter correlates of theory of mind in autism: a voxel-based morphometry study

Autism spectrum disorder (ASD) is characterized by difficulties in theory of mind (ToM) and social communication. Studying structural and functional correlates of ToM in the brain and how autistic and nonautistic groups differ in terms of these correlates can help with diagnosis and understanding the biological mechanisms of ASD. In this study, we investigated white matter volume (WMV) and gray matter volume (GMV) differences between matching autistic and nonautistic samples, and how these structural features relate to age and ToM skills, indexed by the Reading the Mind in the Eyes (RMIE) measure. The results showed widespread GMV and WMV differences between the two groups in regions crucial for social processes. The autistic group did not express the typically observed negative GMV and positive WMV correlations with age at the same level as the nonautistic group, pointing to abnormalities in developmental structural changes. In addition, we found differences between the two groups in how GMV relates to ToM, particularly in the left frontal regions, and how WMV relates to ToM, mostly in the cingulate and corpus callosum. Finally, GMV in the left insula, a region that is part of the salience network, was found to be crucial in distinguishing ToM performance between the two groups.

Structural brain abnormalities and their association with language impairment in school-aged children with Autism Spectrum Disorder

Language impairment is comorbid in most children with Autism Spectrum Disorder (ASD) but its neural basis is poorly understood. Using structural magnetic resonance imaging (MRI), the present study provides the whole-brain comparison of both volume- and surface-based characteristics between groups of children with and without ASD and investigates the relationships between these characteristics in language-related areas and the language abilities of children with ASD measured with standardized tools. A total of 36 school-aged children participated in the study: 18 children with ASD and 18 age- and sex-matched typically developing controls. The results revealed that multiple regions differed between groups of children in gray matter volume, gray matter thickness, gyrification, and cortical complexity (fractal dimension). White matter volume and sulcus depth did not differ between groups of children in any region. Importantly, gray matter thickness and gyrification of language-related areas were related to language functioning in children with ASD. Thus, the results of the present study shed some light on the structural brain abnormalities associated with language impairment in ASD.

Toward evaluation of multiresolution cortical thickness estimation with FreeSurfer, MaCRUISE, and BrainSuite

Advances in Magnetic Resonance Imaging hardware and methodologies allow for promoting the cortical morphometry with submillimeter spatial resolution. In this paper, we generated 3D self-enhanced high-resolution (HR) MRI imaging, by adapting 1 deep learning architecture, and 3 standard pipelines, FreeSurfer, MaCRUISE, and BrainSuite, have been collectively employed to evaluate the cortical thickness. We systematically investigated the differences in cortical thickness estimation for MRI sequences at multiresolution homologously originated from the native image. It has been revealed that there systematically exhibited the preferences in determining both inner and outer cortical surfaces at higher resolution, yielding most deeper cortical surface placements toward GM/WM or GM/CSF boundaries, which directs a consistent reduction tendency of mean cortical thickness estimation; on the contrary, the lower resolution data will most probably provide a more coarse and rough evaluation in cortical surface reconstruction, resulting in a relatively thicker estimation. Although the differences of cortical thickness estimation at the diverse spatial resolution varied with one another, almost all led to roughly one-sixth to one-fifth significant reduction across the entire brain at the HR, independent to the pipelines we applied, which emphasizes on generally coherent improved accuracy in a data-independent manner and endeavors to cost-efficiency with quantitative opportunities.

Bumetanide Effects on Resting-State EEG in Tuberous Sclerosis Complex in Relation to Clinical Outcome: An Open-Label Study

Neuronal excitation-inhibition (E/I) imbalances are considered an important pathophysiological mechanism in neurodevelopmental disorders. Preclinical studies on tuberous sclerosis complex (TSC), suggest that altered chloride homeostasis may impair GABAergic inhibition and thereby E/I-balance regulation. Correction of chloride homeostasis may thus constitute a treatment target to alleviate behavioral symptoms. Recently, we showed that bumetanide-a chloride-regulating agent-improved behavioral symptoms in the open-label study Bumetanide to Ameliorate Tuberous Sclerosis Complex Hyperexcitable Behaviors trial (BATSCH trial; Eudra-CT: 2016-002408-13). Here, we present resting-state EEG as secondary analysis of BATSCH to investigate associations between EEG measures sensitive to network-level changes in E/I balance and clinical response to bumetanide. EEGs of 10 participants with TSC (aged 8-21 years) were available. Spectral power, long-range temporal correlations (LRTC), and functional E/I ratio (fE/I) in the alpha-frequency band were compared before and after 91 days of treatment. Pre-treatment measures were compared against 29 typically developing children (TDC). EEG measures were correlated with the Aberrant Behavioral Checklist-Irritability subscale (ABC-I), the Social Responsiveness Scale-2 (SRS-2), and the Repetitive Behavior Scale-Revised (RBS-R). At baseline, TSC showed lower alpha-band absolute power and fE/I than TDC. Absolute power increased through bumetanide treatment, which showed a moderate, albeit non-significant, correlation with improvement in RBS-R. Interestingly, correlations between baseline EEG measures and clinical outcomes suggest that most responsiveness might be expected in children with network characteristics around the E/I balance point. In sum, E/I imbalances pointing toward an inhibition-dominated network are present in TSC. We established neurophysiological effects of bumetanide although with an inconclusive relationship with clinical improvement. Nonetheless, our results further indicate that baseline network characteristics might influence treatment response. These findings highlight the possible utility of E/I-sensitive EEG measures to accompany new treatment interventions for TSC.

