Altered oscillation patterns and connectivity during picture naming in autism

Lack of effects of eight-week left dorsolateral prefrontal theta burst stimulation on white matter macro/microstructure and connection in autism

Whether brain stimulation could modulate brain structure in autism remains unknown. This study explored the impact of continuous theta burst stimulation (cTBS) over the left dorsolateral prefrontal cortex (DLPFC) on white matter macro/microstructure in intellectually able children and emerging adults with autism. Sixty autistic participants were randomized (30 active) and received active or sham cTBS for eight weeks twice per week, 16 total sessions using a double-blind (participant-, rater-, analyst-blinded) design. All participants received high-angular resolution diffusion MR imaging at baseline and week 8. Twenty-eight participants in the active group and twenty-seven in the sham group with good imaging quality entered the final analysis. With longitudinal fixel-based analysis and network-based statistics, we found no significant difference between the active and sham groups in changes of white matter macro/microstructure and connections following cTBS. In addition, we found no association between baseline white matter macro/microstructure and autistic symptom changes from baseline to week 8 in the active group. In conclusion, we did not find a significant impact of left DLPFC cTBS on white matter macro/microstructure and connections in children and emerging adults with autism. These findings need to be interpreted in the context that the current intellectually able cohort in a single university hospital site limits the generalizability. Future studies are required to investigate if higher stimulation intensities and/or doses, other personal factors, or rTMS parameters might confer significant brain structural changes visible on MRI in ASD.

Circuit-level theories for sensory dysfunction in autism: convergence across mouse models

Individuals with autism spectrum disorder (ASD) exhibit a diverse range of behavioral features and genetic backgrounds, but whether different genetic forms of autism involve convergent pathophysiology of brain function is unknown. Here, we analyze evidence for convergent deficits in neural circuit function across multiple transgenic mouse models of ASD. We focus on sensory areas of neocortex, where circuit differences may underlie atypical sensory processing, a central feature of autism. Many distinct circuit-level theories for ASD have been proposed, including increased excitation-inhibition (E-I) ratio and hyperexcitability, hypofunction of parvalbumin (PV) interneuron circuits, impaired homeostatic plasticity, degraded sensory coding, and others. We review these theories and assess the degree of convergence across ASD mouse models for each. Behaviorally, our analysis reveals that innate sensory detection behavior is heightened and sensory discrimination behavior is impaired across many ASD models. Neurophysiologically, PV hypofunction and increased E-I ratio are prevalent but only rarely generate hyperexcitability and excess spiking. Instead, sensory tuning and other aspects of neural coding are commonly degraded and may explain impaired discrimination behavior. Two distinct phenotypic clusters with opposing neural circuit signatures are evident across mouse models. Such clustering could suggest physiological subtypes of autism, which may facilitate the development of tailored therapeutic approaches.

Study subnetwork developing pattern of autism children by non-negative matrix factorization

BACKGROUND

As a developmental disorder, the brain networks of autism children show abnormal patterns compared with that of typically developing. The differences between them are not stable due to the developing progress of children. It has become a choice to study the differences of developing trajectories between autistic and typically developing children by investigating the change of each group respectively. Related researches studied the developing of brain network by analyzing the relationship between network indices of the entire or sub brain networks and the cognitive developing scores.

METHODS

As a matrix decomposition algorithm, non-negative matrix factorization (NMF) was applied to decompose the association matrices of brain networks. By NMF, we can obtain subnetworks in an unsupervised way. The association matrices of autism and control children were estimated by their magnetoencephalography data. NMF was applied to decompose the matrices to obtain common subnetworks of both groups. Then we calculated the expression of each subnetwork in each child's brain network by two indices, energy and entropy. The relationship between the expression and the cognitive and development indices were investigated.

RESULTS

We found a subnetwork with left lateralization pattern in α band showed different expression tendency in two groups. The expression indices of two groups were correlated with cognitive indices in autism and control group in an opposite way. In γ band, a subnetwork with strong connections on right hemisphere of brain showed a negative correlation between the expression indices and development indices in autism group.

CONCLUSION

NMF algorithm can effectively decompose brain network to meaningful subnetworks. The finding of α band subnetworks confirms the results of abnormal lateralization of autistic children mentioned in relevant studies. We assume the results of decrease of expression of the subnetwork may relate to the dysfunction of mirror neuron. The decrease expression of γ subnetwork of autism may be related to the weaken process of high-frequency neurons in the neurotrophic competition.

