Enhanced connectivity between visual cortex and other regions of the brain in autism: a REM sleep EEG coherence study

The effect of binaural pulse modulation (B.P.M) on brain state in depression and anxiety: a case series

OBJECTIVE

In this pilot study a binaural pulse modulator was tested to see if it leads to a change in self-reported measures of distress. This binaural pulse modulator produces two frequencies that combine to create a binaural pulse to stimulate the nervous system through a differential auditory tone presentation and the response of the user can be adjusted to the appropriate target tone for effective treatment use. Each individual calibrated the binaural pulse to increase the level of emotion experienced while imagining an experience with a similar emotional valence or while engaged in a cognitive function while also listening to the sound. "Treatment" is based on the client's control of the binaural pulses to achieve the desired state. Training focuses on specific aspects of their psychological difficulties while listening to an auditory tone, turning a knob until the sound becomes uncomfortable. Finally, another knob is turned to cancel out the uncomfortable noise which appears to be associated with a reduction in distress.

CASE PRESENTATIONS

Four adult Hispanic participants (three females and one male) were studied with self-reported measures of distress (generalized anxiety disorder 7, Coronavirus Disease Stress Scale, posttraumatic stress disorder checklist for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, and Beck depression scale II) were completed at screening, before treatment, after treatment, 4-weeks post-treatment, and 12-weeks post-treatment. Quantitative electroencephalogram and functional magnetic resonance imaging were also performed before and after treatment.

RESULTS

Preliminary findings indicated that at the end of treatment with binaural pulse modulator there were reported reductions in self-reported levels of distress. Quantitative electroencephalogram as well as functional magnetic resonance imaging changes in brain state were also noted when comparing pre- to post-treatment.

CONCLUSIONS

binaural pulse modulator use appears to result in temporary changes in self-reported levels of distress during treatment. Limitations of the study are reviewed and directions for further research are offered.

Differences in Sleep EEG Coherence and Spindle Metrics in Toddlers With and Without Language Delay: A Prospective Observational Study

Background

Sleep plays a crucial role in early language development, and sleep disturbances are common in children with neurodevelopmental disorders. Examining sleep microarchitecture in toddlers with and without language delays can offer key insights into neurophysiological abnormalities associated with atypical neurodevelopmental trajectories and potentially aid in early detection and intervention.

Methods

Here, we investigated electroencephalogram (EEG) coherence and sleep spindles in 16 toddlers with language delay (LD) compared with a group of 39 typically developing (TD) toddlers. The sample was majority male (n = 34, 62%). Participants were aged 12-to-22 months at baseline, and 34 (LD, n=11; TD, n=23) participants were evaluated again at 36 months of age.

Results

LD toddlers demonstrated increased EEG coherence compared to TD toddlers, with differences most prominent during slow-wave sleep. Within the LD group, lower expressive language skills were associated with higher coherence in REM sleep. Within the TD group, lower expressive language skills were associated with higher coherence in slow-wave sleep. Sleep spindle density, duration, and frequency changed between baseline and follow-up for both groups, with the LD group demonstrating a smaller magnitude of change than the TD group. The direction of change was frequency-dependent for both groups.

Conclusions

These findings indicate that atypical sleep EEG connectivity and sleep spindle development can be detected in toddlers between 12 and 36 months and offers insights into neurophysiological mechanisms underlying the etiology of neurodevelopmental disorders.

Trial registration

https://clinicaltrials.gov/study/NCT01339767; Registration date: 4/20/2011.

Different levels of visuospatial abilities linked to differential brain correlates underlying visual mental segmentation processes in autism

The neural underpinnings of enhanced locally oriented visual processing that are specific to autistics with a Wechsler's Block Design (BD) peak are largely unknown. Here, we investigated the brain correlates underlying visual segmentation associated with the well-established autistic superior visuospatial abilities in distinct subgroups using functional magnetic resonance imaging. This study included 31 male autistic adults (15 with (AUTp) and 16 without (AUTnp) a BD peak) and 28 male adults with typical development (TYP). Participants completed a computerized adapted BD task with models having low and high perceptual cohesiveness (PC). Despite similar behavioral performances, AUTp and AUTnp showed generally higher occipital activation compared with TYP participants. Compared with both AUTnp and TYP participants, the AUTp group showed enhanced task-related functional connectivity within posterior visuoperceptual regions and decreased functional connectivity between frontal and occipital-temporal regions. A diminished modulation in frontal and parietal regions in response to increased PC was also found in AUTp participants, suggesting heavier reliance on low-level processing of global figures. This study demonstrates that enhanced visual functioning is specific to a cognitive phenotypic subgroup of autistics with superior visuospatial abilities and reinforces the need to address autistic heterogeneity by good cognitive characterization of samples in future studies.

Systematic Review on EEG Analysis to Diagnose and Treat Autism by Evaluating Functional Connectivity and Spectral Power

An abnormality in neural connectivity is linked to autism spectrum disorder (ASD). There is no way to test the concept of neural connectivity empirically. According to recent network theory and time series analysis findings, electroencephalography (EEG) can assess neural network architecture, a sign of activity in the brain. This systematic review aims to evaluate functional connectivity and spectral power using EEG signals. EEG records the brain activity of an individual by displaying wavy lines that depict brain cells' communication through electrical impulses. EEG can diagnose various brain disorders, including epilepsy and related seizure illness, brain dysfunction, tumors, and damage. We found 21 studies using two of the most common EEG analysis methods: functional connectivity and spectral power. ASD and non-ASD individuals were found to differ significantly in all selected papers. Due to high heterogeneity in the outcomes, generalizations cannot be drawn, and no single method is currently beneficial as a diagnostic tool. For ASD subtype delineation, the lack of research prevented the evaluation of these techniques as diagnostic tools. These findings confirm the presence of abnormalities in the EEG in ASD, but they are insufficient to diagnose. Our study suggests that EEG is useful in diagnosing ASD by evaluating entropy in the brain. Researchers may be able to develop new diagnostic methods for ASD which focuses on particular stimuli and brainwaves if they conduct more extensive studies with higher numbers and more rigorous study designs.

A randomized controlled trial into the effects of probiotics on electroencephalography in preschoolers with autism

LAY ABSTRACT

This study investigates the effects of a probiotic on preschoolers' brain electrical activity with autism spectrum disorder. Autism is a disorder with an increasing prevalence characterized by an enormous individual, family, and social cost. Although the etiology of autism spectrum disorder is unknown, an interaction between genetic and environmental factors is implicated, converging in altered brain synaptogenesis and, therefore, connectivity. Besides deepening the knowledge on the resting brain electrical activity that characterizes this disorder, this study allows analyzing the positive central effects of a 6-month therapy with a probiotic through a randomized, double-blind placebo-controlled study and the correlations between electroencephalography activity and biochemical and clinical parameters. In subjects treated with probiotics, we observed a decrease of power in frontopolar regions in beta and gamma bands, and increased coherence in the same bands together with a shift in frontal asymmetry, which suggests a modification toward a typical brain activity. Electroencephalography measures were significantly correlated with clinical and biochemical measures. These findings support the importance of further investigations on probiotics' benefits in autism spectrum disorder to better elucidate mechanistic links between probiotics supplementation and changes in brain activity.

Differential neural correlates underlying mental rotation processes in two distinct cognitive profiles in autism

Enhanced visuospatial abilities characterize the cognitive profile of a subgroup of autistics. However, the neural correlates underlying such cognitive strengths are largely unknown. Using functional magnetic resonance imaging (fMRI), we investigated the neural underpinnings of superior visuospatial functioning in different autistic subgroups. Twenty-seven autistic adults, including 13 with a Wechsler's Block Design peak (AUTp) and 14 without (AUTnp), and 23 typically developed adults (TYP) performed a classic mental rotation task. As expected, AUTp participants were faster at the task compared to TYP. At the neural level, AUTp participants showed enhanced bilateral parietal and occipital activation, stronger occipito-parietal and fronto-occipital connectivity, and diminished fronto-parietal connectivity compared to TYP. On the other hand, AUTnp participants presented greater activation in right and anterior regions compared to AUTp. In addition, reduced connectivity between occipital and parietal regions was observed in AUTnp compared to AUTp and TYP participants. A greater reliance on posterior regions is typically reported in the autism literature. Our results suggest that this commonly reported finding may be specific to a subgroup of autistic individuals with enhanced visuospatial functioning. Moreover, this study demonstrated that increased occipito-frontal synchronization was associated with superior visuospatial abilities in autism. This finding contradicts the long-range under-connectivity hypothesis in autism. Finally, given the relationship between distinct cognitive profiles in autism and our observed differences in brain functioning, future studies should provide an adequate characterization of the autistic subgroups in their research. The main limitations are small sample sizes and the inclusion of male-only participants.

