Patterns of altered neural synchrony in the default mode network in autism spectrum disorder revealed with magnetoencephalography (MEG): Relationship to clinical symptomatology

Correlation between autistic traits and brain functional connectivity in preschoolers with autism spectrum disorder: a resting state MEG study

BACKGROUND

Neurophysiological studies recognized that Autism Spectrum Disorder (ASD) is associated with altered patterns of over- and under-connectivity. However, little is known about network organization in children with ASD in the early phases of development and its correlation with the severity of core autistic features.

METHODS

The present study aimed at investigating the association between brain connectivity derived from MEG signals and severity of ASD traits measured with different diagnostic clinical scales, in a sample of 16 children with ASD aged 2 to 6 years.

RESULTS

A significant correlation emerged between connectivity strength in cortical brain areas implicated in several resting state networks (Default mode, Central executive, Salience, Visual and Sensorimotor) and the severity of communication anomalies, social interaction problems, social affect problems, and repetitive behaviors. Seed analysis revealed that this pattern of correlation was mainly caused by global rather than local effects.

CONCLUSIONS

The present evidence suggests that altered connectivity strength in several resting state networks is related to clinical features and may contribute to neurofunctional correlates of ASD. Future studies implementing the same method on a wider and stratified sample may further support functional connectivity as a possible biomarker of the condition.

EEG During Dynamic Facial Emotion Processing Reveals Neural Activity Patterns Associated with Autistic Traits in Children

Altered brain connectivity and atypical neural oscillations have been observed in autism, yet their relationship with autistic traits in non-clinical populations remains underexplored. Here, we employ electroencephalography (EEG) to examine functional connectivity, oscillatory power, and broadband aperiodic activity during a dynamic facial emotion processing (FEP) task in 101 typically developing children aged 4-12 years. We investigate associations between these electrophysiological measures of brain dynamics and autistic traits as assessed by the Social Responsiveness Scale, 2nd Edition (SRS-2). Our results revealed that increased FEP-related connectivity across theta (4-7 Hz) and beta (13-30 Hz) frequencies correlated positively with higher SRS-2 scores, predominantly in right-lateralized (theta) and bilateral (beta) cortical networks. Additionally, a steeper 1/f-like aperiodic slope (spectral exponent) across fronto-central electrodes was associated with higher SRS-2 scores. Greater aperiodic-adjusted theta and alpha oscillatory power further correlated with both higher SRS-2 scores and steeper aperiodic slopes. These findings underscore important links between FEP-related brain dynamics and autistic traits in typically developing children. Future work could extend these findings to assess these EEG-derived markers as potential mechanisms underlying behavioural difficulties in autism.

Effects of transcranial direct current stimulation on brain activity and cortical functional connectivity in children with autism spectrum disorders

Introduction

Transcranial direct current stimulation (tDCS) has emerged as a therapeutic option to mitigate symptoms in individuals with autism spectrum disorder (ASD). Our study investigated the effects of a two-week regimen of tDCS targeting the left dorsolateral prefrontal cortex (DLPFC) in children with ASD, examining changes in rhythmic brain activity and alterations in functional connectivity within key neural networks: the default mode network (DMN), sensorimotor network (SMN), and dorsal attention network (DAN).

Methods

We enrolled twenty-six children with ASD and assigned them randomly to either an active stimulation group (n=13) or a sham stimulation group (n=13). The active group received tDCS at an intensity of 1mA to the left DLPFC for a combined duration of 10 days. Differences in electrical brain activity were pinpointed using standardized low-resolution brain electromagnetic tomography (sLORETA), while functional connectivity was assessed via lagged phase synchronization.

Results

Compared to the typically developing children, children with ASD exhibited lower current source density across all frequency bands. Post-treatment, the active stimulation group demonstrated a significant increase in both current source density and resting state network connectivity. Such changes were not observed in the sham stimulation group.

Conclusion

tDCS targeting the DLPFC may bolster brain functional connectivity in patients with ASD, offering a substantive groundwork for potential clinical applications.