Inter-trial theta phase consistency during face processing in infants is associated with later emerging autism

A growing body of research suggests that consistency in cortical activity may be a promising neurophysiological marker of autism spectrum disorder (ASD). In the current study we examined inter-trial coherence, a measure of phase consistency across trials, in the theta range (t-ITC: 3-6 Hz), as theta has been implicated in the processing of social and emotional stimuli in infants and adults. The sample included infants who had an older sibling with a confirmed ASD diagnosis and typically developing (TD) infants with no family history of ASD. The data were collected as part of the British Autism Study of Infant Siblings (BASIS) study. Infants between 6 and 10 months of age (M_age  = 7.34, SD_age  = 1.21) performed a visual face processing task that included faces and scrambled, "face noise", stimuli. Follow-up assessments in higher likelihood infants were completed at 24 and again at 36 months to determine diagnostic outcomes. Analysis focused on posterior t-ITC during early (0-200 ms) and late (200-500 ms) visual processing stages commonly investigated in infant studies. t-ITC over posterior scalp regions during late stage face processing was significantly higher in TD and higher likelihood infants without ASD (HRA-), indicating reduced consistency in theta-band responses in higher likelihood infants who eventually receive a diagnosis of ASD (HRA+). These findings indicate that the temporal dynamics of theta during face processing relate to ASD outcomes. Reduced consistency of oscillatory dynamics at basic levels of infant sensory processing could have downstream effects on learning and social communication. LAY SUMMARY: We examined the consistency in brain responses to faces in infants at lower or higher familial likelihood for autism. Our results show that the consistency of EEG responses was lower during face processing in higher likelihood infants who eventually received a diagnosis of autism. These findings highlight that reduced consistency in brain activity during face processing in the first year of life is related to emerging autism.

Sex differences in neuronal systems function and behaviour: beyond a single diagnosis in autism spectrum disorders

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that is associated with functional brain alterations that underlie the expression of behaviour. Males are diagnosed up to four times more than females, and sex differences have been identified in memory, cognitive flexibility, verbal fluency, and social communication. Unfortunately, there exists a lack of information on the sex-dependent mechanisms of ASD, as well as biological markers to distinguish sex-specific symptoms in ASD. This can often result in a standardized diagnosis for individuals across the spectrum, despite significant differences in the various ASD subtypes. Alterations in neuronal connectivity and oscillatory activity, such as is observed in ASD, are highly coupled to behavioural states. Yet, despite the well-identified sexual dimorphisms that exist in ASD, these functional patterns have rarely been analyzed in the context of sex differences or symptomology. This review summarizes alterations in neuronal oscillatory function in ASD, discusses the age, region, symptom and sex-specific differences that are currently observed across the spectrum, and potential targets for regulating neuronal oscillatory activity in ASD. The need to identify sex-specific biomarkers, in order to facilitate specific diagnostic criteria and allow for more targeted therapeutic approaches for ASD will also be discussed.

Altered hippocampal-prefrontal communication during anxiety-related avoidance in mice deficient for the autism-associated gene Pogz

Many genes have been linked to autism. However, it remains unclear what long-term changes in neural circuitry result from disruptions in these genes, and how these circuit changes might contribute to abnormal behaviors. To address these questions, we studied behavior and physiology in mice heterozygous for Pogz, a high confidence autism gene. Pogz+/- mice exhibit reduced anxiety-related avoidance in the elevated plus maze (EPM). Theta-frequency communication between the ventral hippocampus (vHPC) and medial prefrontal cortex (mPFC) is known to be necessary for normal avoidance in the EPM. We found deficient theta-frequency synchronization between the vHPC and mPFC in vivo. When we examined vHPC-mPFC communication at higher resolution, vHPC input onto prefrontal GABAergic interneurons was specifically disrupted, whereas input onto pyramidal neurons remained intact. These findings illustrate how the loss of a high confidence autism gene can impair long-range communication by causing inhibitory circuit dysfunction within pathways important for specific behaviors.

Altered neural oscillations and connectivity in the beta band underlie detail-oriented visual processing in autism

Sensory and perceptual anomalies may have a major impact on basic cognitive and social skills in humans. Autism Spectrum Disorder (ASD) represents a special perspective to explore this relationship, being characterized by both these features. The present study employed electroencephalography (EEG) to test whether detail-oriented visual perception, a recognized hallmark of ASD, is associated with altered neural oscillations and functional connectivity in the beta frequency band, considering its role in feedback and top-down reentrant signalling in the typical population. Using a visual crowding task, where participants had to discriminate a peripheral target letter surrounded by flankers at different distances, we found that detail-oriented processing in children with ASD, as compared to typically developing peers, could be attributed to anomalous oscillatory activity in the beta band (15-30 Hz), while no differences emerged in the alpha band (8-12 Hz). Altered beta oscillatory response reflected in turn atypical functional connectivity between occipital areas, where the initial stimulus analysis is accomplished, and infero-temporal regions, where objects identity is extracted. Such atypical beta connectivity predicted both ASD symptomatology and their detail-oriented processing. Overall, these results might be explained by an altered feedback connectivity within the visual system, with potential cascade effects in visual scene parsing and higher order functions.

Brain connectivity analysis in fathers of children with autism

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder in which changes in brain connectivity, associated with autistic-like traits in some individuals. First-degree relatives of children with autism may show mild deficits in social interaction. The present study investigates electroencephalography (EEG) brain connectivity patterns of the fathers who have children with autism while performing facial emotion labeling task. Fifteen biological fathers of children with the diagnosis of autism (Test Group) and fifteen fathers of neurotypical children with no personal or family history of autism (Control Group) participated in this study. Facial emotion labeling task was evaluated using a set of photos consisting of six categories (mild and extreme: anger, happiness, and sadness). Group Independent Component Analysis method was applied to EEG data to extract neural sources. Dynamic causal connectivity of neural sources signals was estimated using the multivariate autoregressive model and quantified by using the Granger causality-based methods. Statistical analysis showed significant differences (p value < 0.01) in the connectivity of neural sources in recognition of some emotions in two groups, which the most differences observed in the mild anger and mild sadness emotions. Short-range connectivity appeared in Test Group and conversely, long-range and interhemispheric connections are observed in Control Group. Finally, it can be concluded that the Test Group showed abnormal activity and connectivity in the brain network for the processing of emotional faces compared to the Control Group. We conclude that neural source connectivity analysis in fathers may be considered as a potential and promising biomarker of ASD.

