Developmental trajectories of EEG aperiodic and periodic components in children 2-44 months of age.

The development of neural circuits has long-lasting effects on brain function, yet our understanding of early circuit development in humans remains limited. Here, periodic EEG power features and aperiodic components were examined from longitudinal EEGs collected from 592 healthy 2-44 month-old infants, revealing age-dependent nonlinear changes suggestive of distinct milestones in early brain maturation. Developmental changes in periodic peaks include (1) the presence and then absence of a 9-10 Hz alpha peak between 2-6 months, (2) nonlinear changes in high beta peaks (20-30 Hz) between 4-18 months, and (3) the emergence of a low beta peak (12-20 Hz) in some infants after six months of age. We hypothesized that the emergence of the low beta peak may reflect maturation of thalamocortical network development. Infant anesthesia studies observe that GABA-modulating anesthetics do not induce thalamocortical mediated frontal alpha coherence until 10-12 months of age. Using a small cohort of infants (n = 23) with EEG before and during GABA-modulating anesthesia, we provide preliminary evidence that infants with a low beta peak have higher anesthesia-induced alpha coherence compared to those without a low beta peak.

Conversational adaptation in children and teens with autism: Differences in talkativeness across contexts.

Successful social communication is complex; it relies on effectively deploying and continuously revising one's behavior to fit the needs of a given conversation, partner, and context. For example, a skilled conversationalist may instinctively become less talkative with a quiet partner and more talkative with a chattier one. Prior research suggests that behavioral flexibility across social contexts can be a particular challenge for individuals with autism spectrum condition (ASC), and that difficulty adapting to the changing needs of a conversation contributes to communicative breakdowns and poor social outcomes. In this study, we examine whether reduced conversational adaptation, as measured by talkativeness, differentiates 48 verbally fluent children and teens with ASC from 50 neurotypical (NT) peers matched on age, intelligence quotient, and sex ratio. Participants completed the Contextual Assessment of Social Skills with two novel conversation partners. The first acted interested in the conversation and talked more (Interested condition), while the second acted bored and talked less (Bored condition). Results revealed that NT participants emulated their conversation partner's behavior by being more talkative in the Interested condition as compared to the Bored condition (z = 9.92, p < 0.001). In contrast, the ASC group did not differentially adapt their behavior to the Bored versus Interested context, instead remaining consistently talkative in both (p = 0.88). The results of this study have implications for understanding social communication and behavioral adaptation in ASC, and may be valuable for clinicians interested in improving conversational competence in verbally fluent individuals with autism. LAY SUMMARY: Social communication-including everyday conversations-can be challenging for individuals on the autism spectrum. In successful conversations, people tend to adjust aspects of their language to be more similar to their partners'. In this study, we found that children and teens with autism did not change their own talkativeness in response to a social partner who was more or less talkative, whereas neurotypical peers did. These findings have clinical implications for improving conversational competence in verbally fluent individuals with autism.

Friend matters: sex differences in social language during autism diagnostic interviews.

BACKGROUND: Autistic individuals frequently experience social communication challenges. Girls are diagnosed with autism less often than boys even when their symptoms are equally severe, which may be due to insufficient understanding of the way autism manifests in girls. Differences in the behavioral presentation of autism, including how people talk about social topics, could contribute to these persistent problems with identification. Despite a growing body of research suggesting that autistic girls and boys present distinct symptom profiles in a variety of domains, including social attention, friendships, social motivation, and language, differences in the way that autistic boys and girls communicate verbally are not yet well understood. Closely analyzing boys' and girls' socially-focused language during semi-structured clinical assessments could shed light on potential sex differences in the behavioral presentation of autistic individuals that may prove useful for identifying and effectively supporting autistic girls. Here, we compare social word use in verbally fluent autistic girls and boys during the interview sections of the ADOS-2 Module 3 and measure associations with clinical phenotype. METHODS: School-aged girls and boys with autism (N = 101, 25 females; aged 6-15) were matched on age, IQ, and parent/clinician ratings of autism symptom severity. Our primary analysis compared the number of social words produced by autistic boys and girls (normalized to account for differences in total word production). Social words are words that make reference to other people, including friends and family. RESULTS: There was a significant main effect of sex on social word production, such that autistic girls used more social words than autistic boys. To identify the specific types of words driving this effect, additional subcategories of friend and family words were analyzed. There was a significant effect of sex on friend words, with girls using significantly more friend words than boys. However, there was no significant main effect of sex on family words, suggesting that sex differences in social word production may be driven by girls talking more about friends compared to boys, not family. To assess relationships between word use and clinical phenotype, we modeled ADOS-2 Social Affect (SA) scores as a function of social word production. In the overall sample, social word use correlated significantly with ADOS-2 SA scores, indicating that participants who used more social words were rated as less socially impaired by clinicians. However, when examined in each sex separately, this result only held for boys. LIMITATIONS: This study cannot speak to the ways in which social word use may differ for younger children, adults, or individuals who are not verbally fluent; in addition, there were more autistic boys than girls in our sample, making it difficult to detect small effects. CONCLUSIONS: Autistic girls used significantly more social words than boys during a diagnostic assessment-despite being matched on age, IQ, and both parent- and clinician-rated autism symptom severity. Sex differences in linguistic markers of social phenotype in autism are especially important in light of the late or missed diagnoses that disproportionately affect autistic girls. Specifically, heightened talk about social topics could complicate autism referral and diagnosis when non-clinician observers expect a male-typical pattern of reduced social focus, which autistic girls may not always exhibit.