Wavelet-Based Biphase Analysis of Brain Rhythms in Automated Wake-Sleep Classification

Many studies in the field of sleep have focused on connectivity and coherence. Still, the nonstationary nature of electroencephalography (EEG) makes many of the previous methods unsuitable for automatic sleep detection. Time-frequency representations and high-order spectra are applied to nonstationary signal analysis and nonlinearity investigation, respectively. Therefore, combining wavelet and bispectrum, wavelet-based bi-phase (Wbiph) was proposed and used as a novel feature for sleep-wake classification. The results of the statistical analysis with emphasis on the importance of the gamma rhythm in sleep detection show that the Wbiph is more potent than coherence in the wake-sleep classification. The Wbiph has not been used in sleep studies before. However, the results and inherent advantages, such as the use of wavelet and bispectrum in its definition, suggest it as an excellent alternative to coherence. In the next part of this paper, a convolutional neural network (CNN) classifier was applied for the sleep-wake classification by Wbiph. The classification accuracy was 97.17% in nonLOSO and 95.48% in LOSO cross-validation, which is the best among previous studies on sleep-wake classification.

REM Sleep EEG Activity and Clinical Correlates in Adults With Autism

We tested the hypothesis of an atypical scalp distribution of electroencephalography (EEG) activity during Rapid Eye Movement (REM) sleep in young autistic adults. EEG spectral activity and ratios along the anteroposterior axis and across hemispheres were compared in 16 neurotypical (NT) young adults and 17 individuals with autism spectrum disorder (ASD). EEG spectral power was lower in the ASD group over the bilateral central and right parietal (beta activity) as well as bilateral occipital (beta, theta, and total activity) recording sites. The NT group displayed a significant posterior polarity of intra-hemispheric EEG activity while EEG activity was more evenly or anteriorly distributed in ASD participants. No significant inter-hemispheric EEG lateralization was found. Correlations between EEG distribution and ASD symptoms using the Autism Diagnostic Interview-Revised (ADI-R) showed that a higher posterior ratio was associated with a better ADI-R score on communication skills, whereas a higher anterior ratio was related to more restricted interests and repetitive behaviors. EEG activity thus appears to be atypically distributed over the scalp surface in young adults with autism during REM sleep within cerebral hemispheres, and this correlates with some ASD symptoms. These suggests the existence in autism of a common substrate between some of the symptoms of ASD and an atypical organization and/or functioning of the thalamo-cortical loop during REM sleep.

Increased EEG coherence in long-distance and short-distance connectivity in children with autism spectrum disorders

INTRODUCTION

Autism spectrum disorder (ASD) is a complex and prevalent neurodevelopmental disorder characterized by deficits in social communication and social interaction as well as repetitive behaviors. Alterations in function connectivity are widely recognized in recent electroencephalogram (EEG) studies. However, most studies have not reached consistent conclusions, which could be due to the developmental nature and the heterogeneity of ASD.

METHODS

Here, EEG coherence analysis was used in a cohort of children with ASD (n = 13) and matched typically developing controls (TD, n = 15) to examine the functional connectivity characteristics in long-distance and short-distance electrode pairs. Subsequently, we explore the association between the connectivity strength of coherence and symptom severity in children with ASD.

RESULTS

Compared with TD group, individuals with ASD showed increased coherence in short-distance electrode pairs in the right temporal-parietal region (delta, alpha, beta bands), left temporal-parietal region (all frequency bands), occipital region (theta, alpha, beta bands), right central-parietal region (delta, alpha, beta bands), and the prefrontal region (only beta band). In the long-distance coherence analysis, the ASD group showed increased coherence in bilateral frontal region, temporal region, parietal region, and frontal-occipital region in alpha and beta bands. The strength of such connections was associated with symptom severity.

DISCUSSION

Our study indicates that abnormal connectivity patterns in neuroelectrophysiology may be of critical importance to acknowledge the underlying brain mechanism.

Evaluation of mismatch negativity as a marker for language impairment in autism spectrum disorder

BACKGROUND

The identification of an early and objective marker of language impairment in autism spectrum disorder (ASD) has the potential to lead to earlier language intervention for affected children. The mismatch negativity (MMN), a passive auditory evoked potential, offers insight into the brain's ability to direct attention to novel sounds. Since exposure to speech is necessary for learning to map meaning onto phonemes, we predicted slower MMN responses to speech sounds would indicate presence of language impairment in ASD.

METHODS

We explored the relationship between MMN latency in children ages 5-10 with ASD plus language impairment (ASD + LI), ASD minus language impairment (ASD-LI), and typically developing children (TD) during an auditory oddball experiment presenting speech and pure tone sounds.

RESULTS

Contrary to our prediction, children with ASD + LI demonstrated decreased MMN latency in the left hemisphere in response to novel vowel sounds compared to children with ASD-LI and TD controls. Parent responses to the Sensory Experiences Questionnaire revealed that all participating individuals with ASD were hypersensitive to sounds.

CONCLUSIONS

Our results lend support to the theory that some children with ASD + LI have increased connectivity in primary sensory cortices at the expense of connectivity to association areas of the brain. This may account for faster speech sound processing despite low language scores in these children. Future studies should focus on individuals with language impairment and hyper-or hyposensitivity to sounds.

Altered sleep architecture, rapid eye movement sleep, and neural oscillation in a mouse model of human chromosome 16p11.2 microdeletion

Sleep abnormalities are common among children with neurodevelopmental disorders. The human chr16p11.2 microdeletion is associated with a range of neurological and neurobehavioral abnormalities. Previous studies of a mouse model of human chr16p11.2 microdeletion (chr16p11.2df/+) have demonstrated pathophysiological changes at the synapses in the hippocampus and striatum; however, the impact of this genetic abnormality on system level brain functions, such as sleep and neural oscillation, has not been adequately investigated. Here, we show that chr16p11.2df/+ mice have altered sleep architecture, with increased wake time and reduced time in rapid eye movement (REM) and non-REM (NREM) sleep. Importantly, several measurements of REM sleep are significantly changed in deletion mice. The REM bout number and the bout number ratio of REM to NREM are decreased in mutant mice, suggesting a deficit in REM-NREM transition. The average REM bout duration is shorter in mutant mice, indicating a defect in REM maintenance. In addition, whole-cell patch clamp recording of the ventrolateral periaqueductal gray (vlPAG)-projecting gamma-aminobutyric acid (GABA)ergic neurons in the lateral paragigantocellular nucleus of ventral medulla of mutant mice reveal that these neurons, which are important for NREM-REM transition and REM maintenance, have hyperpolarized resting membrane potential and increased membrane resistance. These changes in intrinsic membrane properties suggest that these projection-specific neurons of mutant mice are less excitable, and thereby may play a role in deficient NREM-REM transition and REM maintenance. Furthermore, mutant mice exhibit changes in neural oscillation involving multiple frequency classes in several vigilance states. The most significant alterations occur in the theta frequency during wake and REM sleep.

Brain Connectivity Reflected in Electroencephalogram Coherence in Individuals With Autism: A Meta-Analysis

INTRODUCTION

Many theories have been proposed about the etiology of autism. One is related to brain connectivity in patients with autism. Several studies have reported brain connectivity changes in autism disease. This study was performed on Electroencephalogram (EEG) studies that evaluated patients with autism, using functional brain connectivity, and compared them with typically-developing individuals.