Clinical Trial Registration

EU Clinical Trial Register, EudraCT 2016-002408-13 (www.clinicaltrialsregister.eu/ctr-search/trial/2016-002408-13/NL). Registered 25 July 2016.

A meta-analytic investigation of grey matter differences in anorexia nervosa and autism spectrum disorder

Recent research reports Anorexia Nervosa (AN) to be highly dependent upon neurobiological function. Some behaviours, particularly concerning food selectivity are found in populations with both Autism Spectrum Disorder (ASD) and AN, and there is a proportionally elevated number of anorexic patients exhibiting symptoms of ASD. We performed a systematic review of structural MRI literature with the aim of identifying common structural neural correlates common to both AN and ASD. Across 46 ASD publications, a meta‐analysis of volumetric differences between ASD and healthy controls revealed no consistently affected brain regions. Meta‐analysis of 23 AN publications revealed increased volume within the orbitofrontal cortex and medial temporal lobe, and adult‐only AN literature revealed differences within the genu of the anterior cingulate cortex. The changes are consistent with alterations in flexible reward‐related learning and episodic memory reported in neuropsychological studies. There was no structural overlap between ASD and AN. Findings suggest no consistent neuroanatomical abnormality associated with ASD, and evidence is lacking to suggest that reported behavioural similarities between those with AN and ASD are due to neuroanatomical structural similarities.

Findings related to neuroanatomical structure in AN/ASD demonstrate overlap and require revisiting.

Meta‐analytic findings show structural increase/decrease versus healthy controls (LPFC/MTL/OFC) in AN, but no clusters found in ASD.

The neuroanatomy associated with ASD is inconsistent, but findings in AN reflect condition‐related impairment in executive function and sociocognitive behaviours.

Multigraph classification using learnable integration network with application to gender fingerprinting

Multigraphs with heterogeneous views present one of the most challenging obstacles to classification tasks due to their complexity. Several works based on feature selection have been recently proposed to disentangle the problem of multigraph heterogeneity. However, such techniques have major drawbacks. First, the bulk of such works lies in the vectorization and the flattening operations, failing to preserve and exploit the rich topological properties of the multigraph. Second, they learn the classification process in a dichotomized manner where the cascaded learning steps are pieced in together independently. Hence, such architectures are inherently agnostic to the cumulative estimation error from step to step. To overcome these drawbacks, we introduce MICNet (multigraph integration and classifier network), the first end-to-end graph neural network based model for multigraph classification. First, we learn a single-view graph representation of a heterogeneous multigraph using a GNN based integration model. The integration process in our model helps tease apart the heterogeneity across the different views of the multigraph by generating a subject-specific graph template while preserving its geometrical and topological properties conserving the node-wise information while reducing the size of the graph (i.e., number of views). Second, we classify each integrated template using a geometric deep learning block which enables us to grasp the salient graph features. We train, in end-to-end fashion, these two blocks using a single objective function to optimize the classification performance. We evaluate our MICNet in gender classification using brain multigraphs derived from different cortical measures. We demonstrate that our MICNet significantly outperformed its variants thereby showing its great potential in multigraph classification.

Developmental brain structural atypicalities in autism: a voxel-based morphometry analysis

BACKGROUND

Structural magnetic resonance imaging (sMRI) studies have shown atypicalities in structural brain changes in individuals with autism spectrum disorder (ASD), while a noticeable discrepancy in their results indicates the necessity of conducting further researches.

METHODS

The current study investigated the atypical structural brain features of autistic individuals who aged 6-30 years old. A total of 52 autistic individuals and 50 age-, gender-, and intelligence quotient (IQ)-matched typically developing (TD) individuals were included in this study, and were assigned into three based cohorts: childhood (6-12 years old), adolescence (13-18 years old), and adulthood (19-30 years old). Analyses of whole-brain volume and voxel-based morphometry (VBM) on the sMRI data were conducted.

RESULTS

No significant difference was found in the volumes of whole-brain, gray matter, and white matter between the autism and TD groups in the three age-based cohorts. For VBM analyses, the volumes of gray matter in the right superior temporal gyrus and right inferior parietal lobule in the autism group (6-12 years old) were smaller than those in the TD group; the gray matter volume in the left inferior parietal lobule in the autism group (13-18 years old) was larger than that in the TD group; the gray matter volume in the right middle occipital gyrus in the autism group (19-30 years old) was larger than that in the TD group, and the gray matter volume in the left posterior cingulate gyrus in the autism group was smaller than that in the TD group.

CONCLUSION

Autistic individuals showed different atypical regional gray matter volumetric changes in childhood, adolescence, and adulthood compared to their TD peers, indicating that it is essential to consider developmental stages of the brain when exploring brain structural atypicalities in autism.

The Role of Structure MRI in Diagnosing Autism

This study proposes a Computer-Aided Diagnostic (CAD) system to diagnose subjects with autism spectrum disorder (ASD). The CAD system identifies morphological anomalies within the brain regions of ASD subjects. Cortical features are scored according to their contribution in diagnosing a subject to be ASD or typically developed (TD) based on a trained machine-learning (ML) model. This approach opens the hope for developing a new CAD system for early personalized diagnosis of ASD. We propose a framework to extract the cerebral cortex from structural MRI as well as identifying the altered areas in the cerebral cortex. This framework consists of the following five main steps: (i) extraction of cerebral cortex from structural MRI; (ii) cortical parcellation to a standard atlas; (iii) identifying ASD associated cortical markers; (iv) adjusting feature values according to sex and age; (v) building tailored neuro-atlases to identify ASD; and (vi) artificial neural networks (NN) are trained to classify ASD. The system is tested on the Autism Brain Imaging Data Exchange (ABIDE I) sites achieving an average balanced accuracy score of 97±2%. This paper demonstrates the ability to develop an objective CAD system using structure MRI and tailored neuro-atlases describing specific developmental patterns of the brain in autism.

