Parsing evoked and induced gamma response differences in Autism: A visual evoked potential study.

OBJECTIVE: Electroencephalography (EEG) measures of visual evoked potentials (VEPs) provide a targeted approach for investigating neural circuit dynamics. This study separately analyses phase-locked (evoked) and non-phase-locked (induced) gamma responses within the VEP to comprehensively investigate circuit differences in autism. METHODS: We analyzed VEP data from 237 autistic and 114 typically developing (TD) children aged 6-11, collected through the Autism Biomarkers Consortium for Clinical Trials (ABC-CT). Evoked and induced gamma (30-90 Hz) responses were separately quantified using a wavelet-based time-frequency analysis, and group differences were evaluated using a permutation-based clustering procedure. RESULTS: Autistic children exhibited reduced evoked gamma power but increased induced gamma power compared to TD peers. Group differences in induced responses showed the most prominent effect size and remained statistically significant after excluding outliers. CONCLUSIONS: Our study corroborates recent research indicating diminished evoked gamma responses in children with autism. Additionally, we observed a pronounced increase in induced power. Building upon existing ABC-CT findings, these results highlight the potential to detect variations in gamma-related neural activity, despite the absence of significant group differences in time-domain VEP components. SIGNIFICANCE: The contrasting patterns of decreased evoked and increased induced gamma activity in autistic children suggest that a combination of different EEG metrics may provide a clearer characterization of autism-related circuitry than individual markers alone.

Familial Recurrence of Autism: Updates From the Baby Siblings Research Consortium.

OBJECTIVES: Autism spectrum disorder (ASD) is estimated to be ∼10 times higher in children with versus without an autistic sibling in population-based studies. Prospective studies of infant siblings have revealed even higher familial recurrence rates. In the current prospective longitudinal study, we provide updated estimates of familial ASD recurrence using a multinational database of infants with older autistic siblings. METHODS: Data were collated across 18 sites of the Baby Siblings Research Consortium, an international network studying the earliest manifestations of ASD. A total of 1605 infants with an older autistic sibling were followed from early in life to 3 years, when they were classified as ASD or non-ASD. Hierarchical generalized linear modeling, with site as a random effect, was used to examine predictors of recurrence in families and calculate likelihood ratios. RESULTS: A total of 20.2% of siblings developed ASD, which is not significantly higher than the previously reported rate of 18.7%. Male infant sex and >1 older affected sibling were significant predictors of familial recurrence. Proband sex also influenced recurrence rates, with siblings of female probands significantly more likely to develop ASD than siblings of male probands. Race and maternal education were also associated with recurrence in families. CONCLUSIONS: The familial recurrence rate of ASD, as measured in infant sibling studies, has not changed appreciably since previous estimates were made in 2011. Younger siblings of autistic children, particularly those who are male, have an affected female sibling, multiple affected siblings, or are impacted by social inequities, should be closely monitored and promptly referred for diagnostic evaluation.

Family history of psychiatric conditions and development of siblings of children with autism.

Younger siblings (SIBS) of children with autism exhibit a wide range of clinical and subclinical symptoms including social, cognitive, language, and adaptive functioning delays. Identifying factors linked with this phenotypic heterogeneity is essential for improving understanding of the underlying biology of the heterogenous outcomes and for early identification of the most vulnerable SIBS. Prevalence of neurodevelopmental (NDD) and neuropsychiatric disorders (NPD) is significantly elevated in families of children with autism. It remains unknown, however, if the family history associates with the developmental outcomes among the SIBS. We quantified history of the NDDs and NPDs commonly reported in families of children with autism using a parent interview and assessed autism symptoms, verbal, nonverbal, and adaptive skills in a sample of 229 SIBS. Multiple regression analyses were used to examine links between family history and phenotypic outcomes, whereas controlling for birth year, age, sex, demographics, and parental education. Results suggest that family history of schizophrenia, depression, anxiety, bipolar disorder, and intellectual disability associate robustly with dimensional measures of social affect, verbal and nonverbal IQ, and adaptive functioning in the SIBS. Considering family history of these disorders may improve efforts to predict long-term outcomes in younger siblings of children with autism and inform about familial factors contributing to high phenotypic heterogenetity in this cohort.