METHODS

Three scientific databases of ScienceDirect, Medline (PubMed), and BioMed Central were systematically searched through their online search engines. Comprehensive Meta-analysis software analyzed the obtained data.

RESULTS

The systematic search led to 10 papers, in which EEG coherence was used to obtain the brain connectivity of people with autism. To determine the effect size, Cohen's d parameter was used. In the first meta-analysis, the study of the maximum effect size was considered, and all significant effect sizes were evaluated in the second meta-analysis. The effect size was assessed using a random-effects model in both meta-analyses. The results of the first meta-analysis indicated that heterogeneity was not present among the studies (Q=13.345, P>0.1). The evaluation of all effect sizes in the second meta-analysis showed a significant lack of homogeneity among the studies (Q=56.984, P=0.0001).

CONCLUSION

On the whole, autism was found to be related to neural connectivity, and the present research showed the difference in the EEG coherence of people with autism and healthy people. These conclusions require further studies with more extensive data, considering different brain regions, and novel analysis techniques for assessing brain connectivity.

Active Sleep Promotes Functional Connectivity in Developing Sensorimotor Networks

A ubiquitous feature of active (REM) sleep in mammals and birds is its relative abundance in early development. In rat pups across the first two postnatal weeks, active sleep promotes the expression of synchronized oscillatory activity within and between cortical and subcortical sensorimotor structures. Sensory feedback from self-generated myoclonic twitches - which are produced exclusively during active sleep - also triggers neural oscillations in those structures. We have proposed that one of the functions of active sleep in early infancy is to provide a context for synchronizing developing structures. Specifically, neural oscillations contribute to a variety of neurodevelopmental processes, including synapse formation, neuronal differentiation and migration, apoptosis, and the refinement of topographic maps. In addition, synchronized oscillations promote functional connectivity between distant brain areas. Consequently, any condition or manipulation that restricts active sleep can, in turn, deprive the infant animal of substantial sensory experience, resulting in atypical developmental trajectories.

The Default Mode Network in Autism

Autism spectrum disorder (ASD) is characterized by deficits in social communication and interaction. Since its discovery as a major functional brain system, the default mode network (DMN) has been implicated in a number of psychiatric disorders, including ASD. Here we review converging multimodal evidence for DMN dysfunction in the context of specific components of social cognitive dysfunction in ASD: 'self-referential processing' - the ability to process social information relative to oneself and 'theory of mind' or 'mentalizing' - the ability to infer the mental states such as beliefs, intentions, and emotions of others. We show that altered functional and structural organization of the DMN, and its atypical developmental trajectory, are prominent neurobiological features of ASD. We integrate findings on atypical cytoarchitectonic organization and imbalance in excitatory-inhibitory circuits, which alter local and global brain signaling, to scrutinize putative mechanisms underlying DMN dysfunction in ASD. Our synthesis of the extant literature suggests that aberrancies in key nodes of the DMN and their dynamic functional interactions contribute to atypical integration of information about the self in relation to 'other', as well as impairments in the ability to flexibly attend to socially relevant stimuli. We conclude by highlighting open questions for future research.

Increased overall cortical connectivity with syndrome specific local decreases suggested by atypical sleep-EEG synchronization in Williams syndrome

Williams syndrome (7q11.23 microdeletion) is characterized by specific alterations in neurocognitive architecture and functioning, as well as disordered sleep. Here we analyze the region, sleep state and frequency-specific EEG synchronization of whole night sleep recordings of 21 Williams syndrome and 21 typically developing age- and gender-matched subjects by calculating weighted phase lag indexes. We found broadband increases in inter- and intrahemispheric neural connectivity for both NREM and REM sleep EEG of Williams syndrome subjects. These effects consisted of increased theta, high sigma, and beta/low gamma synchronization, whereas alpha synchronization was characterized by a peculiar Williams syndrome-specific decrease during NREM states (intra- and interhemispheric centro-temporal) and REM phases of sleep (occipital intra-area synchronization). We also found a decrease in short range, occipital connectivity of NREM sleep EEG theta activity. The striking increased overall synchronization of sleep EEG in Williams syndrome subjects is consistent with the recently reported increase in synaptic and dendritic density in stem-cell based Williams syndrome models, whereas decreased alpha and occipital connectivity might reflect and underpin the altered microarchitecture of primary visual cortex and disordered visuospatial functioning of Williams syndrome subjects.

How Useful Is Electroencephalography in the Diagnosis of Autism Spectrum Disorders and the Delineation of Subtypes: A Systematic Review

Autism spectrum disorders (ASD) are thought to be associated with abnormal neural connectivity. Presently, neural connectivity is a theoretical construct that cannot be easily measured. Research in network science and time series analysis suggests that neural network structure, a marker of neural activity, can be measured with electroencephalography (EEG). EEG can be quantified by different methods of analysis to potentially detect brain abnormalities. The aim of this review is to examine evidence for the utility of three methods of EEG signal analysis in the ASD diagnosis and subtype delineation. We conducted a review of literature in which 40 studies were identified and classified according to the principal method of EEG analysis in three categories: functional connectivity analysis, spectral power analysis, and information dynamics. All studies identified significant differences between ASD patients and non-ASD subjects. However, due to high heterogeneity in the results, generalizations could not be inferred and none of the methods alone are currently useful as a new diagnostic tool. The lack of studies prevented the analysis of these methods as tools for ASD subtypes delineation. These results confirm EEG abnormalities in ASD, but as yet not sufficient to help in the diagnosis. Future research with larger samples and more robust study designs could allow for higher sensitivity and consistency in characterizing ASD, paving the way for developing new means of diagnosis.

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.

The Contribution of Increased Gamma Band Connectivity to Visual Non-Verbal Reasoning in Autistic Children: A MEG Study

Some individuals with autism spectrum (AS) perform better on visual reasoning tasks than would be predicted by their general cognitive performance. In individuals with AS, mechanisms in the brain’s visual area that underlie visual processing play a more prominent role in visual reasoning tasks than they do in normal individuals. In addition, increased connectivity with the visual area is thought to be one of the neural bases of autistic visual cognitive abilities. However, the contribution of such brain connectivity to visual cognitive abilities is not well understood, particularly in children. In this study, we investigated how functional connectivity between the visual areas and higher-order regions, which is reflected by alpha, beta and gamma band oscillations, contributes to the performance of visual reasoning tasks in typically developing (TD) (n = 18) children and AS children (n = 18). Brain activity was measured using a custom child-sized magneto-encephalograph. Imaginary coherence analysis was used as a proxy to estimate the functional connectivity between the occipital and other areas of the brain. Stronger connectivity from the occipital area, as evidenced by higher imaginary coherence in the gamma band, was associated with higher performance in the AS children only. We observed no significant correlation between the alpha or beta bands imaginary coherence and performance in the both groups. Alpha and beta bands reflect top-down pathways, while gamma band oscillations reflect a bottom-up influence. Therefore, our results suggest that visual reasoning in AS children is at least partially based on an enhanced reliance on visual perception and increased bottom-up connectivity from the visual areas.

Name recognition in autism: EEG evidence of altered patterns of brain activity and connectivity

BACKGROUND

Impaired orienting to social stimuli is one of the core early symptoms of autism spectrum disorder (ASD). However, in contrast to faces, name processing has rarely been studied in individuals with ASD. Here, we investigated brain activity and functional connectivity associated with recognition of names in the high-functioning ASD group and in the control group.

METHODS

EEG was recorded in 15 young males with ASD and 15 matched one-to-one control individuals. EEG data were analyzed with the event-related potential (ERP), event-related desynchronization and event-related synchronization (ERD/S), as well as coherence and direct transfer function (DTF) methods. Four categories of names were presented visually: one's own, close-other's, famous, and unknown.

