Reduced beta connectivity during emotional face processing in adolescents with autism

Oscillatory activity underlying cognitive performance in children and adolescents with autism: a systematic review

Autism spectrum disorder (ASD) is a neurodevelopmental condition that exhibits a widely heterogeneous range of social and cognitive symptoms. This feature has challenged a broad comprehension of this neurodevelopmental disorder and therapeutic efforts to address its difficulties. Current therapeutic strategies have focused primarily on treating behavioral symptoms rather than on brain psychophysiology. During the past years, the emergence of non-invasive brain stimulation techniques (NIBS) has opened alternatives to the design of potential combined treatments focused on the neurophysiopathology of neuropsychiatric disorders like ASD. Such interventions require identifying the key brain mechanisms underlying the symptomatology and cognitive features. Evidence has shown alterations in oscillatory features of the neural ensembles associated with cognitive functions in ASD. In this line, we elaborated a systematic revision of the evidence of alterations in brain oscillations that underlie key cognitive processes that have been shown to be affected in ASD during childhood and adolescence, namely, social cognition, attention, working memory, inhibitory control, and cognitive flexibility. This knowledge could contribute to developing therapies based on NIBS to improve these processes in populations with ASD.

From synaptic dysfunction to atypical emotional processing in autism

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition mainly characterized by social impairments and repetitive behaviors. Among these core symptoms, a notable aspect of ASD is the presence of emotional complexities, including high rates of anxiety disorders. The inherent heterogeneity of ASD poses a unique challenge in understanding its etiological origins, yet the utilization of diverse animal models replicating ASD traits has enabled researchers to dissect the intricate relationship between autism and atypical emotional processing. In this review, we delve into the general findings about the neural circuits underpinning one of the most extensively researched and evolutionarily conserved emotional states: fear and anxiety. Additionally, we explore how distinct ASD animal models exhibit various anxiety phenotypes, making them a crucial tool for dissecting ASD's multifaceted nature. Overall, to a proper display of fear response, it is crucial to properly process and integrate sensorial and visceral cues to the fear-induced stimuli. ASD individuals exhibit altered sensory processing, possibly contributing to the emergence of atypical phobias, a prevailing anxiety disorder manifested in this population. Moreover, these individuals display distinctive alterations in a pivotal fear and anxiety processing hub, the amygdala. By examining the neurobiological mechanisms underlying fear and anxiety regulation, we can gain insights into the factors contributing to the distinctive emotional profile observed in individuals with ASD. Such insights hold the potential to pave the way for more targeted interventions and therapies that address the emotional challenges faced by individuals within the autism spectrum.

Dynamic Functional Connectivity of Emotion Processing in Beta Band with Naturalistic Emotion Stimuli

While naturalistic stimuli, such as movies, better represent the complexity of the real world and are perhaps crucial to understanding the dynamics of emotion processing, there is limited research on emotions with naturalistic stimuli. There is a need to understand the temporal dynamics of emotion processing and their relationship to different dimensions of emotion experience. In addition, there is a need to understand the dynamics of functional connectivity underlying different emotional experiences that occur during or prior to such experiences. To address these questions, we recorded the EEG of participants and asked them to mark the temporal location of their emotional experience as they watched a video. We also obtained self-assessment ratings for emotional multimedia stimuli. We calculated dynamic functional the connectivity (DFC) patterns in all the frequency bands, including information about hubs in the network. The change in functional networks was quantified in terms of temporal variability, which was then used in regression analysis to evaluate whether temporal variability in DFC (tvDFC) could predict different dimensions of emotional experience. We observed that the connectivity patterns in the upper beta band could differentiate emotion categories better during or prior to the reported emotional experience. The temporal variability in functional connectivity dynamics is primarily related to emotional arousal followed by dominance. The hubs in the functional networks were found across the right frontal and bilateral parietal lobes, which have been reported to facilitate affect, interoception, action, and memory-related processing. Since our study was performed with naturalistic real-life resembling emotional videos, the study contributes significantly to understanding the dynamics of emotion processing. The results support constructivist theories of emotional experience and show that changes in dynamic functional connectivity can predict aspects of our emotional experience.

Bottom-up vs. top-down connectivity imbalance in individuals with high-autistic traits: An electroencephalographic study

Brain connectivity is often altered in autism spectrum disorder (ASD). However, there is little consensus on the nature of these alterations, with studies pointing to either increased or decreased connectivity strength across the broad autism spectrum. An important confound in the interpretation of these contradictory results is the lack of information about the directionality of the tested connections. Here, we aimed at disambiguating these confounds by measuring differences in directed connectivity using EEG resting-state recordings in individuals with low and high autistic traits. Brain connectivity was estimated using temporal Granger Causality applied to cortical signals reconstructed from EEG. Between-group differences were summarized using centrality indices taken from graph theory (in degree, out degree, authority, and hubness). Results demonstrate that individuals with higher autistic traits exhibited a significant increase in authority and in degree in frontal regions involved in high-level mechanisms (emotional regulation, decision-making, and social cognition), suggesting that anterior areas mostly receive information from more posterior areas. Moreover, the same individuals exhibited a significant increase in the hubness and out degree over occipital regions (especially the left and right pericalcarine regions, where the primary visual cortex is located), suggesting that these areas mostly send information to more anterior regions. Hubness and authority appeared to be more sensitive indices than the in degree and out degree. The observed brain connectivity differences suggest that, in individual with higher autistic traits, bottom-up signaling overcomes top-down channeled flow. This imbalance may contribute to some behavioral alterations observed in ASD.

Atypical Functional Connectivity During Unfamiliar Music Listening in Children With Autism

Background

Atypical processing of unfamiliar, but less so familiar, stimuli has been described in Autism Spectrum Disorder (ASD), in particular in relation to face processing. We examined the construct of familiarity in ASD using familiar and unfamiliar songs, to investigate the link between familiarity and autism symptoms, such as repetitive behavior.