Autonomic Dysfunction in Autism Spectrum Disorder

Background: There have been previous reports of enhanced sympathoexcitation in autism spectrum disorder (ASD). However, there has been no formal investigation of autonomic dysfunction in ASD. Also, the joint hypermobile form of Ehlers-Danlos syndrome (hE-DS) that maybe overrepresented in ASD and orthostatic related autonomic dysfunction. This study examined the comorbidity of ASD, autonomic dysfunction and hE-DS in two UK autonomic national referral centers. Proven, documented and globally accepted clinical autonomic investigations were used to assess neuro-cardiovascular autonomic function in a cohort of ASD subjects and in age-matched healthy controls. Methods: Clinical data from 28 referrals with a confirmed diagnosis of ASD over a 10-year period were compared with 19 age-matched healthy controls. Autonomic function was determined using methods established in the centers previously described in detail. Results: 20/28 ASD had a diagnosed autonomic condition; 9 had the postural tachycardia syndrome (PoTS), 4 PoTS and vasovagal syncope (VVS), 3 experienced presyncope, 1 essential hyperhidrosis, 1 orthostatic hypotension, 1 VVS alone and 1 a combination of PoTS, VVS and essential hyperhidrosis. 16/20 ASD with autonomic dysfunction had hE-DS. In ASD, basal heart rate and responses to orthostatic tests of autonomic function were elevated, supporting previous findings of increased sympathoexcitation. However, sympathetic vasoconstriction was impaired in ASD. Conclusion: Intermittent neuro-cardiovascular autonomic dysfunction affecting heart rate and blood pressure was over-represented in ASD. There is a strong association with hE-DS. Autonomic dysfunction may further impair quality of life in ASD, particularly in those unable to adequately express their experience of autonomic symptoms.

The relationship between brain abnormalities and autistic psychopathology in pervasive developmental disorders

The aim of the present research has been to determine whether there is a relationship between brain abnormalities found on magnetic resonance imaging (MRI) and autistic psychopathology. A retrospective analysis covering a period between 1998 and 2015 included 489 children with autism (404 boys, 85 girls; average age 8.0 ± 4.2 years) who underwent an MRI of the brain. For clinical diagnosis of autism, the International Classification of Diseases, 10th revision (ICD-10), was used. Autistic psychopathology was evaluated by means of the Autism Diagnostic Interview - Revised. The Spearman nonparametric correlation analysis and chi-square test were used to examine the possible relationships between variables. The group of autistic children did not manifest a statistically significant correlation between the parameters examined on MRI and autistic psychopathology. A correlation between other cysts and repetitive behavior was significant only at trend level (P = 0.054). Gliosis of the brain was significantly more frequent in autistic children with mental retardation than in children without mental retardation (14.1% vs. 7.4%; P = 0.028). Nonmyelinated areas in the brain were significantly more frequent in autistic children with autistic regression than in children without autistic regression (29.9% vs. 15.7%; P = 0.008). Mental retardation was significantly more frequent in autistic children with autistic regression than in children without regression (73.2% vs. 52.5%; P = 0.002). Our research study did not reveal a statistically significant correlation of brain abnormalities on MRI with autistic psychopathology.

Neurodevelopmental atypisms in the context of joint hypermobility, hypermobility spectrum disorders, and Ehlers-Danlos syndromes

Joint hypermobility (JHM), defined as an increased range of joint motion, is a frequent somatic trait in the general population but also the hallmark of many of the hereditary disorders of connective tissue. Ehlers-Danlos syndromes (EDS) belong to this group of diseases and are characterized by tissue fragility, skin abnormalities, and JHM. Between JHM and EDS, there are the so-called hypermobility spectrum disorders (HSD), which is an umbrella term referring to people with symptomatic JHM who do not fulfill criteria for a syndromic connective tissue disorder such as EDS. Among the variety of clinical correlates of JHM/HSD/EDS, neurodevelopmental atypisms are common although often not screened for and identified in the clinical setting. This article reviews the pertinent literature concerning neurodevelopmental conditions for which there is some evidence of an association with JHM/HSD/EDS. These include hyperactivity and attention deficit, learning, communication, and motor problems including tic disorders such as Tourette syndrome and autism spectrum disorders. Underlying mechanism hypotheses for such interconnections are also reviewed. The coexistence of connective tissue-altered conditions and neurodevelopmental atypisms increases disability in patients from an early age. Thus, increased awareness among clinicians and researchers is necessary to promote assessment, diagnosis, and develop management strategies to meet the specific needs of those affected.