RESULTS

Differences between the ASD and control groups were found for ERP, coherence, and DTF. In individuals with ASD, P300 (a positive ERP component) to own-name and to a close-other's name were similar whereas in control participants, P300 to own-name was enhanced when compared to all other names. Analysis of coherence and DTF revealed disruption of fronto-posterior task-related connectivity in individuals with ASD within the beta range frequencies. Moreover, DTF indicated the directionality of those impaired connections-they were going from parieto-occipital to frontal regions. DTF also showed inter-group differences in short-range connectivity: weaker connections within the frontal region and stronger connections within the occipital region in the ASD group in comparison to the control group.

CONCLUSIONS

Our findings suggest a lack of the self-preference effect and impaired functioning of the attentional network during recognition of visually presented names in individuals with ASD.

Name recognition in autism: EEG evidence of altered patterns of brain activity and connectivity

Background

Impaired orienting to social stimuli is one of the core early symptoms of autism spectrum disorder (ASD). However, in contrast to faces, name processing has rarely been studied in individuals with ASD. Here, we investigated brain activity and functional connectivity associated with recognition of names in the high-functioning ASD group and in the control group.

Methods

EEG was recorded in 15 young males with ASD and 15 matched one-to-one control individuals. EEG data were analyzed with the event-related potential (ERP), event-related desynchronization and event-related synchronization (ERD/S), as well as coherence and direct transfer function (DTF) methods. Four categories of names were presented visually: one’s own, close-other’s, famous, and unknown.

Results

Differences between the ASD and control groups were found for ERP, coherence, and DTF. In individuals with ASD, P300 (a positive ERP component) to own-name and to a close-other’s name were similar whereas in control participants, P300 to own-name was enhanced when compared to all other names. Analysis of coherence and DTF revealed disruption of fronto-posterior task-related connectivity in individuals with ASD within the beta range frequencies. Moreover, DTF indicated the directionality of those impaired connections—they were going from parieto-occipital to frontal regions. DTF also showed inter-group differences in short-range connectivity: weaker connections within the frontal region and stronger connections within the occipital region in the ASD group in comparison to the control group.

Conclusions

Our findings suggest a lack of the self-preference effect and impaired functioning of the attentional network during recognition of visually presented names in individuals with ASD.

Electronic supplementary material

The online version of this article (doi:10.1186/s13229-016-0102-z) contains supplementary material, which is available to authorized users.

Sleep and mental disorders: A meta-analysis of polysomnographic research

Investigating sleep in mental disorders has the potential to reveal both disorder-specific and transdiagnostic psychophysiological mechanisms. This meta-analysis aimed at determining the polysomnographic (PSG) characteristics of several mental disorders. Relevant studies were searched through standard strategies. Controlled PSG studies evaluating sleep in affective, anxiety, eating, pervasive developmental, borderline and antisocial personality disorders, attention-deficit-hyperactivity disorder (ADHD), and schizophrenia were included. PSG variables of sleep continuity, depth, and architecture, as well as rapid-eye movement (REM) sleep were considered. Calculations were performed with the "Comprehensive Meta-Analysis" and "R" software. Using random effects modeling, for each disorder and each variable, a separate meta-analysis was conducted if at least 3 studies were available for calculation of effect sizes as standardized means (Hedges' g). Sources of variability, that is, sex, age, and mental disorders comorbidity, were evaluated in subgroup analyses. Sleep alterations were evidenced in all disorders, with the exception of ADHD and seasonal affective disorders. Sleep continuity problems were observed in most mental disorders. Sleep depth and REM pressure alterations were associated with affective, anxiety, autism and schizophrenia disorders. Comorbidity was associated with enhanced REM sleep pressure and more inhibition of sleep depth. No sleep parameter was exclusively altered in 1 condition; however, no 2 conditions shared the same PSG profile. Sleep continuity disturbances imply a transdiagnostic imbalance in the arousal system likely representing a basic dimension of mental health. Sleep depth and REM variables might play a key role in psychiatric comorbidity processes. Constellations of sleep alterations may define distinct disorders better than alterations in 1 single variable. (PsycINFO Database Record

Brain connectivity in autism spectrum disorder

PURPOSE OF REVIEW

Many studies have reported that individuals with autism spectrum disorder (ASD) have different brain connectivity patterns compared with typically developing individuals. However, the results of more recent studies do not unanimously support the traditional view in which individuals with ASD have lower connectivity between distant brain regions and increased connectivity within local brain regions. In this review, we discuss different methods for measuring brain connectivity and how the use of different metrics may contribute to the lack of convergence of investigations of connectivity in ASD.

RECENT FINDINGS

The discrepancy in brain connectivity results across studies may be due to important methodological factors, such as the connectivity measure applied, the age of patients studied, the brain region(s) examined, and the time interval and frequency band(s) in which connectivity was analyzed.

SUMMARY

We conclude that more sophisticated electroencephalography analytic approaches should be utilized to more accurately infer causation and directionality of information transfer between brain regions, which may show dynamic changes of functional connectivity in the brain. Moreover, further investigations of connectivity with respect to behavior and clinical phenotype are needed to probe underlying brain networks implicated in core deficits of ASD.

Epilepsy and Autism

Epilepsy and autistic spectrum disorder frequently coexist in the same individual. Electroencephalogram (EEG) epileptiform activity is also present at a substantially higher rate in children with autism than normally developing children. As with epilepsy, there are a multitude of genetic and environmental factors that can result in autistic spectrum disorder. There is growing consensus from both animal and clinical studies that autism is a disorder of aberrant connectivity. As measured with functional magnetic resonance imaging (MRI) and EEG, the brain in autistic spectrum disorder may be under- or overconnected or have a mixture of over- and underconnectivity. In the case of comorbid epilepsy and autism, an imbalance of the excitatory/inhibitory (E/I) ratio in selected regions of the brain may drive overconnectivity. Understanding the mechanism by which altered connectivity in individuals with comorbid epilepsy and autistic spectrum disorder results in the behaviors specific to the autistic spectrum disorder remains a challenge.

State-Dependent Differences in Functional Connectivity in Young Children With Autism Spectrum Disorder

Background

While there is increasing evidence of altered brain connectivity in autism, the degree and direction of these alterations in connectivity and their uniqueness to autism has not been established. The aim of the present study was to compare connectivity in children with autism to that of typically developing controls and children with developmental delay without autism.

Methods

We assessed EEG spectral power, coherence, phase lag, Pearson and partial correlations, and epileptiform activity during the awake, slow wave sleep, and REM sleep states in 137 children aged 2 to 6 years with autism (n = 87), developmental delay without autism (n = 21), or typical development (n = 29).

Findings

We found that brain connectivity, as measured by coherence, phase lag, and Pearson and partial correlations distinguished children with autism from both neurotypical and developmentally delayed children. In general, children with autism had increased coherence which was most prominent during slow wave sleep.

Interpretation

Functional connectivity is distinctly different in children with autism compared to samples with typical development and developmental delay without autism. Differences in connectivity in autism are state and region related. In this study, children with autism were characterized by a dynamically evolving pattern of altered connectivity.

•

We used EEG to examine the connectivity in young children in awake, rapid eye movement, and slow wave sleep (SWS) states.

•

Differences in coherence between the autism group and the other groups were maximal during SWS.

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Sleep may be the most sensitive time to measure differences in neuro-development before they are observable in behavior.

Shared mechanisms underlie normal healthy sleep and normal brain development. Therefore, we suspect that differences in the way that the brain is behaving during sleep have the potential to tell us about what might be developing incorrectly in people with neurodevelopmental disorders. In addition, sleep evaluations of children allow us to filter out waking distractions, so that we are truly measuring the brain working offline. For instance, the differences in the way the brain was connected that we observed between our three study groups were by far the most notable during slow wave sleep. This finding highlights the importance of taking the state of the brain into account when commenting on the ‘connectedness’ of the brain as a potential biomarker for neurodevelopmental disorders. Future attempts to classify developmental disorders by using differences in connectivity must take into account brain state, whether awake or asleep as well as developmental stage.

