Early neural activation during facial affect processing in adolescents with Autism Spectrum Disorder

Magnetoencephalography for the pediatric population, indications, acquisition and interpretation for the clinician

Magnetoencephalography (MEG) is an imaging technique that enables the assessment of cortical activity via direct measures of neurophysiology. It is a non-invasive and passive technique that is completely painless. MEG has gained increasing prominence in the field of pediatric neuroimaging. This dedicated review article for the pediatric population summarizes the fundamental technical and clinical aspects of MEG for the clinician. We discuss methods tailored for children to improve data quality, including child-friendly MEG facility environments and strategies to mitigate motion artifacts. We provide an in-depth overview on accurate localization of neural sources and different analysis methods, as well as data interpretation. The contemporary platforms and approaches of two quaternary pediatric referral centers are illustrated, shedding light on practical implementations in clinical settings. Finally, we describe the expanding clinical applications of MEG, including its pivotal role in presurgical evaluation of epilepsy patients, presurgical mapping of eloquent cortices (somatosensory and motor cortices, visual and auditory cortices, lateralization of language), its emerging relevance in autism spectrum disorder research and potential future clinical applications, and its utility in assessing mild traumatic brain injury. In conclusion, this review serves as a comprehensive resource of clinicians as well as researchers, offering insights into the evolving landscape of pediatric MEG. It discusses the importance of technical advancements, data acquisition strategies, and expanding clinical applications in harnessing the full potential of MEG to study neurological conditions in the pediatric population.

Joint learning of multi-level dynamic brain networks for autism spectrum disorder diagnosis

Graph convolutional networks (GCNs), with their powerful ability to model non-Euclidean graph data, have shown advantages in learning representations of brain networks. However, considering the complexity, multilayeredness, and spatio-temporal dynamics of brain activities, we have identified two limitations in current GCN-based research on brain networks: 1) Most studies have focused on unidirectional information transmission across brain network levels, neglecting joint learning or bidirectional information exchange among networks. 2) Most of the existing models determine node neighborhoods by thresholding or simply binarizing the brain network, which leads to the loss of edge weight information and weakens the model's sensitivity to important information in the brain network. To address the above issues, we propose a multi-level dynamic brain network joint learning architecture based on GCN for autism spectrum disorder (ASD) diagnosis. Specifically, firstly, constructing different-level dynamic brain networks. Then, utilizing joint learning based on GCN for interactive information exchange among these multi-level brain networks. Finally, designing an edge self-attention mechanism to assign different edge weights to inter-node connections, which allows us to pick out the crucial features for ASD diagnosis. Our proposed method achieves an accuracy of 81.5 %. The results demonstrate that our method enables bidirectional transfer of high-order and low-order information, facilitating information complementarity between different levels of brain networks. Additionally, the use of edge weights enhances the representation capability of ASD-related features.

Atypical oscillatory dynamics during emotional face processing in paediatric obsessive-compulsive disorder with MEG

Children and youth with obsessive-compulsive disorder (OCD) demonstrate difficulties with social, emotional and cognitive functions in addition to the core diagnosis of obsessions and compulsions. This is the first magnetoencephalography (MEG) study to examine whole-brain neurophysiological functional connectivity of emotional face processing networks in paediatric OCD. Seventy-two participants (OCD: n = 36; age 8-17 yrs; typically developing controls: n = 36, age 8-17 yrs) completed an implicit emotional face processing task in the MEG. Functional connectivity networks in canonical frequency bands were compared between groups, and within OCD and control groups between emotions (angry vs. happy). Between groups, participants with OCD showed increased functional connectivity in the gamma band to angry faces, suggesting atypical perception of angry faces in OCD. Within groups, the OCD group showed greater engagement of the beta band, suggesting the over-use of top-down processing when perceiving happy versus angry emotions, while controls engaged in bottom-up gamma processing, also greater to happy faces. Over-activation of top-down processing has been linked to difficulties modifying one's cognitive set. Findings establish altered patterns of neurophysiological connectivity in children with OCD, and are striking in their oscillatory specificity. Our results contribute to a greater understanding of the neurobiology of the disorder, and are foundational for the possibility of alternative targets for intervention.