Are conspecific social videos rewarding to chimpanzees (Pan troglodytes)? A test of the social motivation theory

Many claim that social stimuli are rewarding to primates, but few, if any, studies have explicitly demonstrated their reward value. Here, we examined whether chimpanzees would produce overt responses for the opportunity to view conspecific social, compared to dynamic (video: Experiment 1) and static (picture: Experiment 2) control content. We also explored the relationships between variation in social reward and social behavior and cognition. We provided captive chimpanzees with access to a touchscreen during four, one-hour sessions (two 'conspecific social' and two 'control'). The sessions consisted of ten, 15-second videos (or pictures in Experiment 2) of either chimpanzees engaging in a variety of behaviors (social condition) or vehicles, humans, or other animals engaged in some activity (control condition). For each chimpanzee, we recorded the number of responses to the touchscreen and the frequency of watching the stimuli. Independent t-tests revealed no sex or rearing differences in touching and watching the social or control videos (p>0.05). Repeated measures ANOVAs showed chimpanzees touched and watched the screen significantly more often during the social compared to control video sessions. Furthermore, although chimpanzees did not touch the screen more often during social than control picture sessions in Experiment 2, they did watch the screen more often. Additionally, chimpanzees that previously performed better on a task of social cognition and engaged in more affiliative behavior watched a higher percentage of social videos during the touchscreen task. These results are consistent with the social motivation theory, and indicate social stimuli are intrinsically rewarding, as chimpanzees made more overt responses for the opportunity to view conspecific social, compared to control, content.

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

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

Predicting pediatric anxiety from the temporal pole using neural responses to emotional faces

A prominent cognitive aspect of anxiety is dysregulation of emotional interpretation of facial expressions, associated with neural activity from the amygdala and prefrontal cortex. We report machine learning analysis of fMRI results supporting a key role for a third area, the temporal pole (TP) for childhood anxiety in this context. This finding is based on differential fMRI responses to emotional faces (angry versus fearful faces) in children with one or more of generalized anxiety, separation anxiety, and social phobia (n = 22) compared with matched controls (n = 23). In our machine learning (Adaptive Boosting) model, the right TP distinguished anxious from control children (accuracy = 81%). Involvement of the TP as significant for neurocognitive aspects of pediatric anxiety is a novel finding worthy of further investigation.

Gray Matter Abnormalities of Orbitofrontal Cortex and Striatum in Drug-Naïve Adult Patients With Obsessive-Compulsive Disorder

Objective: This study examined whether obsessive-compulsive disorder (OCD) patients have gray matter abnormalities in regions related to executive function, and whether such abnormalities are associated with impaired executive function. Methods: Multiple scales were administered to 27 first-episode drug-naïve OCD patients and 29 healthy controls. Comprehensive brain morphometric indicators of orbitofrontal cortex (OFC) and three striatum areas (caudate, putamen, and pallidum) were determined. Hemisphere lateralization index was calculated for each region of interest. Correlations between lateralization index and psychological variables were examined in OCD group. Results: The OCD group had greater local gyrification index for the right OFC and greater gray matter volumes of the bilateral putamen and left pallidum than healthy controls. They also had weaker left hemisphere superiority for local gyrification index of the OFC and gray matter volume of the putamen, but stronger left hemisphere superiority for gray matter volume of the pallidum. Patients' lateralization index for local gyrification index of the OFC correlated negatively with Yale-Brown Obsessive Compulsive Scale and Dysexecutive Questionnaire scores, respectively. Conclusion: Structural abnormalities of the bilateral putamen, left pallidum, and right OFC may underlie OCD pathology. Abnormal lateralization in OCD may contribute to the onset of obsessive-compulsive symptoms and impaired executive function.

Decreased grey matter volumes in unaffected mothers of individuals with autism spectrum disorder reflect the broader autism endophenotype

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with an early onset and a strong genetic origin. Unaffected relatives may present similar but subthreshold characteristics of ASD. This broader autism phenotype is especially prevalent in the parents of individuals with ASD, suggesting that it has heritable factors. Although previous studies have demonstrated brain morphometry differences in ASD, they are poorly understood in parents of individuals with ASD. Here, we estimated grey matter volume in 45 mothers of children with ASD (mASD) and 46 age-, sex-, and handedness-matched controls using whole-brain voxel-based morphometry analysis. The mASD group had smaller grey matter volume in the right middle temporal gyrus, temporoparietal junction, cerebellum, and parahippocampal gyrus compared with the control group. Furthermore, we analysed the correlations of these brain volumes with ASD behavioural characteristics using autism spectrum quotient (AQ) and systemizing quotient (SQ) scores, which measure general autistic traits and the drive to systemize. Smaller volumes in the middle temporal gyrus and temporoparietal junction correlated with higher SQ scores, and smaller volumes in the cerebellum and parahippocampal gyrus correlated with higher AQ scores. Our findings suggest that atypical grey matter volumes in mASD may represent one of the neurostructural endophenotypes of ASD.

Brain mRNA Expression Associated with Cortical Volume Alterations in Autism Spectrum Disorder

Numerous studies report abnormal cerebral cortex volume (CCV) in autism spectrum disorder (ASD); however, genes related to CCV abnormalities in ASD remain largely unknown. Here, we identify genes associated with CCV alterations in ASD by performing spatial correlations between the gene expression of 6 donated brains and neuroimaging data from 1,404 ASD patients and 1,499 controls. Based on spatial correlations between gene expression and CCV differences from two independent meta-analyses and between gene expression and individual CCV distributions of 404 patients and 496 controls, we identify 417 genes associated with both CCV differences and individual CCV distributions. These genes are enriched for genetic association signals and genes downregulated in the ASD post-mortem brain. The expression patterns of these genes are correlated with brain activation patterns of language-related neural processes frequently impaired in ASD. These findings highlight a model whereby genetic risk impacts gene expression (downregulated), which leads to CCV alterations in ASD.

Dissociating regional gray matter density and gray matter volume in autism spectrum condition

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Local gray matter structure can be separated into density and volume.