Early executive functioning predicts externalizing problems in neurodiverse preschoolers.

Children with autism spectrum disorder (ASD) often exhibit externalizing problems, which have been linked with increased anxiety and depression, peer rejection, and parental stress. Identification of early predictors of externalizing behaviors in autism will facilitate identification of vulnerable children and implementation of early preventative interventions. There is ample evidence that executive functioning, social functioning, and temperament are predictive of later externalizing problems in general populations, but less is known about these relations in ASD and other neurodiverse populations, particularly in the early preschool years. To address this gap, we assessed the relations between executive functioning, social functioning, and temperament at age 3 and externalizing problems at age 5 in a sample of neurodiverse children with ASD and other neurodevelopmental disorders and delays. Analyses revealed that severity of early executive functioning impairment predicted increased externalizing problems. Severity of social autism symptoms moderated this relationship such that the effect of executive functioning on externalizing problems decreased as autism symptoms increased. These findings suggest that executive functioning is an important target for identifying and developing interventions for vulnerable children and underscore the necessity of considering severity of autism symptoms when researching the development of externalizing problems in children with neurodevelopmental disorders.

Face-to-face live eye-tracking in toddlers with autism: Feasibility and impact of familiarity and face covering.

Studies utilizing eye-tracking methods have potential to promptly capture real-world dynamics of one of the core areas of vulnerability in autism spectrum disorders (ASD), selective social attention. So far, no studies have successfully reported utilizing the method to examine social attention in toddlers with neurodevelopmental vulnerabilities in real world and challenging settings such as an interactive face-to-face. This study examined the feasibility and validity of live eye-tracking method in response to live interaction occurring in several contexts in toddlers with and without ASD. Forty-seven toddlers with ASD, with atypical development (ATYP), or typically developing (TD), underwent a 30-s live eye-tracking procedure during a face-to-face interaction with a masked stranger using child-directed-speech (16 ASD, 14 ATYP, 17 TD; Mage = 23.44 months, SD = 6.02). Out of this group of toddlers, 29 (10 ASD, 8 ATYP, 11 TD, Mage = 21.97 months, SD = 5.76) underwent the same procedure with one of their maskless parent. Task completion rate, calibration accuracy, and affective response (feasibility measures) as well as attention to the task and the social partner (validity measures) were examined. Task completion rate and calibration accuracy were excellent. Despite the challenging context of face-to-face interaction, the toddlers exhibited a neutral affect, and high attention to the task and the speaker. As anticipated, toddlers with ASD looked less at the social partner compared with control groups. However, attention was comparable between the Stranger and Parent conditions, indicating that the effect was consistent regardless of presence of face covering or the familiarity of the interactive partner. The study demonstrates the high feasibility and validity of a live eye-tracking task involving face-to-face interaction in neurodiverse toddlers with social vulnerabilities. The effect of diminished attention to social partners in toddlers with autism is robust and present when interacting with an unfamiliar person and parent. The results suggest that a brief live eye-tracking method constitutes a promising ecologically valid candidate biomarker and potential intervention outcome in autism.

The Selective Social Attention task in children with autism spectrum disorder: Results from the Autism Biomarkers Consortium for Clinical Trials (ABC-CT) feasibility study.

