Brain connectivity in autism spectrum disorder

The Association Between Somatic Health, Autism Spectrum Disorder, and Autistic Traits

This study used a twin cohort to investigate the association of autism spectrum disorder (ASD) and autistic traits with somatic health. A total of 344 twins (172 pairs; mean age 15.56 ± 5.62 years) enriched for ASD and other neurodevelopmental conditions were examined. Medical history and current physical problems were collected with a validated questionnaire to determine twin’s somatic health. The Social Responsiveness Scale (SRS-2) was used to measure the participant’s severity of autistic traits. Identified somatic health issues with significant within-twin pair differences were tested in relation to both ASD diagnosis and autistic traits in a co-twin control model. Twins with ASD exhibited more neurological and immunological health problems compared to those without ASD (p = 0.005 and p = 0.004, respectively). The intra-pair differences of neurological conditions and SRS-2 score were significantly correlated in monozygotic twins differing for autism traits (r = 0.40, p = 0.001), while the correlation was not found for immunological problems. In addition, a conditional model for analysis of within-twin pair effects revealed an association between neurological problems and clinical ASD diagnosis (Odds ratio per neurological problem 3.15, p = 0.02), as well as autistic traits (β = 10.44, p = 0.006), after adjusting for possible effects of co-existing attention deficit hyperactivity disorder and general intellectual abilities. Our findings suggest that neurological problems are associated with autism, and that non-shared environmental factors contribute to the overlap for both clinical ASD and autistic traits. Further population-based twin studies are warranted to validate our results and examine in detailed the shared genetic and environmental contributions of neurological problems and ASD.

Is There a Hemispheric Disconnect in Neurodevelopmental Disorders?

The CYFIP1 gene has been linked to autism and schizophrenia and, while there is a noted heterogeneity, both have been characterized to be disorders of connectivity. Recent studies by Dominquez-Iturza et al. and Silva et al. provide direct evidence for CYFIP1 in functional and structural connectivity in the brain.

Molecular biology of autism's etiology - An alternative mechanism

Autism is a neuropathologic condition believed to be the consequence of cerebral dysconnectivity. Hypomyelination of axons in brain nerve pathways parallels behavioral abnormalities characteristic of autism. The present discussion will examine the functional association of insulin-like growth factor-1 (IGF1) to neo-neuron myelination, especially in autistic children. These structural defects apparently correlate with a reduced level of circulating IGF. In addition, the potential connection of single nucleotide polymorphism to the etiology of autism is considered. Pharmaceutical and nutritional supplements that may enhance IGF1 to reduce the incidence of autism are proposed.

Power spectrum of spontaneous cerebral homodynamic oscillation shows a distinct pattern in autism spectrum disorder

Spontaneous hemodynamic fluctuations recorded by functional near-infrared spectroscopy (fNIRS) from bilateral temporal lobes were analyzed on 25 children with autism spectrum disorder (ASD) and 22 typically developing (TD) children. By frequency domain analysis, a new characteristic was uncovered that the power spectrum of low frequency cerebral hemodynamic oscillation showed a distinct pattern in ASD. More specifically, at the frequency of 0.0200 Hz, the power of oxygenated hemoglobin was larger for TD than ASD, whereas in the band of 0.0267-0.0333 Hz, the power of deoxygenated hemoglobin was larger for ASD than TD. Using these new features and those identified previously together as feature variables for the support vector machine (SVM) classifier, accurate classification between ASD and TD was achieved with a sensitivity of 90.2%, specificity of 95.1% and accuracy of 92.7%.

Family-based exome sequencing and case-control analysis implicate CEP41 as an ASD gene

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder with a strong genetic component. Although next-generation sequencing (NGS) technologies have been successfully applied to gene identification in de novo ASD, the genetic architecture of familial ASD remains largely unexplored. Our approach, which leverages the high specificity and sensitivity of NGS technology, has focused on rare variants in familial autism. We used NGS exome sequencing in 26 families with distantly related affected individuals to identify genes with private gene disrupting and missense variants of interest (VOI). We found that the genes carrying VOIs were enriched for biological processes related to cell projection organization and neuron development, which is consistent with the neurodevelopmental hypothesis of ASD. For a subset of genes carrying VOIs, we then used targeted NGS sequencing and gene-based variant burden case-control analysis to test for association with ASD. Missense variants in one gene, CEP41, associated significantly with ASD (p = 6.185^e-05). Homozygous gene-disrupting variants in CEP41 were initially found to be responsible for recessive Joubert syndrome. Using a zebrafish model, we evaluated the mechanism by which the CEP41 variants might contribute to ASD. We found that CEP41 missense variants affect development of the axonal tract, cranial neural crest migration and social behavior phenotype. Our work demonstrates the involvement of CEP41 heterozygous missense variants in ASD and that biological processes involved in cell projection organization and neuron development are enriched in ASD families we have studied.