Autistic fluid intelligence: Increased reliance on visual functional connectivity with diminished modulation of coupling by task difficulty

Different test types lead to different intelligence estimates in autism, as illustrated by the fact that autistic individuals obtain higher scores on the Raven's Progressive Matrices (RSPM) test than they do on the Wechsler IQ, in contrast to relatively similar performance on both tests in non-autistic individuals. However, the cerebral processes underlying these differences are not well understood. This study investigated whether activity in the fluid “reasoning” network, which includes frontal, parietal, temporal and occipital regions, is differently modulated by task complexity in autistic and non-autistic individuals during the RSPM. In this purpose, we used fMRI to study autistic and non-autistic participants solving the 60 RSPM problems focussing on regions and networks involved in reasoning complexity. As complexity increased, activity in the left superior occipital gyrus and the left middle occipital gyrus increased for autistic participants, whereas non-autistic participants showed increased activity in the left middle frontal gyrus and bilateral precuneus. Using psychophysiological interaction analyses (PPI), we then verified in which regions did functional connectivity increase as a function of reasoning complexity. PPI analyses revealed greater connectivity in autistic, compared to non-autistic participants, between the left inferior occipital gyrus and areas in the left superior frontal gyrus, right superior parietal lobe, right middle occipital gyrus and right inferior temporal gyrus. We also observed generally less modulation of the reasoning network as complexity increased in autistic participants. These results suggest that autistic individuals, when confronted with increasing task complexity, rely mainly on visuospatial processes when solving more complex matrices. In addition to the now well-established enhanced activity observed in visual areas in a range of tasks, these results suggest that the enhanced reliance on visual perception has a central role in autistic cognition.

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Reasoning network is less modulated by problem complexity in autism.

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Autistic individuals rely more extensively on visuospatial processes to solve complex problems.

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Results support the central role of visual perception in autistic cognition.

Anatomic and Functional Connectivity Relationship in Autistic Children During Three Different Experimental Conditions

A group of 21 autistic children were studied for determining the relationship between the anatomic (AC) versus functional (FC) connectivity, considering short-range and long-range brain networks. AC was assessed by the DW-MRI technique and FC by EEG coherence calculation, in three experimental conditions: basal, watching a popular cartoon with audio (V-A), and with muted audio track (VwA). For short-range connections, basal records, statistical significant correlations were found for all EEG bands in the left hemisphere, but no significant correlations were found for fast EEG frequencies in the right hemisphere. For the V-A condition, significant correlations were mainly diminished for the left hemisphere; for the right hemisphere, no significant correlations were found for the fast EEG frequency bands. For the VwA condition, significant correlations for the rapid EEG frequencies mainly disappeared for the right hemisphere. For long-range connections, basal records showed similar correlations for both hemispheres. For the right hemisphere, significant correlations incremented to all EEG bands for the V-A condition, but these significant correlations disappeared for the fast EEG frequencies in the VwA condition. It appears that in a resting-state condition, AC is better associated with functional connectivity for short-range connections in the left hemisphere. The V-A experimental condition enriches the AC and FC association for long-range connections in the right hemisphere. This might be related to an effective connectivity improvement due to full video stimulation (visual and auditory). An impaired audiovisual interaction in the right hemisphere might explain why significant correlations disappeared for the fast EEG frequencies in the VwA experimental condition.

Reduced interhemispheric connectivity in childhood autism detected by electroencephalographic photic driving coherence

The EEG coherence among 14 scalp points during intermittent photic stimulation at 11 fixed frequencies of 3-24 Hz was studied in 14 boys with autism, aged 6-14 years, with relatively intact verbal and intellectual functions, and 19 normally developing boys. The number of interhemispheric coherent connections pertaining to the 20 highest connections of each individual was significantly lower in autistic patients than in the control group at all the EEG beta frequencies corresponding to those of stimulation. The coefficient of coherence values between homologous occipital, parietal and central areas at the same frequencies were also lower in the autistic group in both mono- and bipolar montages due to a deficit in reactive photic driving increase. No differences between the groups were observed in the spontaneous EEG.

QEEG spectral and coherence assessment of autistic children in three different experimental conditions

We studied autistics by quantitative EEG spectral and coherence analysis during three experimental conditions: basal, watching a cartoon with audio (V–A), and with muted audio band (VwA). Significant reductions were found for the absolute power spectral density (PSD) in the central region for delta and theta, and in the posterior region for sigma and beta bands, lateralized to the right hemisphere. When comparing VwA versus the V–A in the midline regions, we found significant decrements of absolute PSD for delta, theta and alpha, and increments for the beta and gamma bands. In autistics, VwA versus V–A tended to show lower coherence values in the right hemisphere. An impairment of visual and auditory sensory integration in autistics might explain our results.

Robust disruptions in electroencephalogram cortical oscillations and large-scale functional networks in autism

BACKGROUND

Autism spectrum disorders (ASD) are increasingly prevalent and have a significant impact on the lives of patients and their families. Currently, the diagnosis is determined by clinical judgment and no definitive physiological biomarker for ASD exists. Quantitative biomarkers obtainable from clinical neuroimaging data - such as the scalp electroencephalogram (EEG) - would provide an important aid to clinicians in the diagnosis of ASD. The interpretation of prior studies in this area has been limited by mixed results and the lack of validation procedures. Here we use retrospective clinical data from a well-characterized population of children with ASD to evaluate the rhythms and coupling patterns present in the EEG to develop and validate an electrophysiological biomarker of ASD.

METHODS

EEG data were acquired from a population of ASD (n = 27) and control (n = 55) children 4-8 years old. Data were divided into training (n = 13 ASD, n = 24 control) and validation (n = 14 ASD, n = 31 control) groups. Evaluation of spectral and functional network properties in the first group of patients motivated three biomarkers that were computed in the second group of age-matched patients for validation.

RESULTS

Three biomarkers of ASD were identified in the first patient group: (1) reduced posterior/anterior power ratio in the alpha frequency range (8-14 Hz), which we label the "peak alpha ratio", (2) reduced global density in functional networks, and (3) a reduction in the mean connectivity strength of a subset of functional network edges. Of these three biomarkers, the first and third were validated in a second group of patients. Using the two validated biomarkers, we were able to classify ASD subjects with 83 % sensitivity and 68 % specificity in a post-hoc analysis.

CONCLUSIONS

This study demonstrates that clinical EEG can provide quantitative biomarkers to assist diagnosis of autism. These results corroborate the general finding that ASD subjects have decreased alpha power gradients and network connectivities compared to control subjects. In addition, this study demonstrates the necessity of using statistical techniques to validate EEG biomarkers identified using exploratory methods.

Sex differences in brain plasticity: a new hypothesis for sex ratio bias in autism

Several observations support the hypothesis that differences in synaptic and regional cerebral plasticity between the sexes account for the high ratio of males to females in autism. First, males are more susceptible than females to perturbations in genes involved in synaptic plasticity. Second, sex-related differences in non-autistic brain structure and function are observed in highly variable regions, namely, the heteromodal associative cortices, and overlap with structural particularities and enhanced activity of perceptual associative regions in autistic individuals. Finally, functional cortical reallocations following brain lesions in non-autistic adults (for example, traumatic brain injury, multiple sclerosis) are sex-dependent. Interactions between genetic sex and hormones may therefore result in higher synaptic and consecutively regional plasticity in perceptual brain areas in males than in females. The onset of autism may largely involve mutations altering synaptic plasticity that create a plastic reaction affecting the most variable and sexually dimorphic brain regions. The sex ratio bias in autism may arise because males have a lower threshold than females for the development of this plastic reaction following a genetic or environmental event.

Intelligence measures and stage 2 sleep in typically-developing and autistic children

The relationship between intelligence measures and 2 EEG measures of non-rapid eye movement sleep, sleep spindles and Sigma activity, was examined in 13 typically-developing (TD) and 13 autistic children with normal IQ and no complaints of poor sleep. Sleep spindles and Sigma EEG activity were computed for frontal (Fp1, Fp2) and central (C3, C4) recording sites. Time in stage 2 sleep and IQ was similar in both groups. Autistic children presented less spindles at Fp2 compared to the TD children. TD children showed negative correlation between verbal IQ and sleep spindle density at Fp2. In the autistic group, verbal and full-scale IQ scores correlated negatively with C3 sleep spindle density. The duration of sleep spindles at Fp1 was shorter in the autistic group than in the TD children. The duration of sleep spindles at C4 was positively correlated with verbal IQ only in the TD group. Fast Sigma EEG activity (13.25-15.75 Hz) was lower at C3 and C4 in autistic children compared to the TD children, particularly in the latter part of the night. Only the TD group showed positive correlation between performance IQ and latter part of the night fast Sigma activity at C4. These results are consistent with a relationship between EEG activity during sleep and cognitive processing in children. The difference between TD and autistic children could derive from dissimilar cortical organization and information processing in these 2 groups.