The Selective Social Attention (SSA) task is a brief eye-tracking task involving experimental conditions varying along socio-communicative axes. Traditionally the SSA has been used to probe socially-specific attentional patterns in infants and toddlers who develop autism spectrum disorder (ASD). This current work extends these findings to preschool and school-age children. Children 4- to 12-years-old with ASD (N = 23) and a typically-developing comparison group (TD; N = 25) completed the SSA task as well as standardized clinical assessments. Linear mixed models examined group and condition effects on two outcome variables: percent of time spent looking at the scene relative to scene presentation time (%Valid), and percent of time looking at the face relative to time spent looking at the scene (%Face). Age and IQ were included as covariates. Outcome variables' relationships to clinical data were assessed via correlation analysis. The ASD group, compared to the TD group, looked less at the scene and focused less on the actress' face during the most socially-engaging experimental conditions. Additionally, within the ASD group, %Face negatively correlated with SRS total T-scores with a particularly strong negative correlation with the Autistic Mannerism subscale T-score. These results highlight the extensibility of the SSA to older children with ASD, including replication of between-group differences previously seen in infants and toddlers, as well as its ability to capture meaningful clinical variation within the autism spectrum across a wide developmental span inclusive of preschool and school-aged children. The properties suggest that the SSA may have broad potential as a biomarker for ASD.

Modeling idiopathic autism in forebrain organoids reveals an imbalance of excitatory cortical neuron subtypes during early neurogenesis.

Idiopathic autism spectrum disorder (ASD) is highly heterogeneous, and it remains unclear how convergent biological processes in affected individuals may give rise to symptoms. Here, using cortical organoids and single-cell transcriptomics, we modeled alterations in the forebrain development between boys with idiopathic ASD and their unaffected fathers in 13 families. Transcriptomic changes suggest that ASD pathogenesis in macrocephalic and normocephalic probands involves an opposite disruption of the balance between excitatory neurons of the dorsal cortical plate and other lineages such as early-generated neurons from the putative preplate. The imbalance stemmed from divergent expression of transcription factors driving cell fate during early cortical development. While we did not find genomic variants in probands that explained the observed transcriptomic alterations, a significant overlap between altered transcripts and reported ASD risk genes affected by rare variants suggests a degree of gene convergence between rare forms of ASD and the developmental transcriptome in idiopathic ASD.

Evaluation of clinical assessments of social abilities for use in autism clinical trials by the autism biomarkers consortium for clinical trials.

Clinical trials in autism spectrum disorder (ASD) often rely on clinician rating scales and parent surveys to measure autism-related features and social behaviors. To aid in the selection of these assessments for future clinical trials, the Autism Biomarkers Consortium for Clinical Trials (ABC-CT) directly compared eight common instruments with respect to acquisition rates, sensitivity to group differences, equivalence across demographic sub-groups, convergent validity, and stability over a 6-week period. The sample included 280 children diagnosed with ASD (65 girls) and 119 neurotypical children (36 girls) aged from 6 to 11 years. Full scale IQ for ASD ranged from 60 to 150 and for neurotypical ranged from 86 to 150. Instruments measured clinician global assessment and autism-related behaviors, social communication abilities, adaptive function, and social withdrawal behavior. For each instrument, we examined only the scales that measured social or communication functioning. Data acquisition rates were at least 97.5% at T1 and 95.7% at T2. All scales distinguished diagnostic groups. Some scales significantly differed by participant and/or family demographic characteristics. Within the ASD group, most clinical instruments exhibited weak (≥ |0.1|) to moderate (≥ |0.4|) intercorrelations. Short-term stability was moderate (ICC: 0.5-0.75) to excellent (ICC: >0.9) within the ASD group. Variations in the degree of stability may inform viability for different contexts of use, such as identifying clinical subgroups for trials versus serving as a modifiable clinical outcome. All instruments were evaluated in terms of their advantages and potential concerns for use in clinical trials.

The Autism Biomarkers Consortium for Clinical Trials: Initial Evaluation of a Battery of Candidate EEG Biomarkers.

