Atypical frontoamygdala functional connectivity in youth with autism

Prefrontal Cortex Responses to Social Video Stimuli in Young Children with and without Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder affecting individuals worldwide and characterized by deficits in social interaction along with the presence of restricted interest and repetitive behaviors. Despite decades of behavioral research, little is known about the brain mechanisms that influence social behaviors among children with ASD. This, in part, is due to limitations of traditional imaging techniques specifically targeting pediatric populations. As a portable and scalable optical brain monitoring technology, functional near infrared spectroscopy (fNIRS) provides a measure of cerebral hemodynamics related to sensory, motor, or cognitive function. Here, we utilized fNIRS to investigate the prefrontal cortex (PFC) activity of young children with ASD and with typical development while they watched social and nonsocial video clips. The PFC activity of ASD children was significantly higher for social stimuli at medial PFC, which is implicated in social cognition/processing. Moreover, this activity was also consistently correlated with clinical measures, and higher activation of the same brain area only during social video viewing was associated with more ASD symptoms. This is the first study to implement a neuroergonomics approach to investigate cognitive load in response to realistic, complex, and dynamic audiovisual social stimuli for young children with and without autism. Our results further confirm that new generation of portable fNIRS neuroimaging can be used for ecologically valid measurements of the brain function of toddlers and preschool children with ASD.

Atypical neural encoding of faces in individuals with autism spectrum disorder

Individuals with autism spectrum disorder (ASD) experience pervasive difficulties in processing social information from faces. However, the behavioral and neural mechanisms underlying social trait judgments of faces in ASD remain largely unclear. Here, we comprehensively addressed this question by employing functional neuroimaging and parametrically generated faces that vary in facial trustworthiness and dominance. Behaviorally, participants with ASD exhibited reduced specificity but increased inter-rater variability in social trait judgments. Neurally, participants with ASD showed hypo-activation across broad face-processing areas. Multivariate analysis based on trial-by-trial face responses could discriminate participant groups in the majority of the face-processing areas. Encoding social traits in ASD engaged vastly different face-processing areas compared to controls, and encoding different social traits engaged different brain areas. Interestingly, the idiosyncratic brain areas encoding social traits in ASD were still flexible and context-dependent, similar to neurotypicals. Additionally, participants with ASD also showed an altered encoding of facial saliency features in the eyes and mouth. Together, our results provide a comprehensive understanding of the neural mechanisms underlying social trait judgments in ASD.

Central Executive and Default Mode Networks: An Appraisal of Executive Function and Social Skill Brain-Behavior Correlates in Youth with Autism Spectrum Disorder

Atypical connectivity patterns have been observed for individuals with autism spectrum disorders (ASD), particularly across the triple-network model. The current study investigated brain-behavior relationships in the context of social skills and executive function profiles for ASD youth. We calculated connectivity measures from diffusion tensor imaging using Bayesian estimation and probabilistic tractography. We replicated prior structural equation modeling of behavioral measures with total default mode network (DMN) connectivity to include comparisons with central executive network (CEN) connectivity and CEN-DMN connectivity. Increased within-CEN connectivity was related to metacognitive strengths. Our findings indicate behavior regulation difficulties in youth with ASD may be attributable to impaired connectivity between the CEN and DMN and social skill difficulties may be exacerbated by impaired within-DMN connectivity.

Amygdalar neurotransmission alterations in the BTBR mice model of idiopathic autism

Autism Spectrum Disorders (ASD) are principally diagnosed by three core behavioural symptoms, such as stereotyped repertoire, communication impairments and social dysfunctions. This complex pathology has been linked to abnormalities of corticostriatal and limbic circuits. Despite experimental efforts in elucidating the molecular mechanisms behind these abnormalities, a clear etiopathogenic hypothesis is still lacking. To this aim, preclinical studies can be really helpful to longitudinally study behavioural alterations resembling human symptoms and to investigate the underlying neurobiological correlates. In this regard, the BTBR T+ Itpr3tf/J (BTBR) mice are an inbred mouse strain that exhibits a pattern of behaviours well resembling human ASD-like behavioural features. In this study, the BTBR mice model was used to investigate neurochemical and biomolecular alterations, regarding Nerve Growth Factor (NGF) and Brain-Derived Neurotrophic Factor (BDNF), together with GABAergic, glutamatergic, cholinergic, dopaminergic and noradrenergic neurotransmissions and their metabolites in four different brain areas, i.e. prefrontal cortex, hippocampus, amygdala and hypothalamus. In our results, BTBR strain reported decreased noradrenaline, acetylcholine and GABA levels in prefrontal cortex, while hippocampal measurements showed reduced NGF and BDNF expression levels, together with GABA levels. Concerning hypothalamus, no differences were retrieved. As regarding amygdala, we found reduced dopamine levels, accompanied by increased dopamine metabolites in BTBR mice, together with decreased acetylcholine, NGF and GABA levels and enhanced glutamate content. Taken together, our data showed that the BTBR ASD model, beyond its face validity, is a useful tool to untangle neurotransmission alterations that could be underpinned to the heterogeneous ASD-like behaviours, highlighting the crucial role played by amygdala.

Abnormal functional connectivity of the reward network is associated with social communication impairments in autism spectrum disorder: A large-scale multi-site resting-state fMRI study

BACKGROUND

The social motivation hypothesis proposes that the social deficits of autism spectrum disorder (ASD) are related to reward system dysfunction. However, functional connectivity (FC) patterns of the reward network in ASD have not been systematically explored yet.

METHODS

The reward network was defined as eight regions of interest (ROIs) per hemisphere, including the nucleus accumbens (NAc), caudate, putamen, anterior cingulate cortex (ACC), ventromedial prefrontal cortex (vmPFC), orbitofrontal cortex (OFC), amygdala, and insula. We computed both the ROI-wise resting-state FC and seed-based whole-brain FC in 298 ASD participants and 348 typically developing (TD) controls from the Autism Brain Imaging Data Exchange I dataset. Two-sample t-tests were applied to obtain the aberrant FCs. Then, the association between aberrant FCs and clinical symptoms was assessed with Pearson's correlation or Spearman's correlation. In addition, Neurosynth Image Decoder was used to generate word clouds verifying the cognitive functions of the aberrant pathways. Furthermore, a three-way multivariate analysis of variance (MANOVA) was conducted to examine the effects of gender, subtype and age on the atypical FCs.