Alterations in sociability and functional brain connectivity caused by early-life seizures are prevented by bumetanide

There is a well-described association between infantile epilepsy and pervasive cognitive and behavioral deficits, including a high incidence of autism spectrum disorders. Despite the robustness of the relationship between early-life seizures and the development of autism, the pathophysiological mechanism by which this occurs has not been explored. As a result of increasing evidence that autism is a disorder of brain connectivity we hypothesized that early-life seizures would interrupt normal brain connectivity during brain maturation and result in an autistic phenotype. Normal rat pups underwent recurrent flurothyl-induced seizures from postnatal (P)days 5-14 and then tested, along with controls, for developmental alterations of development brain oscillatory activity from P18-P25. Specifically we wished to understand how normal changes in rhythmicity in and between brain regions change as a function of age and if this rhythmicity is altered or interrupted by early life seizures. In rat pups with early-life seizures, field recordings from dorsal and ventral hippocampus and prefrontal cortex demonstrated marked increase in coherence as well as a decrease in voltage correlation at all bandwidths compared to controls while there were minimal differences in total power and relative power spectral densities. Rats with early-life seizures had resulting impairment in the sociability and social novelty tests but demonstrated no evidence of increased activity or generalized anxiety as measured in the open field. In addition, rats with early-life seizures had lower seizure thresholds than controls, indicating long-standing alterations in the excitatory/inhibition balance. Bumetanide, a pharmacological agent that blocks the activity of NKCC1 and induces a significant shift of ECl toward more hyperpolarized values, administration at the time of the seizures precluded the subsequent abnormalities in coherence and voltage correlation and resulted in normal sociability and seizure threshold. Taken together these findings indicate that early-life seizures alter the development of oscillations and result in autistic-like behaviors. The altered communication between these brain regions could reflect the physiological underpinnings underlying social cognitive deficits seen in autism spectrum disorders.

A greater involvement of posterior brain areas in interhemispheric transfer in autism: fMRI, DWI and behavioral evidences

A small corpus callosum (CC) is one of the most replicated neurobiological findings in autism spectrum (AS). However, its effect on interhemispheric (IH) communication is unknown. We combined structural (CC area and DWI), functional (task-related fMRI activation and connectivity analyses) as well as behavioral (Poffenberger and Purdue tasks) measures to investigate IH integration in adult AS individuals of typical intelligence. Despite similar behavioral IH transfer time and performances in bimanual tasks, the CC sub-regions connecting frontal and parietal cortical areas were smaller in AS than in non-AS individuals, while those connecting visual regions were similar. The activation of visual areas was lower in AS than in non-AS individuals during the presentation of visual stimuli. Behavioral IH performances were related to the properties of CC subregions connecting motor areas in non-AS individuals, but to the properties of posterior CC regions in AS individuals. Furthermore, there was greater functional connectivity between visual areas in the AS than in the non-AS group. Levels of connectivity were also stronger in visual than in motor regions in the autistic subjects, while the opposite was true for the non-autistic group. Thus, visual IH transfer plays an important role in visuo-motor tasks in AS individuals. These findings extend the well established enhanced role of perception in autistic cognition to visuo-motor IH information transfer.

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The size of the corpus callosum connecting the motor region is reduced in autism.

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The interhemispheric transfer of visuo-motor information is not impaired in autism.

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In autism, the posterior corpus callosum is more involved than the motor sections.

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Plastic reorganization in autism leads to atypical structure–function relationship.

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The results agree with a greater involvement of perceptual brain areas in autism.

EEG hyper-connectivity in high-risk infants is associated with later autism

Background

It has been previously reported that structural and functional brain connectivity in individuals with autism spectrum disorders (ASD) is atypical and may vary with age. However, to date, no measures of functional connectivity measured within the first 2 years have specifically associated with a later ASD diagnosis.

Methods

In the present study, we analyzed functional brain connectivity in 14-month-old infants at high and low familial risk for ASD using electroencephalography (EEG). EEG was recorded while infants attended to videos. Connectivity was assessed using debiased weighted phase lag index (dbWPLI). At 36 months, the high-risk infants were assessed for symptoms of ASD.

Results

As a group, high-risk infants who were later diagnosed with ASD demonstrated elevated phase-lagged alpha-range connectivity as compared to both low-risk infants and high-risk infants who did not go on to ASD. Hyper-connectivity was most prominent over frontal and central areas. The degree of hyper-connectivity at 14 months strongly correlated with the severity of restricted and repetitive behaviors in participants with ASD at 3 years. These effects were not attributable to differences in behavior during the EEG session or to differences in spectral power.

Conclusions

The results suggest that early hyper-connectivity in the alpha frequency range is an important feature of the ASD neurophysiological phenotype.

Electronic supplementary material

The online version of this article (doi:10.1186/1866-1955-6-40) contains supplementary material, which is available to authorized users.

Linking neocortical, cognitive, and genetic variability in autism with alterations of brain plasticity: the Trigger-Threshold-Target model

The phenotype of autism involves heterogeneous adaptive traits (strengths vs. disabilities), different domains of alterations (social vs. non-social), and various associated genetic conditions (syndromic vs. nonsyndromic autism). Three observations suggest that alterations in experience-dependent plasticity are an etiological factor in autism: (1) the main cognitive domains enhanced in autism are controlled by the most plastic cortical brain regions, the multimodal association cortices; (2) autism and sensory deprivation share several features of cortical and functional reorganization; and (3) genetic mutations and/or environmental insults involved in autism all appear to affect developmental synaptic plasticity, and mostly lead to its upregulation. We present the Trigger-Threshold-Target (TTT) model of autism to organize these findings. In this model, genetic mutations trigger brain reorganization in individuals with a low plasticity threshold, mostly within regions sensitive to cortical reallocations. These changes account for the cognitive enhancements and reduced social expertise associated with autism. Enhanced but normal plasticity may underlie non-syndromic autism, whereas syndromic autism may occur when a triggering mutation or event produces an altered plastic reaction, also resulting in intellectual disability and dysmorphism in addition to autism. Differences in the target of brain reorganization (perceptual vs. language regions) account for the main autistic subgroups. In light of this model, future research should investigate how individual and sex-related differences in synaptic/regional brain plasticity influence the occurrence of autism.

Inter-hemispheric coherence of neocortical gamma oscillations during sleep and wakefulness

Oscillations in the gamma frequency band (mainly ≈40 Hz) of the electroencephalogram (EEG) have been involved in the binding of spatially separated but temporally correlated neural events that result in a unified perceptual experience. The extent of these interactions can be examined by means of a mathematical algorithm called "coherence", which reflects the "strength" of functional interactions between cortical areas. As a continuation of a previous study of our group, the present study was conducted to analyze the inter-hemispheric coherence of the EEG gamma frequency band in the cat during alert wakefulness (AW), quiet wakefulness (QW), non-REM (NREM) sleep and REM sleep. Cats were implanted with electrodes in the frontal, parietal and occipital cortices to monitor EEG activity. The degree of coherence in the low (30-45 Hz) and high (60-100 Hz) gamma frequency bands from pairs of EEG recordings was analyzed. A large increase in coherence between all inter-hemispheric cortical regions in the low gamma bands during AW was present compared to the other behavioral states. Furthermore, both low and high gamma coherence between inter-hemispheric heterotopic cortices (different cortical areas of both hemispheres) decreased during REM sleep; this is a pattern that we previously reported between the cortical areas of the same hemisphere (intrahemispheric coherence). In the high gamma band, coherence during REM sleep also decreased compared to the other behavioral states. In contrast, between most of the inter-hemispheric homotopic cortical areas (equivalent or mirror areas of both hemispheres), low gamma coherence was similar during NREM compared to REM sleep. We conclude that in spite of subtle differences between homotopic and heterotopic inter-hemispheric cortices, functional interactions at high frequency decrease during REM sleep.