OBJECTIVE: Numerous candidate EEG biomarkers have been put forward for use in clinical research on autism spectrum disorder (ASD), but biomarker development has been hindered by limited attention to the psychometric properties of derived variables, inconsistent results across small studies, and variable methodology. The authors evaluated the basic psychometric properties of a battery of EEG assays for their potential suitability as biomarkers in clinical trials. METHODS: This was a large, multisite, naturalistic study in 6- to 11-year-old children who either had an ASD diagnosis (N=280) or were typically developing (N=119). The authors evaluated an EEG battery composed of well-studied assays of resting-state activity, face perception (faces task), biological motion perception, and visual evoked potentials (VEPs). Biomarker psychometrics were evaluated in terms of acquisition rates, construct performance, and 6-week stability. Preliminary evaluation of use was explored through group discrimination and phenotypic correlations. RESULTS: Three assays (resting state, faces task, and VEP) show promise in terms of acquisition rates and construct performance. Six-week stability values in the ASD group were moderate (intraclass correlations ≥0.66) for the faces task latency of the P1 and N170, the VEP amplitude of N1 and P1, and resting alpha power. Group discrimination and phenotype correlations were primarily observed for the faces task P1 and N170. CONCLUSIONS: In the context of a large-scale, rigorous evaluation of candidate EEG biomarkers for use in ASD clinical trials, neural response to faces emerged as a promising biomarker for continued evaluation. Resting-state activity and VEP yielded mixed results. The study's biological motion perception assay failed to display construct performance. The results provide information about EEG biomarker performance that is relevant for the next stage of biomarker development efforts focused on context of use.

A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth.

Difficulty with attention is an important symptom in many conditions in psychiatry, including neurodiverse conditions such as autism. There is a need to better understand the neurobiological correlates of attention and leverage these findings in healthcare settings. Nevertheless, it remains unclear if it is possible to build dimensional predictive models of attentional state in a sample that includes participants with neurodiverse conditions. Here, we use 5 datasets to identify and validate functional connectome-based markers of attention. In dataset 1, we use connectome-based predictive modeling and observe successful prediction of performance on an in-scan sustained attention task in a sample of youth, including participants with a neurodiverse condition. The predictions are not driven by confounds, such as head motion. In dataset 2, we find that the attention network model defined in dataset 1 generalizes to predict in-scan attention in a separate sample of neurotypical participants performing the same attention task. In datasets 3-5, we use connectome-based identification and longitudinal scans to probe the stability of the attention network across months to years in individual participants. Our results help elucidate the brain correlates of attentional state in youth and support the further development of predictive dimensional models of other clinically relevant phenotypes.

Concomitant medication use in children with autism spectrum disorder: Data from the Autism Biomarkers Consortium for Clinical Trials.

LAY ABSTRACT: Children with autism spectrum disorder are prescribed a variety of medications that affect the central nervous system (psychotropic medications) to address behavior and mood. In clinical trials, individuals taking concomitant psychotropic medications often are excluded to maintain homogeneity of the sample and prevent contamination of biomarkers or clinical endpoints. However, this choice may significantly diminish the clinical representativeness of the sample. In a recent multisite study designed to identify biomarkers and behavioral endpoints for clinical trials (the Autism Biomarkers Consortium for Clinical Trials), school-age children with autism spectrum disorder were enrolled without excluding for medications, thus providing a unique opportunity to examine characteristics of psychotropic medication use in a research cohort and to guide future decisions on medication-related inclusion criteria. The aims of the current analysis were (1) to quantify the frequency and type of psychotropic medications reported in school-age children enrolled in the ABC-CT and (2) to examine behavioral features of children with autism spectrum disorder based on medication classes. Of the 280 children with autism spectrum disorder in the cohort, 42.5% were taking psychotropic medications, with polypharmacy in half of these children. The most commonly reported psychotropic medications included melatonin, stimulants, selective serotonin reuptake inhibitors, alpha agonists, and antipsychotics. Descriptive analysis showed that children taking antipsychotics displayed a trend toward greater overall impairment. Our findings suggest that exclusion of children taking concomitant psychotropic medications in trials could limit the clinical representativeness of the study population, perhaps even excluding children who may most benefit from new treatment options.