Methods

Forty-eight children, 24 with ASD (21 males, mean age = 9.96 years ± 1.54) and 24 typically developing (TD) controls (21 males, mean age = 10.17 ± 1.90) completed a music familiarity task using individually identified familiar compared to unfamiliar songs, while magnetoencephalography (MEG) was recorded. Each song was presented for 30 s. We used both amplitude envelope correlation (AEC) and the weighted phase lag index (wPLI) to assess functional connectivity between specific regions of interest (ROI) and non-ROI parcels, as well as at the whole brain level, to understand what is preserved and what is impaired in familiar music listening in this population.

Results

Increased wPLI synchronization for familiar vs. unfamiliar music was found for typically developing children in the gamma frequency. There were no significant differences within the ASD group for this comparison. During the processing of unfamiliar music, we demonstrated left lateralized increased theta and beta band connectivity in children with ASD compared to controls. An interaction effect found greater alpha band connectivity in the TD group compared to ASD to unfamiliar music only, anchored in the left insula.

Conclusion

Our results revealed atypical processing of unfamiliar songs in children with ASD, consistent with previous studies in other modalities reporting that processing novelty is a challenge for ASD. Relatively typical processing of familiar stimuli may represent a strength and may be of interest to strength-based intervention planning.

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.

Complexity analysis of the brain activity in Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD) due to cognitive loads/demands induced by Aristotle's type of syllogism/reasoning. A Power Spectral Density and multiscale entropy (MSE) analysis

OBJECTIVE

We aim to investigate whether EEG dynamics differ in adults with ASD (Autism Spectrum Disorders), ADHD (attention-deficit/hyperactivity disorder), compared with healthy subjects during the performance of an innovative cognitive task: Aristotle's valid and invalid syllogisms. We follow the Neuroanatomical differences type of criterion in assessing the results of our study in supporting or not the dual-process theory of Kahneman, 2011) (Systems I & II of thinking).

METHOD

We recorded EEGs from 14 scalp electrodes in 30 adults with ADHD, 30 with ASD and 24 healthy, normal subjects. The subjects were exposed in a set of innovative cognitive tasks (inducing varying cognitive loads), the Aristotle's four types of syllogism mentioned above. The multiscale entropy (MSE), a nonlinear information-theoretic measure or tool was computed to extract features that quantify the complexity of the EEG.

RESULTS

The dynamics of the curves of the grand average of MSE values of the ADHD and ASD participants was significantly in higher levels for the majority of time scales, than the healthy subjects over a number of brain regions (electrodes locations), during the performance of both valid and invalid types of syllogism. This result is seemingly not in accordance of the broadly accepted 'theory' of complexity loss in 'pathological' subjects, but actually this is not the case as explained in the text. ADHD subjects are engaged in System II of thinking, for both Valid and Invalid syllogism, ASD and Control in System I for valid and invalid syllogism, respectively. A surprising and 'provocative' result of this paper, as shown in the next sections, is that the Complexity-variability of ASD and ADHD subjects, when they face Aristotle's types of syllogisms, is higher than that of the control subjects. An explanation is suggested as described in the text. Also, in the case of invalid type of Aristotelian syllogisms, the linguistic and visuo-spatial systems are both engaged ONLY in the temporal and occipital regions of the brain, respectively, of ADHD subjects. In the case of valid type, both above systems are engaged in the temporal and occipital regions of the brain, respectively, of both ASD and ADHD subjects, while in the control subjects only the visuo-spatial type is engaged (Goel et al., 2000; Knauff, 2007).

CONCLUSION

Based on the results of the analysis described in this work, the differences in the EEG complexity between the three groups of participants lead to the conclusion that cortical information processing is changed in ASD and ADHD adults, therefore their level of cortical activation may be insufficient to meet the peculiar cognitive demand of Aristotle's reasoning.

SIGNIFICANCE

The present paper suggest that MSE, is a powerful and efficient nonlinear measure in detecting neural dysfunctions in adults with ASD and ADHD characteristics, when they are called on to perform in a very demanding as well as innovative set of cognitive tasks, that can be considered as a new diagnostic 'benchmark' in helping detecting more effectively such type of disorders. A linear measure alone, as the typical PSD, is not capable in making such a distinction. The work contributes in shedding light on the neural mechanisms of syllogism/reasoning of Aristotelian type, as well as toward understanding how humans reason logically and why 'pathological' subjects deviate from the norms of formal logic.

Atypical development of emotional face processing networks in autism spectrum disorder from childhood through to adulthood

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MEG connectivity to emotional faces in ASD and typical controls 6–39 years of age was investigated.

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Distinct age-related changes in connectivity were observed in the groups to happy and angry faces.

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Age-related between-group differences in functional connectivity were found in gamma band.

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Emotion-specific age-related between-group differences were seen in beta.

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Findings highlight specific neurodevelopmental trajectories to emotional faces in ASD vs. TD.

Impairments in social functioning are hallmarks of autism spectrum disorder (ASD) and atypical functional connectivity may underlie these difficulties. Emotion processing networks typically undergo protracted maturational changes, however, those with ASD show either hyper- or hypo-connectivity with little consensus on the functional connectivity underpinning emotion processing. Magnetoencephalography was used to investigate age-related changes in whole-brain functional connectivity of eight regions of interest during happy and angry face processing in 190 children, adolescents and adults (6–39 years) with and without ASD. Findings revealed age-related changes from child- through to mid-adulthood in functional connectivity in controls and in ASD in theta, as well as age-related between-group differences across emotions, with connectivity decreasing in ASD, but increasing for controls, in gamma. Greater connectivity to angry faces was observed across groups in gamma. Emotion-specific age-related between-group differences in beta were also found, that showed opposite trends with age for happy and angry in ASD. Our results establish altered, frequency-specific developmental trajectories of functional connectivity in ASD, across distributed networks and a broad age range, which may finally help explain the heterogeneity in the literature.

