Brief Report: Reduced Temporal-Central EEG Alpha Coherence During Joint Attention Perception in Adolescents with Autism Spectrum Disorder

Multimodal Kernel-based discriminant correlation analysis data-fusion approach: an automated autism spectrum disorder diagnostic system

Autism spectrum disorder (ASD) diagnostic systems, based on association of multimodal tools such as combination of Electroencephalogram (EEG) and eye-tracking, have emerged as an analytical to provide objective biomarkers. However, the existing feature-redundancy-based systems have lacked in providing knowledge of fusion approaches and robust feature-set. The present paper aims to reduce disorder homogeneity by proposing a multimodal diagnostic system which can incorporate multimodal data. The paper has collected simultaneous-data from three modalities (laptop-performance tool, EEG machine, and Eye-tracker) fused the recorded computational, neural and visual data. The multimodal features are analyzed via proposed multimodal Kernel-based discriminant correlation analysis (MKDCA) fusion approach and classified using state-of-the-art machine-learning classifiers. The proposed framework has considered the distinct cardinality of the feature vectors and fused the group structure among multiple samples after ranking them in increasing order. As per the results, the proposed multimodal system provided fused feature set of 11 influential features out of total 39 features. The SVM classifier has diagnosed ASD with 92% testing accuracy and 0.988 AUC(ROC). The proposed automated fusion-based system has the potential to classify disorder by reducing the disorder heterogeneity and stratifying ASD individuals into homogeneous sub-groups. In future, the correlation of reduced feature set with ASD clinical symptoms accounted by screening scales can provide clinical relevance of proposed model.

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.

Comparison of comprehensive quantitative EEG metrics between typically developing boys and girls in resting state eyes-open and eyes-closed conditions

Introduction

A majority of published studies comparing quantitative EEG (qEEG) in typically developing (TD) children and children with neurodevelopmental or psychiatric disorders have used a control group (e.g., TD children) that combines boys and girls. This suggests a widespread supposition that typically developing boys and girls have similar brain activity at all locations and frequencies, allowing the data from TD boys and girls to be aggregated in a single group.

Methods

In this study, we have rigorously challenged this assumption by performing a comprehensive qEEG analysis on EEG recoding of TD boys (n = 84) and girls (n = 62), during resting state eyes-open and eyes-closed conditions (EEG recordings from Child Mind Institute's Healthy Brain Network (HBN) initiative). Our qEEG analysis was performed over narrow-band frequencies (e.g., separating low α from high α, etc.), included sex, age, and head size as covariates in the analysis, and encompassed computation of a wide range of qEEG metrics that included both absolute and relative spectral power levels, regional hemispheric asymmetry, and inter- and intra-hemispheric magnitude coherences as well as phase coherency among cortical regions. We have also introduced a novel compact yet comprehensive visual presentation of the results that allows comparison of the qEEG metrics of boys and girls for the entire EEG locations, pairs, and frequencies in a single graph.

Results

Our results show there are wide-spread EEG locations and frequencies where TD boys and girls exhibit differences in their absolute and relative spectral powers, hemispheric power asymmetry, and magnitude coherence and phase synchrony.

Discussion

These findings strongly support the necessity of including sex, age, and head size as covariates in the analysis of qEEG of children, and argue against combining data from boys and girls. Our analysis also supports the utility of narrow-band frequencies, e.g., dividing α, β, and γ band into finer sub-scales. The results of this study can serve as a comprehensive normative qEEG database for resting state studies in children containing both eyes open and eyes closed paradigms.

EEG Correlates of Cognitive Functions in a Child with ASD and White Matter Signal Abnormalities: A Case Report with Two-and-a-Half-Year Follow-Up

This research aimed to examine the EEG correlates of different stimuli processing instances in a child with ASD and white matter signal abnormalities and to investigate their relationship to the results of behavioral tests. The prospective case study reports two and a half years of follow-up data from a child aged 38 to 66 months. Cognitive, speech-language, sensory, and EEG correlates of auditory-verbal and auditory-visual-verbal information processing were recorded during five test periods, and their mutual interrelation was analyzed. EEG findings revealed no functional theta frequency range redistribution in the frontal regions favoring the left hemisphere during speech processing. The results pointed to a positive linear trend in the relative theta frequency range and a negative linear trend in the relative alpha frequency range when listening to and watching the cartoon. There was a statistically significant correlation between EEG signals and behavioral test results. Based on the obtained results, it may be concluded that EEG signals and their association with the results of behavioral tests should be evaluated with certain restraints considering the characteristics of the stimuli during EEG recording.