Atypical cortical networks in children at high-genetic risk of psychiatric and neurodevelopmental disorders

Although many genetic risk factors for psychiatric and neurodevelopmental disorders have been identified, the neurobiological route from genetic risk to neuropsychiatric outcome remains unclear. 22q11.2 deletion syndrome (22q11.2DS) is a copy number variant (CNV) syndrome associated with high rates of neurodevelopmental and psychiatric disorders including autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD) and schizophrenia. Alterations in neural integration and cortical connectivity have been linked to the spectrum of neuropsychiatric disorders seen in 22q11.2DS and may be a mechanism by which the CNV acts to increase risk. In this study, magnetoencephalography (MEG) was used to investigate electrophysiological markers of local and global network function in 34 children with 22q11.2DS and 25 controls aged 10-17 years old. Resting-state oscillatory activity and functional connectivity across six frequency bands were compared between groups. Regression analyses were used to explore the relationships between these measures, neurodevelopmental symptoms and IQ. Children with 22q11.2DS had altered network activity and connectivity in high and low frequency bands, reflecting modified local and long-range cortical circuitry. Alpha and theta band connectivity were negatively associated with ASD symptoms while frontal high frequency (gamma band) activity was positively associated with ASD symptoms. Alpha band activity was positively associated with cognitive ability. These findings suggest that haploinsufficiency at the 22q11.2 locus impacts short and long-range cortical circuits, which could be a mechanism underlying neurodevelopmental and psychiatric vulnerability in this high-risk group.

EEG resting-state functional connectivity: evidence for an imbalance of external/internal information integration in autism

Background

Autism spectrum disorder (ASD) is associated with atypical neural activity in resting state. Most of the studies have focused on abnormalities in alpha frequency as a marker of ASD dysfunctions. However, few have explored alpha synchronization within a specific interest in resting-state networks, namely the default mode network (DMN), the sensorimotor network (SMN), and the dorsal attention network (DAN). These functional connectivity analyses provide relevant insight into the neurophysiological correlates of multimodal integration in ASD.

Methods

Using high temporal resolution EEG, the present study investigates the functional connectivity in the alpha band within and between the DMN, SMN, and the DAN. We examined eyes-closed EEG alpha lagged phase synchronization, using standardized low-resolution brain electromagnetic tomography (sLORETA) in 29 participants with ASD and 38 developing (TD) controls (age, sex, and IQ matched).

Results

We observed reduced functional connectivity in the ASD group relative to TD controls, within and between the DMN, the SMN, and the DAN. We identified three hubs of dysconnectivity in ASD: the posterior cingulate cortex, the precuneus, and the medial frontal gyrus. These three regions also presented decreased current source density in the alpha band.

Conclusion

These results shed light on possible multimodal integration impairments affecting the communication between bottom-up and top-down information. The observed hypoconnectivity between the DMN, SMN, and DAN could also be related to difficulties in switching between externally oriented attention and internally oriented thoughts.

Supplementary Information

The online version contains supplementary material available at 10.1186/s11689-022-09456-8.

A Brief Introduction to Magnetoencephalography (MEG) and Its Clinical Applications

Magnetoencephalography (MEG) plays a pivotal role in the diagnosis of brain disorders. In this review, we have investigated potential MEG applications for analysing brain disorders. The signal-to-noise ratio (SNRMEG = 2.2 db, SNREEG < 1 db) and spatial resolution (SRMEG = 2−3 mm, SREEG = 7−10 mm) is higher for MEG than EEG, thus MEG potentially facilitates accurate monitoring of cortical activity. We found that the direct electrophysiological MEG signals reflected the physiological status of neurological disorders and play a vital role in disease diagnosis. Single-channel connectivity, as well as brain network analysis, using MEG data acquired during resting state and a given task has been used for the diagnosis of neurological disorders such as epilepsy, Alzheimer’s, Parkinsonism, autism, and schizophrenia. The workflow of MEG and its potential applications in the diagnosis of disease and therapeutic planning are also discussed. We forecast that computer-aided algorithms will play a prominent role in the diagnosis and prediction of neurological diseases in the future. The outcome of this narrative review will aid researchers to utilise MEG in diagnostics.