Altered Functional Connectivity During Face Processing in Children Born Very Low Birth Weight

Structural brain alterations have been reported in key emotional face processing regions following preterm birth; however, few studies have investigated the functional networks underlying these processes in children born with very low birth weight (VLBW). Using magnetoencephalography (MEG), we examined the functional networks related to the implicit processing of happy and angry faces in 5-year-old VLBW (n = 28) and full-term (FT; n = 24) children. We found that VLBW children showed atypical recruitment of emotional face processing networks in theta (4–7 Hz) compared to FT children. VLBW children showed reduced theta connectivity during processing of angry faces only. This hypo-connected theta-band network was anchored in the left orbitofrontal and parietal regions, involved in the higher level processing of faces and emotion regulation. At the behavioural level, despite VLBW children performing within the normal range, FT children had significantly higher affect recognition scores. Our MEG results suggest a selective impairment in processing angry faces, which would negatively impact social functioning in VLBW children. In FT children, greater recruitment of this theta-band network was positively associated with improved affect recognition scores. Thus, our findings suggest an important role of theta oscillations in early face processing, deficits which may contribute to broader socio-emotional impairments in VLBW children.

Mild traumatic brain injury is associated with dysregulated neural network functioning in children and adolescents

Mild traumatic brain injury is highly prevalent in paediatric populations, and can result in chronic physical, cognitive and emotional impairment, known as persistent post-concussive symptoms. Magnetoencephalography has been used to investigate neurophysiological dysregulation in mild traumatic brain injury in adults; however, whether neural dysrhythmia persists in chronic mild traumatic brain injury in children and adolescents is largely unknown. We predicted that children and adolescents would show similar dysfunction as adults, including pathological slow-wave oscillations and maladaptive, frequency-specific, alterations to neural connectivity. Using magnetoencephalography, we investigated regional oscillatory power and distributed brain-wide networks in a cross-sectional sample of children and adolescents in the chronic stages of mild traumatic brain injury. Additionally, we used a machine learning pipeline to identify the most relevant magnetoencephalography features for classifying mild traumatic brain injury and to test the relative classification performance of regional power versus functional coupling. Results revealed that the majority of participants with chronic mild traumatic brain injury reported persistent post-concussive symptoms. For neurophysiological imaging, we found increased regional power in the delta band in chronic mild traumatic brain injury, predominantly in bilateral occipital cortices and in the right inferior temporal gyrus. Those with chronic mild traumatic brain injury also showed dysregulated neuronal coupling, including decreased connectivity in the delta range, as well as hyper-connectivity in the theta, low gamma and high gamma bands, primarily involving frontal, temporal and occipital brain areas. Furthermore, our multivariate classification approach combined with functional connectivity data outperformed regional power in terms of between-group classification accuracy. For the first time, we establish that local and large-scale neural activity are altered in youth in the chronic phase of mild traumatic brain injury, with the majority presenting persistent post-concussive symptoms, and that dysregulated interregional neural communication is a reliable marker of lingering paediatric ‘mild’ traumatic brain injury.

Children with autism spectrum disorder show altered functional connectivity and abnormal maturation trajectories in response to inverted faces

The processing of information conveyed by faces is a critical component of social communication. While the neurophysiology of processing upright faces has been studied extensively in autism spectrum disorder (ASD), less is known about the neurophysiological abnormalities associated with processing inverted faces in ASD. We used magnetoencephalography (MEG) to study both long-range and local functional connectivity, with the latter assessed using local cross-frequency coupling, in response to inverted faces stimuli, in 7-18 years old individuals with ASD and age and IQ matched typically developing (TD) individuals. We found abnormally reduced coupling between the phase of the alpha rhythm and the amplitude of the gamma rhythm in the fusiform face area (FFA) in response to inverted faces, as well as reduced long-range functional connectivity between the FFA and the inferior frontal gyrus (IFG) in response to inverted faces in the ASD group. These group differences were absent in response to upright faces. The magnitude of functional connectivity between the FFA and the IFG was significantly correlated with the severity of ASD, and FFA-IFG long-range functional connectivity increased with age in TD group, but not in the ASD group. Our findings suggest that both local and long-range functional connectivity are abnormally reduced in children with ASD when processing inverted faces, and that the pattern of abnormalities associated with the processing of inverted faces differs from the pattern of upright faces in ASD, likely due to the presumed greater reliance on top-down regulations necessary for efficient processing of inverted faces. LAY SUMMARY: We found alterations in the neurophysiological responses to inverted faces in children with ASD, that were not reflected in the evoked responses, and were not observed in the responses to upright faces. These alterations included reduced local functional connectivity in the fusiform face area (FFA), and decreased long-range alpha-band modulated functional connectivity between the FFA and the left IFG. The magnitude of long-range functional connectivity between the FFA and the inferior frontal gyrus was correlated with the severity of ASD.

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.

Atypical Resting State Functional Neural Network in Children With Autism Spectrum Disorder: Graph Theory Approach

Measuring whole brain networks is a promising approach to extract features of autism spectrum disorder (ASD), a brain disorder of widespread regions. Objectives of this study were to evaluate properties of resting-state functional brain networks in children with and without ASD and to evaluate their relation with social impairment severity. Magnetoencephalographic (MEG) data were recorded for 21 children with ASD (7 girls, 60-89 months old) and for 25 typically developing (TD) control children (10 girls, 60-91 months old) in a resting state while gazing at a fixation cross. After signal sources were localized onto the Desikan-Killiany brain atlas, statistical relations between localized activities were found and evaluated in terms of the phase lag index. After brain networks were constructed and after matching with intelligence using a coarsened exact matching algorithm, ASD and TD graph theoretical measures were compared. We measured autism symptoms severity using the Social Responsiveness Scale and investigated its relation with altered small-worldness using linear regression models. Children with ASD were found to have significantly lower small-worldness in the beta band (p = 0.007) than TD children had. Lower small-worldness in the beta band of children with ASD was associated with higher Social Responsiveness Scale total t-scores (p = 0.047). Significant relations were also inferred for the Social Awareness (p = 0.008) and Social Cognition (p = 0.015) sub-scales. Results obtained using graph theory demonstrate a difference between children with and without ASD in MEG-derived resting-state functional brain networks, and the relation of that difference with social impairment. Combining graph theory and MEG might be a promising approach to establish a biological marker for ASD.