Significance of Beta-Band Oscillations in Autism Spectrum Disorders During Motor Response Inhibition Tasks: A MEG Study

In Autism Spectrum Disorders (ASD), impaired response inhibition and lack of adaptation are hypothesized to underlie core ASD symptoms, such as social communication and repetitive, stereotyped behavior. Thus, the aim of the present study was to compare neural correlates of inhibition, post-error adaptation, and reaction time variability in ASD and neuro-typical control (NTC) participants by investigating possible differences in error-related changes of oscillatory MEG activity. Twelve male NTC (mean age 20.3 ± 3.7) and fourteen male patients with ASD (mean age 17.8 ± 2.9) were included in the analysis. Subjects with ASD showed increased error-related reaction time variability. MEG analysis revealed decreased beta power in the ASD group in comparison to the NTC group over the centro-parietal channels in both, the pre-stimulus and post-response interval. In the ASD group, mean centro-parietal beta power negatively correlated with dimensional autism symptoms. In both groups, false alarms were followed by an early increase in temporo-frontal theta to alpha power; and by a later decrease in alpha to beta power at central and posterior sensors. Single trial correlations were additionally studied in the ASD group, who showed a positive correlation of pre-stimulus beta power with post-response theta, alpha, and beta power, particularly after hit trials. On a broader scale, the results deliver important insights into top-down control deficits that may relate to core symptoms observed in ASD.

Brain Network Organization Correlates with Autistic Features in Preschoolers with Autism Spectrum Disorders and in Their Fathers: Preliminary Data from a DWI Analysis

Autism Spectrum Disorders (ASD) is a group of neurodevelopmental disorders that is characterized by an altered brain connectivity organization. Autistic traits below the clinical threshold (i.e., the broad autism phenotype; BAP) are frequent among first-degree relatives of subjects with ASD; however, little is known regarding whether subthreshold behavioral manifestations of ASD mirror also at the neuroanatomical level in parents of ASD probands. To this aim, we applied advanced diffusion network analysis to MRI of 16 dyads consisting of a child with ASD and his father in order to investigate: (i) the correlation between structural network organization and autistic features in preschoolers with ASD (all males; age range 1.5-5.2 years); (ii) the correlation between structural network organization and BAP features in the fathers of individuals with ASD (fath-ASD). Local network measures significantly correlated with autism severity in ASD children and with BAP traits in fath-ASD, while no significant association emerged when considering the global measures of brain connectivity. Notably, an overlap of some brain regions that are crucial for social functioning (cingulum, superior temporal gyrus, inferior temporal gyrus, middle frontal gyrus, frontal pole, and amygdala) in patients with ASD and fath-ASD was detected, suggesting an intergenerational transmission of these neural substrates. Overall, the results of this study may help in elucidating the neurostructural endophenotype of ASD, paving the way for bridging connections between underlying genetic and ASD symptomatology.

Postnatal development and maturation of layer 1 in the lateral prefrontal cortex and its disruption in autism

Autism is a neurodevelopmental connectivity disorder characterized by cortical network disorganization and imbalance in excitation/inhibition. However, little is known about the development of autism pathology and the disruption of laminar-specific excitatory and inhibitory cortical circuits. To begin to address these issues, we examined layer 1 of the lateral prefrontal cortex (LPFC), an area with prolonged development and maturation that is affected in autism. We focused on layer 1 because it contains a distinctive, diverse population of interneurons and glia, receives input from feedback and neuromodulatory pathways, and plays a critical role in the development, maturation, and function of the cortex. We used unbiased quantitative methods at high resolution to study the morphology, neurochemistry, distribution, and density of neurons and myelinated axons in post-mortem brain tissue from children and adults with and without autism. We cross-validated our findings through comparisons with neighboring anterior cingulate cortices and optimally-fixed non-human primate tissue. In neurotypical controls we found an increase in the density of myelinated axons from childhood to adulthood. Neuron density overall declined with age, paralleled by decreased density of inhibitory interneurons labeled by calretinin (CR), calbindin (CB), and parvalbumin (PV). Importantly, we found PV neurons in layer 1 of typically developing children, previously detected only perinatally. In autism there was disorganization of cortical networks within layer 1: children with autism had increased variability in the trajectories and thickness of myelinated axons in layer 1, while adults with autism had a reduction in the relative proportion of thin axons. Neurotypical postnatal changes in layer 1 of LPFC likely underlie refinement of cortical activity during maturation of cortical networks involved in cognition. Our findings suggest that disruption of the maturation of feedback pathways, rather than interneurons in layer 1, has a key role in the development of imbalance between excitation and inhibition in autism.