Brain hyperconnectivity in children with autism and its links to social deficits

Autism spectrum disorder (ASD), a neurodevelopmental disorder affecting nearly 1 in 88 children, is thought to result from aberrant brain connectivity. Remarkably, there have been no systematic attempts to characterize whole-brain connectivity in children with ASD. Here, we use neuroimaging to show that there are more instances of greater functional connectivity in the brains of children with ASD in comparison to those of typically developing children. Hyperconnectivity in ASD was observed at the whole-brain and subsystems levels, across long- and short-range connections, and was associated with higher levels of fluctuations in regional brain signals. Brain hyperconnectivity predicted symptom severity in ASD, such that children with greater functional connectivity exhibited more severe social deficits. We replicated these findings in two additional independent cohorts, demonstrating again that at earlier ages, the brain of children with ASD is largely functionally hyperconnected in ways that contribute to social dysfunction. Our findings provide unique insights into brain mechanisms underlying childhood autism.

Defining the contribution of CNTNAP2 to autism susceptibility

Multiple lines of genetic evidence suggest a role for CNTNAP2 in autism. To assess its population impact we studied 2148 common single nucleotide polymorphisms (SNPs) using transmission disequilibrium test (TDT) across the entire ~3.3 Mb CNTNAP2 locus in 186 (408 trios) multiplex and 323 simplex families with autistic spectrum disorder (ASD). This analysis yielded two SNPs with nominal statistical significance (rs17170073, p = 2.0 x 10^-4; rs2215798, p = 1.6 x 10^-4) that did not survive multiple testing. In a combined analysis of all families, two highly correlated (r² = 0.99) SNPs in intron 14 showed significant association with autism (rs2710093, p = 9.0 x 10^-6; rs2253031, p = 2.5 x 10^-5). To validate these findings and associations at SNPs from previous autism studies (rs7794745, rs2710102 and rs17236239) we genotyped 2051 additional families (572 multiplex and 1479 simplex). None of these variants were significantly associated with ASD after corrections for multiple testing. The analysis of Mendelian errors within each family did not indicate any segregating deletions. Nevertheless, a study of CNTNAP2 gene expression in brains of autistic patients and of normal controls, demonstrated altered expression in a subset of patients (p = 1.9 x10^-5). Consequently, this study suggests that although CNTNAP2 dysregulation plays a role in some cases, its population contribution to autism susceptibility is limited.

Complexity of spontaneous brain activity in mental disorders

Recent reports of functional and anatomical studies have provided evidence that aberrant neural connectivity lies at the heart of many mental disorders. Information related to neural networks has elucidated the nonlinear dynamical complexity in brain signals over a range of temporal scales. The recent advent of nonlinear analytic methods, which have served for the quantitative description of the brain signal complexity, has provided new insights into aberrant neural connectivity in many mental disorders. Although many studies have underpinned aberrant neural connectivity, findings related to complexity behavior are still inconsistent. This inconsistency might result from (i) heterogeneity in mental disorders, (ii) analytical issues, (iii) interference of typical development and aging. First, most mental disorders are heterogeneous in their clinical feature or intrinsic pathological mechanisms. Second, neurophysiologic output signals from complex brain connectivity might be characterized with multiple time scales or frequencies. Finally, age-related brain complexity changes must be considered when investigating pathological brain because typical brain complexity is not constant across generations. Future systematic studies addressing these issues will greatly expand our knowledge of neural connections and dynamics related to mental disorders.

Comparison of white matter integrity between autism spectrum disorder subjects and typically developing individuals: a meta-analysis of diffusion tensor imaging tractography studies

BACKGROUND

Aberrant brain connectivity, especially with long-distance underconnectivity, has been recognized as a candidate pathophysiology of autism spectrum disorders. However, a number of diffusion tensor imaging studies investigating people with autism spectrum disorders have yielded inconsistent results.

METHODS

To test the long-distance underconnectivity hypothesis, we performed a systematic review and meta-analysis of diffusion tensor imaging studies in subjects with autism spectrum disorder. Diffusion tensor imaging studies comparing individuals with autism spectrum disorders with typically developing individuals were searched using MEDLINE, Web of Science and EMBASE from 1980 through 1 August 2012. Standardized mean differences were calculated as an effect size of the tracts.

RESULTS

A comprehensive literature search identified 25 relevant diffusion tensor imaging studies comparing autism spectrum disorders and typical development with regions-of-interest methods. Among these, 14 studies examining regions of interest with suprathreshold sample sizes were included in the meta-analysis. A random-effects model demonstrated significant fractional anisotropy reductions in the corpus callosum (P = 0.023, n = 387 (autism spectrum disorders/typically developing individuals: 208/179)), left uncinate fasciculus (P = 0.011, n = 242 (117/125)), and left superior longitudinal fasciculus (P = 0.016, n = 182 (96/86)), and significant increases of mean diffusivity in the corpus callosum (P = 0.006, n = 254 (129/125)) and superior longitudinal fasciculus bilaterally (P = 0.031 and 0.011, left and right, respectively, n = 109 (51/58)), in subjects with autism spectrum disorders compared with typically developing individuals with no significant publication bias.

CONCLUSION

The current meta-analysis of diffusion tensor imaging studies in subjects with autism spectrum disorders emphasizes important roles of the superior longitudinal fasciculus, uncinate fasciculus, and corpus callosum in the pathophysiology of autism spectrum disorders and supports the long-distance underconnectivity hypothesis.

Task-related functional connectivity in autism spectrum conditions: an EEG study using wavelet transform coherence

BACKGROUND

Autism Spectrum Conditions (ASC) are a set of pervasive neurodevelopmental conditions characterized by a wide range of lifelong signs and symptoms. Recent explanatory models of autism propose abnormal neural connectivity and are supported by studies showing decreased interhemispheric coherence in individuals with ASC. The first aim of this study was to test the hypothesis of reduced interhemispheric coherence in ASC, and secondly to investigate specific effects of task performance on interhemispheric coherence in ASC.

METHODS

We analyzed electroencephalography (EEG) data from 15 participants with ASC and 15 typical controls, using Wavelet Transform Coherence (WTC) to calculate interhemispheric coherence during face and chair matching tasks, for EEG frequencies from 5 to 40 Hz and during the first 400 ms post-stimulus onset.

RESULTS

Results demonstrate a reduction of interhemispheric coherence in the ASC group, relative to the control group, in both tasks and for all electrode pairs studied. For both tasks, group differences were generally observed after around 150 ms and at frequencies lower than 13 Hz. Regarding within-group task comparisons, while the control group presented differences in interhemispheric coherence between faces and chairs tasks at various electrode pairs (FT7-FT8, TP7-TP8, P7-P8), such differences were only seen for one electrode pair in the ASC group (T7-T8). No significant differences in EEG power spectra were observed between groups.

CONCLUSIONS

Interhemispheric coherence is reduced in people with ASC, in a time and frequency specific manner, during visual perception and categorization of both social and inanimate stimuli and this reduction in coherence is widely dispersed across the brain.Results of within-group task comparisons may reflect an impairment in task differentiation in people with ASC relative to typically developing individuals.Overall, the results of this research support the value of WTC in examining the time-frequency microstructure of task-related interhemispheric EEG coherence in people with ASC.

Task-related functional connectivity in autism spectrum conditions: an EEG study using wavelet transform coherence

Background

Autism Spectrum Conditions (ASC) are a set of pervasive neurodevelopmental conditions characterized by a wide range of lifelong signs and symptoms. Recent explanatory models of autism propose abnormal neural connectivity and are supported by studies showing decreased interhemispheric coherence in individuals with ASC. The first aim of this study was to test the hypothesis of reduced interhemispheric coherence in ASC, and secondly to investigate specific effects of task performance on interhemispheric coherence in ASC.