RESULTS

For the within network analysis, the left ACC showed weaker FCs with both the right amygdala and left NAc in ASD compared with TD, which were negatively correlated with the Autism Diagnostic Observation Schedule (ADOS) total scores and Social Responsiveness Scale (SRS) total scores respectively. For the whole-brain analysis, weaker FC (i.e., FC between the left vmPFC and left calcarine gyrus, and between the right vmPFC and left precuneus) accompanied by stronger FC (i.e., FC between the left caudate and right insula) were exhibited in ASD relative to TD, which were positively associated with the SRS motivation scores. Additionally, we detected the main effect of age on FC between the left vmPFC and left calcarine gyrus, of subtype on FC between the right vmPFC and left precuneus, of age and age-by-gender interaction on FC between the left caudate and right insula.

CONCLUSIONS

Our findings highlight the crucial role of abnormal FC patterns of the reward network in the core social deficits of ASD, which have the potential to reveal new biomarkers for ASD.

Early-in-life isoflurane exposure alters resting-state functional connectivity in juvenile non-human primates

BACKGROUND

Clinical studies suggest that anaesthesia exposure early in life affects neurobehavioural development. We designed a non-human primate (NHP) study to evaluate cognitive, behavioural, and brain functional and structural alterations after isoflurane exposure during infancy. These NHPs displayed decreased close social behaviour and increased astrogliosis in specific brain regions, most notably in the amygdala. Here we hypothesise that resting-state functional connectivity MRI can detect alterations in connectivity of brain areas that relate to these social behaviours and astrogliosis.

METHODS

Imaging was performed in 2-yr-old NHPs under light anaesthesia, after early-in-life (postnatal days 6-12) exposure to 5 h of isoflurane either one or three times, or to room air. Brain images were segmented into 82 regions of interest; the amygdala and the posterior cingulate cortex were chosen for a seed-based resting-state functional connectivity MRI analysis.

RESULTS

We found differences between groups in resting-state functional connectivity of the amygdala and the auditory cortices, medial premotor cortex, and posterior cingulate cortex. There were also alterations in resting-state functional connectivity between the posterior cingulate cortex and secondary auditory, polar prefrontal, and temporal cortices, and the anterior insula. Relationships were identified between resting-state functional connectivity alterations and the decrease in close social behaviour and increased astrogliosis.

CONCLUSIONS

Early-in-life anaesthesia exposure in NHPs is associated with resting-state functional connectivity alterations of the amygdala and the posterior cingulate cortex with other brain regions, evident at the juvenile age of 2 yr. These changes in resting-state functional connectivity correlate with the decrease in close social behaviour and increased astrogliosis. Using resting-state functional connectivity MRI to study the neuronal underpinnings of early-in-life anaesthesia-induced behavioural alterations could facilitate development of a biomarker for anaesthesia-induced developmental neurotoxicity.

Cortical responses to social stimuli in infants at elevated likelihood of ASD and/or ADHD: A prospective cross-condition fNIRS study

Autism spectrum disorders (ASD) and attention-deficit hyperactivity disorder (ADHD) are highly prevalent neurodevelopmental conditions that often co-occur and present both common and distinct neurodevelopmental profiles. Studying the developmental pathways leading to the emergence of ASD and/or ADHD symptomatology is crucial in understanding neurodiversity and discovering the mechanisms that underpin it. This study used functional near-infrared spectroscopy (fNIRS) to investigate differences in cortical specialization to social stimuli between 4- to 6-month-old infants at typical and elevated likelihood of ASD and/or ADHD. Results showed that infants at both elevated likelihood of ASD and ADHD had reduced selectivity to vocal sounds in left middle and superior temporal gyrus. Furthermore, infants at elevated likelihood of ASD showed attenuated responses to visual social stimuli in several cortical regions compared to infants at typical likelihood. Individual brain responses to visual social stimuli were associated with later autism traits, but not ADHD traits. These outcomes support our previous observations showing atypical social brain responses in infants at elevated likelihood of ASD and align with later atypical brain responses to social stimuli observed in children and adults with ASD. These findings highlight the importance of characterizing antecedent biomarkers of atypicalities in processing socially relevant information that might contribute to both phenotypic overlap and divergence across ASD and ADHD conditions and their association with the later emergence of behavioural symptoms.

Nodal properties of the resting-state brain functional network in childhood and adolescence

BACKGROUND AND PURPOSE

Changes in the topological properties of brain functional network nodes during childhood and adolescence can provide more detailed and intuitive information on the rules of brain development. This study aims to explore the characteristics of nodal attributes in child and adolescent brain functional networks and analyze the correlation between nodal attributes in different brain regions and age.

METHODS

Forty-two healthy volunteers aged 6-18 years who were right-handed primary and middle school students were recruited, and the subgroup analysis included children (6-12 years, n = 19) and adolescents (13-18 years, n = 23). Resting-state functional magnetic resonance imaging data were collected using a 3.0 Tesla MRI scanner. The topological properties of the functional brain network were analyzed using graph theory.

RESULTS

Compared with the children group, the degree centrality and nodal efficiency of multiple brain regions in the adolescent group were significantly increased, and the nodal shortest path was reduced (q<0.05, false discovery rate corrected). These brain regions were widely distributed in the whole brain and significantly correlated with age. Compared with the children group, reduced degree centralities were observed in the left dorsolateral fusiform gyrus, left rostral cuneus gyrus, and right medial superior occipital gyrus.

CONCLUSION

The transmission efficiency of the brain's core network gradually increased, and the subnetwork function gradually improved in children and adolescents with age. The functional development of each brain area in the occipital visual cortex was uneven and there was functional differentiation within the occipital visual cortex.