Classification of evoked responses to inverted faces reveals both spatial and temporal cortical response abnormalities in Autism spectrum disorder

The neurophysiology of face processing has been studied extensively in the context of social impairments associated with autism spectrum disorder (ASD), but the existing studies have concentrated mainly on univariate analyses of responses to upright faces, and, less frequently, inverted faces. The small number of existing studies on neurophysiological responses to inverted face in ASD have used univariate approaches, with divergent results. Here, we used a data-driven, classification-based, multivariate machine learning decoding approach to investigate the temporal and spatial properties of the neurophysiological evoked response for upright and inverted faces, relative to the neurophysiological evoked response for houses, a neutral stimulus. 21 (2 females) ASD and 29 (4 females) TD participants ages 7 to 19 took part in this study. Group level classification accuracies were obtained for each condition, using first the temporal domain of the evoked responses, and then the spatial distribution of the evoked responses on the cortical surface, each separately. We found that classification of responses to inverted neutral faces vs. houses was less accurate in ASD compared to TD, in both the temporal and spatial domains. In contrast, there were no group differences in the classification of evoked responses to upright neutral faces relative to houses. Using the classification in the temporal domain, lower decoding accuracies in ASD were found around 120 ms and 170 ms, corresponding the known components of the evoked responses to faces. Using the classification in the spatial domain, lower decoding accuracies in ASD were found in the right superior marginal gyrus (SMG), intra-parietal sulcus (IPS) and posterior superior temporal sulcus (pSTS), but not in core face processing areas. Importantly, individual classification accuracies from both the temporal and spatial classifiers correlated with ASD severity, confirming the relevance of the results to the ASD phenotype.

Emotional face processing across neurodevelopmental disorders: a dynamic faces study in children with autism spectrum disorder, attention deficit hyperactivity disorder and obsessive-compulsive disorder

Autism spectrum disorder (ASD) is classically associated with poor face processing skills, yet evidence suggests that those with obsessive-compulsive disorder (OCD) and attention deficit hyperactivity disorder (ADHD) also have difficulties understanding emotions. We determined the neural underpinnings of dynamic emotional face processing across these three clinical paediatric groups, including developmental trajectories, compared with typically developing (TD) controls. We studied 279 children, 5-19 years of age but 57 were excluded due to excessive motion in fMRI, leaving 222: 87 ASD, 44 ADHD, 42 OCD and 49 TD. Groups were sex- and age-matched. Dynamic faces (happy, angry) and dynamic flowers were presented in 18 pseudo-randomized blocks while fMRI data were collected with a 3T MRI. Group-by-age interactions and group difference contrasts were analysed for the faces vs. flowers and between happy and angry faces. TD children demonstrated different activity patterns across the four contrasts; these patterns were more limited and distinct for the NDDs. Processing happy and angry faces compared to flowers yielded similar activation in occipital regions in the NDDs compared to TDs. Processing happy compared to angry faces showed an age by group interaction in the superior frontal gyrus, increasing with age for ASD and OCD, decreasing for TDs. Children with ASD, ADHD and OCD differentiated less between dynamic faces and dynamic flowers, with most of the effects seen in the occipital and temporal regions, suggesting that emotional difficulties shared in NDDs may be partly attributed to shared atypical visual information processing.

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.

Attenuated long-range temporal correlations of electrocortical oscillations in patients with autism spectrum disorder

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The LRTCs of beta and low-gamma oscillations were significantly attenuated in ASD patients compared to TD participants.

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The regions with attenuated LRTCs were mainly located in certain social functions related cortical networks.

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ASD is associated with highly volatile neuronal states of electrocortical oscillations.

The aim of this study was to investigate the long-range temporal correlations (LRTCs) of instantaneous amplitude of electrocortical oscillations in patients with autism spectrum disorder (ASD). Using the resting-state electroencephalography (EEG) of 15 patients with ASD (aged between 5˜18 years, mean age = 11.6 years, SD = 4.4 years) and 18 typical developing (TD) people (aged between 5˜18 years, mean age = 8.9 years, SD = 2.4 years), we estimated the LRTCs of neuronal oscillations amplitude of 84 predefined cortical regions of interest using detrended fluctuation analysis (DFA) after confirming the presence of scale invariance. We found that the DFA exponents of instantaneous amplitude of beta and low-gamma oscillations were significantly attenuated in patients with ASD compared to TD participants. Moreover, the regions with attenuated DFA exponent were mainly located in social functions related cortical networks, including the default mode network (DMN), the mirror neuron system (MNS) and the salience network (SN). These findings suggest that ASD is associated with highly volatile neuronal states of electrocortical oscillations, which may be related to social and cognitive dysfunction in patients with 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.