Multi-View Feature Enhancement Based on Self-Attention Mechanism Graph Convolutional Network for Autism Spectrum Disorder Diagnosis

Functional connectivity (FC) network based on resting-state functional magnetic resonance imaging (rs-fMRI) has become an important tool to explore and understand the brain, which can provide objective basis for the diagnosis of neurodegenerative diseases, such as autism spectrum disorder (ASD). However, most functional connectivity (FC) networks only consider the unilateral features of nodes or edges, and the interaction between them is ignored. In fact, their integration can provide more comprehensive and crucial information in the diagnosis. To address this issue, a new multi-view brain network feature enhancement method based on self-attention mechanism graph convolutional network (SA-GCN) is proposed in this article, which can enhance node features through the connection relationship among different nodes, and then extract deep-seated and more discriminative features. Specifically, we first plug the pooling operation of self-attention mechanism into graph convolutional network (GCN), which can consider the node features and topology of graph network at the same time and then capture more discriminative features. In addition, the sample size is augmented by a "sliding window" strategy, which is beneficial to avoid overfitting and enhance the generalization ability. Furthermore, to fully explore the complex connection relationship among brain regions, we constructed the low-order functional graph network (Lo-FGN) and the high-order functional graph network (Ho-FGN) and enhance the features of the two functional graph networks (FGNs) based on SA-GCN. The experimental results on benchmark datasets show that: (1) SA-GCN can play a role in feature enhancement and can effectively extract more discriminative features, and (2) the integration of Lo-FGN and Ho-FGN can achieve the best ASD classification accuracy (79.9%), which reveals the information complementarity between them.

Shared and Distinct Patterns of Functional Connectivity to Emotional Faces in Autism Spectrum Disorder and Attention-Deficit/Hyperactivity Disorder Children

Impairments in emotional face processing are demonstrated by individuals with neurodevelopmental disorders (NDDs), including autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD), which is associated with altered emotion processing networks. Despite accumulating evidence of high rates of diagnostic overlap and shared symptoms between ASD and ADHD, functional connectivity underpinning emotion processing across these two neurodevelopmental disorders, compared to typical developing peers, has rarely been examined. The current study used magnetoencephalography to investigate whole-brain functional connectivity during the presentation of happy and angry faces in 258 children (5–19 years), including ASD, ADHD and typically developing (TD) groups to determine possible differences in emotion processing. Data-driven clustering was also applied to determine whether the patterns of connectivity differed among diagnostic groups. We found reduced functional connectivity in the beta band in ASD compared to TD, and a further reduction in the ADHD group compared to the ASD and the TD groups, across emotions. A group-by-emotion interaction in the gamma frequency band was also observed. Greater connectivity to happy compared to angry faces was found in the ADHD and TD groups, while the opposite pattern was seen in ASD. Data-driven subgrouping identified two distinct subgroups: NDD-dominant and TD-dominant; these subgroups demonstrated emotion- and frequency-specific differences in connectivity. Atypicalities in specific brain networks were strongly correlated with the severity of diagnosis-specific symptoms. Functional connectivity strength in the beta network was negatively correlated with difficulties in attention; in the gamma network, functional connectivity strength to happy faces was positively correlated with adaptive behavioural functioning, but in contrast, negatively correlated to angry faces. Our findings establish atypical frequency- and emotion-specific patterns of functional connectivity between NDD and TD children. Data-driven clustering further highlights a high degree of comorbidity and symptom overlap between the ASD and ADHD children.

Sex differences in automatic emotion regulation in adolescents with autism spectrum disorder

Autism may be underdiagnosed in females because their social difficulties are often less noticeable. This study explored sex differences in automatic facial emotion processing in 45 adolescents with autism spectrum disorder (22 female, 23 male), age 10-16 years, performing active target detection task and Go/NoGo tasks where faces with positive and negative emotional expressions served as irrelevant distractors. The combined sample demonstrated more accurate performance on the target detection (response initiation) than the Go/NoGo task (response inhibition), replicating findings previously reported in typical participants. Females exhibited greater difficulty than males with response initiation in the target detection task, especially in the context of angry faces, while males found withholding a response in the Go/NoGo block with happy faces more challenging. Electrophysiological data revealed no sex differences or emotion discrimination effects during the early perceptual processing of faces indexed by the occipitotemporal N170. Autistic males demonstrated increased frontal N2 and parietal P3 amplitudes compared to females, suggesting greater neural resource allocation to automatic emotion regulation processes. The associations between standardized behavioral measures (autism severity, theory of mind skills) and brain responses also varied by sex: more adaptive social functioning was related to the speed of perceptual processing (N170 latency) in females and the extent of deliberate attention allocation (P3 amplitudes) in males. Together, these findings suggest that males and females with autism may rely on different strategies for social functioning and highlight the importance of considering sex differences in autism. LAY SUMMARY: Females with autism may exhibit less noticeable social difficulties than males. This study demonstrates that autistic females are more successful than males at inhibiting behavioral responses in emotional contexts, while males are more likely to initiate a response. At the neural level, social functioning in females is related to the speed of automatic perceptual processing of facial cues, and in males, to the extent of active attention allocation to the stimuli. These findings highlight the importance of considering sex differences in autism diagnosis and treatment selection.