Functional connectivity between the amygdala and prefrontal cortex underlies processing of emotion ambiguity

Processing facial expressions of emotion draws on a distributed brain network. In particular, judging ambiguous facial emotions involves coordination between multiple brain areas. Here, we applied multimodal functional connectivity analysis to achieve network-level understanding of the neural mechanisms underlying perceptual ambiguity in facial expressions. We found directional effective connectivity between the amygdala, dorsomedial prefrontal cortex (dmPFC), and ventromedial PFC, supporting both bottom-up affective processes for ambiguity representation/perception and top-down cognitive processes for ambiguity resolution/decision. Direct recordings from the human neurosurgical patients showed that the responses of amygdala and dmPFC neurons were modulated by the level of emotion ambiguity, and amygdala neurons responded earlier than dmPFC neurons, reflecting the bottom-up process for ambiguity processing. We further found parietal-frontal coherence and delta-alpha cross-frequency coupling involved in encoding emotion ambiguity. We replicated the EEG coherence result using independent experiments and further showed modulation of the coherence. EEG source connectivity revealed that the dmPFC top-down regulated the activities in other brain regions. Lastly, we showed altered behavioral responses in neuropsychiatric patients who may have dysfunctions in amygdala-PFC functional connectivity. Together, using multimodal experimental and analytical approaches, we have delineated a neural network that underlies processing of emotion ambiguity.

Associations between thalamocortical functional connectivity and sensory over-responsivity in infants at high likelihood for ASD

Despite growing evidence implicating thalamic functional connectivity atypicalities in autism spectrum disorder (ASD), it remains unclear how such alterations emerge early in human development. Because the thalamus plays a critical role in sensory processing and neocortical organization early in life, its connectivity with other cortical regions could be key for studying the early onset of core ASD symptoms. Here, we investigated emerging thalamocortical functional connectivity in infants at high (HL) and typical (TL) familial likelihood for ASD in early and late infancy. We report significant thalamo-limbic hyperconnectivity in 1.5-month-old HL infants, and thalamo-cortical hypoconnectivity in prefrontal and motor regions in 9-month-old HL infants. Importantly, early sensory over-responsivity (SOR) symptoms in HL infants predicted a direct trade-off in thalamic connectivity whereby stronger thalamic connectivity with primary sensory regions and basal ganglia was inversely related to connectivity with higher order cortices. This trade-off suggests that ASD may be characterized by early differences in thalamic gating. The patterns reported here could directly underlie atypical sensory processing and attention to social vs. nonsocial stimuli observed in ASD. These findings lend support to a theoretical framework of ASD whereby early disruptions in sensorimotor processing and attentional biases early in life may cascade into core ASD symptomatology.

A revisit of the amygdala theory of autism: Twenty years after

The human amygdala has long been implicated to play a key role in autism spectrum disorder (ASD). Yet it remains unclear to what extent the amygdala accounts for the social dysfunctions in ASD. Here, we review studies that investigate the relationship between amygdala function and ASD. We focus on studies that employ the same task and stimuli to directly compare people with ASD and patients with focal amygdala lesions, and we also discuss functional data associated with these studies. We show that the amygdala can only account for a limited number of deficits in ASD (primarily face perception tasks but not social attention tasks), a network view is, therefore, more appropriate. We next discuss atypical brain connectivity in ASD, factors that can explain such atypical brain connectivity, and novel tools to analyze brain connectivity. Lastly, we discuss new opportunities from multimodal neuroimaging with data fusion and human single-neuron recordings that can enable us to better understand the neural underpinnings of social dysfunctions in ASD. Together, the influential amygdala theory of autism should be extended with emerging data-driven scientific discoveries such as machine learning-based surrogate models to a broader framework that considers brain connectivity at the global scale.

Review of Progress in Diagnostic Studies of Autism Spectrum Disorder Using Neuroimaging

This review article summarizes the recent advances in the diagnostic studies of autism spectrum disorders (ASDs) considering some of the most influential research articles from the last two decades. ASD is a heterogeneous neurodevelopmental disorder characterized by abnormalities in social interaction, communication, and behavioral patterns as well as some unique strengths and differences. The current diagnosis systems are based on autism diagnostic observation schedule (ADOS) or autism diagnostic interview-revised (ADI-R), but biological markers are also important for an effective diagnosis of ASDs. The amalgamation of neuroimaging techniques, such as structural and functional magnetic resonance imaging (sMRI and fMRI), with machine-learning and deep-learning approaches helps throw new light on typical biological markers of ASDs at the early stage of life. To assess the performance of a deep neural network, we develop a light-weighted CNN model for ASD classification. The overall accuracy, precision, and F1-score of the proposed model are 99.92%, 99.93% and 99.92%, respectively. All the neuroimaging studies we have reviewed can be divided into 3 categories, viz. thickness, volume and functional connectivity-based studies. We conclude with a discussion of the major findings of considered studies and promising directions for future research in this field.

Early Social Adversity, Altered Brain Functional Connectivity, and Mental Health

Early adverse environmental exposures during brain development are widespread risk factors for the onset of severe mental disorders and strong and consistent predictors of stress-related mental and physical illness and reduced life expectancy. Current evidence suggests that early negative experiences alter plasticity processes during developmentally sensitive time windows and affect the regular functional interaction of cortical and subcortical neural networks. This, in turn, may promote a maladapted development with negative consequences on the mental and physical health of exposed individuals. In this review, we discuss the role of functional magnetic resonance imaging-based functional connectivity phenotypes as potential biomarker candidates for the consequences of early environmental exposures-including but not limited to-childhood maltreatment. We take an expanded concept of developmentally relevant adverse experiences from infancy over childhood to adolescence as our starting point and focus our review of functional connectivity studies on a selected subset of functional magnetic resonance imaging-based phenotypes, including connectivity in the limbic and within the frontoparietal as well as default mode networks, for which we believe there is sufficient converging evidence for a more detailed discussion in a developmental context. Furthermore, we address specific methodological challenges and current knowledge gaps that complicate the interpretation of early stress effects on functional connectivity and deserve particular attention in future studies. Finally, we highlight the forthcoming prospects and challenges of this research area with regard to establishing functional connectivity measures as validated biomarkers for brain developmental processes and individual risk stratification and as target phenotypes for mechanism-based interventions.