Long-range functional coupling predicts performance: Oscillatory EEG networks in multisensory processing

The integration of sensory signals from different modalities requires flexible interaction of remote brain areas. One candidate mechanism to establish communication in the brain is transient synchronization of oscillatory neural signals. Although there is abundant evidence for the involvement of cortical oscillations in brain functions based on the analysis of local power, assessment of the phase dynamics among spatially distributed neuronal populations and their relevance for behavior is still sparse. In the present study, we investigated the interaction between remote brain areas by analyzing high-density electroencephalogram (EEG) data obtained from human participants engaged in a visuotactile pattern matching task. We deployed an approach for purely data-driven clustering of neuronal phase coupling in source space, which allowed imaging of large-scale functional networks in space, time and frequency without defining a priori constraints. Based on the phase coupling results, we further explored how brain areas interacted across frequencies by computing phase-amplitude coupling. Several networks of interacting sources were identified with our approach, synchronizing their activity within and across the theta (∼5 Hz), alpha (∼10 Hz), and beta (∼20 Hz) frequency bands and involving multiple brain areas that have previously been associated with attention and motor control. We demonstrate the functional relevance of these networks by showing that phase delays - in contrast to spectral power - were predictive of task performance. The data-driven analysis approach employed in the current study allowed an unbiased examination of functional brain networks based on EEG source level connectivity data. Showcased for multisensory processing, our results provide evidence that large-scale neuronal coupling is vital to long-range communication in the human brain and relevant for the behavioral outcome in a cognitive task.

Topological Properties of Resting-State fMRI Functional Networks Improve Machine Learning-Based Autism Classification

Automatic algorithms for disease diagnosis are being thoroughly researched for use in clinical settings. They usually rely on pre-identified biomarkers to highlight the existence of certain problems. However, finding such biomarkers for neurodevelopmental disorders such as Autism Spectrum Disorder (ASD) has challenged researchers for many years. With enough data and computational power, machine learning (ML) algorithms can be used to interpret the data and extract the best biomarkers from thousands of candidates. In this study, we used the fMRI data of 816 individuals enrolled in the Autism Brain Imaging Data Exchange (ABIDE) to introduce a new biomarker extraction pipeline for ASD that relies on the use of graph theoretical metrics of fMRI-based functional connectivity to inform a support vector machine (SVM). Furthermore, we split the dataset into 5 age groups to account for the effect of aging on functional connectivity. Our methodology achieved better results than most state-of-the-art investigations on this dataset with the best model for the >30 years age group achieving an accuracy, sensitivity, and specificity of 95, 97, and 95%, respectively. Our results suggest that measures of centrality provide the highest contribution to the classification power of the models.

Abnormal Alpha Rhythm During Self-Referential Processing in Schizophrenia Patients

Schizophrenia patients exhibited a psychological abnormal appearance when they recognized objects related to themselves. This cognitive process is associated with self-referential processing. In this study, the self-referential memory (SRM) task was performed by 18 schizophrenia patients and 18 healthy controls. In the encoding stage of the SRM task, the behavioral experiment data and electroencephalogram (EEG) data were recorded in three experimental conditions (self-referential condition, other-referential condition, and physical condition). For data analysis, the electrophysiological performance of the time-frequency distribution, phase lag index (PLI) strengths, phase synchronization connectivity, and brain-network properties were assessed in schizophrenia patients compared to healthy controls. We found that schizophrenia patients exhibited abnormal alpha oscillation characteristics at the time of 100-300 ms poststimulus during the self-referential condition, which consisted of diminished time-frequency distributions over the prefrontal, parietal, and occipital regions; lower functional connectivity strengths of the PLI in the parietal and occipital areas; higher global efficiency and the lower characteristic path length; and nodal efficiency of local areas (increased nodal efficiency in temporal regions and decreased nodal efficiency in occipital region) for dynamic network topology properties. Furthermore, the evoked power of the alpha band during the self-referential condition was significantly correlated with the SRM bias score in the patients (r = 0.595, p = 0.009). These results provided electrophysiological evidence and supported the hypothesis that an abnormal alpha rhythm might be the principal factor of dysfunctional self-referential processing in schizophrenia patients.

Increased Functional Connectivity During Emotional Face Processing in Children With Autism Spectrum Disorder

Individuals with autism spectrum disorder (ASD) demonstrate poor social functioning, which may be related to atypical emotional face processing. Altered functional connectivity among brain regions, particularly involving limbic structures may be implicated. The current magnetoencephalography (MEG) study investigated whole-brain functional connectivity of eight a priori identified brain regions during the implicit presentation of happy and angry faces in 20 7 to 10-year-old children with ASD and 22 typically developing controls. Findings revealed a network of increased alpha-band phase synchronization during the first 400 ms of happy face processing in children with ASD compared to controls. This network of increased alpha-band phase synchronization involved the left fusiform gyrus, right insula, and frontal regions critical for emotional face processing. In addition, greater connectivity strength of the left fusiform gyrus (maximal 85 to 208 ms) and right insula (maximal 73 to 270 ms) following happy face presentation in children with ASD compared to typically developing controls was found. These findings reflect altered neuronal communication in children with ASD only to happy faces during implicit emotional face processing.

Increased Functional Brain Network Efficiency During Audiovisual Temporal Asynchrony Integration Task in Aging

Audiovisual integration significantly changes over the lifespan, but age-related functional connectivity in audiovisual temporal asynchrony integration tasks remains underexplored. In the present study, electroencephalograms (EEGs) of 27 young adults (22–25 years) and 25 old adults (61–76 years) were recorded during an audiovisual temporal asynchrony integration task with seven conditions [auditory (A), visual (V), AV, A50V, A100V, V50A and V100A]. We calculated the phase lag index (PLI)-weighted connectivity networks modulated by the audiovisual tasks and found that the PLI connections showed obvious dynamic changes after stimulus onset. In the theta (4–7 Hz) and alpha (8–13 Hz) bands, the AV and V50A conditions induced stronger functional connections and higher global and local efficiencies, reflecting a stronger audiovisual integration effect, which was attributed to the auditory information arriving at the primary auditory cortex earlier than the visual information reaching the primary visual cortex. Importantly, the functional connectivity and network efficiencies of old adults revealed higher global and local efficiencies and higher degree in both the theta and alpha bands. These larger network efficiencies indicated that old adults might experience more difficulties in attention and cognitive control during the audiovisual integration task with temporal asynchrony than young adults. There were significant associations between network efficiencies and peak time of integration only in young adults. We propose that an audiovisual task with multiple conditions might arouse the appropriate attention in young adults but would lead to a ceiling effect in old adults. Our findings provide new insights into the network topography of old adults during audiovisual integration and highlight higher functional connectivity and network efficiencies due to greater cognitive demand.