Abnormal cortical responses elicited by audiovisual movies in patients with autism spectrum disorder with atypical sensory behavior: A magnetoencephalographic study

BACKGROUND

Atypical sensory behavior disrupts behavioral adaptation in children with autism spectrum disorder (ASD); however, neural correlates of sensory dysfunction using magnetoencephalography (MEG) remain unclear.

METHOD

We used MEG to measure the cortical activation elicited by visual (uni)/audiovisual (multisensory) movies in 46 children (7-14 years) were included in final analysis: 13 boys with atypical audiovisual behavior in ASD (AAV+), 10 without this condition, and 23 age-matched typically developing boys.

RESULTS

The AAV+ group demonstrated an increase in the cortical activation in the bilateral insula in response to unisensory movies and in the left occipital, right superior temporal sulcus (rSTS), and temporal regions to multisensory movies. These increased responses were correlated with severity of the sensory impairment. Increased theta-low gamma oscillations were observed in the rSTS in AAV+.

CONCLUSION

The findings suggest that AAV is attributed to atypical neural networks centered on the rSTS.

Neural-level associations of non-verbal pragmatic comprehension in young Finnish autistic adults

This video-based study examines the pragmatic non-verbal comprehension skills and corresponding neural-level findings in young Finnish autistic adults, and controls. Items from the Assessment Battery of Communication (ABaCo) were chosen to evaluate the comprehension of non-verbal communication. Inter-subject correlation (ISC) analysis of the functional magnetic resonance imaging data was used to reveal the synchrony of brain activation across participants during the viewing of pragmatically complex scenes of ABaCo videos. The results showed a significant difference between the ISC maps of the autistic and control groups in tasks involving the comprehension of non-verbal communication, thereby revealing several brain regions where correlation of brain activity was greater within the control group. The results suggest a possible weaker modulation of brain states in response to the pragmatic non-verbal communicative situations in autistic participants. Although there was no difference between the groups in behavioural responses to ABaCo items, there was more variability in the accuracy of the responses in the autistic group. Furthermore, mean answering and reaction times correlated with the severity of autistic traits. The results indicate that even if young autistic adults may have learned to use compensatory resources in their communicative-pragmatic comprehension, pragmatic processing in naturalistic situations still requires additional effort.

Case of Asperger's Syndrome and Lesion of the Right Amygdala: Deficits in Implicit and Explicit Fearful Face Recognition

Introduction: Studies of brain-damaged patients revealed that amygdala lesions cause deficits in the processing and recognition of emotional faces. Patients with autism spectrum disorders (ASD) have similar deficits also related to dysfunctions of the limbic system including the amygdala.

Methods: We investigated a male patient who had been diagnosed with Asperger's syndrome. He also presented with a lesion of the right mesial temporal cortex, including the amygdala. We used functional magnetic resonance imaging (fMRI) to investigate neuronal processing during a passive viewing task of implicit and explicit emotional faces. Clinical assessment included a facial emotion recognition task.

Results: There was no amygdala activation on both sides during the presentation of masked emotional faces compared to the no-face control condition. Presentation of unmasked happy and angry faces activated the left amygdala compared to the no-face control condition. There was no amygdala activation in response to unmasked fearful faces on both sides. In the facial emotion recognition task, the patient biased positive and neutral expressions as negative.

Conclusions: This case report describes a male patient with right amygdala damage and an ASD. He displayed a non-response of the amygdala to fearful faces and tended to misinterpret fearful expressions. Moreover, a non-reactivity of both amygdalae to emotional facial expressions at an implicit processing level was revealed. It is discussed whether the deficient implicit processing of facial emotional information and abnormalities in fear processing could contribute and aggravate the patient's impairments in social behavior and interaction.

Atypical spatiotemporal activation of cerebellar lobules during emotional face processing in adolescents with autism

Autism spectrum disorder (ASD) is characterized by social deficits and atypical facial processing of emotional expressions. The underlying neuropathology of these abnormalities is still unclear. Recent studies implicate cerebellum in emotional processing; other studies show cerebellar abnormalities in ASD. Here, we elucidate the spatiotemporal activation of cerebellar lobules in ASD during emotional processing of happy and angry faces in adolescents with ASD and typically developing (TD) controls. Using magnetoencephalography, we calculated dynamic statistical parametric maps across a period of 500 ms after emotional stimuli onset and determined differences between group activity to happy and angry emotions. Following happy face presentation, adolescents with ASD exhibited only left‐hemispheric cerebellar activation in a cluster extending from lobule VI to lobule V (compared to TD controls). Following angry face presentation, adolescents with ASD exhibited only midline cerebellar activation (posterior IX vermis). Our findings indicate an early (125–175 ms) overactivation in cerebellar activity only for happy faces and a later overactivation for both happy (250–450 ms) and angry (250–350 ms) faces in adolescents with ASD. The prioritized hemispheric activity (happy faces) could reflect the promotion of a more flexible and adaptive social behavior, while the latter midline activity (angry faces) may guide conforming behavior.