Dissociating regional gray matter density and gray matter volume in autism spectrum condition.

BACKGROUND: Despite decades of research, there is continued uncertainty regarding whether autism is associated with a specific profile of gray matter (GM) structure. This inconsistency may stem from the widespread use of voxel-based morphometry (VBM) methods that combine indices of GM density and GM volume. If GM density or volume, but not both, prove different in autism, the traditional VBM approach of combining the two indices may obscure the difference. The present study measures GM density and volume separately to examine whether autism is associated with alterations in GM volume, density, or both. METHODS: Differences in MRI-based GM density and volume were examined in 6-25 year-olds with a diagnosis of autism spectrum disorder (n = 213, 80.8% male, IQ 47-154) and a typically developing (TD) sample (n = 190, 71.6% male, IQ 67-155). High-resolution T1-weighted anatomical images were collected on a single MRI scanner. Regional density and volume were estimated via whole-brain parcellation comprised of 1625 parcels. Parcel-wise analyses were conducted using generalized additive models while controlling the false discovery rate (FDR, q < 0.05). Volume differences in the 68-region Desikan-Killiany atlas derived from Freesurfer were also examined, to establish the generalizability of findings across methods. RESULTS: No density differences were observed between the autistic and TD groups, either in individual parcels or whole brain mean density. Increased volume was observed in autism compared to the TD group when controlling for Age, Sex, and IQ, both at the level of the whole brain (total volume) and in 45 parcels (2.8% of total parcels). Parcels with greater volume included inferior, middle, and superior temporal gyrus, inferior and superior frontal gyrus, precuneus, and fusiform gyrus. Converging evidence from a standard Freesurfer pipeline also identified greater volume in a number of overlapping regions. LIMITATIONS: The method for determining "density" is not a direct measure of neuronal density, and this study cannot reveal underlying cellular differences. While this study represents possibly the largest single-site sample of its kind, it is underpowered to detect very small differences. CONCLUSIONS: These results provide compelling evidence that autism is associated with regional GM volumetric differences, which are more prominent than density differences. This underscores the importance of examining volume and density separately, and suggests that direct measures of volume (e.g. region-of-interest or tensor-based morphometry approaches) may be more sensitive to autism-relevant differences in neuroanatomy than concentration/density-based approaches.

Evidence against the "normalization" prediction of the early brain overgrowth hypothesis of autism.

BACKGROUND: The frequently cited Early Overgrowth Hypothesis of autism spectrum disorder (ASD) postulates that there is overgrowth of the brain in the first 2 years of life, which is followed by a period of arrested growth leading to normalized brain volume in late childhood and beyond. While there is consistent evidence for early brain overgrowth, there is mixed evidence for normalization of brain volume by middle childhood. The outcome of this debate is important to understanding the etiology and neurodevelopmental trajectories of ASD. METHODS: Brain volume was examined in two very large single-site samples of children, adolescents, and adults. The primary sample comprised 456 6-25-year-olds (ASD n = 240, typically developing controls (TDC) n = 216), including a large number of females (n = 102) and spanning a wide IQ range (47-158). The replication sample included 175 males. High-resolution T1-weighted anatomical MRI images were examined for group differences in total brain, cerebellar, ventricular, gray, and white matter volumes. RESULTS: The ASD group had significantly larger total brain, cerebellar, gray matter, white matter, and lateral ventricular volumes in both samples, indicating that brain volume remains enlarged through young adulthood, rather than normalizing. There were no significant age or sex interactions with diagnosis in these measures. However, a significant diagnosis-by-IQ interaction was detected in the larger sample, such that increased brain volume was related to higher IQ in the TDCs, but not in the ASD group. Regions-of-significance analysis indicated that total brain volume was larger in ASD than TDC for individuals with IQ less than 115, providing a potential explanation for prior inconsistent brain size results. No relationships were found between brain volume and measures of autism symptom severity within the ASD group. LIMITATIONS: Our cross-sectional sample may not reflect individual changes over time in brain volume and cannot quantify potential changes in volume prior to age 6. CONCLUSIONS: These findings challenge the "normalization" prediction of the brain overgrowth hypothesis by demonstrating that brain enlargement persists across childhood into early adulthood. The findings raise questions about the clinical implications of brain enlargement, since we find that it neither confers cognitive benefits nor predicts increased symptom severity in ASD.

Deviation from normative brain development is associated with symptom severity in autism spectrum disorder.