Motor cortex excitability and inhibitory imbalance in autism spectrum disorder assessed with transcranial magnetic stimulation: a systematic review

Cortical excitation/inhibition (E/I) imbalances contribute to various clinical symptoms observed in autism spectrum disorder (ASD). However, the detailed pathophysiologic underpinning of E/I imbalance remains uncertain. Transcranial magnetic stimulation (TMS) motor-evoked potentials (MEP) are a non-invasive tool for examining cortical inhibition in ASD. Here, we conducted a systematic review on TMS neurophysiology in motor cortex (M1) such as MEPs and short-interval intracortical inhibition (SICI) between individuals with ASD and controls. Out of 538 initial records, we identified six articles. Five studies measured MEP, where four studies measured SICI. There were no differences in MEP amplitudes between the two groups, whereas SICI was likely to be reduced in individuals with ASD compared with controls. Notably, SICI largely reflects GABA(A) receptor-mediated function. Conversely, other magnetic resonance spectroscopy and postmortem methodologies assess GABA levels. The present review demonstrated that there may be neurophysiological deficits in GABA receptor-mediated function in ASD. In conclusion, reduced GABAergic function in the neural circuits could underlie the E/I imbalance in ASD, which may be related to the pathophysiology of clinical symptoms of ASD. Therefore, a novel treatment that targets the neural circuits related to GABA(A) receptor-mediated function in regions involved in the pathophysiology of ASD may be promising.

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.

Toward the Language Oscillogenome

Language has been argued to arise, both ontogenetically and phylogenetically, from specific patterns of brain wiring. We argue that it can further be shown that core features of language processing emerge from particular phasal and cross-frequency coupling properties of neural oscillations; what has been referred to as the language ‘oscillome.’ It is expected that basic aspects of the language oscillome result from genetic guidance, what we will here call the language ‘oscillogenome,’ for which we will put forward a list of candidate genes. We have considered genes for altered brain rhythmicity in conditions involving language deficits: autism spectrum disorders, schizophrenia, specific language impairment and dyslexia. These selected genes map on to aspects of brain function, particularly on to neurotransmitter function. We stress that caution should be adopted in the construction of any oscillogenome, given the range of potential roles particular localized frequency bands have in cognition. Our aim is to propose a set of genome-to-language linking hypotheses that, given testing, would grant explanatory power to brain rhythms with respect to language processing and evolution.

Autistic traits in epilepsy models: Why, when and how?

Autism spectrum disorder (ASD) is a common comorbidity of epilepsy and seizures and/or epileptiform activity are observed in a significant proportion of ASD patients. Current research also implies that autistic traits can be observed to a various degree in mice and rats with seizures. This suggests that there are shared mechanisms in both ASD and epilepsy syndromes. Here, we first review the standard, validated methods used to assess autistic traits in animal models as well as their limitations with regards to epilepsy models. We then discuss two of the potential pathological processes that could be shared between ASD and epilepsy. We first focus on functional implications of neuroinflammation including changes to excitable networks mediated by inflammatory regulators. Finally we examine mechanisms at the cellular and network level involved in neuronal excitability, timing and network coordination that may directly lead to behavioral disturbances present in both epilepsy and ASD. This mini-review summarizes the work first presented at an Investigators Workshop at the 2016 American Epilepsy Society meeting.

Role of inter-trial phase coherence in atypical auditory evoked potentials to speech and nonspeech stimuli in children with autism

OBJECTIVE

This autism study investigated how inter-trial phase coherence (ITPC) drives abnormalities in auditory evoked potential (AEP) responses for speech and nonspeech stimuli.

METHODS

Auditory P1-N2 responses and ITPCs in the theta band (4-7 Hz) for pure tones and words were assessed with EEG data from 15 school-age children with autism and 16 age-matched typically developing (TD) controls.

RESULTS

The autism group showed enhanced P1 and reduced N2 for both speech and nonspeech stimuli in comparison with the TD group. Group differences were also found with enhanced theta ITPC for P1 followed by ITPC reduction for N2 in the autism group. The ITPC values were significant predictors of P1 and N2 amplitudes in both groups.

CONCLUSIONS

Abnormal trial-to-trial phase synchrony plays an important role in AEP atypicalities in children with autism. ITPC-driven enhancement as well as attenuation in different AEP components may coexist, depending on the stage of information processing.

SIGNIFICANCE

It is necessary to examine the time course of auditory evoked potentials and the corresponding inter-trial coherence of neural oscillatory activities to better understand hyper- and hypo- sensitive responses in autism, which has important implications for sensory based treatment.

Stimulus dependent neural oscillatory patterns show reliable statistical identification of autism spectrum disorder in a face perceptual decision task

OBJECTIVE

Electroencephalographic biomarkers have been widely investigated in autism, in the search for diagnostic, prognostic and therapeutic outcome measures. Here we took advantage of the information available in temporal oscillatory patterns evoked by simple perceptual decisions to investigate whether stimulus dependent oscillatory signatures can be used as potential biomarkers in autism spectrum disorder (ASD).

METHODS

We studied an extensive set of stimuli (9 categories of faces) and performed data driven classification (Support vector machine, SVM) of ASD vs. Controls with features based on the EEG power responses. We carried out an extensive time-frequency and synchrony analysis of distinct face categories requiring different processing mechanisms in terms of non-holistic vs. holistic processing.