Abnormal amygdala functional connectivity and deep learning classification in multifrequency bands in autism spectrum disorder: A multisite functional magnetic resonance imaging study

Previous studies have explored resting-state functional connectivity (rs-FC) of the amygdala in patients with autism spectrum disorder (ASD). However, it remains unclear whether there are frequency-specific FC alterations of the amygdala in ASD and whether FC in specific frequency bands can be used to distinguish patients with ASD from typical controls (TCs). Data from 306 patients with ASD and 314 age-matched and sex-matched TCs were collected from 28 sites in the Autism Brain Imaging Data Exchange database. The bilateral amygdala, defined as the seed regions, was used to perform seed-based FC analyses in the conventional, slow-5, and slow-4 frequency bands at each site. Image-based meta-analyses were used to obtain consistent brain regions across 28 sites in the three frequency bands. By combining generative adversarial networks and deep neural networks, a deep learning approach was applied to distinguish patients with ASD from TCs. The meta-analysis results showed frequency band specificity of FC in ASD, which was reflected in the slow-5 frequency band instead of the conventional and slow-4 frequency bands. The deep learning results showed that, compared with the conventional and slow-4 frequency bands, the slow-5 frequency band exhibited a higher accuracy of 74.73%, precision of 74.58%, recall of 75.05%, and area under the curve of 0.811 to distinguish patients with ASD from TCs. These findings may help us to understand the pathological mechanisms of ASD and provide preliminary guidance for the clinical diagnosis of ASD.

Emotional descriptions increase accidental harm punishment and its cortico-limbic signatures during moral judgment in autism

Individuals with autism spectrum disorder (ASD) present difficulties in integrating mental state information in complex moral tasks. Yet, ASD research has not examined whether this process is influenced by emotions, let alone while capturing its neural bases. We investigated how language-induced emotions modulate intent-based moral judgment in ASD. In a fMRI task, 30 adults with ASD and 27 neurotypical controls read vignettes whose protagonists commit harm either accidentally or intentionally, and then decided how much punishment the protagonist deserved. Emotional content was manipulated across scenarios through the use of graphic language (designed to trigger arousing negative responses) vs. plain (just-the-facts, emotionless) language. Off-line functional connectivity correlates of task performance were also analyzed. In ASD, emotional (graphic) descriptions amplified punishment ratings of accidental harms, associated with increased activity in fronto-temporo-limbic, precentral, and postcentral/supramarginal regions (critical for emotional and empathic processes), and reduced connectivity among the orbitofrontal cortex and the angular gyrus (involved in mentalizing). Language manipulation did not influence intentional harm processing in ASD. In conclusion, in arousing and ambiguous social situations that lack intentionality clues (i.e. graphic accidental harm scenarios), individuals with ASD would misuse their emotional responses as the main source of information to guide their moral decisions. Conversely, in face of explicit harmful intentions, they would be able to compensate their socioemotional alterations and assign punishment through non-emotional pathways. Despite limitations, such as the small sample size and low ecological validity of the task, results of the present study proved reliable and have relevant theoretical and translational implications.

Functional connectivity between the amygdala and prefrontal cortex underlies processing of emotion ambiguity

Processing facial expressions of emotion draws on a distributed brain network. In particular, judging ambiguous facial emotions involves coordination between multiple brain areas. Here, we applied multimodal functional connectivity analysis to achieve network-level understanding of the neural mechanisms underlying perceptual ambiguity in facial expressions. We found directional effective connectivity between the amygdala, dorsomedial prefrontal cortex (dmPFC), and ventromedial PFC, supporting both bottom-up affective processes for ambiguity representation/perception and top-down cognitive processes for ambiguity resolution/decision. Direct recordings from the human neurosurgical patients showed that the responses of amygdala and dmPFC neurons were modulated by the level of emotion ambiguity, and amygdala neurons responded earlier than dmPFC neurons, reflecting the bottom-up process for ambiguity processing. We further found parietal-frontal coherence and delta-alpha cross-frequency coupling involved in encoding emotion ambiguity. We replicated the EEG coherence result using independent experiments and further showed modulation of the coherence. EEG source connectivity revealed that the dmPFC top-down regulated the activities in other brain regions. Lastly, we showed altered behavioral responses in neuropsychiatric patients who may have dysfunctions in amygdala-PFC functional connectivity. Together, using multimodal experimental and analytical approaches, we have delineated a neural network that underlies processing of emotion ambiguity.

Significance Statement

A large number of different brain regions participate in emotion processing. However, it remains elusive how these brain regions interact and coordinate with each other and collectively encode emotions, especially when the task requires orchestration between different brain areas. In this study, we employed multimodal approaches that well complemented each other to comprehensively study the neural mechanisms of emotion ambiguity. Our results provided a systematic understanding of the amygdala-PFC network underlying emotion ambiguity with fMRI-based connectivity, EEG coordination of cortical regions, synchronization of brain rhythms, directed information flow of the source signals, and latency of single-neuron responses. Our results further shed light on neuropsychiatric patients who have abnormal amygdala-PFC connectivity.

The relationships between dynamic resting-state networks and social behavior in autism spectrum disorder revealed by fuzzy entropy-based temporal variability analysis of large-scale network

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder characterized by a core deficit in social processes. However, it is still unclear whether the core clinical symptoms of the disorder can be reflected by the temporal variability of resting-state network functional connectivity (FC). In this article, we examined the large-scale network FC temporal variability at the local region, within-network, and between-network levels using the fuzzy entropy technique. Then, we correlated the network FC temporal variability to social-related scores. We found that the social behavior correlated with the FC temporal variability of the precuneus, parietal, occipital, temporal, and precentral. Our results also showed that social behavior was significantly negatively correlated with the temporal variability of FC within the default mode network, between the frontoparietal network and cingulo-opercular task control network, and the dorsal attention network. In contrast, social behavior correlated significantly positively with the temporal variability of FC within the subcortical network. Finally, using temporal variability as a feature, we construct a model to predict the social score of ASD. These findings suggest that the network FC temporal variability has a close relationship with social behavioral inflexibility in ASD and may serve as a potential biomarker for predicting ASD symptom severity.