Altered Periodic Dynamics in the Default Mode Network in Autism and Attention-Deficit/Hyperactivity Disorder

BACKGROUND

Altered resting-state functional connectivity in the default mode network (DMN) is characteristic of both autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD). Standard analytical pipelines for resting-state functional connectivity focus on linear correlations in activation time courses between neural networks or regions of interest. These features may be insensitive to temporally lagged or nonlinear relationships.

METHODS

In a twin cohort study comprising 292 children, including 52 with a diagnosis of ASD and 70 with a diagnosis of ADHD, we applied nonlinear analytical methods to characterize periodic dynamics in the DMN. Using recurrence quantification analysis and related methods, we measured the prevalence, duration, and complexity of periodic processes within and between DMN regions of interest. We constructed generalized estimating equations to compare these features between neurotypical children and children with ASD and/or ADHD while controlling for familial relationships, and we leveraged machine learning algorithms to construct models predictive of ASD or ADHD diagnosis.

RESULTS

In within-pair analyses of twins with discordant ASD diagnoses, we found that DMN signal dynamics were significantly different in dizygotic twins but not in monozygotic twins. Considering our full sample, we found that these patterns allowed a robust predictive classification of both ASD (81.0% accuracy; area under the curve = 0.85) and ADHD (82% accuracy; area under the curve = 0.87) cases.

CONCLUSIONS

These findings indicate that synchronized periodicity among regions comprising the DMN relates both to neurotypical function and to ASD and/or ADHD, and they suggest generally that a dynamical analysis of network interconnectivity may be a useful methodology for future neuroimaging studies.

Imbalanced Gamma-band Functional Brain Networks of Autism Spectrum Disorders

Resting gamma-band brain networks are known as an inhibitory component in functional brain networks. Although autism spectrum disorder (ASD) is considered as with imbalanced brain networks, the inhibitory component remains not fully explored. The study reported 10 children with ASD and 10 typically-developing (TD) controls. The power spectral density analysis of the gamma-band signal in the cerebral cortex was performed at the source level. The normalized phase transfer entropy values (nPTEs) were calculated to construct brain connectivity. Gamma-band activity of the ASD group was lower than the TD children. The significantly inhibited brain regions were mainly distributed in the bilateral frontal and temporal lobes. Connectivity analysis showed alterations in the connections from key nodes of the social brain network. The behavior assessments in the ASD group revealed a significantly positive correlation between the total score of Childhood Autism Rating Scale and the regional nPTEs of the right transverse temporal gyrus. Our results provide strong evidence that the gamma-band brain networks of ASD children have a lower level of brain activities and different distribution of information flows. Clinical meanings of such imbalances of both activity and connectivity were also worthy of further explorations.

Alterations of Regional Homogeneity in Preschool Boys With Autism Spectrum Disorders

Objectives

The study was aimed at investigating the alterations of local spontaneous brain activity in preschool boys with autism spectrum disorders (ASD).

Methods

Based on regional homogeneity (ReHo), the acquired resting state functional magnetic resonance imaging (fMRI) data sets, which included 86 boys with ASD and 54 typically developing (TD) boys, were used to detect regional brain activity. Pearson correlation analysis was used to study the relationship between abnormal ReHo value and the Childhood Autism Rating Scale (CARS), Autism Behavior Checklist (ABC), developmental quotient, and age.

Results

In the ASD group, we found increased ReHo in the right calcarine as well as decreased ReHo in the opercular part of the left inferior frontal gyrus, the left middle temporal gyrus, the left angular gyrus, and the right medial orbital frontal cortex (p < 0.05, false discovery rate correction). We did not find a correlation between the results of brain regions and the CARS, ABC, and age.