Hypoconnectivity between anterior insula and amygdala associates with future vulnerabilities in social development in a neurodiverse sample of neonates.

Altered resting state functional connectivity (FC) involving the anterior insula (aINS), a key node in the salience network, has been reported consistently in autism. Here we examined, for the first time, FC between the aINS and the whole brain in a sample of full-term, postmenstrual age (PMA) matched neonates (mean 44.0 weeks, SD = 1.5) who due to family history have high likelihood (HL) for developing autism (n = 12) and in controls (n = 41) without family history of autism (low likelihood, LL). Behaviors associated with autism were evaluated between 12 and 18 months (M = 17.3 months, SD = 2.5) in a subsample (25/53) of participants using the First Year Inventory (FYI). Compared to LL controls, HL neonates showed hypoconnectivity between left aINS and left amygdala. Lower connectivity between the two nodes was associated with higher FYI risk scores in the social domain (r(25) = -0.561, p = .003) and this association remained robust when maternal mental health factors were considered. Considering that a subsample of LL participants (n = 14/41) underwent brain imaging during the fetal period at PMA 31 and 34 weeks, in an exploratory analysis, we evaluated prospectively development of the LaINS-Lamy connectivity and found that the two areas strongly coactivate throughout the third trimester of pregnancy. The study identifies left lateralized anterior insula-amygdala connectivity as a potential target of further investigation into neural circuitry that enhances likelihood of future onset of social behaviors associated with autism during neonatal and potentially prenatal periods.

Functional Connectome-Based Predictive Modeling in Autism.

Autism is a heterogeneous neurodevelopmental condition, and functional magnetic resonance imaging-based studies have helped advance our understanding of its effects on brain network activity. We review how predictive modeling, using measures of functional connectivity and symptoms, has helped reveal key insights into this condition. We discuss how different prediction frameworks can further our understanding of the brain-based features that underlie complex autism symptomatology and consider how predictive models may be used in clinical settings. Throughout, we highlight aspects of study interpretation, such as data decay and sampling biases, that require consideration within the context of this condition. We close by suggesting exciting future directions for predictive modeling in autism.

Early predictors of language skills at 3 years of age vary based on diagnostic outcome: A baby siblings research consortium study.

While previous work has identified the early predictors of language skills in infants at elevated familial risk (ER) and low familial risk (LR) for autism spectrum disorder (ASD), no studies to date have explored whether these predictors vary based on diagnostic outcome of ASD or no ASD. The present study used a large, multisite dataset to examine associations between a set of commonly studied predictor variables (infant gesture abilities, fine motor skills, nonverbal cognition, and maternal education level), measured at 12 months, and language skills, measured at 3 years, across three diagnostic outcome groups-infants with ASD ("ASD"), ER infants without ASD ("ER-no ASD"), and LR infants without ASD ("LR-no ASD"). Findings revealed that the predictors of language skills differed across groups, as gesture abilities were positively associated with language skills in the ER-no ASD group but negatively associated with language skills in the ASD group. Furthermore, maternal education level was positively associated with language skills in the ASD and LR-no ASD groups only. Variability in these early predictors may help explain why language skills are heterogeneous across the autism spectrum, and, with further study, may help clinicians identify those in need of additional and/or specialized intervention services that support language development. LAY SUMMARY: The present study identified predictors of language skills in infants with and without autism spectrum disorder (ASD). Maternal education level and 12-month gesture abilities predicted 3-year language skills in infants with ASD. Measuring these predictors early in life may help identify infants and families in need of additional and/or specialized intervention services that support language development.

Identifying Age Based Maturation in the ERP Response to Faces in Children With Autism: Implications for Developing Biomarkers for Use in Clinical Trials.