Translating neuroimaging changes to neuro-endophenotypes of autistic spectrum disorder: a narrative review

Background

Autism-spectrum disorder is a neurodevelopmental disorder with heterogeneity in etiopathogenesis and clinical presentation. Neuroanatomical and neurophysiological abnormalities may represent neural endophenotypes for autism spectrum disorders which may help identify subgroups of patients seemingly similar in clinical presentation yet different in their pathophysiological underpinnings. Furthermore, a thorough understanding of the pathophysiology of disease can pave the way to effective treatments, prevention, and prognostic predictions. The aim of this review is to identify the predominant neural endophenotypes in autism-spectrum disorder. The evidence was researched at the following electronic databases: Pubmed, PsycINFO, Scopus, Web of Science, and EMBASE.

Results

Enlarged brain, especially frontotemporal cortices have been consistently reported by structural neuroimaging, whereas functional neuroimaging has revealed frontotemporal dysconnectivity.

Conclusions

Regrettably, many of these findings have not been consistent. Therefore, translating these findings into neural endophenotype is by far an attempt in its budding stage. The structural and functional neuroimaging changes may represent neural endophenotypes unique to autism-spectrum disorder. Despite inconsistent results, a clinically meaningful finding may require combined efforts of autism-spectrum-disorder researchers focused on different aspects of basic, genetic, neuroimaging, and clinical research.

Topological analysis of brain dynamics in autism based on graph and persistent homology

Autism spectrum disorder (ASD) is a heterogeneous disorder with a rapidly growing prevalence. In recent years, the dynamic functional connectivity (DFC) technique has been used to reveal the transient connectivity behavior of ASDs' brains by clustering connectivity matrices in different states. However, the states of DFC have not been yet studied from a topological point of view. In this paper, this study was performed using global metrics of the graph and persistent homology (PH) and resting-state functional magnetic resonance imaging (fMRI) data. The PH has been recently developed in topological data analysis and deals with persistent structures of data. The structural connectivity (SC) and static FC (SFC) were also studied to know which one of the SC, SFC, and DFC could provide more discriminative topological features when comparing ASDs with typical controls (TCs). Significant discriminative features were only found in states of DFC. Moreover, the best classification performance was offered by persistent homology-based metrics and in two out of four states. In these two states, some networks of ASDs compared to TCs were more segregated and isolated (showing the disruption of network integration in ASDs). The results of this study demonstrated that topological analysis of DFC states could offer discriminative features which were not discriminative in SFC and SC. Also, PH metrics can provide a promising perspective for studying ASD and finding candidate biomarkers.

Intrinsic Structural Connectivity of the Default Mode Network and Behavioral Correlates of Executive Function and Social Skills in Youth with Autism Spectrum Disorders

Brain connectivity of individuals with autism spectrum disorders (ASD) is heterogenous, as are the behavioral manifestations. The current study investigated brain-behavior relationships in the context of social skills and executive function profiles with data from the Autism Brain Imaging Database Exchange II. We calculated connectivity measures from diffusion tensor imaging using Bayesian estimation and probabilistic tractography. Subsequently, we performed structural equation modeling by regressing three latent factors, yielded from an exploratory factor analysis, onto total default mode network (DMN) connectivity. Both social regulation processing and self-directed cognitive processing factors moderately, negatively correlated with total DMN connectivity. Our findings indicate social regulation processing difficulties in youth with ASD may be attributable to impaired connectivity between the anterior and posterior DMN.

Attenuated link between the medial prefrontal cortex and the amygdala in children with autism spectrum disorder: Evidence from effective connectivity within the "social brain"

Although accumulating neuroimaging studies have reported that social behavior deficits in children with autism spectrum disorders (ASD) are commonly attributed to the dysfunction of social brain regions underlying social cognition, the dynamic interaction within the social brain network and its association with social deficits remain unclear. Here, resting-state functional magnetic resonance imaging data obtained from Autism Brain Imaging Data Exchange (I and II) were analyzed in 105 children with ASD and 102 demographically matched typically developing controls (TDCs) (age range: 7-12 years old). Term-based meta-analysis combined the prior reference and anatomical labeling were used to define the regions of interests of the social brain network, and multivariate Granger causality analysis with blind deconvolution was employed to assess the effective connectivity within the social brain network in the ASD and TDC groups. Between-group comparison revealed significantly attenuated effective connectivity from the medial prefrontal cortex (mPFC) to the bilateral amygdala in children with the ASD group compared with TDC group. In addition, raw values of the effective connectivity from the mPFC to the bilateral amygdala were used to predict social deficits in ASD. Our findings indicate the impaired mPFC-amygdala pathway and its association with social deficits in children with ASD and provide a new perspective into the neuropathology of the developing autistic brain.

The Brain-Gut-Microbiome System: Pathways and Implications for Autism Spectrum Disorder

Gastrointestinal dysfunction is one of the most prevalent physiological symptoms of autism spectrum disorder (ASD). A growing body of largely preclinical research suggests that dysbiotic gut microbiota may modulate brain function and social behavior, yet little is known about the mechanisms that underlie these relationships and how they may influence the pathogenesis or severity of ASD. While various genetic and environmental risk factors have been implicated in ASD, this review aims to provide an overview of studies elucidating the mechanisms by which gut microbiota, associated metabolites, and the brain interact to influence behavior and ASD development, in at least a subgroup of individuals with gastrointestinal problems. Specifically, we review the brain-gut-microbiome system and discuss findings from current animal and human studies as they relate to social-behavioral and neurological impairments in ASD, microbiota-targeted therapies (i.e., probiotics, fecal microbiota transplantation) in ASD, and how microbiota may influence the brain at molecular, structural, and functional levels, with a particular interest in social and emotion-related brain networks. A deeper understanding of microbiome-brain-behavior interactions has the potential to inform new therapies aimed at modulating this system and alleviating both behavioral and physiological symptomatology in individuals with ASD.

Testing a Developmental Model of Positive Parenting, Amygdala–Subgenual Anterior Cingulate Cortex Connectivity, and Depressive Symptoms in Adolescents Before and During the COVID-19 Pandemic

Background

Neurobiological measures may inform our understanding of individual differences in adolescents’ general risk for and resilience to depressive symptoms, including during the COVID-19 pandemic. We tested a developmental model linking variation in amygdala–subgenual anterior cingulate cortex (sgACC) resting-state connectivity to perceived parenting experiences earlier in adolescence, to concurrent depressive symptoms before the pandemic, and to subsequent depressive symptoms during the pandemic.