Conclusions

Our study found spontaneous activity changes in multiple brain regions, especially the visual and language-related areas of ASD, that may help to further understand the clinical characteristics of boys with ASD.

Predictive Processing during a Naturalistic Statistical Learning Task in ASD

Children's sensitivity to regularities within the linguistic stream, such as the likelihood that syllables co-occur, is foundational to speech segmentation and language acquisition. Yet, little is known about the neurocognitive mechanisms underlying speech segmentation in typical development and in neurodevelopmental disorders that impact language acquisition such as autism spectrum disorder (ASD). Here, we investigate the neural signals of statistical learning in 15 human participants (children ages 8-12) with a clinical diagnosis of ASD and 14 age-matched and gender-matched typically developing peers. We tracked the evoked neural responses to syllable sequences in a naturalistic statistical learning corpus using magnetoencephalography (MEG) in the left primary auditory cortex, posterior superior temporal gyrus (pSTG), and inferior frontal gyrus (IFG), across three repetitions of the passage. In typically developing children, we observed a neural index of learning in all three regions of interest (ROIs), measured by the change in evoked response amplitude as a function of syllable surprisal across passage repetitions. As surprisal increased, the amplitude of the neural response increased; this sensitivity emerged after repeated exposure to the corpus. Children with ASD did not show this pattern of learning in all three regions. We discuss two possible hypotheses related to children's sensitivity to bottom-up sensory deficits and difficulty with top-down incremental processing.

Continued development of auditory ability in autism spectrum disorder children: A clinical study on click-evoked auditory brainstem response

OBJECTIVES

The study aimed to analyze the developmental mode of auditory at the level of brainstem in preschool autistic children using click-evoked auditory brainstem response (click-ABR).

METHODS

Twenty children with autism spectrum disorder (ASD) and 20 age matched typical development children (TD) were recruited. The detail data recorded from click-ABR were collected at two time periods (T1 and T2).

RESULTS

There was no significant change in TD group at two time periods. In ASD group, wave V latency was significantly shortened at T2 compared to that recorded at T1. The interpeak latency of I-V was short at T2 versus at T1 in the autistic children. Compared to the TD group, ASD was associated with longer latencies for waves V and longer interpeak latencies of I-III, I-V at T1. In addition, ASD group also indicated longer latencies of wave III and wave V, longer interpeak latencies of I-III and I-V at T2 compared to the TD group.

CONCLUSIONS

ASD group had immature and dysfunction developmental mode in auditory stimuli perception at the level of brainstem. The performance of auditory ability in children with ASD improved gradually with ages. However, there are still differences compared with TD children.

Prospects for Future Methodological Development and Application of Magnetoencephalography Devices in Psychiatry

Magnetoencephalography (MEG) is a functional neuroimaging tool that can record activity from the entire cortex on the order of milliseconds. MEG has been used to investigate numerous psychiatric disorders, such as schizophrenia, bipolar disorder, major depression, dementia, and autism spectrum disorder. Although several review papers on the subject have been published, perspectives and opinions regarding the use of MEG in psychiatric research have primarily been discussed from a psychiatric research point of view. Owing to a newly developed MEG sensor, the use of MEG devices will soon enter a critical period, and now is a good time to discuss the future of MEG use in psychiatric research. In this paper, we will discuss MEG devices from a methodological point of view. We will first introduce the utilization of MEG in psychiatric research and the development of its technology. Then, we will describe the principle theory of MEG and common algorithms, which are useful for applying MEG tools to psychiatric research. Next, we will consider three topics-child psychiatry, resting-state networks, and cortico-subcortical networks-and address the future use of MEG in psychiatry from a broader perspective. Finally, we will introduce the newly developed device, the optically-pumped magnetometer, and discuss its future use in MEG systems in psychiatric research from a methodological point of view. We believe that state-of-the-art electrophysiological tools, such as this new MEG system, will further contribute to our understanding of the core pathology in various psychiatric disorders and translational research.

