Reduced covariation between brain morphometry and local spontaneous activity in young children with ASD.

While disruptions in brain maturation in the first years of life in ASD are well documented, little is known about how the brain structure and function are related in young children with ASD compared to typically developing peers. We applied a multivariate pattern analysis to examine the covariation patterns between brain morphometry and local brain spontaneous activity in 38 toddlers and preschoolers with ASD and 31 typically developing children using T1-weighted structural MRI and resting-state fMRI data acquired during natural sleep. The results revealed significantly reduced brain structure-function correlations in ASD. The resultant brain structure and function composite indices were associated with age among typically developing children, but not among those with ASD, suggesting mistiming of typical brain maturational trajectories early in life in autism. Additionally, the brain function composite indices were associated with the overall developmental and adaptive behavior skills in the ASD group, highlighting the neurodevelopmental significance of early local brain activity in autism.

Sleep Problems in Preschoolers With Autism Spectrum Disorder Are Associated With Sensory Sensitivities and Thalamocortical Overconnectivity.

BACKGROUND: Projections between the thalamus and sensory cortices are established early in development and play an important role in regulating sleep as well as in relaying sensory information to the cortex. Atypical thalamocortical functional connectivity frequently observed in children with autism spectrum disorder (ASD) might therefore be linked to sensory and sleep problems common in ASD. METHODS: Here, we investigated the relationship between auditory-thalamic functional connectivity measured during natural sleep functional magnetic resonance imaging, sleep problems, and sound sensitivities in 70 toddlers and preschoolers (1.5-5 years old) with ASD compared with a matched group of 46 typically developing children. RESULTS: In children with ASD, sleep problems and sensory sensitivities were positively correlated, and increased sleep latency was associated with overconnectivity between the thalamus and auditory cortex in a subsample with high-quality magnetic resonance imaging data (n = 29). In addition, auditory cortex blood oxygen level-dependent signal amplitude was elevated in children with ASD, potentially reflecting reduced sensory gating or a lack of auditory habituation during natural sleep. CONCLUSIONS: These findings indicate that atypical thalamocortical functional connectivity can be detected early in development and may play a crucial role in sleep problems and sensory sensitivities in ASD.

Cortical myelination in toddlers and preschoolers with autism spectrum disorder.

Intracortical myelin is thought to play a significant role in the development of neural circuits and functional networks, with consistent evidence of atypical network connectivity in children with autism spectrum disorder (ASD). However, little is known about the development of intracortical myelin in the first years of life in ASD, during the critical neurodevelopmental period when autism symptoms first emerge. Using T1-weighted (T1w) and T2w structural magnetic resonance imaging (MRI) in 21 young children with ASD and 16 typically developing (TD) children, ages 1.5-5.5 years, we demonstrate the feasibility of estimating intracortical myelin in vivo using the T1w/T2w ratio as a proxy. The resultant T1w/T2w maps were largely comparable with those reported in prior T1w/T2w studies in TD children and adults, and revealed no group differences between TD children and those with ASD. However, differential associations between T1w/T2w and age were identified in several early myelinated regions (e.g., visual, posterior cingulate, precuneus cortices) in the ASD and TD groups, with age-related increase in estimated myelin content across the toddler and preschool years detected in TD children, but not in children with ASD. The atypical age-related effects in intracortical myelin, suggesting a disrupted myelination in the first years of life in ASD, may be related to the aberrant brain network connectivity reported in young children with ASD in some of the same cortical regions and circuits.

Externalizing Behaviors are Associated with Increased Parenting Stress in Caregivers of Young Children with Autism.

Parents of children diagnosed with autism spectrum disorder (ASD) report higher levels of stress than parents of typically developing children. Few studies have examined factors associated with parental stress in early childhood. Even fewer have investigated the simultaneous influence of sociodemographic, clinical, and developmental variables on parental stress. We examined factors associated with stress in parents of young children with ASD. Multiple regression models were used to test for associations between socioeconomic indices, developmental measures, and parental stress. Externalizing behaviors, communication, and socialization skills accounted for variance in parental stress, controlling for ASD diagnosis. Results highlight the importance of interventions aimed at reducing externalizing behaviors in young children as well as addressing stress in caregivers of children with ASD.

Resting state functional networks in 1-to-3-year-old typically developing children.

Brain functional networks undergo substantial development and refinement during the first years of life. Yet, the maturational pathways of functional network development remain poorly understood. Using resting-state fMRI data acquired during natural sleep from 24 typically developing toddlers, ages 1.5-3.5 years, we aimed to examine the large-scale resting-state functional networks and their relationship with age and developmental skills. Specifically, two network organization indices reflecting network connectivity and spatial variability were derived. Our results revealed that reduced spatial variability or increased network homogeneity in one of the default mode network components was associated with age, with older children displaying less spatially variable posterior DMN subcomponent, consistent with the notion of increased spatial and functional specialization. Further, greater network homogeneity in higher-order functional networks, including the posterior default mode, salience, and language networks, was associated with more advanced developmental skills measured with a standardized assessment of early learning, regardless of age. These results not only improve our understanding of brain functional network development during toddler years, but also inform the relationship between brain network organization and emerging cognitive and behavioral skills.

[Formula: see text] Neural correlates of socioeconomic status in early childhood: a systematic review of the literature.