Processing of pragmatic communication in ASD: a video-based brain imaging study

Social and pragmatic difficulties in autism spectrum disorder (ASD) are widely recognized, although their underlying neural level processing is not well understood. The aim of this study was to examine the activity of the brain network components linked to social and pragmatic understanding in order to reveal whether complex socio-pragmatic events evoke differences in brain activity between the ASD and control groups. Nineteen young adults (mean age 23.6 years) with ASD and 19 controls (mean age 22.7 years) were recruited for the study. The stimulus data consisted of video clips showing complex social events that demanded processing of pragmatic communication. In the analysis, the functional magnetic resonance imaging signal responses of the selected brain network components linked to social and pragmatic information processing were compared. Although the processing of the young adults with ASD was similar to that of the control group during the majority of the social scenes, differences between the groups were found in the activity of the social brain network components when the participants were observing situations with concurrent verbal and non-verbal communication events. The results suggest that the ASD group had challenges in processing concurrent multimodal cues in complex pragmatic communication situations.

Changing Faces: Dynamic Emotional Face Processing in Autism Spectrum Disorder Across Childhood and Adulthood

BACKGROUND

Autism spectrum disorder (ASD) is classically associated with poor emotional face processing. Few studies, however, have used more ecological dynamic stimuli. We contrasted functional magnetic resonance imaging measures of dynamic emotional face processing in ASD and typically developing (TD) cohorts across a wide age range to determine if the processing and age-related trajectories differed between participants with and without ASD.

METHODS

Functional magnetic resonance imaging data collected from 200 participants (5-42 years old; 107 in ASD cohort, 93 in TD cohort) during the presentation of dynamic emotional faces (neutral-to-happy, neutral-to-angry) and dynamic flowers (closed-to-open) were analyzed. Group differences and group-by-age interactions in the faces versus flowers and between emotion contrasts were investigated.

RESULTS

Differences in activation between dynamic faces and flowers in occipital regions, including the fusiform gyri, were reduced in the ASD group. Contrasting the two emotions, ASD compared with TD participants showed increased engagement of the precentral, postcentral, and superior temporal gyri to happy faces and increased activation to angry faces occipitally. Emotion processing regions, such as insula, temporal pole, and frontal regions, showed increased recruitment with age to happy faces compared with both angry faces and flowers in the TD group, but decreased recruitment with age in the ASD group.

CONCLUSIONS

Using dynamic stimuli, we demonstrated that participants with ASD processed faces similarly to nonface stimuli, and age-related atypicalities were more pronounced to happy faces in participants with ASD. We demonstrated emotion-specific atypicalities in a large group of participants with ASD that underscore persistent difficulties from childhood into mid-adulthood.

Development of Cognitive and Physical Exercise Systems, Clinical Recordings, Large-Scale Data Analytics, and Virtual Coaching for Heart Failure Patients: Protocol for the BioTechCOACH-ForALL Project

Background

Heart failure is a chronic disease affecting patient morbidity and mortality. Current guidelines for heart failure patient treatment are focused on improving their clinical status, functional capacity, and quality of life. However, these guidelines implement numerous instructions including medical treatment adherence, physical activity, and self-care management. The complexity of the therapeutic instructions makes them difficult to follow especially by older adults.

Objective

The challenge of this project is to (1) measure real-life adherence to a regular physical exercise program and (2) attempt to influence older adult patients with heart failure toward embracing a more physically active self-care lifestyle.

Methods

This research consists of two studies, including a lab experiment and a pragmatic evaluation of technology at patients’ homes. The lab experiment aims at exploring in an objective way (measuring neurophysiological responses to stimuli) patient engagement with different characteristics of virtual agents, while the home study is a 3-phase prospective study where the developed technology platform is tested by heart failure patients in their own home environments. Patients undergo evaluation of their physical activity and cognitive status using standard evaluation methods (6-minute walk test, questionnaires) and receive wearable devices to accurately measure everyday life activity levels (home study phases 1-3). During home study phases 2 and 3, exergames (serious games for physical exercise) to provide a physical exercise plan as a joyful activity are delivered to patients’ private households and e-coaching techniques are implemented in the final phase (home study phase 3) of the protocol, to influence patient attitudes toward a more healthy and recommended lifestyle.

Results

The trial is still ongoing. Recruitment is ongoing, and the project has progressed for some participants through phase 2 of the home study. The sample size for both studies is 28 participants; 10 have already been included in the study, and both baseline clinical and patient-reported outcome data are retrieved. Phases 2 and 3 of the home pilot study are expected to be completed within 6 months.