Altered temporal stability in dynamic neural networks underlies connectivity changes in neurodevelopment

Network connectivity is an integral feature of human brain function, and characterising its maturational trajectory is a critical step towards understanding healthy and atypical neurodevelopment. Here, we used magnetoencephalography (MEG) to investigate both stationary (i.e. time averaged) and rapidly modulating (dynamic) electrophysiological connectivity, in participants aged from mid-childhood to early adulthood (youngest participant 9 years old; oldest participant 25 years old). Stationary functional connectivity (measured via inter-regional coordination of neural oscillations) increased with age in the alpha and beta frequency bands, particularly in bilateral parietal and temporo-parietal connections. Our dynamic analysis (also applied to alpha/beta oscillations) revealed the spatiotemporal signatures of 8 dynamic networks; these modulate on a ∼100 ms time scale, and temporal stability in attentional networks was found to increase with age. Significant overlap was found between age-modulated dynamic networks and inter-regional oscillatory coordination, implying that altered network dynamics underlie age related changes in functional connectivity. Our results provide novel insights into brain network electrophysiology, and lay a foundation for future work in childhood disorders.

Maturational trajectories of local and long-range functional connectivity in autism during face processing

Autism spectrum disorder (ASD) is characterized neurophysiologically by, among other things, functional connectivity abnormalities in the brain. Recent evidence suggests that the nature of these functional connectivity abnormalities might not be uniform throughout maturation. Comparing between adolescents and young adults (ages 14-21) with ASD and age- and IQ-matched typically developing (TD) individuals, we previously documented, using magnetoencephalography (MEG) data, that local functional connectivity in the fusiform face areas (FFA) and long-range functional connectivity between FFA and three higher order cortical areas were all reduced in ASD. Given the findings on abnormal maturation trajectories in ASD, we tested whether these results extend to preadolescent children (ages 7-13). We found that both local and long-range functional connectivity were in fact normal in this younger age group in ASD. Combining the two age groups, we found that local and long-range functional connectivity measures were positively correlated with age in TD, but negatively correlated with age in ASD. Last, we showed that local functional connectivity was the primary feature in predicting age in ASD group, but not in the TD group. Furthermore, local functional connectivity was only correlated with ASD severity in the older group. These results suggest that the direction of maturation of functional connectivity for processing of faces from childhood to young adulthood is itself abnormal in ASD, and that during the processing of faces, these trajectory abnormalities are more pronounced for local functional connectivity measures than they are for long-range functional connectivity measures.

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.

Neural Correlates of Explicit Versus Implicit Facial Emotion Processing in ASD

The underlying neural mechanisms of implicit and explicit facial emotion recognition (FER) were studied in children and adolescents with autism spectrum disorder (ASD) compared to matched typically developing controls (TDC). EEG was obtained from N = 21 ASD and N = 16 TDC. Task performance, visual (P100, N170) and cognitive (late positive potential) event-related-potentials, as well as coherence were compared across groups. TDC showed a task-dependent increase and a stronger lateralization of P100 amplitude during the explicit task and task-dependent modulation of intra-hemispheric coherence in the beta band. In contrast, the ASD group showed no task dependent modulation. Results indicate disruptions in early visual processing and top-down attentional processes as contributing factors to FER deficits in ASD.

Increased local connectivity of brain functional networks during facial processing in schizophrenia: evidence from EEG data

Schizophrenia is often considered to be a disconnection syndrome. The abnormal interactions between large-scale functional brain networks result in cognitive and perceptual deficits. The present study investigated event-related functional connectivity networks to compare facial processing in individuals with and without schizophrenia. Faces and tables were presented to participants, and event-related phase synchrony, represented by the phase lag index (PLI), was calculated. In addition, cortical oscillatory dynamics may be useful for understanding the neural mechanisms underlying the disparate cognitive and functional impairments in schizophrenic patients. Therefore, the dynamic graph theoretical networks related to facial processing were compared between individuals with and without schizophrenia. Our results showed that event-related phase synchrony was significantly reduced in distributed networks, and normalized clustering coefficients were significantly increased in schizophrenic patients relative to those of the controls. The present data suggest that schizophrenic patients have specific alterations, indicated by increased local connectivity in gamma oscillations during facial processing.

Is functional brain connectivity atypical in autism? A systematic review of EEG and MEG studies

BACKGROUND

Although it is well recognized that autism is associated with altered patterns of over- and under-connectivity, specifics are still a matter of debate. Little has been done so far to synthesize available literature using whole-brain electroencephalography (EEG) and magnetoencephalography (MEG) recordings.

OBJECTIVES

1) To systematically review the literature on EEG/MEG functional and effective connectivity in autism spectrum disorder (ASD), 2) to synthesize and critically appraise findings related with the hypothesis that ASD is characterized by long-range underconnectivity and local overconnectivity, and 3) to provide, based on the literature, an analysis of tentative factors that are likely to mediate association between ASD and atypical connectivity (e.g., development, topography, lateralization).

METHODS

Literature reviews were done using PubMed and PsychInfo databases. Abstracts were screened, and only relevant articles were analyzed based on the objectives of this paper. Special attention was paid to the methodological characteristics that could have created variability in outcomes reported between studies.