EEG Data Collection in Children with ASD: The Role of State in Data Quality and Spectral Power

BACKGROUND

Electroencephalography can elucidate neurobiological mechanisms underlying heterogeneity in ASD. Studying the full range of children with ASD introduces methodological challenges stemming from participants' difficulties tolerating the data collection process, leading to diminished EEGdataretentionandincreasedvariabilityin participant 'state' during the recording. Quantifying state will improve data collection methods and aide in interpreting results.

OBJECTIVES

Observationally quantify participant state during the EEG recording; examine its relationship to child characteristics, data retention and spectral power.

METHODS

Participants included 5-11 year-old children with D (N=39) and age-matched TD children (N=16). Participants were acclimated to the EEG environment using behavioral strategies. EEG was recorded while participants watched a video of bubbles. Participant 'state' was rated using a Likert scale (Perceived State Rating: PSR).

RESULTS

Participants with ASD had more elevated PSR than TD participants. Less EEG data were retained in participants with higher PSR scores, but this was not related to age or IQ. TD participants had higher alpha power compared with the ASD group. Within the ASD group, participants with high PSR had decreased frontal alpha power.

CONCLUSIONS

Given supportive strategies, EEG data was collected from children with ASD across cognitive levels. Participant state influenced both EEG data retention and alpha spectral power. Alpha suppression is linked to attention and vigilance, suggesting that these participants were less 'at rest'. This highlights the importance of considering state when conducting EEG studies with challenging participants, both to increase data retention rates and to quantify the influence of state on EEG variables.

Aberrant Development and Synaptic Transmission of Cerebellar Cortex in a VPA Induced Mouse Autism Model

Autistic spectral disorder (ASD) is a prevalent neurodevelopmental disease that affects multiple brain regions. Both clinical and animal studies have revealed the possible involvement of the cerebellum in ASD pathology. In this study, we generated a rodent ASD model through a single prenatal administration of valproic acid (VPA) into pregnant mice, followed by cerebellar morphological and functional studies of the offspring. Behavioral studies showed that VPA exposure led to retardation of critical motor reflexes in juveniles and impaired learning in a tone-conditioned complex motor task in adults. These behavioral phenotypes were associated with premature migration and excess apoptosis of the granular cell (GC) precursor in the cerebellar cortex during the early postnatal period, and the decreased cell density and impaired dendritic arborization of the Purkinje neurons. On acute cerebellar slices, suppressed synaptic transmission of the Purkinje cells were reported in the VPA-treated mice. In summary, converging evidence from anatomical, electrophysiological and behavioral abnormalities in the VPA-treated mice suggest cerebellar pathology in ASD and indicate the potential values of motor dysfunction in the early diagnosis of ASD.

Sex-Dependent Motor Deficit and Increased Anxiety-Like States in Mice Lacking Autism-Associated Gene Slit3

Altered neuronal connectivity has been implicated in the pathophysiology of Autism Spectrum Disorder (ASD). SLIT/ROBO signaling plays an important role in developmental processes of neuronal connectivity, including axon guidance, neuronal migration, and axonal and dendritic branching. Genetic evidence supports that SLIT3, one of the genes encoding SLITs, is associated with ASD. Yet the causal link between SLIT3 mutation and autism symptoms has not been examined. Here we assessed ASD-associated behaviors in Slit3 knockout (KO) mice. Our data showed that Slit3-KO mice exhibited reduced marble burying behaviors but normal social behaviors. In addition, Slit3-KO mice displayed hypolocomotion in the open field test and impaired motor coordination in the rotarod test. Anxiety-like behaviors were mainly observed in female KO mice assessed by three types of behavioral tests, namely, the open field test, elevated plus maze test, and light/dark box test. No differences were observed between KO and wildtype mice in recognition memory in the novel object recognition test or depression-like behavior in the tail suspension test. Taken together, loss of Slit3 may result in disrupted neural circuits related to motor function and increased anxiety-like states, which are co-occurring symptoms in ASD.