Recent proposals have suggested the potential for neural biomarkers to improve clinical trial processes in neurodevelopmental conditions; however, few efforts have identified whether chronological age-based adjustments will be necessary (as used in standardized behavioral assessments). Event-related potentials (ERPs) demonstrate early differences in the processing of faces vs. objects in the visual processing system by 4 years of age and age-based improvement (decreases in latency) through adolescence. Additionally, face processing has been proposed to be related to social skills as well as autistic social-communication traits. While previous reports suggest delayed latency in individuals with autism spectrum disorder (ASD), extensive individual and age based heterogeneity exists. In this report, we utilize a sample of 252 children with ASD and 118 children with typical development (TD), to assess the N170 and P100 ERP component latencies (N170L and P100L, respectively), to upright faces, the face specificity effect (difference between face and object processing), and the inversion effect (difference between face upright and inverted processing) in relation to age. First, linear mixed models (LMMs) were fitted with fixed effect of age at testing and random effect of participant, using all available data points to characterize general age-based development in the TD and ASD groups. Second, LMM models using only the TD group were used to calculate age-based residuals in both groups. The purpose of residualization was to assess how much variation in ASD participants could be accounted for by chronological age-related changes. Our data demonstrate that the N170L and P100L responses to upright faces appeared to follow a roughly linear relationship with age. In the ASD group, the distribution of the age-adjusted residual values suggest that ASD participants were more likely to demonstrate slower latencies than would be expected for a TD child of the same age, similar to what has been identified using unadjusted values. Lastly, using age-adjusted values for stratification, we found that children who demonstrated slowed age-adjusted N170L had lower verbal and non-verbal IQ and worse face memory. These data suggest that age must be considered in assessing the N170L and P100L response to upright faces as well, and these adjusted values may be used to stratify children within the autism spectrum.

Patterns of Intervention Utilization Among School-Aged Children with Autism Spectrum Disorder: Findings from a Multi-Site Research Consortium.

When designing and interpreting results from clinical trials evaluating treatments for children on the autism spectrum, a complicating factor is that most children receive a range of concurrent treatments. Thus, it is important to better understand the types and hours of interventions that participants typically receive as part of standard of care, as well as to understand the child, family, and geographic factors that are associated with different patterns of service utilization. In this multi-site study, we interviewed 280 caregivers of 6-to-11-year-old school-aged children on the autism spectrum about the types and amounts of interventions their children received in the prior 6 weeks. Reported interventions were coded as "evidence-based practice" or "other interventions," reflecting the level of empirical support. Results indicated that children received a variety of interventions with varying levels of empirical evidence and a wide range of hours (0 to 79.3 hours/week). Children with higher autism symptom levels, living in particular states, and who identified as non-Hispanic received more evidence-based intervention hours. Higher parental education level related to more hours of other interventions. Children who were younger, had lower cognitive ability, and with higher autism symptom levels received a greater variety of interventions overall. Thus, based on our findings, it would seem prudent when designing clinical trials to take into consideration a variety of factors including autism symptom levels, age, cognitive ability, ethnicity, parent education and geographic location. Future research should continue to investigate the ethnic, racial, and socioeconomic influences on school-aged intervention services.

Elevated symptoms of executive dysfunction predict lower adaptive functioning in 3-year-olds with autism spectrum disorder.

