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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. 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). 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. 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. 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.

Biomarkers for autism may reveal causes of the condition and could be used to improve diagnosis and enable earlier detection of autism spectrum disorders. Walsh and colleagues discuss the major scientific challenges in the search for autism biomarkers and consider a number of important social and ethical concerns arising from biomarker development and application. There is widespread hope that the discovery of valid biomarkers for autism will both reveal the causes of autism and enable earlier and more targeted methods for diagnosis and intervention. However, growing enthusiasm about recent advances in this area of autism research needs to be tempered by an awareness of the major scientific challenges and the important social and ethical concerns arising from the development of biomarkers and their clinical application. Collaborative approaches involving scientists and other stakeholders must combine the search for valid, clinically useful autism biomarkers with efforts to ensure that individuals with autism and their families are treated with respect and understanding.

AbstractAutism spectrum disorder (referred to here as autism) is one of several overlapping neurodevelopmental conditions that have variable impacts on different individuals. This variability results from dynamic interactions between biological and non-biological risk factors, which result in increasing differentiation between individuals over time. Although this differentiation continues well into adulthood, the infancy period is when the brain and behavior develop rapidly, and when the first signs and symptoms of autism emerge. This review discusses advances in our understanding of the causal pathways leading to autism and overlapping neurodevelopmental conditions. Research is also mapping trajectories of brain and behavioral development for some risk groups, namely later born siblings of children with autism and/or infants referred because of developmental concerns. This knowledge has been useful in improving early identification and establishing the feasibility of targeted interventions for infant risk groups before symptoms arise. However, key knowledge gaps remain, such as the discovery of protective factors (biological or environmental) that may mitigate the impact of risk. Also, the dynamic mechanisms that underlie the associations between risk factors and outcomes need further research. These include the processes of resilience, which may explain why some individuals at risk for autism achieve better than expected outcomes. Bridging these knowledge gaps would help to provide tools for early identification and intervention that reflect dynamic developmental pathways from risk to outcomes.

•Thirteen surface templates for infants (0–2 years old) are proposed.•Templates can be used for EEG and MEG source reconstruction using existing toolboxes.•A relatively modest impact of age differences was found in this age range.•Correlation analysis confirms increasing source differences with age differences.•Sources reconstructed with infants versus adult templates substantially differ. Electroencephalographic (EEG) source reconstruction is a powerful approach that allows anatomical localization of electrophysiological brain activity. Algorithms used to estimate cortical sources require an anatomical model of the head and the brain, generally reconstructed using magnetic resonance imaging (MRI). When such scans are unavailable, a population average can be used for adults, but no average surface template is available for cortical source imaging in infants. To address this issue, we introduce a new series of 13 anatomical models for subjects between zero and 24 months of age. These templates are built from MRI averages and boundary element method (BEM) segmentation of head tissues available as part of the Neurodevelopmental MRI Database. Surfaces separating the pia mater, the gray matter, and the white matter were estimated using the Infant FreeSurfer pipeline. The surface of the skin as well as the outer and inner skull surfaces were extracted using a cube marching algorithm followed by Laplacian smoothing and mesh decimation. We post-processed these meshes to correct topological errors and ensure watertight meshes. Source reconstruction with these templates is demonstrated and validated using 100 high-density EEG recordings from 7-month-old infants. Hopefully, these templates will support future studies on EEG-based neuroimaging and functional connectivity in healthy infants as well as in clinical pediatric populations. [Display omitted]

There is evidence of negative impact of social distancing and confinement measures to manage the COVID-19 pandemic on children, including increased anxiety and depression and behaviour difficulties. Paradoxically, positive impacts like increased support and more self-care activities have also been documented. Little is known about the impact of the COVID-19 pandemic on the children with disability and the potential role of familial, environmental, and biological factors on mitigating this impact. The aims of the study were 1) identifying profiles of functioning across multiple domains during the COVID-19 pandemic and 2) examining the extent to which parenting self-efficacy, support in accessing schooling, and type of diagnosis predict the likelihood of resilience among children with disability, after controlling for household income and single-parent status. An online survey developed from COVID-19 guidance recommendations, was available from June 11- July 21, 2020, and resulted in a convenience sample of caregivers across Canada ( n = 883) of children with disability (mean age of 9.4 years old, SD age = 5.7, 58% male). We conducted latent class analysis to examine the number of latent profiles on caregiver-reported changes of 12 functioning domains, as either ‘worsening’, ‘no change’, or ‘improving’. Most participants belonged to ‘stable’ or ‘worsening’ profiles. However, we identified a small subgroup with improvements in child functioning, a pattern indicative of a ‘resilient’ profile. Using a multinomial logistic regression, we found that diagnosis type, parenting self-efficacy and support in accessing schooling were associated with membership in the Resilient or Stable profiles compared to the Worsening profile, after controlling for single-parent status and income. Taken together, our findings identified variability in responses to adversity that is dependent on the child’s diagnosis type, parenting self-efficacy, and support in accessing schooling. By identifying potentially modifiable predictors of resilience, namely parenting self-efficacy and support in accessing schooling, we signal the potential for tailored supports for different diagnoses, through interventions that enhance caregiver empowerment, access to schooling, access to health and social services, and/or mitigate disparities resulting from social disadvantage.