Conclusions

The main challenge of the project is the change of attitude of older age heart failure patients through an e-coaching system. Given the adoption of a cocreation and living lab approach and the main objective for real-life evaluation, the project is ready to react to any collected feedback, even during the implementation of the research plan. Clinical assessment and objective evaluation are expected to provide all required information for reliable findings.

Trial Registration

ClinicalTrials.gov NCT03877328; https://clinicaltrials.gov/ct2/show/NCT03877328

International Registered Report Identifier (IRRID)

DERR1-10.2196/17714

Diagnosis of Autism Spectrum Disorder Using Central-Moment Features From Low- and High-Order Dynamic Resting-State Functional Connectivity Networks

The sliding-window-based dynamic functional connectivity networks (D-FCNs) derived from resting-state functional magnetic resonance imaging (rs-fMRI) are effective methods for diagnosing various neurological diseases, including autism spectrum disorder (ASD). However, traditional D-FCNs are low-order networks based on pairwise correlation between brain regions, thus overlooking high-level interactions across multiple regions of interest (ROIs). Moreover, D-FCNs suffer from the temporal mismatching issue, i.e., subnetworks in the same temporal window do not have temporal correspondence across different subjects. To address the above problems, we first construct a novel high-order D-FCNs based on the principle of “correlation’s correlation” to further explore the higher level and more complex interaction relationships among multiple ROIs. Furthermore, we propose to use a central-moment method to extract temporal-invariance properties contained in either low- or high-order D-FCNs. Finally, we design and train an ensemble classifier by fusing the features extracted from conventional FCN, low-order D-FCNs, and high-order D-FCNs for the diagnosis of ASD and normal control subjects. Our method achieved the best ASD classification accuracy (83%), and our results revealed the features extracted from different networks fingerprinting the autistic brain at different connectional levels.

Emotional face processing in autism spectrum disorder: Effects in gamma connectivity

Impairments in social functioning are characteristic of autism spectrum disorder (ASD). Differences in functional networks during face processing in ASD compared to controls have been reported; however, the spatial-temporal dynamics of networks underlying affective processing are still not well understood. The current magnetoencephalography study examined whole-brain functional connectivity to implicit happy and angry faces in 104 adults with and without ASD. A network of reduced gamma band (30-55 Hz) phase synchrony occurring 80-308 ms following angry face presentation was found in adults with ASD compared to controls. The network involved widespread connections primarily anchored in frontal regions, including bilateral orbitofrontal areas, bilateral inferior frontal gyri, and left middle frontal gyrus extending to occipital, temporal, parietal, and subcortical regions. This finding suggests disrupted long-range neuronal communication to angry faces. Additionally, reduced gamma band-specific connectivity may reflect altered E/I balance in brain regions critical for emotional face processing in ASD.

Enhanced Early Visual Responses During Implicit Emotional Faces Processing in Autism Spectrum Disorder

Research on Autism Spectrum Disorder (ASD) has focused on processing of socially-relevant stimuli, such as faces. Nonetheless, before being 'social', faces are visual stimuli. The present magnetoencephalography study investigated the time course of brain activity during an implicit emotional task in visual emotion-related regions in 19 adults with ASD (mean age 26.3 ± 4.4) and 19 typically developed controls (26.4 ± 4). The results confirmed previously-reported differences between groups in brain responses to emotion and a hypo-activation in the ASD group in the right fusiform gyrus around 150 ms. However, the ASD group also presented early enhanced activity in the occipital region. These results support that impaired face processing in ASD might be sustained by atypical responses in primary visual areas.

Happy and Angry Faces Elicit Atypical Neural Activation in Children With Autism Spectrum Disorder

BACKGROUND

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by significant impairments in social interactions and communication. The ability to accurately perceive and interpret emotional faces is critical to successful social interactions. However, few studies have investigated the spatiotemporal profile of the neural mechanisms underlying emotional face processing in ASD, particularly in children. The current study fills this important gap.

METHODS

Participants were 55 children: 28 children with ASD (mean age = 9.5 ± 1.3 years) and 27 control children (mean age = 8.5 ± 1.3 years). All children completed an implicit emotional face task while magnetoencephalography was recorded. We examined spatiotemporal differences between the groups in neural activation during implicit processing of emotional faces.

RESULTS

Within-group analyses demonstrated greater right middle temporal (300-375 ms) and superior temporal (300-400 ms) activation to angry faces than to happy faces in control children, while children with ASD showed greater activation from 250 to 500 ms to happy faces than to angry faces across frontal and temporal regions. Between-group analyses demonstrated that children with ASD showed similar patterns of late (425-500 ms) posterior cingulate and thalamic underactivity to both angry and happy faces relative to control children, suggesting general atypical processing of emotional information.

CONCLUSIONS

Atypical posterior cingulate cortex and thalamus recruitment in children with ASD to emotional faces suggests poor modulation of toggling between the default mode network and task-based processing. Increased neural activity to happy faces compared with angry faces in children with ASD suggests reduced salience or immature response to anger, which in turn could contribute to deficits in social cognition in ASD.