Methods

We used data from a longitudinal study that included three waves (N = 214 adolescents; ages 9–15 years at time 1 [T1], 11–17 years at T2, and 12–19 years during the pandemic at T3). We assessed positive parenting (warm and supportive) (T1), depressive symptoms (T1 to T3), and functional connectivity between the sgACC and basolateral (BLA) and centromedial amygdala (T1 and T2). We modeled associations among earlier positive parenting, amygdala–sgACC connectivity, and depressive symptoms before and during the pandemic.

Results

Less positive parenting at T1 was associated prospectively with stronger BLA–sgACC connectivity at T2 (β = −0.22) over and above the effect of BLA–sgACC connectivity at T1. Stronger BLA–sgACC connectivity, in turn, was associated with heightened depressive symptoms, both before the pandemic (r = 0.21) and during the pandemic (β = 0.19; independent of the effect of pre-pandemic symptoms).

Conclusions

Adolescents who experience less positive parenting may develop a pattern of BLA–sgACC connectivity that increases their risk for mental health problems. BLA–sgACC connectivity may be associated with depressive symptoms in general, including during periods of heightened risk for adolescents, such as the pandemic.

Repeated Sessions of Transcranial Direct Current Stimulation on Adolescents With Autism Spectrum Disorder: Study Protocol for a Randomized, Double-Blind, and Sham-Controlled Clinical Trial

Background: Social-emotional difficulties are a core symptom of autism spectrum disorder (ASD). Accordingly, individuals with ASD have problems with social cognition such as recognizing emotions from other peoples' faces. Various results from functional magnetic resonance imaging and electroencephalography studies as well as eye-tracking data reveal a neurophysiological basis of these deficits by linking them to abnormal brain activity. Thus, an intervention targeting the neural origin of ASD impairments seems warranted. A safe method able to influence neural activity is transcranial direct current stimulation (tDCS). This non-invasive brain stimulation method has already demonstrated promising results in several neuropsychiatric disorders in adults and children. The aim of this project is to investigate the effects of tDCS on ASD symptoms and their neural correlates in children and adolescents with ASD. Method: This study is designed as a double-blind, randomized, and sham-controlled trial with a target sample size of 20 male participants (aged 12-17 years) diagnosed with ASD. Before randomization, the participants will be stratified into comorbid depression, comorbid ADHS/conduct disorder, or no-comorbidity groups. The intervention phase comprises 10 sessions of anodal or sham tDCS applied over the left prefrontal cortex within 2 consecutive weeks. To engage the targeted brain regions, participants will perform a social cognition training during the stimulation. TDCS-induced effects on ASD symptoms and involved neural circuits will be investigated through psychological, neurophysiological, imaging, and behavioral data at pre- and post-measurements. Tolerability will be evaluated using a standardized questionnaire. Follow-up assessments 1 and 6 months after the intervention will examine long-lasting effects. Discussion: The results of this study will provide insights into the changeability of social impairments in ASD by investigating social and emotional abilities on different modalities following repeated sessions of anodal tDCS with an intra-simulation training. Furthermore, this trial will elucidate the tolerability and the potential of tDCS as a new treatment approach for ASD in adolescents. Clinical Trial Registration: The study is ongoing and has been registered in the German Registry of Clinical Trials (DRKS00017505) on 02/07/2019.

Shared and Distinct Topologically Structural Connectivity Patterns in Autism Spectrum Disorder and Attention-Deficit/Hyperactivity Disorder

Background

Previous neuroimaging studies have described shared and distinct neurobiological mechanisms between autism spectrum disorders (ASDs) and attention-deficit/hyperactivity disorder (ADHD). However, little is known about the similarities and differences in topologically structural connectivity patterns between the two disorders.

Methods

Diffusion tensor imaging (DTI) and deterministic tractography were used to construct the brain white matter (WM) structural networks of children and adolescents (age range, 6–16 years); 31 had ASD, 34 had ADHD, and 30 were age- and sex-matched typically developing (TD) individuals. Then, graph theoretical analysis was performed to investigate the alterations in the global and node-based properties of the WM structural networks in these groups. Next, measures of ASD traits [Social Responsiveness Scale (SRS)] and ADHD traits (Swanson, Nolan, and Pelham, version IV scale, SNAP-IV) were correlated with the alterations to determine the functional significance of such changes.

Results

First, there were no significant differences in the global network properties among the three groups; moreover, compared with that of the TD group, nodal degree (Ki) of the right amygdala (AMYG.R) and right parahippocampal gyrus (PHG.R) were found in both the ASD and ADHD groups. Also, the ASD and ADHD groups shared four additional hubs, including the left middle temporal gyrus (MTG.L), left superior temporal gyrus (STG.L), left postcentral gyrus (PoCG.L), and right middle frontal gyrus (MFG.R) compared with the TD group. Moreover, the ASD and ADHD groups exhibited no significant differences regarding regional connectivity characteristics. Second, the ADHD group showed significantly increased nodal betweenness centrality (Bi) of the left hippocampus (HIP.L) compared with the ASD group; also, compared with the ADHD group, the ASD group lacked the left anterior cingulate gyrus (ACG.L) as a hub. Last, decreased nodal efficiency (Enodal) of the AMYG.R, Ki of the AMYG.R, and Ki of the PHG.R were associated with higher SRS scores in the ASD group. Decreased Ki of the PHG.R was associated with higher SRS scores in the full sample, whereas decreased Bi of the PHG.R was associated with lower oppositional defiance subscale scores of the SNAP-IV in the ADHD group, and decreased Bi of the HIP.L was associated with lower inattention subscale scores of the SNAP-IV in the full sample.

Conclusion

From the perspective of the topological properties of brain WM structural networks, ADHD and ASD have both shared and distinct features. More interestingly, some shared and distinct topological properties of WM structures are related to the core symptoms of these disorders.