Neurodevelopmental Disorders Affecting Sociability: Recent Research Advances and Future Directions in Autism Spectrum Disorder and Williams Syndrome

PURPOSE OF REVIEW

In this review, we summarize current knowledge and hypotheses on the nature of social abnormalities in autism spectrum disorder (ASD) and Williams syndrome (WS).

RECENT FINDINGS

Social phenotypes in ASD and WS appear to reflect analogous disruptions in social cognition, and distinct patterns of social motivation, which appears to be reduced in ASD and enhanced in WS. These abnormalities likely originate from heterogeneous vulnerabilities that disrupt the interplay between domain-general and social domain-specific cognitive and motivational processes during early development. Causal pathways remain unclear. Advances and research gaps in our understanding of the social phenotypes in ASD and WS highlight the importance of (1) parsing the construct of sociability, (2) adopting a developmental perspective, (3) including samples that are representative of the spectrum of severity within ASD and WS in neuroscientific research, and (4) adopting transdiagnostic treatment approaches to target shared areas of impairment across diagnostic boundaries.

Alpha Waves as a Neuromarker of Autism Spectrum Disorder: The Challenge of Reproducibility and Heterogeneity

Background: There is no consensus in the literature concerning the presence of abnormal alpha wave profiles in patients with autism spectrum disorder (ASD). This may be due to phenotypic heterogeneity among patients as well as the limited sample sizes utilized. Here we present our results of alpha wave profile analysis based on a sample larger than most of those in the field, performed using a robust processing pipeline. Methods: We compared the alpha waves profiles at rest in children with ASD to those of age-, sex-, and IQ-matched control individuals. We used linear regression and non-parametric normative models using age as covariate forparsing the clinical heterogeneity. We explored the correlation between EEG profiles and the patient's brain volumes, obtained from structural MRI. We automatized the detection of the alpha peak and visually quality controled our MRI measurements. We assessed the robustness of our results by running the EEG preprocessing with two different versions of Matlab as well as Python. Results: A simple linear regression between peak power or frequency of the alpha waves and the status or age of the participants did not allow to identify any statistically significant relationship. The non-parametric normative model (which took account the non-linear effect of age on the alpha profiles) suggested that participants with ASD displayed more variability than control participants for both frequency and amplitude of the alpha peak (p < 0.05). Independent of the status of the individual, we also observed weak associations (uncorrected p < 0.05) between the alpha frequency, and the volumes of several cortical and subcortical structures (in particular the striatum), but which did not survive correction for multiple testing and changed between analysis pelines. Discussions: Our study did not find evidence for abnormal alpha wave profiles in ASD. We propose, however, an analysis pipeline to perform standardized and automatized EEG analyses on large cohorts. These should help the community to address the challenge of clinical heterogeneity of ASD and to tackle the problems of reproducibility.

Differences in Cortical Structure and Functional MRI Connectivity in High Functioning Autism

Autism spectrum disorders (ASD) represent a complex group of neurodevelopmental conditions characterized by deficits in communication and social behaviors. We examined the functional connectivity (FC) of the default mode network (DMN) and its relation to multimodal morphometry to investigate superregional, system-level alterations in a group of 22 adolescents and young adults with high-functioning autism compared to age-, and intelligence quotient-matched 29 healthy controls. The main findings were that ASD patients had gray matter (GM) reduction, decreased cortical thickness and larger cortical surface areas in several brain regions, including the cingulate, temporal lobes, and amygdala, as well as increased gyrification in regions associated with encoding visual memories and areas of the sensorimotor component of the DMN, more pronounced in the left hemisphere. Moreover, patients with ASD had decreased connectivity between the posterior cingulate cortex, and areas of the executive control component of the DMN and increased FC between the anteromedial prefrontal cortex and areas of the sensorimotor component of the DMN. Reduced cortical thickness in the right inferior frontal lobe correlated with higher social impairment according to the scores of the Autism Diagnostic Interview-Revised (ADI-R). Reduced cortical thickness in left frontal regions, as well as an increased cortical thickness in the right temporal pole and posterior cingulate, were associated with worse scores on the communication domain of the ADI-R. We found no association between scores on the restrictive and repetitive behaviors domain of ADI-R with structural measures or FC. The combination of these structural and connectivity abnormalities may help to explain some of the core behaviors in high-functioning ASD and need to be investigated further.