Background: Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition. The degree to which the brain development in ASD deviates from typical brain development, and how this deviation relates to observed behavioral outcomes at the individual level are not well-studied. We hypothesize that the degree of deviation from typical brain development of an individual with ASD would relate to observed symptom severity. Methods: The developmental changes in anatomical (cortical thickness, surface area, and volume) and diffusion metrics (fractional anisotropy and apparent diffusion coefficient) were compared between a sample of ASD (n = 247) and typically developing children (TDC) (n = 220) aged 6-25. Machine learning was used to predict age (brain age) from these metrics in the TDC sample, to define a normative model of brain development. This model was then used to compute brain age in the ASD sample. The difference between chronological age and brain age was considered a developmental deviation index (DDI), which was then correlated with ASD symptom severity. Results: Machine learning model trained on all five metrics accurately predicted age in the TDC (r = 0.88) and the ASD (r = 0.85) samples, with dominant contributions to the model from the diffusion metrics. Within the ASD group, the DDI derived from fractional anisotropy was correlated with ASD symptom severity (r = - 0.2), such that individuals with the most advanced brain age showing the lowest severity, and individuals with the most delayed brain age showing the highest severity. Limitations: This work investigated only linear relationships between five specific brain metrics and only one measure of ASD symptom severity in a limited age range. Reported effect sizes are moderate. Further work is needed to investigate developmental differences in other age ranges, other aspects of behavior, other neurobiological measures, and in an independent sample before results can be clinically applicable. Conclusions: Findings demonstrate that the degree of deviation from typical brain development relates to ASD symptom severity, partially accounting for the observed heterogeneity in ASD. Our approach enables characterization of each individual with reference to normative brain development and identification of distinct developmental subtypes, facilitating a better understanding of developmental heterogeneity in ASD.

Pre- and Paralinguistic Vocal Production in ASD: Birth Through School Age.

PURPOSE OF REVIEW: We review what is known about how pre-linguistic vocal differences in autism spectrum disorder (ASD) unfold across development and consider whether vocalization features can serve as useful diagnostic indicators. RECENT FINDINGS: Differences in the frequency and acoustic quality of several vocalization types (e.g., babbles and cries) during the first year of life are associated with later ASD diagnosis. Paralinguistic features (e.g., prosody) measured during early and middle childhood can accurately classify current ASD diagnosis using cross-validated machine learning approaches. Pre-linguistic vocalization differences in infants are promising behavioral markers of later ASD diagnosis. In older children, paralinguistic features hold promise as diagnostic indicators as well as clinical targets. Future research efforts should focus on (1) bridging the gap between basic research and practical implementations of early vocalization-based risk assessment tools, and (2) demonstrating the clinical impact of targeting atypical vocalization features during social skill interventions for older children.

Evaluation of the Social Motivation Hypothesis of Autism: A Systematic Review and Meta-analysis.

Importance: The social motivation hypothesis posits that individuals with autism spectrum disorder (ASD) find social stimuli less rewarding than do people with neurotypical activity. However, functional magnetic resonance imaging (fMRI) studies of reward processing have yielded mixed results. Objectives: To examine whether individuals with ASD process rewarding stimuli differently than typically developing individuals (controls), whether differences are limited to social rewards, and whether contradictory findings in the literature might be due to sample characteristics. Data Sources: Articles were identified in PubMed, Embase, and PsycINFO from database inception until June 1, 2017. Functional MRI data from these articles were provided by most authors. Study Selection: Publications were included that provided brain activation contrasts between a sample with ASD and controls on a reward task, determined by multiple reviewer consensus. Data Extraction and Synthesis: When fMRI data were not provided by authors, multiple reviewers extracted peak coordinates and effect sizes from articles to recreate statistical maps using seed-based d mapping software. Random-effects meta-analyses of responses to social, nonsocial, and restricted interest stimuli, as well as all of these domains together, were performed. Secondary analyses included meta-analyses of wanting and liking, meta-regression with age, and correlations with ASD severity. All procedures were conducted in accordance with Meta-analysis of Observational Studies in Epidemiology guidelines. Main Outcomes and Measures: Brain activation differences between groups with ASD and typically developing controls while processing rewards. All analyses except the domain-general meta-analysis were planned before data collection. Results: The meta-analysis included 13 studies (30 total fMRI contrasts) from 259 individuals with ASD and 246 controls. Autism spectrum disorder was associated with aberrant processing of both social and nonsocial rewards in striatal regions and increased activation in response to restricted interests (social reward, caudate cluster: d = -0.25 [95% CI, -0.41 to -0.08]; nonsocial reward, caudate and anterior cingulate cluster: d = -0.22 [95% CI, -0.42 to -0.02]; restricted interests, caudate and nucleus accumbens cluster: d = 0.42 [95% CI, 0.07 to 0.78]). Conclusions and Relevance: Individuals with ASD show atypical processing of social and nonsocial rewards. Findings support a broader interpretation of the social motivation hypothesis of ASD whereby general atypical reward processing encompasses social reward, nonsocial reward, and perhaps restricted interests. This meta-analysis also suggests that prior mixed results could be driven by sample age differences, warranting further study of the developmental trajectory for reward processing in ASD.