RESULTS

We found that the neuronal oscillatory responses of low gamma frequency band, locked to photographic and abstract two-tone (Mooney) face stimulus presentation are decreased in ASD vs. the control group. We also found decreased time-frequency (TF) responses in the beta band in ASD after 350 ms, possibly related to motor preparation. On the other hand, synchrony in the 30-45 Hz band showed a distinct spatial pattern in ASD. These power changes enabled accurate classification of ASD with an SVM approach. SVM accuracy was approximately 85%. ROC curves showed about 94% AUC (area under the curve). Combination of Mooney and Photographic face stimuli evoked features enabled a better separation between groups, reaching an AUC of 98.6%.

CONCLUSION

We identified a relative decrease in EEG responses to face stimuli in ASD in the beta (15-30 Hz; >350 ms) and gamma (30-45 Hz; 55-80 Hz; 50-350 ms) frequency ranges. These can be used as input of a machine learning approach to separate between groups with high accuracy.

SIGNIFICANCE

Future studies can use EEG time-frequency patterns evoked by particular types of faces as a diagnostic biomarker and potentially as outcome measures in therapeutic trials.

Ripe for solution: Delayed development of multisensory processing in autism and its remediation

Difficulty integrating inputs from different sensory sources is commonly reported in individuals with Autism Spectrum Disorder (ASD). Accumulating evidence consistently points to altered patterns of behavioral reactions and neural activity when individuals with ASD observe or act upon information arriving through multiple sensory systems. For example, impairments in the integration of seen and heard speech appear to be particularly acute, with obvious implications for interpersonal communication. Here, we explore the literature on multisensory processing in autism with a focus on developmental trajectories. While much remains to be understood, some consistent observations emerge. Broadly, sensory integration deficits are found in children with an ASD whereas these appear to be much ameliorated, or even fully recovered, in older teenagers and adults on the spectrum. This protracted delay in the development of multisensory processing raises the possibility of applying early intervention strategies focused on multisensory integration, to accelerate resolution of these functions. We also consider how dysfunctional cross-sensory oscillatory neural communication may be one key pathway to impaired multisensory processing in ASD.

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.

Inter-trial Coherence of Medial Frontal Theta Oscillations Linked to Differential Feedback Processing in Youth and Young Adults with Autism

BACKGROUND

Impairment in prediction and appreciation for choice outcomes could contribute to several core symptoms of ASD. We examined electroencephalography (EEG) oscillations in 27 youth and young adults diagnosed with autism spectrum disorder (ASD) and 22 IQ-matched neurotypical controls while they performed a chance-based reward prediction task.

METHOD

We re-analyzed our previously published ERP data (Larson et al., 2011) and examined theta band oscillations (4-8 Hz) at frontal midline sites, within a timing window that overlaps with the feedback-related negativity (FRN). We focused on event-related changes after presentation of feedback for reward (WIN) and punitive (LOSE) outcomes, both for spectral power and inter-trial phase coherence.

RESULTS

In our reward prediction task, for both groups, medial frontal theta power and phase coherence were greater following LOSE compared to WIN feedback. However, compared to controls, inter-trial coherence of medial frontal theta was significantly lower overall (across both feedback types) for individuals with ASD. Our results indicate that while individuals with ASD are sensitive to the valence of reward feedback, comparable to their neurotypical peers, they have reduced synchronization of medial frontal theta activity during feedback processing.

CONCLUSIONS

This finding are consistent with previous studies showing neural variability in ASD and suggest that the processes underlying decision-making and reinforcement learning may be atypical and less efficient in ASD.

Brain oscillations and connectivity in autism spectrum disorders (ASD): new approaches to methodology, measurement and modelling

Although atypical social behaviour remains a key characterisation of ASD, the presence of sensory and perceptual abnormalities has been given a more central role in recent classification changes. An understanding of the origins of such aberrations could thus prove a fruitful focus for ASD research. Early neurocognitive models of ASD suggested that the study of high frequency activity in the brain as a measure of cortical connectivity might provide the key to understanding the neural correlates of sensory and perceptual deviations in ASD. As our review shows, the findings from subsequent research have been inconsistent, with a lack of agreement about the nature of any high frequency disturbances in ASD brains. Based on the application of new techniques using more sophisticated measures of brain synchronisation, direction of information flow, and invoking the coupling between high and low frequency bands, we propose a framework which could reconcile apparently conflicting findings in this area and would be consistent both with emerging neurocognitive models of autism and with the heterogeneity of the condition.