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.

Electroencephalogram Analysis of Magnetic Stimulation at Different Acupoints

Magnetic stimulation has some similarities with acupuncture, and it has broad application prospects because of its non-invasiveness and easy quantification. This paper combines magnetic stimulation technology with electroencephalography to analyze the time-frequency and the brain functional network results elicited by magnetic stimulation at different acupoints. This paper hopes to observe the different effects of stimulating different acupoints on the brain from the perspective of EEG. The EEG signals during magnetic stimulation at ST36, ST40, and GB37 were recorded, respectively. The time-frequency results showed that the magnetic stimulation at ST36 and ST40 on the Foot Yangming Stomach Meridian increased the energy in the left parietal lobe and the right central region, and the energy increased mainly in the theta and alpha bands. However, during the magnetic stimulation at GB37 on the Foot Shaoyang Gallbladder Meridian, the energy in the central region and the frontal lobe increased, and the energy increased mainly in the delta, theta, and alpha bands. Moreover, the energy in the right parietal lobe decreased during magnetic stimulation at GB37. The results of brain functional network were also consistent with time-frequency results. The brain network connections of GB37 stimulation in the central region were significantly less than that of ST36 and ST40 (p < 0.01). In addition, the connections between central region and frontal lobe and the connections between central region and parietal lobe of GB37 stimulation were significantly different from that of ST36 and ST40 (p < 0.01). The above results indicate that ST36 and ST40 on the same meridian have similar effects on the brain, while GB37 on the other meridian has completely different effects from ST36 and ST40. The results of this paper explain the reason why stimulating ST36 and ST40 can treat similar diseases from the perspective of EEG, and also explain that stimulating GB37 has significantly different effects on the brain from that of ST36 and ST40.

Electroacupuncture Alters BCI-Based Brain Network in Stroke Patients

Goal. Stroke patients are usually accompanied by motor dysfunction, which greatly affects daily life. Electroacupuncture is a kind of nondrug therapy that can effectively improve motor function. However, the effect of electroacupuncture is hard to be measured immediately in clinic. This paper is aimed to reveal the instant changes in brain activity of three groups of stroke patients before, during, and after the electroacupuncture treatment by the EEG analysis in the alpha band and beta band. Methods. Seven different functional connectivity indicators including Pearson correlation coefficient, spectral coherence, mutual information, phase locking value, phase lag index, partial directed coherence, and directed transfer function were used to build the BCI-based brain network in stroke patients. Results and Conclusion. The results showed that the brain activity based on the alpha band of EEG decreased after the electroacupuncture treatment, while in the beta band of EEG, the brain activity decreased only in the first two groups. Significance. This method could be used to evaluate the effect of electroacupuncture instantly and quantitatively. The study will hopefully provide some neurophysiological evidence of the relationship between changes in brain activity and the effects of electroacupuncture. The study of BCI-based brain network changes in the alpha and beta bands before, during, and after electroacupuncture in stroke patients of different periods is helpful in adjusting and selecting the electroacupuncture regimens for different patients. The trial was registered on the Chinese clinical trial registry (ChiCTR2000036959).

Oscillatory neural network alterations in young people with tuberous sclerosis complex and associations with co-occurring symptoms of autism spectrum disorder and attention-deficit/hyperactivity disorder

Tuberous sclerosis complex (TSC) is a genetic disorder caused by mutations on the TSC1/TSC2 genes, which result in alterations in molecular signalling pathways involved in neurogenesis and hamartomas in the brain and other organs. TSC carries a high risk for autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD), although the reasons for this are unclear. One proposal is that TSC-related alterations in molecular signalling during neurogenesis lead to atypical development of neural networks, which are involved in the occurrence of ASD and ADHD in TSC. We investigated this proposal in young people with TSC who have been studied longitudinally since their diagnosis in childhood. Electroencephalography (EEG) was used to examine oscillatory connectivity in functional neural networks and local and global network organisation during three tasks (resting-state, attentional and inhibitory control Go/Nogo task, upright and inverted face processing task) in participants with TSC (n = 48) compared to an age- and sex-matched group of typically developing Controls (n = 20). Compared to Controls, the TSC group showed hypoconnected neural networks in the alpha frequency during the resting-state and in the theta and alpha frequencies during the Go/Nogo task (P ≤ .008), as well as reduced local network organisation in the theta and alpha frequencies during the Go/Nogo task (F = 3.95, P = .010). There were no significant group differences in network metrics during the face processing task. Increased connectivity in the hypoconnected alpha-range resting-state network was associated with greater ASD and inattentive ADHD symptoms (rho≥.40, P ≤ .036). Reduced local network organisation in the theta-range during the Go/Nogo task was significantly associated with higher hyperactive/impulsive ADHD symptoms (rho = -.43, P = .041). These findings suggest that TSC is associated with widespread hypoconnectivity in neural networks and support the proposal that altered network function may be involved in the co-occurrence of ASD and ADHD in TSC.