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Gray matter density increased and volume decreased with age in adolescence.

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Increased gray matter density but reduced volume in girls relative to boys.

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Autism is associated with increased gray matter volume, but not density.

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Regions with increased volume align with prior studies in autistic youth.

Background

Despite decades of research, there is continued uncertainty regarding whether autism is associated with a specific profile of gray matter (GM) structure. This inconsistency may stem from the widespread use of voxel-based morphometry (VBM) methods that combine indices of GM density and GM volume. If GM density or volume, but not both, prove different in autism, the traditional VBM approach of combining the two indices may obscure the difference. The present study measures GM density and volume separately to examine whether autism is associated with alterations in GM volume, density, or both.

Methods

Differences in MRI-based GM density and volume were examined in 6–25 year-olds with a diagnosis of autism spectrum disorder (n = 213, 80.8% male, IQ 47–154) and a typically developing (TD) sample (n = 190, 71.6% male, IQ 67–155). High-resolution T1-weighted anatomical images were collected on a single MRI scanner. Regional density and volume were estimated via whole-brain parcellation comprised of 1625 parcels. Parcel-wise analyses were conducted using generalized additive models while controlling the false discovery rate (FDR, q < 0.05). Volume differences in the 68-region Desikan-Killiany atlas derived from Freesurfer were also examined, to establish the generalizability of findings across methods.

Results

No density differences were observed between the autistic and TD groups, either in individual parcels or whole brain mean density. Increased volume was observed in autism compared to the TD group when controlling for Age, Sex, and IQ, both at the level of the whole brain (total volume) and in 45 parcels (2.8% of total parcels). Parcels with greater volume included inferior, middle, and superior temporal gyrus, inferior and superior frontal gyrus, precuneus, and fusiform gyrus. Converging evidence from a standard Freesurfer pipeline also identified greater volume in a number of overlapping regions.

Limitations

The method for determining “density” is not a direct measure of neuronal density, and this study cannot reveal underlying cellular differences. While this study represents possibly the largest single-site sample of its kind, it is underpowered to detect very small differences.

Conclusions

These results provide compelling evidence that autism is associated with regional GM volumetric differences, which are more prominent than density differences. This underscores the importance of examining volume and density separately, and suggests that direct measures of volume (e.g. region-of-interest or tensor-based morphometry approaches) may be more sensitive to autism-relevant differences in neuroanatomy than concentration/density-based approaches.

Left hemispheric deficit in the sustained neuromagnetic response to periodic click trains in children with ASD

BACKGROUND

Deficits in perception and production of vocal pitch are often observed in people with autism spectrum disorder (ASD), but the neural basis of these deficits is unknown. In magnetoencephalogram (MEG), spectrally complex periodic sounds trigger two continuous neural responses-the auditory steady state response (ASSR) and the sustained field (SF). It has been shown that the SF in neurotypical individuals is associated with low-level analysis of pitch in the 'pitch processing center' of the Heschl's gyrus. Therefore, alternations in this auditory response may reflect atypical processing of vocal pitch. The SF, however, has never been studied in people with ASD.

METHODS

We used MEG and individual brain models to investigate the ASSR and SF evoked by monaural 40 Hz click trains in boys with ASD (N = 35) and neurotypical (NT) boys (N = 35) aged 7-12-years.

RESULTS

In agreement with the previous research in adults, the cortical sources of the SF in children were located in the left and right Heschl's gyri, anterolateral to those of the ASSR. In both groups, the SF and ASSR dominated in the right hemisphere and were higher in the hemisphere contralateral to the stimulated ear. The ASSR increased with age in both NT and ASD children and did not differ between the groups. The SF amplitude did not significantly change between the ages of 7 and 12 years. It was moderately attenuated in both hemispheres and was markedly delayed and displaced in the left hemisphere in boys with ASD. The SF delay in participants with ASD was present irrespective of their intelligence level and severity of autism symptoms.

LIMITATIONS

We did not test the language abilities of our participants. Therefore, the link between SF and processing of vocal pitch in children with ASD remains speculative.

CONCLUSION

Children with ASD demonstrate atypical processing of spectrally complex periodic sound at the level of the core auditory cortex of the left-hemisphere. The observed neural deficit may contribute to speech perception difficulties experienced by children with ASD, including their poor perception and production of linguistic prosody.

A voxel-wise assessment of growth differences in infants developing autism spectrum disorder

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Pediatric neuroimaging study of Autism Spectrum Disorder.

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Longitudinal Tensor Based Morphometry of the presymptomatic period of ASD.

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Differences in voxelwise growth trajectories of children with ASD.

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Regions with differences have been implicated in the core symptoms of ASD.

Autism Spectrum Disorder (ASD) is a phenotypically and etiologically heterogeneous developmental disorder typically diagnosed around 4 years of age. The development of biomarkers to help in earlier, presymptomatic diagnosis could facilitate earlier identification and therefore earlier intervention and may lead to better outcomes, as well as providing information to help better understand the underlying mechanisms of ASD. In this study, magnetic resonance imaging (MRI) scans of infants at high familial risk, from the Infant Brain Imaging Study (IBIS), at 6, 12 and 24 months of age were included in a morphological analysis, fitting a mixed-effects model to Tensor Based Morphometry (TBM) results to obtain voxel-wise growth trajectories. Subjects were grouped by familial risk and clinical diagnosis at 2 years of age. Several regions, including the posterior cingulate gyrus, the cingulum, the fusiform gyrus, and the precentral gyrus, showed a significant effect for the interaction of group and age associated with ASD, either as an increased or a decreased growth rate of the cerebrum. In general, our results showed increased growth rate within white matter with decreased growth rate found mostly in grey matter. Overall, the regions showing increased growth rate were larger and more numerous than those with decreased growth rate. These results detail, at the voxel level, differences in brain growth trajectories in ASD during the first years of life, previously reported in terms of overall brain volume and surface area.