The Broad Autism (Endo)Phenotype: Neurostructural and Neurofunctional Correlates in Parents of Individuals with Autism Spectrum Disorders

Autism Spectrum Disorders (ASD) are a set of neurodevelopmental disorders with an early-onset and a strong genetic component in their pathogenesis. According to genetic and epidemiological data, ASD relatives present personality traits similar to, but not as severe as the defining features of ASD, which have been indicated as the "Broader Autism Phenotype" (BAP). BAP features seem to be more prevalent in first-degree relatives of individuals with ASD than in the general population. Characterizing brain profiles of relatives of autistic probands may help to understand ASD endophenotype. The aim of this review was to provide an up-to-date overview of research findings on the neurostructural and neurofunctional substrates in parents of individuals with ASD (pASD). The primary hypothesis was that, like for the behavioral profile, the pASD express an intermediate neurobiological pattern between ASD individuals and healthy controls. The 13 reviewed studies evaluated structural magnetic resonance imaging (MRI) brain volumes, chemical signals using magnetic resonance spectroscopy (MRS), task-related functional activation by functional magnetic resonance imaging (fMRI), electroencephalography (EEG), or magnetoencephalography (MEG) in pASD.The studies showed that pASD are generally different from healthy controls at a structural and functional level despite often not behaviorally impaired. More atypicalities in neural patterns of pASD seem to be associated with higher scores at BAP assessment. Some of the observed atypicalities are the same of the ASD probands. In addition, the pattern of neural correlates in pASD resembles that of adult individuals with ASD, or it is specific, possibly due to a compensatory mechanism. Future studies should ideally include a group of pASD and HC with their ASD and non-ASD probands respectively. They should subgrouping the pASD according to the BAP scores, considering gender as a possible confounding factor, and correlating these scores to underlying brain structure and function. These types of studies may help to understand the genetic mechanisms involved in the various clinical dimension of ASD.

Dysfunction of sensory oscillations in Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is a highly prevalent developmental disability characterized by deficits in social communication and interaction, restricted interests, and repetitive behaviors. Recently, anomalous sensory and perceptual function has gained an increased level of recognition as an important feature of ASD. A specific impairment in the ability to integrate information across brain networks has been proposed to contribute to these disruptions. A crucial mechanism for these integrative processes is the rhythmic synchronization of neuronal excitability across neural populations; collectively known as oscillations. In ASD there is believed to be a deficit in the ability to efficiently couple functional neural networks using these oscillations. This review discusses evidence for disruptions in oscillatory synchronization in ASD, and how disturbance of this neural mechanism contributes to alterations in sensory and perceptual function. The review also frames oscillatory data from the perspective of prevailing neurobiologically-inspired theories of ASD.

Measuring neural excitation and inhibition in autism: Different approaches, different findings and different interpretations

The balance of neural excitation and inhibition (E/I balance) is often hypothesised to be altered in autism spectrum disorder (ASD). One widely held view is that excitation levels are elevated relative to inhibition in ASD. Understanding whether, and how, E/I balance may be altered in ASD is important given the recent interest in trialling pharmacological interventions for ASD which target inhibitory neurotransmitter function. Here we provide a critical review of evidence for E/I balance in ASD. We conclude that data from a number of domains provides support for alteration in excitation and inhibitory neurotransmission in ASD, but when considered collectively, the available literature provide little evidence to support claims for either a net increase in excitation or a net increase in inhibition. Strengths and limitations of available techniques are considered, and directions for future research discussed.

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

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

SIGNIFICANCE STATEMENT

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

The Oscillopathic Nature of Language Deficits in Autism: From Genes to Language Evolution

Autism spectrum disorders (ASD) are pervasive neurodevelopmental disorders involving a number of deficits to linguistic cognition. The gap between genetics and the pathophysiology of ASD remains open, in particular regarding its distinctive linguistic profile. The goal of this article is to attempt to bridge this gap, focusing on how the autistic brain processes language, particularly through the perspective of brain rhythms. Due to the phenomenon of pleiotropy, which may take some decades to overcome, we believe that studies of brain rhythms, which are not faced with problems of this scale, may constitute a more tractable route to interpreting language deficits in ASD and eventually other neurocognitive disorders. Building on recent attempts to link neural oscillations to certain computational primitives of language, we show that interpreting language deficits in ASD as oscillopathic traits is a potentially fruitful way to construct successful endophenotypes of this condition. Additionally, we will show that candidate genes for ASD are overrepresented among the genes that played a role in the evolution of language. These genes include (and are related to) genes involved in brain rhythmicity. We hope that the type of steps taken here will additionally lead to a better understanding of the comorbidity, heterogeneity, and variability of ASD, and may help achieve a better treatment of the affected populations.

Cognitive Deficits Associated with Nav1.1 Alterations: Involvement of Neuronal Firing Dynamics and Oscillations

Brain oscillations play a critical role in information processing and may, therefore, be essential to uncovering the mechanisms of cognitive impairment in neurological disease. In Dravet syndrome (DS), a mutation in SCN1A, coding for the voltage-gated sodium channel Nav1.1, is associated with severe cognitive impairment and seizures. While seizure frequency and severity do not correlate with the extent of impairment, the slowing of brain rhythms may be involved. Here we investigate the role of Nav1.1 on brain rhythms and cognition using RNA interference. We demonstrate that knockdown of Nav1.1 impairs fast- and burst-firing properties of neurons in the medial septum in vivo. The proportion of neurons that fired phase-locked to hippocampal theta oscillations was reduced, and medial septal regulation of theta rhythm was disrupted. During a working memory task, this deficit was characterized by a decrease in theta frequency and was negatively correlated with performance. These findings suggest a fundamental role for Nav1.1 in facilitating fast-firing properties in neurons, highlight the importance of precise temporal control of theta frequency for working memory, and imply that Nav1.1 deficits may disrupt information processing in DS via a dysregulation of brain rhythms.