Multimodal approaches to functional connectivity in autism spectrum disorders: An integrative perspective

Atypical functional connectivity has been implicated in autism spectrum disorders (ASDs). However, the literature to date has been largely inconsistent, with mixed and conflicting reports of hypo- and hyper-connectivity. These discrepancies are partly due to differences between various neuroimaging modalities. Functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and magnetoencephalography (MEG) measure distinct indices of functional connectivity (e.g., blood-oxygenation level-dependent [BOLD] signal vs. electrical activity). Furthermore, each method has unique benefits and disadvantages with respect to spatial and temporal resolution, vulnerability to specific artifacts, and practical implementation. Thus far, functional connectivity research on ASDs has remained almost exclusively unimodal; therefore, interpreting findings across modalities remains a challenge. Multimodal integration of fMRI, EEG, and MEG data is critical in resolving discrepancies in the literature, and working toward a unifying framework for interpreting past and future findings. This review aims to provide a theoretical foundation for future multimodal research on ASDs. First, we will discuss the merits and shortcomings of several popular theories in ASD functional connectivity research, using examples from the literature to date. Next, the neurophysiological relationships between imaging modalities, including their relationship with invasive neural recordings, will be reviewed. Finally, methodological approaches to multimodal data integration will be presented, and their future application to ASDs will be discussed. Analyses relating transient patterns of neural activity ("states") are particularly promising. This strategy provides a comparable measure across modalities, captures complex spatiotemporal patterns, and is a natural extension of recent dynamic fMRI research in ASDs. © 2017 Wiley Periodicals, Inc. Develop Neurobiol 78: 456-473, 2018.

Motor development and delay: advances in assessment of motor skills in autism spectrum disorders

PURPOSE OF REVIEW

Motor impairments in neurodevelopmental disorders, specifically autism spectrum disorder (ASD), are prevalent and pervasive. Moreover, motor impairments may be the first sign of atypical development in ASD and likely contribute to abnormalities in social communication. However, measurement of motor function in ASD has lagged behind other behavioral phenotyping. Quantitative and neurodiagnostic measures of motor function can help identify specific motor impairments in ASD and the underlying neural mechanisms that might be implicated. These findings can serve as markers of early diagnosis, clinical stratification, and treatment targets.

RECENT FINDINGS

Here, we briefly review recent studies on the importance of motor function to other developmental domains in ASD. We then highlight studies that have applied quantitative and neurodiagnostic measures to better measure motor impairments in ASD and the neural mechanisms that may contribute to these abnormalities.

SUMMARY

Information from advanced quantitative and neurodiagnostic methods of motor function contribute to a better understanding of the specific and subtle motor impairments in ASD, and the relationship of motor function to language and social development. Greater utilization of these methods can assist with early diagnosis and development of targeted interventions. However, there remains a need to utilize these approaches in children with neurodevelopmental disorders across a developmental trajectory and with varying levels of cognitive function.

Traffic-Related Air Pollution and Autism Spectrum Disorder: A Population-Based Nested Case-Control Study in Israel

Accumulating evidence suggests that perinatal air pollutant exposures are associated with increased risk of autism spectrum disorder (ASD), but evidence for traffic pollutants outside the United States is inconclusive. We assessed the association between nitrogen dioxide, a traffic pollution tracer, and risk of ASD. We conducted a nested case-control study among the entire population of children born during 2005-2009 in the central coastal area of Israel. Cases were identified through the National Insurance Institute of Israel (n = 2,098). Controls were a 20% random sample of the remaining children (n = 54,191). Exposure was based on an optimized dispersion model. We estimated adjusted odds ratios and 95% confidence intervals using logistic regression and a distributed-lag model. In models mutually adjusted for the 2 periods, the odds ratio per 5.85-parts per billion (ppb) increment of nitrogen dioxide exposure during pregnancy (median, 16.8 ppb; range, 7.5-31.2 ppb) was 0.77 (95% confidence interval: 0.59, 1.00), and the odds ratio for exposure during the 9 months after birth was 1.40 (95% confidence interval: 1.09, 1.80). A distributed-lag model revealed reduced risk around week 13 of pregnancy and elevated risk around week 26 after birth. These findings suggest that postnatal exposure to nitrogen dioxide in Israel is associated with increased odds of ASD, and prenatal exposure with lower odds. The latter may relate to selection effects.