How face blurring affects body language processing of static gestures in women and men

The role of facial coding in body language comprehension was investigated by event-related potential recordings in 31 participants viewing 800 photographs of gestures (iconic, deictic and emblematic), which could be congruent or incongruent with their caption. Facial information was obscured by blurring in half of the stimuli. The task consisted of evaluating picture/caption congruence. Quicker response times were observed in women than in men to congruent stimuli, and a cost for incongruent vs congruent stimuli was found only in men. Face obscuration did not affect accuracy in women as reflected by omission percentages, nor reduced their cognitive potentials, thus suggesting a better comprehension of face deprived pantomimes. N170 response (modulated by congruity and face presence) peaked later in men than in women. Late positivity was much larger for congruent stimuli in the female brain, regardless of face blurring. Face presence specifically activated the right superior temporal and fusiform gyri, cingulate cortex and insula, according to source reconstruction. These regions have been reported to be insufficiently activated in face-avoiding individuals with social deficits. Overall, the results corroborate the hypothesis that females might be more resistant to the lack of facial information or better at understanding body language in face-deprived social information.

Magnetoencephalography and the infant brain

Magnetoencephalography (MEG) is a non-invasive neuroimaging technique that provides whole-head measures of neural activity with millisecond temporal resolution. Over the last three decades, MEG has been used for assessing brain activity, most commonly in adults. MEG has been used less often to examine neural function during early development, in large part due to the fact that infant whole-head MEG systems have only recently been developed. In this review, an overview of infant MEG studies is provided, focusing on the period from birth to three years. The advantages of MEG for measuring neural activity in infants are highlighted (See Box 1), including the ability to assess activity in brain (source) space rather than sensor space, thus allowing direct assessment of neural generator activity. Recent advances in MEG hardware and source analysis are also discussed. As the review indicates, efforts in this area demonstrate that MEG is a promising technology for studying the infant brain. As a noninvasive technology, with emerging hardware providing the necessary sensitivity, an expected deliverable is the capability for longitudinal infant MEG studies evaluating the developmental trajectory (maturation) of neural activity. It is expected that departures from neuro-typical trajectories will offer early detection and prognosis insights in infants and toddlers at-risk for neurodevelopmental disorders, thus paving the way for early targeted interventions.

Neuromodulation and a Reconceptualization of Autism Spectrum Disorders: Using the Locus Coeruleus Functioning as an Exemplar

The Autism Spectrum Disorders (ASD) are a heterogeneous group of developmental disorders. Although, ASD can be reliably diagnosed, the etiology, pathophysiology, and treatment targets remain poorly characterized. While there are many atypical findings in anatomy, genetics, connectivity, and other biologic parameters, there remains no discreet hypothesis to explain the core signs as well as the very frequent comorbidities. Due to this, designing targets for treatments can only be done by assuming each symptom is a result of a discreet abnormality which is likely not the case. Neuronal circuity remains a major focus of research but rarely taking into account the functioning of the brain is highly dependent on various systems, including the neuromodulatory substances originating in the midbrain. A hypothesis is presented which explores the possibility of explaining many of the symptoms found in ASD in terms of inefficient neuromodulation using the functioning of the locus coeruleus and norepinephrine (LC/NE) as exemplars. The basic science of LC/NE is reviewed. Several functions found to be impaired in ASD including learning, attention, sensory processing, emotional regulation, autonomic functioning, adaptive and repetitive behaviors, sleep, language acquisition, initiation, and prompt dependency are examined in terms of the functioning of the LC/NE system. Suggestions about possible treatment directions are explored.

[Preliminary application of Early Start Denver Model in children with autism spectrum disorder]

OBJECTIVE

To investigate the clinical effect of the Early Start Denver Model (ESDM) in children with autism spectrum disorder (ASD).

METHODS

Forty children aged 2-5 years who were diagnosed with ASD from September 2017 to January 2018 were enrolled in the study and were randomly divided into conventional intervention group and ESDM intervention group (n=20 each). Both groups were assessed by the Aberrant Behavior Checklist (ABC), Childhood Autism Rating Scale (CARS), and Clinical Global Impression-Severity (CGI-S) scale before intervention and by the ABC, CARS, CGI-S scale, and Clinical Global Impression-Improvement (CGI-I) scale after 3 months of intervention.