Synchronizing Brain Rhythms to Improve Cognition

Impaired cognition is common in many neuropsychiatric disorders and severely compromises quality of life. Synchronous electrophysiological rhythms represent a core mechanism for sculpting communication dynamics among large-scale brain networks that underpin cognition and its breakdown in neuropsychiatric disorders. Here, we review an emerging neuromodulation technology called transcranial alternating current stimulation that has shown remarkable early results in rapidly improving various domains of human cognition by modulating properties of rhythmic network synchronization. Future noninvasive neuromodulation research holds promise for potentially rescuing network activity patterns and improving cognition, setting groundwork for the development of drug-free, circuit-based therapeutics for people with cognitive brain disorders.

Theory of Mind Deficits and Neurophysiological Operations in Autism Spectrum Disorders: A Review

Theory of Mind (ToM) is a multifaceted skill set which encompasses a variety of cognitive and neurobiological aspects. ToM deficits have long been regarded as one of the most disabling features in individuals with Autism Spectrum Disorder. One of the theories that attempts to account for these impairments is that of “broken mirror neurons”. The aim of this review is to present the most recent available studies with respect to the connection between the function of mirror neurons in individuals with ASD and ToM-reflecting sensorimotor, social and attentional stimuli. The majority of these studies approach the theory of broken mirror neurons critically. Only studies from the last 15 years have been taken into consideration. Findings from electroencephalography (EEG) studies so far indicate that further research is necessary to shed more light on the mechanisms underlying the connection(s) between ToM and neurophysiological operations.

Modulation Effect of Acupuncture on Functional Brain Networks and Classification of Its Manipulation With EEG Signals

Acupuncture manipulation is the key of Chinese medicine acupuncture therapy. In clinical practice, different acupuncture manipulations are required to achieve different therapeutic effects, which means it is crucial to distinguish different acupuncture manipulations. In this paper, we proposed a classification framework for different acupuncture manipulations, which employed the graph theory and machine learning method. Multichannel EEG signals evoked by acupuncture at "Zusanli" acupoint were recorded from healthy humans by two acupuncture manipulations: twirling-rotating (TR) and lifting-thrusting (LT). Phase locking value was used to estimate the phase synchronization of pair-wise EEG channels. It was found that acupunctured by TR manipulation exhibit significantly higher synchronization degree than acupunctured by LT manipulation. With the construction of functional brain network, the topological features of graph theory were extracted. Taken the network features as inputs, machine learning classifiers were established to classify acupuncture manipulations. The highest accuracy can achieve 92.14% with support vector machine. By further optimizing the network features utilized in machine learning classifiers, it was found that the combination of node betweenness and small world network index is the most effective factor for acupuncture manipulations classification. These findings suggested that our approach provides new ideas for automatically identify acupuncture manipulations from the perspective of functional brain networks and machine learning methods.

Autism spectrum disorder: Trends in research exploring etiopathogenesis

Autism spectrum disorder is a neurodevelopmental condition in which affected individuals have difficulties while interacting and communicating socially, and repetitive behaviors. It has a multifactorial etiology. Various risk factors, including genetic and environmental influences, have been explored while trying to understand its causation. As older evidence was suggestive of a high heritability, a majority of research focused on finding the underlying genetic causes of autism. Due to these efforts, there have been advances in the knowledge of some of the genetic factors associated with autism. But a recent trend also shows an increasing interest in exploration of various potential environmental triggers. These efforts have brought us closer to understanding the elusive disorder more so than ever before. The current review discusses the recent trends in research exploring the etiopathogenesis of autism spectrum disorder.