RESULTS

Our synthesis provides relatively strong support for long-range underconnectivity in ASD, whereas the status of local connectivity remains unclear. This observation was also mirrored by a similar relationship with lower frequencies being often associated with underconnectivity and higher frequencies being associated with both under- and over-connectivity. Putting together these observations, we propose that ASD is characterized by a general trend toward an under-expression of lower-band wide-spread integrative processes compensated by more focal, higher-frequency, locally specialized, and segregated processes. Further investigation is, however, needed to corroborate the conclusion and its generalizability across different tasks. Of note, abnormal lateralization in ASD, specifically an elevated left-over-right EEG and MEG functional connectivity ratio, has been also reported consistently across studies.

CONCLUSIONS

The large variability in study samples and methodology makes a systematic quantitative analysis (i.e. meta-analysis) of this body of research impossible. Nevertheless, a general trend supporting the hypothesis of long-range functional underconnectivity can be observed. Further research is necessary to more confidently determine the status of the hypothesis of short-range overconnectivity. Frequency-band specific patterns and their relationships with known symptoms of autism also need to be further clarified.

Disconnection from others in autism is more than just a feeling: whole-brain neural synchrony in adults during implicit processing of emotional faces

Background

Socio-emotional difficulties in autism spectrum disorder (ASD) are thought to reflect impaired functional connectivity within the “social brain”. Nonetheless, a whole-brain characterization of the fast responses in functional connectivity during implicit processing of emotional faces in adults with ASD is lacking.

Methods

The present study used magnetoencephalography to investigate early responses in functional connectivity, as measured by interregional phase synchronization, during implicit processing of angry, neutral and happy faces. The sample (n = 44) consisted of 22 young adults with ASD and 22 age- and sex-matched typically developed (TD) controls.

Results

Reduced phase-synchrony in the beta band around 300 ms emerged during processing of angry faces in the ASD compared to TD group, involving key areas of the social brain. In the same time window, de-synchronization in the beta band in the amygdala was reduced in the ASD group across conditions.

Conclusions

This is the first demonstration of atypical global and local synchrony patterns in the social brain in adults with ASD during implicit processing of emotional faces. The present results replicate and substantially extend previous findings on adolescents, highlighting that atypical brain synchrony during processing of socio-emotional stimuli is a hallmark of clinical sequelae in autism.

Electronic supplementary material

The online version of this article (doi:10.1186/s13229-017-0123-2) contains supplementary material, which is available to authorized users.

The Functional Role of Neural Oscillations in Non-Verbal Emotional Communication

Effective interpersonal communication depends on the ability to perceive and interpret nonverbal emotional expressions from multiple sensory modalities. Current theoretical models propose that visual and auditory emotion perception involves a network of brain regions including the primary sensory cortices, the superior temporal sulcus (STS), and orbitofrontal cortex (OFC). However, relatively little is known about how the dynamic interplay between these regions gives rise to the perception of emotions. In recent years, there has been increasing recognition of the importance of neural oscillations in mediating neural communication within and between functional neural networks. Here we review studies investigating changes in oscillatory activity during the perception of visual, auditory, and audiovisual emotional expressions, and aim to characterize the functional role of neural oscillations in nonverbal emotion perception. Findings from the reviewed literature suggest that theta band oscillations most consistently differentiate between emotional and neutral expressions. While early theta synchronization appears to reflect the initial encoding of emotionally salient sensory information, later fronto-central theta synchronization may reflect the further integration of sensory information with internal representations. Additionally, gamma synchronization reflects facilitated sensory binding of emotional expressions within regions such as the OFC, STS, and, potentially, the amygdala. However, the evidence is more ambiguous when it comes to the role of oscillations within the alpha and beta frequencies, which vary as a function of modality (or modalities), presence or absence of predictive information, and attentional or task demands. Thus, the synchronization of neural oscillations within specific frequency bands mediates the rapid detection, integration, and evaluation of emotional expressions. Moreover, the functional coupling of oscillatory activity across multiples frequency bands supports a predictive coding model of multisensory emotion perception in which emotional facial and body expressions facilitate the processing of emotional vocalizations.

Perceptual Integration Deficits in Autism Spectrum Disorders Are Associated with Reduced Interhemispheric Gamma-Band Coherence

The integration of visual details into a holistic percept is essential for object recognition. This integration has been reported as a key deficit in patients with autism spectrum disorders (ASDs). The weak central coherence account posits an altered disposition to integrate features into a coherent whole in ASD. Here, we test the hypothesis that such weak perceptual coherence may be reflected in weak neural coherence across different cortical sites. We recorded magnetoencephalography from 20 adult human participants with ASD and 20 matched controls, who performed a slit-viewing paradigm, in which objects gradually passed behind a vertical or horizontal slit so that only fragments of the object were visible at any given moment. Object recognition thus required perceptual integration over time and, in case of the horizontal slit, also across visual hemifields. ASD participants were selectively impaired in the horizontal slit condition, indicating specific difficulties in long-range synchronization between the hemispheres. Specifically, the ASD group failed to show condition-related enhancement of imaginary coherence between the posterior superior temporal sulci in both hemispheres during horizontal slit-viewing in contrast to controls. Moreover, local synchronization reflected in occipitocerebellar beta-band power was selectively reduced for horizontal compared with vertical slit-viewing in ASD. Furthermore, we found disturbed connectivity between right posterior superior temporal sulcus and left cerebellum. Together, our results suggest that perceptual integration deficits co-occur with specific patterns of abnormal global and local synchronization in ASD.

SIGNIFICANCE STATEMENT

The weak central coherence account proposes a tendency of individuals with autism spectrum disorders (ASDs) to focus on details at the cost of an integrated coherent whole. Here, we provide evidence, at the behavioral and the neural level, that visual integration in object recognition is impaired in ASD, when details had to be integrated across both visual hemifields. We found enhanced interhemispheric gamma-band coherence in typically developed participants when communication between cortical hemispheres was required by the task. Importantly, participants with ASD failed to show this enhanced coherence between bilateral posterior superior temporal sulci. The findings suggest that visual integration is disturbed at the local and global synchronization scale, which might bear implications for object recognition in ASD.