Electrophysiological biomarkers of diagnosis and outcome in neurodevelopmental disorders

PURPOSE OF REVIEW

The heterogeneity in clinical presentation and outcome in neurodevelopmental disorders such as attention deficit hyperactivity disorder (ADHD) autism spectrum disorder (ASD) necessitates the identification and validation of biomarkers that can guide diagnosis, predict developmental outcomes, and monitor treatment response. Electrophysiology holds both practical and theoretical advantages as a clinical biomarker in neurodevelopmental disorders, and considerable effort has been invested in the search for electroencephalography (EEG) biomarkers in ADHD and ASD.

RECENT FINDINGS

Here, we discuss the major themes in the evaluation of biomarkers and then review studies that have applied EEG to better inform diagnosis, focusing on the controversy surrounding the theta:beta ratio in ADHD; prediction of risk, highlighting recent studies of infants at high risk for ASD; and treatment monitoring, presenting new efforts in the redefinition of outcome measures in clinical trials of ASD treatment.

SUMMARY

We conclude that insights gained from EEG studies will contribute significantly to a more mechanistic understanding of these disorders and to the development of biomarkers that can assist with diagnosis, prognosis, and intervention. There is a need, however, to utilize approaches that accommodate, rather than ignore, diagnostic heterogeneity and individual differences.

Behavioral, perceptual, and neural alterations in sensory and multisensory function in autism spectrum disorder

Although sensory processing challenges have been noted since the first clinical descriptions of autism, it has taken until the release of the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) in 2013 for sensory problems to be included as part of the core symptoms of autism spectrum disorder (ASD) in the diagnostic profile. Because sensory information forms the building blocks for higher-order social and cognitive functions, we argue that sensory processing is not only an additional piece of the puzzle, but rather a critical cornerstone for characterizing and understanding ASD. In this review we discuss what is currently known about sensory processing in ASD, how sensory function fits within contemporary models of ASD, and what is understood about the differences in the underlying neural processing of sensory and social communication observed between individuals with and without ASD. In addition to highlighting the sensory features associated with ASD, we also emphasize the importance of multisensory processing in building perceptual and cognitive representations, and how deficits in multisensory integration may also be a core characteristic of ASD.

Whole-brain functional hypoconnectivity as an endophenotype of autism in adolescents

Endophenotypes are heritable and quantifiable markers that may assist in the identification of the complex genetic underpinnings of psychiatric conditions. Here we examined global hypoconnectivity as an endophenotype of autism spectrum conditions (ASCs). We studied well-matched groups of adolescent males with autism, genetically-related siblings of individuals with autism, and typically-developing control participants. We parcellated the brain into 258 regions and used complex-network analysis to detect a robust hypoconnectivity endophenotype in our participant group. We observed that whole-brain functional connectivity was highest in controls, intermediate in siblings, and lowest in ASC, in task and rest conditions. We identified additional, local endophenotype effects in specific networks including the visual processing and default mode networks. Our analyses are the first to show that whole-brain functional hypoconnectivity is an endophenotype of autism in adolescence, and may thus underlie the heritable similarities seen in adolescents with ASC and their relatives.

Event-related potentials to repeated speech in 9-month-old infants at risk for autism spectrum disorder

Background

Atypical neural responses to repeated auditory and linguistic stimuli have been reported both in individuals with autism spectrum disorder (ASD) and their first-degree relatives. Recent work suggests that the younger siblings of children with ASD have atypical event-related potentials (ERPs) to repeated tones at 9 months of age; however, the functional significance is unclear, and it is unknown whether this atypicality is also present in response to linguistic stimuli.

Methods

We analyzed ERPs to repetitive and deviant consonant-vowel stimuli at 9 months in 35 unaffected high-risk-for-autism (HRA) infant siblings of children with ASD and 45 low-risk control (LRC) infants. We examined a positive component, the P150, over frontal and central electrode sites and investigated the relationships between this component and later behavior.

Results

Over frontal electrodes, HRA infants had larger-amplitude ERPs to repetitions of the standard than LRC infants, whereas ERPs to the deviant did not differ between HRA and LRC infants. Furthermore, for HRA infants, the amplitude of ERPs to the standards was positively correlated with later language ability.

Conclusions

Our work suggests that atypical ERPs to repeated speech during infancy are a possible endophenotype of ASD but that this atypicality is associated with beneficial, rather than disordered, language development. Potential mechanisms driving these relationships and implications for development are discussed.

γ-band abnormalities as markers of autism spectrum disorders

Autism is a behaviorally diagnosed neurodevelopmental disorder with no current biomarkers with high specificity and sensitivity. γ-band abnormalities have been reported in many studies of autism spectrum disorders. γ-band activity is associated with perceptual and cognitive functions that are compromised in autism. Some γ-band deficits have also been seen in unaffected first-degree relatives, suggesting heritability of these findings. This review covers the published literature on γ abnormalities in autism, the proposed mechanisms underlying the deficits and the potential for translation into new treatments. Although the utility of γ-band metrics as diagnostic biomarkers is currently limited, such changes in autism are also useful as endophenotypes, for evaluating potential neural mechanisms, and for use as surrogate markers of treatment response to interventions.