Oscillatory neural networks underlying resting-state, attentional control and social cognition task conditions in children with ASD, ADHD and ASD+ADHD

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are common and impairing neurodevelopmental disorders that frequently co-occur. The neurobiological mechanisms involved in ASD and ADHD are not fully understood. However, alterations in large-scale neural networks have been proposed as core deficits in both ASD and ADHD and may help to disentangle the neurobiological basis of these disorders and their co-occurrence. In this study, we examined similarities and differences in large-scale oscillatory neural networks between boys aged 8-13 years with ASD (n = 19), ADHD (n = 18), ASD + ADHD (n = 29) and typical development (Controls, n = 26). Oscillatory neural networks were computed using graph-theoretical methods from electroencephalographic (EEG) data collected during an eyes-open resting-state and attentional control and social cognition tasks in which we previously reported disorder-specific atypicalities in oscillatory power and event-related potentials (ERPs). We found that children with ASD showed significant hypoconnectivity in large-scale networks during all three task conditions compared to children without ASD. In contrast, children with ADHD showed significant hyperconnectivity in large-scale networks during the attentional control and social cognition tasks, but not during the resting-state, compared to children without ADHD. Children with co-occurring ASD + ADHD did not differ from children with ASD when paired with this group and vice versa when paired with the ADHD group, indicating that these children showed both ASD-like hypoconnectivity and ADHD-like hyperconnectivity. Our findings suggest that ASD and ADHD are associated with distinct alterations in large-scale oscillatory networks, and these atypicalities present together in children with both disorders. These alterations appear to be task-independent in ASD but task-related in ADHD, and may underlie other neurocognitive atypicalities in these disorders.

Beta oscillations precede joint attention and correlate with mentalization in typical development and autism

A precursor of adult social functioning is joint attention (JA), which is the capacity to share attention on an object with another person. JA precedes the development of the capacity to attribute mental states to others (i.e., mentalization or theory of mind). The neural mechanisms involved in the development of mentalization are not fully understood. Electroencephalographic recordings were made of children while they watched stimuli on a screen and their interaction with the experimenter was assessed. We tested whether neuronal activity preceding JA correlates with mentalization in typically developing (TD) children and whether this activity is impaired in children with autistic spectrum disorder (ASD) who evidence deficits in JA and mentalization skills. Both groups exhibited JA behavior with comparable frequency. TD children displayed a higher amplitude of negative central (Nc) event-related potential preceding JA behavior (∼500 msec after stimuli presentation), than did the ASD group. Previous to JA behavior, TD children demonstrated beta oscillatory activity in the temporoparietal region, while ASD children did not show an increase in beta activity. In both groups, the beta power correlated with mentalization, suggesting that this specific neuronal mechanism is involved in mentalization, which used during social interaction.

EEG Frequency Bands in Psychiatric Disorders: A Review of Resting State Studies

A significant proportion of the electroencephalography (EEG) literature focuses on differences in historically pre-defined frequency bands in the power spectrum that are typically referred to as alpha, beta, gamma, theta and delta waves. Here, we review 184 EEG studies that report differences in frequency bands in the resting state condition (eyes open and closed) across a spectrum of psychiatric disorders including depression, attention deficit-hyperactivity disorder (ADHD), autism, addiction, bipolar disorder, anxiety, panic disorder, post-traumatic stress disorder (PTSD), obsessive compulsive disorder (OCD) and schizophrenia to determine patterns across disorders. Aggregating across all reported results we demonstrate that characteristic patterns of power change within specific frequency bands are not necessarily unique to any one disorder but show substantial overlap across disorders as well as variability within disorders. In particular, we show that the most dominant pattern of change, across several disorder types including ADHD, schizophrenia and OCD, is power increases across lower frequencies (delta and theta) and decreases across higher frequencies (alpha, beta and gamma). However, a considerable number of disorders, such as PTSD, addiction and autism show no dominant trend for spectral change in any direction. We report consistency and validation scores across the disorders and conditions showing that the dominant result across all disorders is typically only 2.2 times as likely to occur in the literature as alternate results, and typically with less than 250 study participants when summed across all studies reporting this result. Furthermore, the magnitudes of the results were infrequently reported and were typically small at between 20% and 30% and correlated weakly with symptom severity scores. Finally, we discuss the many methodological challenges and limitations relating to such frequency band analysis across the literature. These results caution any interpretation of results from studies that consider only one disorder in isolation, and for the overall potential of this approach for delivering valuable insights in the field of mental health.