Consensus Paper: Cerebellum and Social Cognition

The traditional view on the cerebellum is that it controls motor behavior. Although recent work has revealed that the cerebellum supports also nonmotor functions such as cognition and affect, only during the last 5 years it has become evident that the cerebellum also plays an important social role. This role is evident in social cognition based on interpreting goal-directed actions through the movements of individuals (social "mirroring") which is very close to its original role in motor learning, as well as in social understanding of other individuals' mental state, such as their intentions, beliefs, past behaviors, future aspirations, and personality traits (social "mentalizing"). Most of this mentalizing role is supported by the posterior cerebellum (e.g., Crus I and II). The most dominant hypothesis is that the cerebellum assists in learning and understanding social action sequences, and so facilitates social cognition by supporting optimal predictions about imminent or future social interaction and cooperation. This consensus paper brings together experts from different fields to discuss recent efforts in understanding the role of the cerebellum in social cognition, and the understanding of social behaviors and mental states by others, its effect on clinical impairments such as cerebellar ataxia and autism spectrum disorder, and how the cerebellum can become a potential target for noninvasive brain stimulation as a therapeutic intervention. We report on the most recent empirical findings and techniques for understanding and manipulating cerebellar circuits in humans. Cerebellar circuitry appears now as a key structure to elucidate social interactions.

Approaches to Understanding Multisensory Dysfunction in Autism Spectrum Disorder

Abnormal sensory responses are a DSM-5 symptom of autism spectrum disorder (ASD), and research findings demonstrate altered sensory processing in ASD. Beyond difficulties with processing information within single sensory domains, including both hypersensitivity and hyposensitivity, difficulties in multisensory processing are becoming a core issue of focus in ASD. These difficulties may be targeted by treatment approaches such as "sensory integration," which is frequently applied in autism treatment but not yet based on clear evidence. Recently, psychophysical data have emerged to demonstrate multisensory deficits in some children with ASD. Unlike deficits in social communication, which are best understood in humans, sensory and multisensory changes offer a tractable marker of circuit dysfunction that is more easily translated into animal model systems to probe the underlying neurobiological mechanisms. Paralleling experimental paradigms that were previously applied in humans and larger mammals, we and others have demonstrated that multisensory function can also be examined behaviorally in rodents. Here, we review the sensory and multisensory difficulties commonly found in ASD, examining laboratory findings that relate these findings across species. Next, we discuss the known neurobiology of multisensory integration, drawing largely on experimental work in larger mammals, and extensions of these paradigms into rodents. Finally, we describe emerging investigations into multisensory processing in genetic mouse models related to autism risk. By detailing findings from humans to mice, we highlight the advantage of multisensory paradigms that can be easily translated across species, as well as the potential for rodent experimental systems to reveal opportunities for novel treatments. LAY SUMMARY: Sensory and multisensory deficits are commonly found in ASD and may result in cascading effects that impact social communication. By using similar experiments to those in humans, we discuss how studies in animal models may allow an understanding of the brain mechanisms that underlie difficulties in multisensory integration, with the ultimate goal of developing new treatments. Autism Res 2020, 13: 1430-1449. © 2020 International Society for Autism Research, Wiley Periodicals, Inc.

Altered Connectivity During a False-Belief Task in Adults With Autism Spectrum Disorder

BACKGROUND

Deficits in social communication are one of the main features of autism spectrum disorder (ASD). Adults with ASD show atypical brain activity during false-belief understanding, an aspect of social communication involving the ability to infer that an individual can have an incorrect belief about a situation. Our study is the first to investigate whether adults with ASD exhibit differences in frequency-specific functional connectivity patterns during false-belief reasoning.

METHODS

We used magnetoencephalography to contrast functional connectivity underlying false-belief understanding between 40 adults with ASD and 39 control adults. We examined whole-brain phase synchrony measures during a false-belief task in 3 frequency bands: theta (4-7 Hz), alpha (8-14 Hz), and beta (15-30 Hz).

RESULTS

Adults with ASD demonstrated reduced theta-band connectivity compared with control adults between several right-lateralized and midline regions such as the medial prefrontal cortex, right temporoparietal junction, right inferior frontal gyrus, and right superior temporal gyrus. During false-belief trials, they also recruited a network in the beta band that included primary visual regions such as the bilateral inferior occipital gyri and the left anterior temporoparietal junction.

CONCLUSIONS

Reduced theta-band synchrony between areas associated with mentalizing, inhibition, and visual processing implies some difficulty in communication among these functions in ASD. This impairment in top-down control in the theta band may be counterbalanced by their engagement of a beta-band network because both the left anterior temporoparietal junction and beta-band oscillations are associated with attentional processes. Thus, adults with ASD demonstrate alternative neural mechanisms for successful false-belief reasoning.

Comparative meta-analyses of brain structural and functional abnormalities during cognitive control in attention-deficit/hyperactivity disorder and autism spectrum disorder

BACKGROUND

People with attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) have abnormalities in frontal, temporal, parietal and striato-thalamic networks. It is unclear to what extent these abnormalities are distinctive or shared. This comparative meta-analysis aimed to identify the most consistent disorder-differentiating and shared structural and functional abnormalities.