Excitation-inhibition balance as a framework for investigating mechanisms in neuropsychiatric disorders

In 2003 Rubenstein and Merzenich hypothesized that some forms of Autism (ASD) might be caused by a reduction in signal-to-noise in key neural circuits, which could be the result of changes in excitatory-inhibitory (E-I) balance. Here, we have clarified the concept of E-I balance, and updated the original hypothesis in light of the field's increasingly sophisticated understanding of neuronal circuits. We discuss how specific developmental mechanisms, which reduce inhibition, affect cortical and hippocampal functions. After describing how mutations of some ASD genes disrupt inhibition in mice, we close by suggesting that E-I balance represents an organizing framework for understanding findings related to pathophysiology and for identifying appropriate treatments.

Developmental Effects on Auditory Neural Oscillatory Synchronization Abnormalities in Autism Spectrum Disorder

Previous studies have found alterations in 40 Hz oscillatory activity in response to auditory stimuli in adults with Autism Spectrum Disorder (ASD). The current study sought to examine the specificity and developmental trajectory of these findings by driving the cortex to oscillate at a range of frequencies in both children and adults with and without ASD. Fifteen participants with ASD (3 female, aged 6–23 years) and 15 age-matched controls (4 female, aged 6–25 years) underwent dense-array EEG as they listened to a carrier tone amplitude-modulated by a sinusoid linearly increasing in frequency from 0–100 Hz over 2 s. EEG data were analyzed for inter-trial phase coherence (ITPC) and single-trial power (STP). Older participants with ASD displayed significantly decreased ability to phase-lock to the stimulus in the low gamma frequency range relative to their typically developing (TD) counterparts, while younger ASD and TD did not significantly differ from each other. An interaction between age and diagnosis suggested that TD and ASD also show different developmental trajectories for low gamma power; TD showed a significant decrease in low gamma power with age, while ASD did not. Regardless of age, increased low gamma STP was significantly correlated with increased clinical scores for repetitive behaviors in the ASD group, particularly insistence on sameness. This study contributes to a growing body of evidence supporting alterations in auditory processing in ASD. Older ASD participants showed more pronounced low gamma deficits than younger participants, suggesting an altered developmental trajectory for neural activity contributing to auditory processing deficits that may also be more broadly clinically relevant. Future studies are needed employing a longitudinal approach to confirm findings of this cross-sectional study.

Chronic Early Stress Impairs Default Mode Network Connectivity in Preadolescents and Their Mothers

BACKGROUND

Early life stress (ELS) bears long-term negative consequences throughout life. Yet ELS effect is mostly unknown, and no study has followed children to test its impact on the default mode network (DMN) in relation to maternal behavior across childhood. Focusing on brain oscillations, we utilized a unique cohort of war-exposed preadolescent children (11-13 years of age) and their mothers followed from early childhood to examine the effects of ELS combined with observed parenting on DMN connectivity and power in mother and child.

METHODS

Participants included 161 mothers and children (children: 39 exposed/36 control subjects; mothers: 44 exposed/42 control subjects) who underwent magnetoencephalography scanning during rest.

RESULTS

Stress exposure reduced DMN connectivity in mother and child; however, in mothers, the impaired connectivity occurred in the alpha band, whereas among children it occurred in the theta band, a biomarker of the developing brain. Maternal anxiety, depression, and posttraumatic symptoms in early childhood predicted lower maternal DMN connectivity. Among children, the experience of intrusive, anxious, and uncontained parenting across the first decade and greater cortisol production in late childhood predicted reduced DMN connectivity in preadolescence. Impairments to theta DMN connectivity increased in children with posttraumatic stress disorder.

CONCLUSIONS

Findings indicate that ELS disrupts the synchronous coordination of distinct brain areas into coherent functioning of the DMN network, a core network implicated in self-relevant processes. Results suggest that one pathway for the lifelong effects of ELS on psychopathology and physical illness relate to impaired coherence of the DMN and its role in maintaining quiescence, alternating internal and external attention, and supporting the sense of self.