RESULTS

After 3 months of intervention, the total scores of ABC and CARS were both significantly decreased in the two groups (P<0.01); the scores on the social withdrawal and hyperactivity subscales of ABC were significantly decreased in the conventional intervention group (P<0.01), and the scores on the mood swings, social withdrawal, hyperactivity, and stereotyped behavior subscales of ABC were significantly decreased in the ESDM intervention group (P<0.01). Compared with the conventional intervention group, the ESDM intervention group had significantly greater changes in total score of ABC, scores on three subscales of ABC (mood swings, social withdrawal, and hyperactivity), and total score of CARS after intervention (P<0.05). After 3 months of intervention, the CGI-I scoring system showed that the disease improvement was significantly better in the ESDM intervention group than in the conventional intervention group (P<0.05).

CONCLUSIONS

Both conventional intervention and ESDM intervention can improve the social withdrawal and hyperactivity in children with ASD aged 2 to 5 years, but ESDM is more effective in improving the aberrant behavior of children with ASD.

Enhancing the representation of functional connectivity networks by fusing multi-view information for autism spectrum disorder diagnosis

Functional connectivity network provides novel insights on how distributed brain regions are functionally integrated, and its deviations from healthy brain have recently been employed to identify biomarkers for neuropsychiatric disorders. However, most of brain network analysis methods utilized features extracted only from one functional connectivity network for brain disease detection and cannot provide a comprehensive representation on the subtle disruptions of brain functional organization induced by neuropsychiatric disorders. Inspired by the principles of multi-view learning which utilizes information from multiple views to enhance object representation, we propose a novel multiple network based framework to enhance the representation of functional connectivity networks by fusing the common and complementary information conveyed in multiple networks. Specifically, four functional connectivity networks corresponding to the four adjacent values of regularization parameter are generated via a sparse regression model with group constraint ( l_2,1 -norm), to enhance the common intrinsic topological structure and limit the error rate caused by different views. To obtain a set of more meaningful and discriminative features, we propose using a modified version of weighted clustering coefficients to quantify the subtle differences of each group-sparse network at local level. We then linearly fuse the selected features from each individual network via a multi-kernel support vector machine for autism spectrum disorder (ASD) diagnosis. The proposed framework achieves an accuracy of 79.35%, outperforming all the compared single network methods for at least 7% improvement. Moreover, compared with other multiple network methods, our method also achieves the best performance, that is, with at least 11% improvement in accuracy.

Visual and auditory emotion recognition problems as familial cross-disorder phenomenon in ASD and ADHD

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are frequently comorbid disorders. Emotion recognition problems are considered an important familial deficit in ASD, but this is unknown in ADHD. Very few studies have directly compared emotion recognition performance of youth with ASD and/or ADHD and of their unaffected siblings across age to quantify the contribution of emotion recognition problems to the ADHD phenotype. We therefore devised a study of 64 ASD+ADHD participants, 89 ASD-only participants, 111 ADHD-only participants, 122 unaffected ASD(+ADHD) siblings, 69 unaffected ADHD-only siblings and 220 controls aged 7-18 years, who had completed two tasks assessing auditory and visual emotion recognition. Factor analysis was used to detect underlying dimensions of emotion recognition capacity. Linear mixed models were used to compare performance across groups and to assess age effects. The factor-analysis revealed four factors separating speed and accuracy regarding visual and auditory emotion recognition. ASD+ADHD, ASD-only, and ADHD-only participants all performed worse than controls. ASD+ADHD, ASD-only, and ADHD-only participants did not differ in the severity of their emotion recognition problems. Both unaffected sibling groups performed intermediate between patients and controls. For ASD+ADHD and ADHD-only participants, group differences were more marked in adolescence than childhood, whereas in ASD participants this was not observed. We conclude that emotion recognition problems are a familial deficit in ADHD to a similar extent as in ASD. Emotion recognition problems specifically - and social cognition problems more generally - should be assessed in clinical practice for ADHD.

Young Adults with Autism Spectrum Disorder Show Early Atypical Neural Activity during Emotional Face Processing

Social cognition is impaired in autism spectrum disorder (ASD). The ability to perceive and interpret affect is integral to successful social functioning and has an extended developmental course. However, the neural mechanisms underlying emotional face processing in ASD are unclear. Using magnetoencephalography (MEG), the present study explored neural activation during implicit emotional face processing in young adults with and without ASD. Twenty-six young adults with ASD and 26 healthy controls were recruited. Participants indicated the location of a scrambled pattern (target) that was presented alongside a happy or angry face. Emotion-related activation sources for each emotion were estimated using the Empirical Bayes Beamformer (p_corr ≤ 0.001) in Statistical Parametric Mapping 12 (SPM12). Emotional faces elicited elevated fusiform, amygdala and anterior insula and reduced anterior cingulate cortex (ACC) activity in adults with ASD relative to controls. Within group comparisons revealed that angry vs. happy faces elicited distinct neural activity in typically developing adults; there was no distinction in young adults with ASD. Our data suggest difficulties in affect processing in ASD reflect atypical recruitment of traditional emotional processing areas. These early differences may contribute to difficulties in deriving social reward from faces, ascribing salience to faces, and an immature threat processing system, which collectively could result in deficits in emotional face processing.