Methods

We analyzed electroencephalography (EEG) data from 15 participants with ASC and 15 typical controls, using Wavelet Transform Coherence (WTC) to calculate interhemispheric coherence during face and chair matching tasks, for EEG frequencies from 5 to 40 Hz and during the first 400 ms post-stimulus onset.

Results

Results demonstrate a reduction of interhemispheric coherence in the ASC group, relative to the control group, in both tasks and for all electrode pairs studied. For both tasks, group differences were generally observed after around 150 ms and at frequencies lower than 13 Hz. Regarding within-group task comparisons, while the control group presented differences in interhemispheric coherence between faces and chairs tasks at various electrode pairs (FT7-FT8, TP7-TP8, P7-P8), such differences were only seen for one electrode pair in the ASC group (T7-T8). No significant differences in EEG power spectra were observed between groups.

Conclusions

Interhemispheric coherence is reduced in people with ASC, in a time and frequency specific manner, during visual perception and categorization of both social and inanimate stimuli and this reduction in coherence is widely dispersed across the brain.

Results of within-group task comparisons may reflect an impairment in task differentiation in people with ASC relative to typically developing individuals.

Overall, the results of this research support the value of WTC in examining the time-frequency microstructure of task-related interhemispheric EEG coherence in people with ASC.

A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls - a large case control study

BACKGROUND

The autism rate has recently increased to 1 in 100 children. Genetic studies demonstrate poorly understood complexity. Environmental factors apparently also play a role. Magnetic resonance imaging (MRI) studies demonstrate increased brain sizes and altered connectivity. Electroencephalogram (EEG) coherence studies confirm connectivity changes. However, genetic-, MRI- and/or EEG-based diagnostic tests are not yet available. The varied study results likely reflect methodological and population differences, small samples and, for EEG, lack of attention to group-specific artifact.

METHODS

Of the 1,304 subjects who participated in this study, with ages ranging from 1 to 18 years old and assessed with comparable EEG studies, 463 children were diagnosed with autism spectrum disorder (ASD); 571 children were neuro-typical controls (C). After artifact management, principal components analysis (PCA) identified EEG spectral coherence factors with corresponding loading patterns. The 2- to 12-year-old subsample consisted of 430 ASD- and 554 C-group subjects (n = 984). Discriminant function analysis (DFA) determined the spectral coherence factors' discrimination success for the two groups. Loading patterns on the DFA-selected coherence factors described ASD-specific coherence differences when compared to controls.

RESULTS

Total sample PCA of coherence data identified 40 factors which explained 50.8% of the total population variance. For the 2- to 12-year-olds, the 40 factors showed highly significant group differences (P < 0.0001). Ten randomly generated split half replications demonstrated high-average classification success (C, 88.5%; ASD, 86.0%). Still higher success was obtained in the more restricted age sub-samples using the jackknifing technique: 2- to 4-year-olds (C, 90.6%; ASD, 98.1%); 4- to 6-year-olds (C, 90.9%; ASD 99.1%); and 6- to 12-year-olds (C, 98.7%; ASD, 93.9%). Coherence loadings demonstrated reduced short-distance and reduced, as well as increased, long-distance coherences for the ASD-groups, when compared to the controls. Average spectral loading per factor was wide (10.1 Hz).

CONCLUSIONS

Classification success suggests a stable coherence loading pattern that differentiates ASD- from C-group subjects. This might constitute an EEG coherence-based phenotype of childhood autism. The predominantly reduced short-distance coherences may indicate poor local network function. The increased long-distance coherences may represent compensatory processes or reduced neural pruning. The wide average spectral range of factor loadings may suggest over-damped neural networks.

Atypical lexicosemantic function of extrastriate cortex in autism spectrum disorder: evidence from functional and effective connectivity

Previous studies have suggested atypically enhanced activity of visual cortex during language processing in autism spectrum disorder (ASD). However, it remains unclear whether visual cortical participation reflects isolated processing within posterior regions or functional cooperation with distal brain regions, such as left inferior frontal gyrus (LIFG). We addressed this question using functional connectivity MRI (fcMRI) and structural equation modeling in 14 adolescents and adults with ASD and 14 matched typically developing (TD) participants. Data were analyzed to isolate low-frequency intrinsic fluctuations, by regressing out effects of a semantic decision task. For a right extrastriate seed derived from the strongest cluster of atypical activation in the ASD group, widespread effects of increased connectivity in prefrontal and medial frontal lobes bilaterally were observed for the ASD group, compared to the TD group. A second analysis for a seed in LIFG, derived from pooled activation effects in both groups, also yielded widespread effects of overconnectivity in the ASD group, especially in temporal lobes. Structural equation modeling showed that whereas right extrastriate cortex did not impact function of language regions (left and right IFG, left middle temporal gyrus) in the TD model, it was an integral part of a language circuit in the ASD group. These results suggest that atypical extrastriate activation during language processing in ASD reflects integrative (not isolated) processing. Furthermore, our findings are inconsistent with previous reports of functional underconnectivity in ASD, probably related to removal of task effects required to isolate intrinsic low-frequency fluctuations.

Parameters of semantic multisensory integration depend on timing and modality order among people on the autism spectrum: evidence from event-related potentials

Individuals with autism spectrum disorders (ASD) report difficulty integrating simultaneously presented visual and auditory stimuli (Iarocci & McDonald, 2006), albeit showing enhanced perceptual processing of unisensory stimuli, as well as an enhanced role of perception in higher-order cognitive tasks (Enhanced Perceptual Functioning (EPF) model; Mottron, Dawson, Soulières, Hubert, & Burack, 2006). Individuals with an ASD also integrate auditory-visual inputs over longer periods of time than matched typically developing (TD) peers (Kwakye, Foss-Feig, Cascio, Stone & Wallace, 2011). To tease apart the dichotomy of both extended multisensory processing and enhanced perceptual processing, we used behavioral and electrophysiological measurements of audio-visual integration among persons with ASD. 13 TD and 14 autistics matched on IQ completed a forced choice multisensory semantic congruence task requiring speeded responses regarding the congruence or incongruence of animal sounds and pictures. Stimuli were presented simultaneously or sequentially at various stimulus onset asynchronies in both auditory first and visual first presentations. No group differences were noted in reaction time (RT) or accuracy. The latency at which congruent and incongruent waveforms diverged was the component of interest. In simultaneous presentations, congruent and incongruent waveforms diverged earlier (circa 150 ms) among persons with ASD than among TD individuals (around 350 ms). In sequential presentations, asymmetries in the timing of neuronal processing were noted in ASD which depended on stimulus order, but these were consistent with the nature of specific perceptual strengths in this group. These findings extend the Enhanced Perceptual Functioning Model to the multisensory domain, and provide a more nuanced context for interpreting ERP findings of impaired semantic processing in ASD.

Functional connectivity for an "island of sparing" in autism spectrum disorder: an fMRI study of visual search

Although autism is usually characterized with respect to sociocommunicative impairments, visual search is known as a domain of relative performance strength in this disorder. This study used functional MRI during visual search in children with autism spectrum disorder (n = 19; mean age = 13;10) and matched typically developing children (n = 19; mean age = 14;0). We selected regions of interest within two attentional networks known to play a crucial role in visual search processes, such as goal-directed selective attention, filtering of irrelevant distractors, and detection of behaviorally-relevant information, and examined activation and connectivity within and between these attentional networks. Additionally, based on prior research suggesting links between visual search abilities and autism symptomatology, we tested for correlations between sociocommunicative impairments and behavioral and neural indices of search. Contrary to many previous functional connectivity magnetic resonance imaging studies of autism that reported functional underconnectivity for task domains of weakness, we found atypically increased connectivity within and between attentional networks in autism. Additionally, we found increased functional connectivity for occipital regions, both locally and for long-distance connections with frontal regions. Both behavioral and neural indices of search were correlated with sociocommunicative impairment in children with autism. This association suggests that strengths in nonsocial visuospatial processing may be related to the development of core autistic sociocommunicative impairments.