A dual comparative approach: integrating lines of evidence from human evolutionary neuroanatomy and neurodevelopmental disorders

The evolution of the human brain has been marked by a nearly 3-fold increase in size since our divergence from the last common ancestor shared with chimpanzees and bonobos. Despite increased interest in comparative neuroanatomy and phylogenetic methods, relatively little is known regarding the effects that this enlargement has had on its internal organization, and how certain areas of the brain have differentially expanded over evolutionary time. Analyses of the microstructure of several regions of the human cortex and subcortical structures have demonstrated subtle changes at the cellular and molecular level, suggesting that the human brain is more than simply a 'scaled-up' primate brain. Ongoing research in comparative neuroanatomy has much to offer regarding our understanding of human brain evolution. Through analysis of the neuroanatomical phenotype at the level of reorganization in cytoarchitecture and cellular morphology, new data continue to highlight changes in cell density and organization associated with volumetric changes in discrete regions. An understanding of the functional significance of variation in neural circuitry can further be approached through studies of atypical human development. Many neurodevelopmental disorders cause disruption in systems associated with uniquely human features of cognition, including language and social cognition. Understanding the genetic and developmental mechanisms that underlie variation in the human cognitive phenotype can help to clarify the functional significance of interspecific variation. By uniting approaches from comparative neuroanatomy and neuropathology, insights can be gained that clarify trends in human evolution. Here, we explore these lines of evidence and their significance for understanding functional variation between species as well as within neuropathological variation in the human brain.

Gamma deficits as a neural signature of cognitive impairment in children treated for brain tumors

Cognitive impairment is consistently reported in children treated for brain tumors, particularly in the categories of processing speed, memory, and attention. Although tumor site, hydrocephalus, chemotherapy, and cranial radiation therapy (CRT) are all associated with poorer function, CRT predicts the greatest deficits. There is a particularly high correlation between CRT and slowed information-processing speed. Cortical gamma-band oscillations have been associated with processing behaviorally relevant information; however, their role in the maintenance of cognition in individuals with processing deficits is unclear. We examined gamma oscillations using magnetoencephalography (MEG) in children undergoing CRT to test whether gamma characteristics can be a signature of cognitive impairment in this population. We collected resting-state data as well as data from baseline and active periods during two visual-motor reaction time tasks of varying cognitive loads from 18 healthy children and 20 patients. We found that only high-gamma oscillations (60-100 Hz), and not low-gamma oscillations (30-59 Hz), showed significant group differences in absolute power levels. Overall, compared with healthy children, patients showed the following: (1) lower total high-gamma (60-100 Hz) power during the resting state, as well as during task-related baseline and performance measures; (2) no change in gamma reactivity to increases in cognitive load; and (3) slower processing speeds both inside and outside MEG. Our findings show that high-gamma oscillations are disrupted in children after treatment for a brain tumor. The temporal dynamic of the high-gamma response during information processing may index cognitive impairment in humans with neurological injury.

Elucidating the neurophysiological underpinnings of autism spectrum disorder: new developments

The study of neurophysiological approaches together with rare and common risk factors for Autism Spectrum Disorder (ASD) allows elucidating the specific underlying neurobiology of ASD. Whereas most neurophysiologically based research in ASD to date has focussed on case-control differences based on the DSM- or ICD-based categorical ASD diagnosis, more recent studies have aimed at studying genetically and/or neurophysiologically defined homogeneous ASD subgroups for specific neuronal biomarkers. This review addresses the neurophysiological investigation of ASD by evoked and event-related potentials, by EEG/MEG connectivity measures such as coherence, and transcranial magnetic stimulation. As an example of classical neurophysiological studies in ASD, we report event-related potential studies which have illustrated which brain areas and processing stages are affected in the visual perception of socially relevant stimuli. However, a paradigm shift has taken place in recent years focussing on how these findings can be tracked down to basic neuronal functions such as deficits in cortico-cortical connectivity and the interaction between brain areas. Disconnectivity, for example, can again be related to genetically induced shifts in the excitation/inhibition balance. Genetic causes of ASD may be grouped by their effects on the brain's system level to identify ASD subgroups which respond differentially to therapeutic interventions.

The implications of brain connectivity in the neuropsychology of autism

Autism is a neurodevelopmental disorder that has been associated with atypical brain functioning. Functional connectivity MRI (fcMRI) studies examining neural networks in autism have seen an exponential rise over the last decade. Such investigations have led to the characterization of autism as a distributed neural systems disorder. Studies have found widespread cortical underconnectivity, local overconnectivity, and mixed results suggesting disrupted brain connectivity as a potential neural signature of autism. In this review, we summarize the findings of previous fcMRI studies in autism with a detailed examination of their methodology, in order to better understand its potential and to delineate the pitfalls. We also address how a multimodal neuroimaging approach (incorporating different measures of brain connectivity) may help characterize the complex neurobiology of autism at a global level. Finally, we also address the potential of neuroimaging-based markers in assisting neuropsychological assessment of autism. The quest for a neural marker for autism is still ongoing, yet new findings suggest that aberrant brain connectivity may be a promising candidate.