METHODS

Systematic literature search was conducted for whole-brain voxel-based morphometry (VBM) and functional magnetic resonance imaging (fMRI) studies of cognitive control comparing people with ASD or ADHD with typically developing controls. Regional gray matter volume (GMV) and fMRI abnormalities during cognitive control were compared in the overall sample and in age-, sex- and IQ-matched subgroups with seed-based d mapping meta-analytic methods.

RESULTS

Eighty-six independent VBM (1533 ADHD and 1295 controls; 1445 ASD and 1477 controls) and 60 fMRI datasets (1001 ADHD and 1004 controls; 335 ASD and 353 controls) were identified. The VBM meta-analyses revealed ADHD-differentiating decreased ventromedial orbitofrontal (z = 2.22, p < 0.0001) but ASD-differentiating increased bilateral temporal and right dorsolateral prefrontal GMV (zs ⩾ 1.64, ps ⩽ 0.002). The fMRI meta-analyses of cognitive control revealed ASD-differentiating medial prefrontal underactivation but overactivation in bilateral ventrolateral prefrontal cortices and precuneus (zs ⩾ 1.04, ps ⩽ 0.003). During motor response inhibition specifically, ADHD relative to ASD showed right inferior fronto-striatal underactivation (zs ⩾ 1.14, ps ⩽ 0.003) but shared right anterior insula underactivation.

CONCLUSIONS

People with ADHD and ASD have mostly distinct structural abnormalities, with enlarged fronto-temporal GMV in ASD and reduced orbitofrontal GMV in ADHD; and mostly distinct functional abnormalities, which were more pronounced in ASD.

Novel Contribution of Secreted Amyloid-β Precursor Protein to White Matter Brain Enlargement in Autism Spectrum Disorder

The most replicated neuroanatomical finding in autism is the tendency toward brain overgrowth, especially in younger children. Research shows that both gray and white matter are enlarged. Proposed mechanisms underlying brain enlargement include abnormal inflammatory and neurotrophic signals that lead to excessive, aberrant dendritic connectivity via disrupted pruning and cell adhesion, and enlargement of white matter due to excessive gliogenesis and increased myelination. Amyloid-β protein precursor (βAPP) and its metabolites, more commonly associated with Alzheimer's disease (AD), are also dysregulated in autism plasma and brain tissue samples. This review highlights findings that demonstrate how one βAPP metabolite, secreted APPα, and the ADAM family α-secretases, may lead to increased brain matter, with emphasis on increased white matter as seen in autism. sAPPα and the ADAM family α-secretases contribute to the anabolic, non-amyloidogenic pathway, which is in contrast to the amyloid (catabolic) pathway known to contribute to Alzheimer disease. The non-amyloidogenic pathway could produce brain enlargement via genetic mechanisms affecting mRNA translation and polygenic factors that converge on molecular pathways (mitogen-activated protein kinase/MAPK and mechanistic target of rapamycin/mTOR), promoting neuroinflammation. A novel mechanism linking the non-amyloidogenic pathway to white matter enlargement is proposed: α-secretase and/or sAPPα, activated by ERK receptor signaling activates P13K/AKt/mTOR and then Rho GTPases favoring myelination via oligodendrocyte progenitor cell (OPC) activation of cofilin. Applying known pathways in AD to autism should allow further understanding and provide options for new drug targets.

White Matter Connectome Edge Density in Children with Autism Spectrum Disorders: Potential Imaging Biomarkers Using Machine-Learning Models

Prior neuroimaging studies have reported white matter network underconnectivity as a potential mechanism for autism spectrum disorder (ASD). In this study, we examined the structural connectome of children with ASD using edge density imaging (EDI), and then applied machine-learning algorithms to identify children with ASD based on tract-based connectivity metrics. Boys aged 8-12 years were included: 14 with ASD and 33 typically developing children. The edge density (ED) maps were computed from probabilistic streamline tractography applied to high angular resolution diffusion imaging. Tract-based spatial statistics was used for voxel-wise comparison and coregistration of ED maps in addition to conventional diffusion tensor imaging (DTI) metrics of fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD). Tract-based average DTI/connectome metrics were calculated and used as input for different machine-learning models: naïve Bayes, random forest, support vector machines (SVMs), and neural networks. For these models, cross-validation was performed with stratified random sampling ( × 1,000 permutations). The average accuracy among validation samples was calculated. In voxel-wise analysis, the body and splenium of corpus callosum, bilateral superior and posterior corona radiata, and left superior longitudinal fasciculus showed significantly lower ED in children with ASD; whereas, we could not find significant difference in FA, MD, and RD maps between the two study groups. Overall, machine-learning models using tract-based ED metrics had better performance in identification of children with ASD compared with those using FA, MD, and RD. The EDI-based random forest models had greater average accuracy (75.3%), specificity (97.0%), and positive predictive value (81.5%), whereas EDI-based polynomial SVM had greater sensitivity (51.4%) and negative predictive values (77.7%). In conclusion, we found reduced density of connectome edges in the posterior white matter tracts of children with ASD, and demonstrated the feasibility of connectome-based machine-learning algorithms in identification of children with ASD.

Reduction in grey matter volume and its correlation with clinical symptoms in Chinese boys with low functioning autism spectrum disorder

BACKGROUND

Previous studies have reported changes within grey matter (GM) volume in children with autism spectrum disorder (ASD); however, little is known about GM volume changes and the relation with symptom severity in Chinese boys with low functioning autism spectrum disorder (LFASD).