Overlaps and distinctions between attention deficit/hyperactivity disorder and autism spectrum disorder in young adulthood: Systematic review and guiding framework for EEG-imaging research

Attention deficit/hyperactivity disorders (ADHD) and autism spectrum disorders (ASD) frequently co-occur. However, we know little about the neural basis of the overlaps and distinctions between these disorders, particularly in young adulthood - a critical time window for brain plasticity across executive and socioemotional domains. Here, we systematically review 75 articles investigating ADHD and ASD in young adult samples (mean ages 16-26) using cognitive tasks, with neural activity concurrently measured via electroencephalography (EEG) - the most accessible neuroimaging technology. The majority of studies focused on event-related potentials (ERPs), with some beginning to capitalise on oscillatory approaches. Overlapping and specific profiles for ASD and ADHD were found mainly for four neurocognitive domains: attention processing, performance monitoring, face processing and sensory processing. No studies in this age group directly compared both disorders or considered dual diagnosis with both disorders. Moving forward, understanding of ADHD, ASD and their overlap in young adulthood would benefit from an increased focus on cross-disorder comparisons, using similar paradigms and in well-powered samples and longitudinal cohorts.

Interhemispheric alpha-band hypoconnectivity in children with autism spectrum disorder

Diverse genetic and environmental etiologies converge onto circuit level brain dysfunction in autism spectrum disorder (ASD), manifesting at a macroscopic level as aberrant neural connectivity. Previous studies have described atypical patterns of decreased short range and increased long range connectivity in ASD [1 ]. However, it remains unclear whether group level features of circuit dysfunction are consistently present across the range of cognitive function seen in the autism spectrum.

The dynamics of neural oscillations in the alpha range (6-12 Hz) are exquisitely sensitive to healthy development of functional and structural connectivity. Alpha-band coherence, measured with high temporal-precision electroencephalography (EEG) therefore represents an ideal tool for studying neural connectivity in developmental populations.

Here we examined spontaneous alpha phase coherence in a heterogeneous sample of 59 children with ASD and 39 age matched typically developing children. Using a data driven approach, we conducted an unbiased examination of all possible atypical connectivity patterns across all cortical regions.

Long-range hypoconnectivity was present in children with ASD compared to typically developing children, with temporal interhemispheric connectivity showing the largest difference between the two groups. Decreased long range alpha coherence distinguishes a heterogeneous group of ASD children from typically developing children. Interhemispheric temporal hypoconnectivity represents a fundamental functional difference in children with ASD across a wide cognitive and age range that may reflect white matter disturbances or increased signal variability at temporal sites in ASD.

Social decision making in autism: On the impact of mirror neurons, motor control, and imitative behaviors

The Mirror Neuron System (MNS) plays a crucial role in action perception and imitative behavior, which is suggested to be impaired in Autism Spectrum Disorders (ASDs). In this review, we discuss the plausibility and empirical evidence of a neural interaction between the MNS, action perception, empathy, imitative behavior, and their impact on social decision making in ASDs. To date, there is no consensus regarding a particular theory in ASDs and its underlying mechanisms. Some theories have completely focused on social difficulties, others have emphasized sensory aspects. Based on the current studies, we suggest a multilayer neural network model including the MNS on a first layer and transforming this information to a higher layer network responsible for reasoning. Future studies with ASD participants combining behavioral tasks with neuroimaging methods and transcranial brain stimulation as well as computational modeling can help validate and complement this suggested model. Moreover, we propose applying the behavioral paradigms, and the neurophysiological markers mentioned in this review article for evaluating psychiatric treatment approaches in ASDs. The investigation of modulating effects of different treatment approaches on the neurophysiological markers of the MNS can help find specific subgroups of ASDs patients and support tailored psychiatric interventions.