Altered Thalamocortical Connectivity in 6-Week-Old Infants at High Familial Risk for Autism Spectrum Disorder

Converging evidence from neuroimaging studies has revealed altered connectivity in cortical-subcortical networks in youth and adults with autism spectrum disorder (ASD). Comparatively little is known about the development of cortical-subcortical connectivity in infancy, before the emergence of overt ASD symptomatology. Here, we examined early functional and structural connectivity of thalamocortical networks in infants at high familial risk for ASD (HR) and low-risk controls (LR). Resting-state functional connectivity and diffusion tensor imaging data were acquired in 52 6-week-old infants. Functional connectivity was examined between 6 cortical seeds-prefrontal, motor, somatosensory, temporal, parietal, and occipital regions-and bilateral thalamus. We found significant thalamic-prefrontal underconnectivity, as well as thalamic-occipital and thalamic-motor overconnectivity in HR infants, relative to LR infants. Subsequent structural connectivity analyses also revealed atypical white matter integrity in thalamic-occipital tracts in HR infants, compared with LR infants. Notably, aberrant connectivity indices at 6 weeks predicted atypical social development between 9 and 36 months of age, as assessed with eye-tracking and diagnostic measures. These findings indicate that thalamocortical connectivity is disrupted at both the functional and structural level in HR infants as early as 6 weeks of age, providing a possible early marker of risk for ASD.

The Development of Brain Network in Males with Autism Spectrum Disorders from Childhood to Adolescence: Evidence from fNIRS Study

In the current study, functional near-infrared spectroscopy (fNIRS) was used to collect resting-state signals from 77 males with autism spectrum disorders (ASD, age: 6~16.25) and 40 typically developing (TD) males (age: 6~16.58) in the theory-of-mind (ToM) network. The graph theory analysis was used to obtain the brain network properties in ToM network, and the multiple regression analysis demonstrated that males with ASD showed a comparable global network topology, and a similar age-related decrease in the medial prefrontal cortex area (mPFC) compared to TD individuals. Nevertheless, participants with ASD showed U-shaped trajectories of nodal metrics of right temporo-parietal junction (TPJ), and an age-related decrease in the left middle frontal gyrus (MFG), while trajectories of TD participants were opposite. The nodal metrics of the right TPJ was negatively associated with the social deficits of ASD, while the nodal metrics of the left MFG was negatively associated with the communication deficits of ASD. Current findings suggested a distinct developmental trajectory of the ToM network in males with ASD from childhood to adolescence.

Functional brain abnormalities associated with comorbid anxiety in autism spectrum disorder

Anxiety disorders are common in autism spectrum disorder (ASD) and associated with social-communication impairment and repetitive behavior symptoms. The neurobiology of anxiety in ASD is unknown, but amygdala dysfunction has been implicated in both ASD and anxiety disorders. Using resting-state functional magnetic resonance imaging, we compared amygdala-prefrontal and amygdala-striatal connections across three demographically matched groups studied in the Autism Brain Imaging Data Exchange (ABIDE): ASD with a comorbid anxiety disorder (N = 25; ASD + Anxiety), ASD without a comorbid disorder (N = 68; ASD-NoAnx), and typically developing controls (N = 139; TD). Relative to ASD-NoAnx and TD controls, ASD + Anxiety individuals had decreased connectivity between the amygdala and dorsal/rostral anterior cingulate cortex (dACC/rACC). The functional connectivity of these connections was not affected in ASD-NoAnx, and amygdala connectivity with ventral ACC/medial prefrontal cortex (mPFC) circuits was not different in ASD + Anxiety or ASD-NoAnx relative to TD. Decreased amygdala-dorsomedial prefrontal cortex (dmPFC)/rACC connectivity was associated with more severe social impairment in ASD + Anxiety; amygdala-striatal connectivity was associated with restricted, repetitive behavior (RRB) symptom severity in ASD-NoAnx individuals. These findings suggest comorbid anxiety in ASD is associated with disrupted emotion-monitoring processes supported by amygdala-dACC/mPFC pathways, whereas emotion regulation systems involving amygdala-ventromedial prefrontal cortex (vmPFC) are relatively spared. Our results highlight the importance of accounting for comorbid anxiety for parsing ASD neurobiological heterogeneity.

Serotonin differentially modulates the temporal dynamics of the limbic response to facial emotions in male adults with and without autism spectrum disorder (ASD): a randomised placebo-controlled single-dose crossover trial

Emotion processing-including signals from facial expressions-is often altered in individuals with autism spectrum disorder (ASD). The biological basis of this is poorly understood but may include neurochemically mediated differences in the responsivity of key 'limbic' regions (including amygdala, ventromedial prefrontal cortex (vmPFC) and nucleus accumbens (NAc)). Emerging evidence also suggests that ASD may be a disorder of brain temporal dynamics. Moreover, serotonin (5-HT) has been shown to be a key regulator of both facial-emotion processing and brain dynamics, and 5-HT abnormalities have been consistently implicated in ASD. To date, however, no one has examined how 5-HT influences the dynamics of facial-emotion processing in ASD. Therefore, we compared the influence of 5-HT on the responsivity of brain dynamics during facial-emotion processing in individuals with and without ASD. Participants completed a facial-emotion processing fMRI task at least 8 days apart using a randomised double-blind crossover design. At each visit they received either a single 20-mg oral dose of the selective serotonin reuptake inhibitor (SSRI) citalopram or placebo. We found that citalopram (which increases levels of 5-HT) caused sustained activation in key limbic regions during processing of negative facial emotions in adults with ASD-but not in neurotypical adults. The neurotypical adults' limbic response reverted more rapidly to baseline following a 5-HT-challenge. Our results suggest that serotonergic homoeostatic control of the temporal dynamics in limbic regions is altered in adults with ASD, and provide a fresh perspective on the biology of ASD.

Facial Expression Processing Across the Autism-Psychosis Spectra: A Review of Neural Findings and Associations With Adverse Childhood Events

Autism spectrum disorder (ASD) and primary psychosis are classified as distinct neurodevelopmental disorders, yet they display overlapping epidemiological, environmental, and genetic components as well as endophenotypic similarities. For instance, both disorders are characterized by impairments in facial expression processing, a crucial skill for effective social communication, and both disorders display an increased prevalence of adverse childhood events (ACE). This narrative review provides a brief summary of findings from neuroimaging studies investigating facial expression processing in ASD and primary psychosis with a focus on the commonalities and differences between these disorders. Individuals with ASD and primary psychosis activate the same brain regions as healthy controls during facial expression processing, albeit to a different extent. Overall, both groups display altered activation in the fusiform gyrus and amygdala as well as altered connectivity among the broader face processing network, probably indicating reduced facial expression processing abilities. Furthermore, delayed or reduced N170 responses have been reported in ASD and primary psychosis, but the significance of these findings is questioned, and alternative frequency-tagging electroencephalography (EEG) measures are currently explored to capture facial expression processing impairments more selectively. Face perception is an innate process, but it is also guided by visual learning and social experiences. Extreme environmental factors, such as adverse childhood events, can disrupt normative development and alter facial expression processing. ACE are hypothesized to induce altered neural facial expression processing, in particular a hyperactive amygdala response toward negative expressions. Future studies should account for the comorbidity among ASD, primary psychosis, and ACE when assessing facial expression processing in these clinical groups, as it may explain some of the inconsistencies and confound reported in the field.