METHOD

GM volume was analysed using SPM 8 and compared between 16 boys with LFASD as well as 16 typically developing (TD) boys (using REST 1.8). Additionally, the correlation between GM volume and clinical symptoms was analysed, using subscales within the Autism Behaviour Checklist (ABC).

RESULTS

The comparison showed a reduced volume of GM in 11 clusters in the boys with LFASD (i.e., the left inferior frontal gyrus, orbital part; right superior temporal gyrus, superior frontal gyrus, dorsolateral; precuneus and postcentral; bilateral rectus and middle temporal gyrus) and 1 area with increased GM volume (right caudate) compared to the TD group. Additionally, the GM volume of the left inferior frontal gyrus, orbital part was negatively correlated with the Social subscale score of the ABC (r = -0.765, P = 0.002), and the GM volume of the left Rectus was negatively associated with the Language, Body concept and Self-care subscale scores and the total score on the ABC(r = -0.624, P = 0.023; r = -0.657, P = 0.011; r = -0.618, P = 0.025; r = -0.625, P = 0.022). Further, the GM volume of the right Caudate was negatively correlated with the Sensory subscale on the ABC (r = -0.593, P = 0.033).

CONCLUSION

In conclusion, the current study's findings display that the GM volume was widely reduced in Chinese boys with LFASD compared to TD boys and negatively correlated with the clinical symptoms, indicating a possible pathological mechanism of LFASD.

Autism, Joint Hypermobility-Related Disorders and Pain

Autism Spectrum Disorder (ASD) and Joint Hypermobility-Related Disorders are blanket terms for two etiologically and clinically heterogeneous groups of pathologies that usually appears in childhood. These conditions are seen by different medical fields, such as psychiatry in the case of ASD, and musculoskeletal disciplines and genetics in the case of hypermobility-related disorders. Thus, a link between them is rarely established in clinical setting, despite a scarce but growing body of research suggesting that both conditions co-occur more often than expected by chance. Hypermobility is a frequent sign of hereditary disorders of connective tissue (e.g., Ehlers-Danlos syndromes, Marfan syndrome), in which the main characteristic is the multisystem fragility that prone to proprioceptive and motor coordination dysfunction and hence to trauma and chronic pain. Considering the high probability that pain remains disregarded and untreated in people with ASD due to communication and methodological difficulties, increasing awareness about the interconnection between ASD and hypermobility-related disorders is relevant, since it may help identify those ASD patients susceptible to chronic pain.

Support Vector Machines, Multidimensional Scaling and Magnetic Resonance Imaging Reveal Structural Brain Abnormalities Associated With the Interaction Between Autism Spectrum Disorder and Sex

Despite substantial efforts, it remains difficult to identify reliable neuroanatomic biomarkers of autism spectrum disorder (ASD) based on magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). Studies which use standard statistical methods to approach this task have been hampered by numerous challenges, many of which are innate to the mathematical formulation and assumptions of general linear models (GLM). Although the potential of alternative approaches such as machine learning (ML) to identify robust neuroanatomic correlates of psychiatric disease has long been acknowledged, few studies have attempted to evaluate the abilities of ML to identify structural brain abnormalities associated with ASD. Here we use a sample of 110 ASD patients and 83 typically developing (TD) volunteers (95 females) to assess the suitability of support vector machines (SVMs, a robust type of ML) as an alternative to standard statistical inference for identifying structural brain features which can reliably distinguish ASD patients from TD subjects of either sex, thereby facilitating the study of the interaction between ASD diagnosis and sex. We find that SVMs can perform these tasks with high accuracy and that the neuroanatomic correlates of ASD identified using SVMs overlap substantially with those found using conventional statistical methods. Our results confirm and establish SVMs as powerful ML tools for the study of ASD-related structural brain abnormalities. Additionally, they provide novel insights into the volumetric, morphometric, and connectomic correlates of this epidemiologically significant disorder.

Altered Anterior Insular Asymmetry in Pre-teen and Adolescent Youth with Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is hallmarked by social-emotional reciprocity deficits. Social-emotional responding requires the clear recognition of social cues as well as the internal monitoring of emotional salience. Insular cortex is central to the salience network, and plays a key role in approach-avoidance emotional valuation. Consistent right anterior insular hypoactivity and variable volumetric differences of insular cortical volumes were shown previously. The current study analyzed anterior and posterior insular volume/asymmetry changes in ASD across age. Age was used as an additional grouping variable as previous studies indicated differential regional volume in ASD individuals before and after puberty onset. In the current sample, pre-teen ASD expressed left lateralized anterior insula, while adolescent ASD had right lateralization. Typically developing (TD) individuals expressed the opposite lateralization of anterior insula in both age-groups (right greater than left anterior insular volume among pre-teen TD and left greater than right anterior insular volume among adolescent TD). Social-emotional calibrated severity scores from the ADOS were positively correlated with leftward anterior insular asymmetry and negatively correlated with proportional right anterior insular volumes in ASD. Insular cortex has a lateralized role in autonomic nervous system regulation (parasympathetic control in the left, sympathetic control in the right). Atypical insular asymmetry in ASD may contribute to the development of networks with a diminished salience signal to human faces and voices, and may lead to more learned passive avoidant responses to such stimuli at younger ages, leading to more distressed responses in adolescence. Data here supports the use of early behavioral intervention to increase awareness of and reward for social-emotional cues.