Heart Rate Variability During a Joint Attention Task in Toddlers With Autism Spectrum Disorders

Background: Autism Spectrum Disorders (ASD) are a heterogeneous group of neurodevelopmental disorders featuring early impairments in social domain, with autonomic nervous system (ANS) unbalance possibly representing a useful marker for such disturbances. Impairments in joint attention (JA) are one of the earliest markers of social deficits in ASD. In this study, we assessed the feasibility of using wearable technologies for characterizing the ANS response in ASD toddlers during the presentation of JA stimuli. Methods: Twenty ASD toddlers and 20 age- and gender-matched typically developed (TD) children were recorded at baseline and during a JA task through an unobtrusive chest strap for electrocardiography (ECG). Specific algorithms for feature extraction, including Heart Rate (HR), Standard Deviation of the Normal-to-Normal Intervals (SDNN), Coefficient of Variation (CV), pNN10 as well as low frequency (LF) and high frequency (HF), were applied to the ECG signal and a statistical comparison between the two groups was performed. Results: As regards the single phases, SDNN (p = 0.04) and CV (p = 0.021) were increased in ASD at baseline together with increased LF absolute power (p = 0.034). Moreover, CV remained higher in ASD during the task (p = 0.03). Considering the phase and group interaction, LF increased from baseline to task in TD group (p = 0.04) while it decreased in the ASD group (p = 0.04). Conclusions: The results of this study indicate the feasibility of characterizing the ANS response in ASD toddlers through a minimally obtrusive tool. Our analysis showed an increased SDNN and CV in toddlers with ASD particularly at baseline compared to TD and lower LF during the task. These findings could suggest the possibility of using the proposed approach for evaluating physiological correlates of JA response in young children with ASD.

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.

An integrated EEG and eye-tracking approach for the study of responding and initiating joint attention in Autism Spectrum Disorders

Autism Spectrum Disorders (ASD) are characterised by impairment in joint attention (JA), which has two components: the response to JA and the initiation of JA. Literature suggests a correlation between JA and neural circuitries, although this link is still largely unexplored in ASD. In this pilot study, we aimed at investigating the neural correlates of responding and initiating JA in high-functioning children with ASD and evaluating the changes in brain function and visual pattern after six months of rehabilitative treatment using an integrated EEG/eye-tracking system. Our results showed that initiating and responding JA subtend both overlapping (i.e. frontal and temporal) and specialized (i.e. parietal for responding JA and occipital for initiating JA) neural circuitries. In addition, in a subgroup of subjects, we observed trends of changes in both brain activity and connectivity after rehabilitative treatment in both the two tasks, which were correlated with modifications in gaze measures. These preliminary results, if confirmed in a larger sample, suggest the feasibility of using the proposed multimodal approach to characterise JA-related brain circuitries and visual pattern in ASD individuals and to monitor longitudinal changes in response to rehabilitative intervention.

Deqi Induction by HT7 Acupuncture Alters Theta and Alpha Band Coherence in Human Healthy Subjects

The aim of this preliminary study is to investigate the changes in phase synchronization in the theta and alpha bands before and during the performance of classical acupuncture on the Sinmun (HT7). The electroencephalogram (EEG) signals from nine healthy young subjects were recorded before and during acupuncture in the “closed-eye” state. The EEG signals were acquired from 19 surface scalp electrodes (FP1, FP2, F7, F3, Fz F4, F8, T3, C3, Cz, C4, T4, T5, P3, Pz, P4, T6, O1, and O2). Needles were inserted into the HT7 bilaterally and were then manipulated to induce deqi and retained for 15 minutes. Phase synchronization was measured by phase coherence. In the theta band, coherence significantly increased between the temporal (T5, T6) and occipital areas (O1, O2) during the acupuncture stimulation. In the alpha band, coherence significantly increased between the left temporal area (T5) and other areas (frontal, parietal, and occipital). Phase coherence in the theta and alpha bands tended to increase during the retention of the acupuncture needles after deqi. Therefore, it can be concluded that acupuncture stimulation with deqi is clinically effective via the central nervous system (CNS).

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.

Electroencephalogram Coherence Patterns in Autism: An Updated Review

Electrophysiologic studies suggest that autism spectrum disorder is characterized by aberrant anatomic and functional neural circuitry. During normal brain development, pruning and synaptogenesis facilitate ongoing changes in both short- and long-range neural wiring. In developmental disorders such as autism, this process may be perturbed and lead to abnormal neural connectivity. Careful analysis of electrophysiologic connectivity patterns using EEG coherence may provide a way to probe the resulting differences in neurological function between people with and without autism. There is general consensus that electroencephalogram coherence patterns differ between individuals with and without autism spectrum disorders; however, the exact nature of the differences and their clinical significance remain unclear. Here we review recent literature comparing electroencephalogram coherence patterns between patients with autism spectrum disorders or at high risk for autism and their nonautistic or low-risk for autism peers.