Early alterations of social brain networks in young children with autism

Social impairments are a hallmark of Autism Spectrum Disorders (ASD), but empirical evidence for early brain network alterations in response to social stimuli is scant in ASD. We recorded the gaze patterns and brain activity of toddlers with ASD and their typically developing peers while they explored dynamic social scenes. Directed functional connectivity analyses based on electrical source imaging revealed frequency specific network atypicalities in the theta and alpha frequency bands, manifesting as alterations in both the driving and the connections from key nodes of the social brain associated with autism. Analyses of brain-behavioural relationships within the ASD group suggested that compensatory mechanisms from dorsomedial frontal, inferior temporal and insular cortical regions were associated with less atypical gaze patterns and lower clinical impairment. Our results provide strong evidence that directed functional connectivity alterations of social brain networks is a core component of atypical brain development at early stages of ASD.

Newborns are attracted to voices, faces and social gestures. Paying attention to these social cues in everyday life helps infants and young children learn how to interact with others. During this period of development, a network of connections forms between different parts of the brain that helps children to understand other people’s social behaviors.

During their first year of life, infants who later develop autism spectrum disorders (ASD) pay less attention to social cues. This early indifference to these important signals leads to social deficits in children with ASD. They are less able to understand other people’s behaviors or engage in typical social interactions. It’s not yet clear why children with ASD are less attuned to social cues. But is likely that the development of brain networks essential for understanding social behavior suffers as a result. Studying how such networks develop in typical very young children and those with ASD may help scientist learn more.

Now, Sperdin et al. confirm there are differences in the social brain-networks of very young children with ASD compared with their typical peers. In the experiment, 3-year-old children with ASD and without watched videos of other children playing, while Sperdin et al. recorded what they looked at and what happened in their brains. Eyemovements were measured with a tracker, and the brain activity was recorded using an electroencephalogram (EEG), which uses sensors placed on the scalp to measure electrical signals.

What children with ASD looked at was different than their typical peers, and these differences corresponded with alterations in the brain networks that process social information. Children with ASD who had less severe symptoms had stronger activity in these brain networks. What they looked at also was more similar to typical children. This suggests less severely affected children with ASD may be able to compensate that way.

Identifying ASD-like behaviors and brain differences early in life may help scientists to better understand what causes the condition. It may also help clinicians provide more individualized therapies early in life when the brain is most adaptable. Long-term studies of these brain-network differences in children with ASD are necessary to better understand how therapies can influence these changes.

A theoretical rut: revisiting and critically evaluating the generalized under/over-connectivity hypothesis of autism

In 2004, two papers proposed that pervasive functional under-connectivity (Just et al., ) or a trade-off between excessive local connectivity at the cost of distal under-connectivity (Belmonte et al., ) characterizes atypical brain organization in autism. Here, we take stock of the most recent and rigorous functional and structural connectivity findings with a careful eye toward evaluating the extent to which they support these original hypotheses. Indeed, the empirical data do not support them. From rsfMRI studies in adolescents and adults, there is an emerging consensus regarding long-range functional connections indicating cortico-cortical under-connectivity, specifically involving the temporal lobes, combined with subcortical-cortical over-connectivity. In contrast, there is little to no consensus regarding local functional connectivity or findings from task-based functional connectivity studies. The structural connectivity data suggest that white matter tracts are pervasively weak, particularly in the temporal lobe. Together, these findings are revealing how deeply complex the story is regarding atypical neural network organization in autism. In other words, distance and strength of connectivity as individual factors or as interacting factors do not consistently explain the patterns of atypical neural connectivity in autism. Therefore, we make several methodological recommendations and highlight developmental considerations that will help researchers in the field cultivate new hypotheses about the nature and mechanisms of potentially aberrant functional and structural connectivity in autism.