Differential mirror neuron system (MNS) activation during action observation with and without social-emotional components in autism: a meta-analysis of neuroimaging studies

Background

Impaired imitation has been found to be an important factor contributing to social communication deficits in individuals with autism spectrum disorder (ASD). It has been hypothesized that the neural correlate of imitation, the mirror neuron system (MNS), is dysfunctional in ASD, resulting in imitation impairment as one of the key behavioral manifestations in ASD. Previous MNS studies produced inconsistent results, leaving the debate of whether “broken” mirror neurons in ASD are unresolved.

Methods

This meta-analysis aimed to explore the differences in MNS activation patterns between typically developing (TD) and ASD individuals when they observe biological motions with or without social-emotional components. Effect size signed differential mapping (ES-SDM) was adopted to synthesize the available fMRI data.

Results

ES-SDM analysis revealed hyperactivation in the right inferior frontal gyrus and left supplementary motor area in ASD during observation of biological motions. Subgroup analysis of experiments involving the observation of stimuli with or without emotional component revealed hyperactivation in the left inferior parietal lobule and left supplementary motor during action observation without emotional components, whereas hyperactivation of the right inferior frontal gyrus was found during action observation with emotional components in ASD. Subgroup analyses of age showed hyperactivation of the bilateral inferior frontal gyrus in ASD adolescents, while hyperactivation in the right inferior frontal gyrus was noted in ASD adults. Meta-regression within ASD individuals indicated that the right cerebellum crus I activation increased with age, while the left inferior temporal gyrus activation decreased with age.

Limitations

This meta-analysis is limited in its generalization of the findings to individuals with ASD by the restricted age range, heterogeneous study sample, and the large within-group variation in MNS activation patterns during object observation. Furthermore, we only included action observation studies which might limit the generalization of our results to the imitation deficits in ASD. In addition, the relatively small sample size for individual studies might also potentially overestimate the effect sizes.

Conclusion

The MNS is impaired in ASD. The abnormal activation patterns were found to be modulated by the nature of stimuli and age, which might explain the contradictory results from earlier studies on the “broken mirror neuron” debate.

Cranio-Facial Characteristics in Children with Autism Spectrum Disorders (ASD)

Background: Cranio-facial anomalies frequently occur in neurodevelopmental disorders because both face and brain are derived from neuroectoderm. The identification of differences in the facial phenotype of children with Autism Spectrum Disorders (ASD) may reflect alterations in embryologic brain development in children with ASD. Methods: we evaluated 33 caucasian children with ASD using a 2D computerized photogrammetry. Anthropometric euclidean measurements and landmarks located on the soft tissue of the face and head, were based on five cranio-facial indexes. Relationships between anthropometric z-scores and participant characteristics (i.e., age, Global IQ, severity of autistic symptoms measured using the CARS checklist) were assessed. Results: Cephalic index z-score differed significantly from 0 in our ASD group (p = 0.019). Moreover, a significant negative correlation was found between Facial Index z-score and CARS score (p = 0.003); conversely, a positive correlation was found between Interchantal Index z-score and CARS score (p = 0.028). Conclusion: our measurements shows a dolichocephalic head shape which is not correlated with autism severity. Importantly, two craniofacial markers were significantly correlated with autism severity: increased orbital hyperthelorism and decrease of height of the facial midline. These data support previous findings of craniofacial anomalies in autism spectrum disorder suggesting an “ASD facial phenotype” that could be used to improve ASD diagnoses.

Thalamocortical Hyperconnectivity and Amygdala-Cortical Hypoconnectivity in Male Patients With Autism Spectrum Disorder

Background: Analyses of resting-state functional magnetic resonance imaging (rs-fMRI) have been performed to investigate pathophysiological changes in the brains of patients with autism spectrum disorder (ASD) relative to typically developing controls (CTLs). However, the results of these previous studies, which have reported mixed patterns of hypo- and hyperconnectivity, are controversial, likely due to the small sample sizes and limited age range of included participants. Methods: To overcome this issue, we analyzed multisite neuroimaging data from a large sample (n = 626) of male participants aged between 5 and 29 years (mean age = 13 years). The rs-fMRI data were preprocessed using SPM12 and DPARSF software, and signal changes in 90 brain regions were extracted. Multiple linear regression was used to exclude the effect of site differences in connectivity data. Subcortical-cortical connectivity was computed using connectivities in the hippocampus, amygdala, caudate nucleus, putamen, pallidum, and thalamus. Eighty-eight connectivities in each structure were compared between patients with ASD and CTLs using multiple linear regression with group, age, and age × group interactions, head movement parameters, and overall connectivity as variables. Results: After correcting for multiple comparisons, patients in the ASD group exhibited significant increases in connectivity between the thalamus and 19 cortical regions distributed throughout the fronto-parietal lobes, including the temporo-parietal junction and posterior cingulate cortices. In addition, there were significant decreases in connectivity between the amygdala and six cortical regions. The mean effect size of hyperconnectivity (0.25) was greater than that for hypoconnectivity (0.08). No other subcortical structures showed significant group differences. A group-by-age interaction was observed for connectivity between the thalamus and motor-somatosensory areas. Conclusions: These results demonstrate that pathophysiological changes associated with ASD are more likely related to thalamocortical hyperconnectivity than to amygdala-cortical hypoconnectivity. Future studies should examine full sets of clinical and behavioral symptoms in combination with functional connectivity to explore possible biomarkers for ASD.