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.

Characterising intra- and inter-intrinsic network synchrony in combat-related post-traumatic stress disorder

Soldiers with post-traumatic stress disorder (PTSD) exhibit elevated gamma-band synchrony in left fronto-temporal cortex, and connectivity measures in these regions correlate with comorbidities and PTSD severity, which suggests increased gamma synchrony is related to symptomology. However, little is known about the role of intrinsic, phase-synchronised networks in the disorder. Using magnetoencephalography (MEG), we characterised spectral connectivity in the default-mode, salience, visual, and attention networks during resting-state in a PTSD population and a trauma-exposed control group. Intrinsic network connectivity was examined in canonical frequency bands. We observed increased inter-network synchronisation in the PTSD group compared with controls in the gamma (30-80 Hz) and high-gamma range (80-150 Hz). Analyses of connectivity and symptomology revealed that PTSD severity was positively associated with beta synchrony in the ventral-attention-to-salience networks, and gamma synchrony within the salience network, but also negatively correlated with beta synchrony within the visual network. These novel results show that frequency-specific, network-level atypicalities may reflect trauma-related alterations of ongoing functional connectivity, and correlations of beta synchrony in attentional-to-salience and visual networks with PTSD severity suggest complicated network interactions mediate symptoms. These results contribute to accumulating evidence that PTSD is a complicated network-based disorder expressed as altered neural interactions.

Desynchronization of fronto-temporal networks during working memory processing in autism

BACKGROUND

Mounting evidence suggests that autism is a network disorder, characterized by atypical brain connectivity, especially in the context of high level cognitive processes such as working memory (WM). Accordingly, atypical WM processes have been related to the social and cognitive deficits observed in children with autism spectrum disorder (ASD).

METHODS

We used magnetoencephalography (MEG) to investigate connectivity differences during a high memory load (2-back) WM task between 17 children with ASD and 20 age-, sex-, and IQ-matched controls.

RESULTS

We identified reduced inter-regional alpha-band (9-15 Hz) phase synchronization in children with ASD during the WM task. Reduced WM-related brain synchronization encompassed fronto-temporal networks (ps < 0.04 corrected) previously associated with challenging high-level conditions (i.e. the left insula and the anterior cingulate cortex (ACC)) and memory encoding and/or recognition (i.e. the right middle temporal gyrus and the right fusiform gyrus). Additionally, we found that reduced connectivity processes related to the right fusiform were correlated with the severity of symptoms in children with ASD, suggesting that such atypicalities could be directly related to the behavioural deficits observed.

DISCUSSION

This study provides new evidence of atypical long-range synchronization in children with ASD in fronto-temporal areas that crucially contribute to challenging WM tasks, but also emotion regulation and social cognition processes. Thus, these results support the network disorder hypothesis of ASD and argue for a specific pathophysiological contribution of brain processes related to working memory and executive functions on the symptomatology of autism.

Development of Network Synchronization Predicts Language Abilities

Synchronization of oscillations among brain areas is understood to mediate network communication supporting cognition, perception, and language. How task-dependent synchronization during word production develops throughout childhood and adolescence, as well as how such network coherence is related to the development of language abilities, remains poorly understood. To address this, we recorded magnetoencephalography while 73 participants aged 4-18 years performed a verb generation task. Atlas-guided source reconstruction was performed, and phase synchronization among regions was calculated. Task-dependent increases in synchronization were observed in the theta, alpha, and beta frequency ranges, and network synchronization differences were observed between age groups. Task-dependent synchronization was strongest in the theta band, as were differences between age groups. Network topologies were calculated for brain regions associated with verb generation and were significantly associated with both age and language abilities. These findings establish the maturational trajectory of network synchronization underlying expressive language abilities throughout childhood and adolescence and provide the first evidence for an association between large-scale neurophysiological network synchronization and individual differences in the development of language abilities.

Schizophrenia Related Variants in CACNA1C also Confer Risk of Autism

Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders with a strong genetic component. Many lines of evidence indicated that ASD shares common genetic variants with other psychiatric disorders (for example, schizophrenia). Previous studies detected that calcium channels are involved in the etiology of many psychiatric disorders including schizophrenia and autism. Significant association between CACNA1C (calcium channel, voltage-dependent, L type, alpha 1C subunit) and schizophrenia was detected. Furthermore, rare mutation in CACNA1C is suggested to cause Timothy syndrome, a multisystem disorder including autism-associated phenotype. However, there is no evidence for association between CACNA1C and autism in Chinese Han population. To investigate the association between single nucleotide polymorphisms (SNP) in CACNA1C and autism, we first performed a family-based association study between eighteen SNPs in CACNA1C and autism in 239 trios. All SNPs were genotyped by using Sequenom genotyping platform. Two SNPs (rs1006737 and rs4765905) have a trend of association with autism. To further confirm the association between these two SNPs with autism, we expanded the sample size to 553 trios by adding 314 trios. Association analyses for SNPs and haplotype were performed by using family-based association test (FBAT) and Haploview software. Permutation tests were used for multiple testing corrections of the haplotype analyses (n=10,000). The significance level for all statistical tests was two-tailed (p<0.05). The results demonstrated that G allele of rs1006737 and G allele of rs4765905 showed a preferential transmission to affected offspring in 553 trios (p=0.035). Haplotype analyses showed that two haplotypes constructed from rs1006737 and rs4765905 were significantly associated with autism (p=0.030, 0.023, respectively; Global p=0.046). These results were still significant after permutation correction (n=10,000, p=0.027). Our research suggests that CACNA1C might play a role in the genetic etiology of autism in Chinese Han population.