This study examined the trajectories of autistic symptom severity in an inception cohort of 187 children with ASD assessed across four time points from diagnosis to age 10. Trajectory groups were derived using multivariate cluster analysis. A two trajectory/cluster solution was selected. Change in trajectory slopes revealed a turning point marked by plateauing in symptom reduction during the period of transition to school (age 6) for one of the two trajectories. Trajectories were labelled: Continuously Improving (27%) and Improving then Plateauing (73% of sample). Children in the two trajectories differed in levels of symptom severity, language, cognitive, and adaptive functioning skills. Study findings can inform the development of more personalized services for children with ASD transitioning into the school system.

Early difficulties in engaging attentive brain states in social settings could affect learning and have cascading effects on social development. We investigated this possibility using multichannel electroencephalography during a face/non-face paradigm in 8-month-old infants with (FH, n = 91) and without (noFH, n = 40) a family history of autism spectrum disorder (ASD). An event-related potential component reflecting attention engagement, the Nc, was compared between FH infants who received a diagnosis of ASD at 3 years of age (FH-ASD; n = 19), FH infants who did not (FH-noASD; n = 72) and noFH infants (who also did not, hereafter noFH-noASD; n = 40). ‘Prototypical’ microstates during social attention were extracted from the noFH-noASD group and examined in relation to later categorical and dimensional outcome. Machine-learning was used to identify the microstate features that best predicted ASD and social adaptive skills at three years. Results suggested that whilst measures of brain state timing were related to categorical ASD outcome, brain state strength was related to dimensional measures of social functioning. Specifically, the FH-ASD group showed shorter Nc latency relative to other groups, and duration of the attentive microstate responses to faces was informative for categorical outcome prediction. Reduced Nc amplitude difference between faces with direct gaze and a non-social control stimulus and strength of the attentive microstate to faces contributed to the prediction of dimensional variation in social skills. Taken together, this provides consistent evidence that atypical attention engagement precedes the emergence of difficulties in socialization and indicates that using the spatio-temporal characteristics of whole-brain activation to define brain states in infancy provides an important new approach to understanding of the neurodevelopmental mechanisms that lead to ASD.

Whilst joint attention (JA) impairments in autism have been widely studied, little is known about the early development of gaze following, a precursor to establishing JA. We employed eye-tracking to record gaze following longitudinally in infants with and without a family history of autism spectrum disorder (ASD) at 7 and 13 months. No group difference was found between at-risk and low-risk infants in gaze following behaviour at either age. However, despite following gaze successfully at 13 months, at-risk infants with later emerging socio-communication difficulties (both those with ASD and atypical development at 36 months of age) allocated less attention to the congruent object compared to typically developing at-risk siblings and low-risk controls. The findings suggest that the subtle emergence of difficulties in JA in infancy may be related to ASD and other atypical outcomes.

Autism spectrum disorder (ASD) is often grouped with other brain-related phenotypes into a broader category of neurodevelopmental disorders (NDDs). In clinical practice, providers need to decide which genes to test in individuals with ASD phenotypes, which requires an understanding of the level of evidence for individual NDD genes that supports an association with ASD. Consensus is currently lacking about which NDD genes have sufficient evidence to support a relationship to ASD. Estimates of the number of genes relevant to ASD differ greatly among research groups and clinical sequencing panels, varying from a few to several hundred. This Roadmap discusses important considerations necessary to provide an evidence-based framework for the curation of NDD genes based on the level of information supporting a clinically relevant relationship between a given gene and ASD.A curated list of genes that are relevant to autism spectrum disorder (ASD) would greatly benefit clinical genetic testing. This Roadmap discusses the need for an evidence-based framework for gene curation that is based on the level of information supporting a clinically relevant relationship between a given gene and ASD.

Autistic adults with speech, language and/or cognitive challenges are often excluded from research, particularly from studies examining first-person perspectives, as these generally require that participants have strong speech, language, and cognitive skills. The current pilot study extends previous work and examines whether the framework can be adapted for use with a pre-existing interview the - version (CANDID-R). Eleven young autistic adults with complex communication needs completed the CANDID-R interview using visual supports. These visual supports were provided to assist participants' comprehension of interview questions and to support them in answering the interview questions. Participants' caregivers also completed the interview and their answers to specific validation questions were compared to those of their adult children. Additionally, behavioral observations were also completed. The findings from this pilot study indicate that our adaptation of the framework was, at least partially successful in supporting participants in answering the interview questions. Additionally, behavioral observations indicate that the visual supports helped participants remain engaged throughout the interview. However, results also indicate that further adaptations, which we discuss, will be required. Autistic people with complex communication needs must be included in research about the lived experiences of autistic people. Building on previous work, we show that, with dedication and imagination, equitable and inclusive research is possible.