Executive functioning (EF) deficits co-occur frequently with autism spectrum disorder (ASD) and have a long-term detrimental impact on quality of life of children and their families. Timely identification of risk for EF vulnerabilities may hasten access to early intervention and alleviate their long-term consequences. This study examines (1) if EF deficits are elevated in toddlers with ASD compared to nonautistic siblings of children with ASD, typically developing (TYP) toddlers, and toddlers with atypical developmental presentation; and (2) if EF deficits have a detrimental effect on adaptive functioning in ASD. Participants were recruited between September 2014 and October 2019 and included 73 toddlers with ASD, 33 nonautistic siblings of children with ASD, 35 toddlers with atypical development, and 28 TYP toddlers matched on chronological age (M = 39.01 months, SD = 3.11). EF deficits were measured using the BRIEF-P; adaptive skills were measured using the VABS-II. Whenever appropriate, analyses were controlled for MSEL verbal and nonverbal developmental quotient, ADOS-2 autism severity scores, and sex. Analyses revealed that toddlers with ASD exhibited elevated BRIEF-P scores across all domains compared to each of the three comparison groups. Higher BRIEF-P scores were associated with lower adaptive social, communication, and daily living skills while controlling for symptom severity, verbal and nonverbal functioning, and sex. In conclusion, marked vulnerabilities in EF are already present in 3-year-old toddlers with ASD and are predictive of the level of adaptive functioning in ASD. EF vulnerabilities in toddlers should be targeted for intervention to improve long-term outcomes in ASD. LAY SUMMARY: Many children with autism experience vulnerabilities in executive functioning (EF), which may include challenges with inhibition, working memory, cognitive flexibility, and planning. The study shows that these vulnerabilities can already be detected at age three and that their presence is linked with lower social, communication, and daily living skills. Screening children with ASD for EF challenges and helping those who have difficulties may improve their long-term outcomes.

Attention to audiovisual speech does not facilitate language acquisition in infants with familial history of autism.

BACKGROUND: Due to familial liability, siblings of children with ASD exhibit elevated risk for language delays. The processes contributing to language delays in this population remain unclear. METHODS: Considering well-established links between attention to dynamic audiovisual cues inherent in a speaker's face and speech processing, we investigated if attention to a speaker's face and mouth differs in 12-month-old infants at high familial risk for ASD but without ASD diagnosis (hr-sib; n = 91) and in infants at low familial risk (lr-sib; n = 62) for ASD and whether attention at 12 months predicts language outcomes at 18 months. RESULTS: At 12 months, hr-sib and lr-sib infants did not differ in attention to face (p = .14), mouth preference (p = .30), or in receptive and expressive language scores (p = .36, p = .33). At 18 months, the hr-sib infants had lower receptive (p = .01) but not expressive (p = .84) language scores than the lr-sib infants. In the lr-sib infants, greater attention to the face (p = .022) and a mouth preference (p = .025) contributed to better language outcomes at 18 months. In the hr-sib infants, neither attention to the face nor a mouth preference was associated with language outcomes at 18 months. CONCLUSIONS: Unlike low-risk infants, high-risk infants do not appear to benefit from audiovisual prosodic and speech cues in the service of language acquisition despite intact attention to these cues. We propose that impaired processing of audiovisual cues may constitute the link between genetic risk factors and poor language outcomes observed across the autism risk spectrum and may represent a promising endophenotype in autism.

Atypical Intrinsic Hemispheric Interaction Associated with Autism Spectrum Disorder Is Present within the First Year of Life.

Autism spectrum disorder (ASD) is characterized by atypical connectivity lateralization of functional networks. However, previous studies have not directly investigated if differences in specialization between ASD and typically developing (TD) peers are present in infancy, leaving the timing of onset of these differences relatively unknown. We studied the hemispheric asymmetries of connectivity in children with ASD and infants later meeting the diagnostic criteria for ASD. Analyses were performed in 733 children with ASD and TD peers and in 71 infants at high risk (HR) or normal risk (NR) for ASD, with data collected at 1 month and 9 months of age. Comparing children with ASD (n = 301) to TDs (n = 432), four regions demonstrated group differences in connectivity: posterior cingulate cortex (PCC), posterior superior temporal gyrus, extrastriate cortex, and anterior prefrontal cortex. At 1 month, none of these regions exhibited group differences between ASD (n = 10), HR-nonASD (n = 15), or NR (n = 18) infants. However, by 9 months, the PCC and extrastriate exhibited atypical connectivity in ASD (n = 11) and HR-nonASD infants (n = 24) compared to NR infants (n = 22). Connectivity did not correlate with symptoms in either sample. Our results demonstrate that differences in network asymmetries associated with ASD risk are observable prior to the age of a reliable clinical diagnosis.