The relation between face-emotion recognition and social function in adolescents with autism spectrum disorders: A case control study

An altered processing of emotions may contribute to a reduced ability for social interaction and communication in autism spectrum disorder, ASD. We investigated how face-emotion recognition in ASD is different from typically developing across adolescent age groups. Fifty adolescents diagnosed with ASD and 49 typically developing (age 12–21 years) were included. The ASD diagnosis was underpinned by parent-rated Social Communication Questionnaire. We used a cued GO/ NOGO task with pictures of facial expressions and recorded reaction time, intra-individual variability of reaction time and omissions/commissions. The Social Responsiveness Scale was used as a measure of social function. Analyses were conducted for the whole group and for young (< 16 years) and old (≥ 16 years) age groups. We found no significant differences in any task measures between the whole group of typically developing and ASD and no significant correlations with the Social Responsiveness Scale. However, there was a non-significant tendency for longer reaction time in the young group with ASD (p = 0.099). The Social Responsiveness Scale correlated positively with reaction time (r = 0.30, p = 0.032) and intra-individual variability in reaction time (r = 0.29, p = 0.037) in the young group and in contrast, negatively in the old group (r = -0.23, p = 0.13; r = -0.38, p = 0.011, respectively) giving significant age group interactions for both reaction time (p = 0.008) and intra-individual variability in reaction time (p = 0.001). Our findings suggest an age-dependent association between emotion recognition and severity of social problems indicating a delayed development of emotional understanding in ASD. It also points towards alterations in top-down attention control in the ASD group. This suggests novel disease-related features that should be investigated in more details in experimental settings.

μ opioid receptor, social behaviour and autism spectrum disorder: reward matters

The endogenous opioid system is well known to relieve pain and underpin the rewarding properties of most drugs of abuse. Among opioid receptors, the μ receptor mediates most of the analgesic and rewarding properties of opioids. Based on striking similarities between social distress, physical pain and opiate withdrawal, μ receptors have been proposed to play a critical role in modulating social behaviour in humans and animals. This review summarizes experimental data demonstrating such role and proposes a novel model, the μ opioid receptor balance model, to account for the contribution of μ receptors to the subtle regulation of social behaviour. Interestingly, μ receptor null mice show behavioural deficits similar to those observed in patients with autism spectrum disorder (ASD), including severe impairment in social interactions. Therefore, after a brief summary of recent evidence for blunted (social) reward processes in subjects with ASD, we review here arguments for altered μ receptor function in this pathology. This article is part of a themed section on Emerging Areas of Opioid Pharmacology. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v175.14/issuetoc.

Wanting it Too Much: An Inverse Relation Between Social Motivation and Facial Emotion Recognition in Autism Spectrum Disorder

This study examined social motivation and early-stage face perception as frameworks for understanding impairments in facial emotion recognition (FER) in a well-characterized sample of youth with autism spectrum disorders (ASD). Early-stage face perception (N170 event-related potential latency) was recorded while participants completed a standardized FER task, while social motivation was obtained via parent report. Participants with greater social motivation exhibited poorer FER, while those with shorter N170 latencies exhibited better FER for child angry faces stimuli. Social motivation partially mediated the relationship between a faster N170 and better FER. These effects were all robust to variations in IQ, age, and ASD severity. These findings augur against theories implicating social motivation as uniformly valuable for individuals with ASD, and augment models suggesting a close link between early-stage face perception, social motivation, and FER in this population. Broader implications for models and development of FER in ASD are discussed.

Magnetoencephalography in the study of children with autism spectrum disorder

Magnetoencephalography (MEG) is a non-invasive neuroimaging technique that provides a measure of cortical neural activity on a millisecond timescale with high spatial resolution. MEG has been clinically applied to various neurological diseases, including epilepsy and cognitive dysfunction. In the past decade, MEG has also emerged as an important investigatory tool in neurodevelopmental studies. It is therefore an opportune time to review how MEG is able to contribute to the study of atypical brain development. We limit this review to autism spectrum disorder (ASD). The relevant published work for children was accessed using PubMed on 5 January 2015. Case reports, case series, and papers on epilepsy were excluded. Owing to their accurate separation of brain activity in the right and left hemispheres and the higher accuracy of source localization, MEG studies have added new information related to auditory-evoked brain responses to findings from previous electroencephalography studies of children with ASD. In addition, evidence of atypical brain connectivity in children with ASD has accumulated over the past decade. MEG is well suited for the study of neural activity with high time resolution even in young children. Although further studies are still necessary, the detailed findings provided by neuroimaging methods may aid clinical diagnosis and even contribute to the refinement of diagnostic categories for neurodevelopmental disorders in the future.