Idiosyncratic organization of cortical networks in autism spectrum disorder

Neuroimaging studies of Autism Spectrum Disorder (ASD) have yielded inconsistent results indicating either increases or decreases in functional connectivity, or both. Recent findings suggest that these seemingly divergent results might be underpinned by greater inter-individual variability in brain network connectivity in ASD. We tested the hypothesis that the spatial patterns of intrinsic connectivity networks (ICNs) are more idiosyncratic in ASD, and demonstrated that this increased variability is associated with symptomatology. We estimated whole brain functional connectivity based on resting state functional magnetic resonance imaging (fMRI) data obtained from the Autism Brain Imaging Data Exchange I & II (ABIDE I & II) repository: 422 (69 females) participants with ASD and 424 (59 females) typically developing (TD) participants between 6 and 30 years of age. We clustered individuals' patterns of resting state functional connectivity into seven networks, each representing an ICN, and assessed the heterogeneity of each vertex on the cortical surface across individuals in terms of its incorporation into a particular ICN. We found that the incorporation of individual anatomical locations (vertices) to a common network was less consistent across individuals in ASD, indicating a more idiosyncratic organization of ICNs in the ASD brain. This spatial shifting effect was particularly pronounced in the Sensory-Motor Network (SMN) and the Default Mode Network (DMN). We also found that this idiosyncrasy in large-scale brain network organization was correlated with ASD symptomatology (ADOS). These results support the view that idiosyncratic functional connectivity is a hallmark of the ASD brain. We provide the first evidence that the anatomical organization of ICNs is idiosyncratic in ASD, as well as providing evidence that such abnormalities in brain network organization may contribute to the symptoms of ASD.

Facilitating Neurofeedback in Children with Autism and Intellectual Impairments Using TAGteach

Individuals with autism and intellectual impairments tend to be excluded from research due to their difficulties with methodological compliance. This study focuses on using Teaching with Acoustic Guidance-TAGteach-to behaviorally prepare children with autism and a IQ ≤ 80 to participate in a study on neurofeedback training (NFT). Seven children (ages 6-8) learned the prerequisite skills identified in a task analysis in an average of 5 h of TAGteach training, indicating that this is a feasible method of preparing intellectually-impaired children with autism to participate in NFT and task-dependent electroencephalography measures. TAGteach may thus have the potential to augment this population's ability to participate in less accessible treatments and behavioral neuroscientific studies.

Age and Gender Effects on Intrinsic Connectivity in Autism Using Functional Integration and Segregation

BACKGROUND

The objective of this study was to examine intrinsic whole-brain functional connectivity in autism spectrum disorder (ASD) using the framework of functional segregation and integration. Emphasis was given to potential gender and developmental effects as well as identification of specific networks that may contribute to the global results.

METHODS

We leveraged an open data resource (N = 1587) of resting-state functional magnetic resonance imaging data in the Autism Brain Imaging Data Exchange (ABIDE) initiative, combining data from more than 2100 unique cross-sectional datasets in ABIDE I and ABIDE II collected at different sites. Modularity and global efficiency were utilized to assess functional segregation and integration, respectively. A meta-analytic approach for handling site differences was used. The effects of age, gender, and diagnostic category on segregation and integration were assessed using linear regression.

RESULTS

Modularity decreased nonlinearly in the ASD group with age, as evidenced by an increase and then decrease over development. Global efficiency had an opposite relationship with age by first decreasing and then increasing in the ASD group. Both modularity and global efficiency remained largely stable in the typically developing control group during development, representing a significantly different effect than seen in the ASD group. Age effects on modularity were localized to the somatosensory network. Finally, a marginally significant interaction between age, gender, and diagnostic category was found for modularity.

CONCLUSIONS

Our results support prior work that suggested a quadratic effect of age on brain development in ASD, while providing new insights about the specific characteristics of developmental and gender effects on intrinsic connectivity in ASD.

Neural networks underlying language and social cognition during self-other processing in Autism spectrum disorders

The social communication impairments defining autism spectrum disorders (ASD) may be built upon core deficits in perspective-taking, language processing, and self-other representation. Self-referential processing entails the ability to incorporate self-awareness, self-judgment, and self-memory in information processing. Very few studies have examined the neural bases of integrating self-other representation and semantic processing in individuals with ASD. The main objective of this functional MRI study is to examine the role of language and social brain networks in self-other processing in young adults with ASD. Nineteen high-functioning male adults with ASD and 19 age-sex-and-IQ-matched typically developing (TD) control participants made "yes" or "no" judgments of whether an adjective, presented visually, described them (self) or their favorite teacher (other). Both ASD and TD participants showed significantly increased activity in the medial prefrontal cortex (MPFC) during self and other processing relative to letter search. Analyses of group differences revealed significantly reduced activity in left inferior frontal gyrus (LIFG), and left inferior parietal lobule (LIPL) in ASD participants, relative to TD controls. ASD participants also showed significantly weaker functional connectivity of the anterior cingulate cortex (ACC) with several brain areas while processing self-related words. The LIFG and IPL are important regions functionally at the intersection of language and social roles; reduced recruitment of these regions in ASD participants may suggest poor level of semantic and social processing. In addition, poor connectivity of the ACC may suggest the difficulty in meeting the linguistic and social demands of this task in ASD. Overall, this study provides new evidence of the altered recruitment of the neural networks underlying language and social cognition in ASD.

A Network Neuroscience of Neurofeedback for Clinical Translation

In the emerging field of network neuroscience, the brain is represented as a network of discrete yet functionally and structurally interconnected areas. Mathematical and computational tools to characterize the organization of this network can provide insights into the principles guiding brain structure and function, and can pinpoint differences between healthy individuals and individuals suffering from psychiatric disease or neurological disorders. The field is now faced with the question of how to devise clinical interventions that target these network alterations. Potential solutions to this question include the combination of emerging theories of network control with cutting-edge interventions such as neurofeedback. Each of these techniques may now be mature enough to combine to obtain a theoretically-motivated framework informing viable neuropsychiatric therapies.

Increased fronto-hippocampal connectivity in the Prrxl1 knockout mouse model of congenital hypoalgesia

Despite the large number of studies addressing how prolonged painful stimulation affects brain functioning, there are only a handful of studies aimed at uncovering if persistent conditions of reduced pain perception would also result in brain plasticity. Permanent hypoalgesia induced by neonatal injection of capsaicin or carrageenan has already been shown to affect learning and memory and to induce alterations in brain gene expression. In this study, we used the Prrxl1 model of congenital mild hypoalgesia to conduct a detailed study of the neurophysiological and behavioral consequences of reduced pain experience. Prrxl1 knockout animals are characterized by selective depletion of small diameter primary afferents and abnormal development of the superficial dorsal laminae of the spinal cord, resulting in diminished pain perception but normal tactile and motor behaviour. Behavioral testing of Prrxl1 mice revealed that these animals have reduced anxiety levels, enhanced memory performance, and improved fear extinction. Neurophysiological recordings from awake behaving Prrxl1 mice show enhanced altered fronto-hippocampal connectivity in the theta- and gamma-bands. Importantly, although inflammatory pain by Complete Freund Adjuvant injection caused a decrease in fronto-hippocampal connectivity in the wild-type animals, Prrxl1 mice maintained the baseline levels. The onset of inflammatory pain also reverted the differences in forebrain expression of stress- and monoamine-related genes in Prrxl1 mice. Altogether our results suggest that congenital hypoalgesia may have an effect on brain plasticity that is the inverse of what is usually observed in animal models of chronic pain.

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.

Epigenetic Research in Neuropsychiatric Disorders: the "Tissue Issue"

PURPOSE OF REVIEW

Evidence has linked neuropsychiatric disorders with epigenetic marks as either a biomarker of disease, biomarker of exposure, or mechanism of disease processes. Neuropsychiatric epidemiologic studies using either target brain tissue or surrogate blood tissue each have methodological challenges and distinct advantages.

RECENT FINDINGS

Brain tissue studies are challenged by small sample sizes of cases and controls, incomplete phenotyping, post-mortem timing, and cellular heterogeneity, but the use of a primary disease relevant tissue is critical. Blood-based studies have access to much larger sample sizes and more replication opportunities, as well as the potential for longitudinal measurements, both prior to onset and during the course of treatments. Yet, blood studies also are challenged by cell-type heterogeneity, and many question the validity of using peripheral tissues as a brain biomarker. Emerging evidence suggests that these limitations to blood-based epigenetic studies are surmountable, but confirmation in target tissue remains important.

SUMMARY

Epigenetic mechanisms have the potential to help elucidate biology connecting experiential risk factors with neuropsychiatric disease manifestation. Cross-tissue studies as well as advanced epidemiologic methods should be employed to more effectively conduct neuropsychiatric epigenetic research.