It is now established that socioeconomic variables are associated with cognitive, academic achievement, and psychiatric outcomes. Recent years have shown the advance in our understanding of how socioeconomic status (SES) relates to brain development in the first years of life (ages 0-5 years). However, it remains unknown which neural structures and functions are most sensitive to the environmental experiences associated with SES. Pubmed, PsycInfo, and Google Scholar databases from January 1, 2000, to December 31, 2019, were systematically searched using terms "Neural" OR "Neuroimaging" OR "Brain" OR "Brain development," AND "Socioeconomic" OR "SES" OR "Income" OR "Disadvantage" OR "Education," AND "Early childhood" OR "Early development". Nineteen studies were included in the full review after applying all exclusion criteria. Studies revealed associations between socioeconomic and neural measures and indicated that, in the first years of life, certain neural functions and structures (e.g., those implicated in language and executive function) may be more sensitive to socioeconomic context than others. Findings broadly support the hypothesis that SES associations with neural structure and function operate on a gradient. Socioeconomic status is reflected in neural architecture and function of very young children, as early as shortly after birth, with its effects possibly growing throughout early childhood as a result of postnatal experiences. Although socioeconomic associations with neural measures were relatively consistent across studies, results from this review are not conclusive enough to supply a neural phenotype of low SES. Further work is necessary to understand causal mechanisms underlying SES-brain associations.

Greater functional connectivity between sensory networks is related to symptom severity in toddlers with autism spectrum disorder.

BACKGROUND: Symptoms of autism spectrum disorder (ASD) emerge in the first years of life. Yet, little is known about the organization and development of functional brain networks in ASD proximally to the symptom onset. Further, the relationship between brain network connectivity and emerging ASD symptoms and overall functioning in early childhood is not well understood. METHODS: Resting-state fMRI data were acquired during natural sleep from 24 young children with ASD and 23 typically developing (TD) children, aged 17-45 months. Intrinsic functional connectivity (iFC) within and between resting-state functional networks was derived with independent component analysis (ICA). RESULTS: Increased iFC between visual and sensorimotor networks was found in young children with ASD compared to TD participants. Within the ASD group, the degree of overconnectivity between visual and sensorimotor networks was associated with greater autism symptoms. Age-related weakening of the visual-auditory between-network connectivity was observed in the ASD but not the TD group. CONCLUSIONS: Taken together, these results provide evidence for disrupted functional network maturation and differentiation, particularly involving visual and sensorimotor networks, during the first years of life in ASD. The observed pattern of greater visual-sensorimotor between-network connectivity associated with poorer clinical outcomes suggests that disruptions in multisensory brain circuitry may play a critical role for early development of behavioral skills and autism symptomatology in young children with ASD.

Socioeconomic Factors Account for Variability in Language Skills in Preschoolers with Autism Spectrum Disorders.

OBJECTIVE: Although no longer required for a diagnosis, language delays are extremely common in children diagnosed with autism spectrum disorders (ASD). Factors associated with socioeconomic status (SES) have broad-reaching impact on language development in early childhood. Despite recent advances in characterizing autism in early childhood, the relationship between SES and language development in ASD has not received much attention. THE OBJECTIVE OF THIS STUDY WAS: to examine whether toddlers and preschoolers with ASD from low-resource families are more likely to experience language delays above and beyond those associated with autism itself. METHODS: Developmental and diagnostic assessments including the Mullen Scales of Early Learning, the Autism Diagnostic Observation Schedule, Second Edition, and the Vineland Adaptive Behavior Scales were obtained from 62 young children with ASD and 45 typically developing children aged 15 to 64 months. Sociodemographic information including household income, maternal education, and racial/ethnic identity was obtained from caregivers. Multiple regression models were used to test for associations between socioeconomic indices and language scores. RESULTS: Maternal education accounted for variability in expressive language (EL) and receptive language (RL), with lower SES indices associated with lower language skills, and more so in children with ASD. CONCLUSION: These results demonstrate that variability in EL and RL skills in young children with autism can be accounted for by socioeconomic variables. These findings highlight the necessity for targeted intervention and effective implementation strategies for children with ASD from low-resource households and communities and for policies designed to improve learning opportunities and access to services for these young children and their families.

Association of White Matter Structure With Autism Spectrum Disorder and Attention-Deficit/Hyperactivity Disorder.

Importance: Clinical overlap between autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) is increasingly appreciated, but the underlying brain mechanisms remain unknown to date. Objective: To examine associations between white matter organization and 2 commonly co-occurring neurodevelopmental conditions, ASD and ADHD, through both categorical and dimensional approaches. Design, Setting, and Participants: This investigation was a cross-sectional diffusion tensor imaging (DTI) study at an outpatient academic clinical and research center, the Department of Child and Adolescent Psychiatry at New York University Langone Medical Center. Participants were children with ASD, children with ADHD, or typically developing children. Data collection was ongoing from December 2008 to October 2015. Main Outcomes and Measures: The primary measure was voxelwise fractional anisotropy (FA) analyzed via tract-based spatial statistics. Additional voxelwise DTI metrics included radial diffusivity (RD), mean diffusivity (MD), axial diffusivity (AD), and mode of anisotropy (MA). Results: This cross-sectional DTI study analyzed data from 174 children (age range, 6.0-12.9 years), selected from a larger sample after quality assurance to be group matched on age and sex. After quality control, the study analyzed data from 69 children with ASD (mean [SD] age, 8.9 [1.7] years; 62 male), 55 children with ADHD (mean [SD] age, 9.5 [1.5] years; 41 male), and 50 typically developing children (mean [SD] age, 9.4 [1.5] years; 38 male). Categorical analyses revealed a significant influence of ASD diagnosis on several DTI metrics (FA, MD, RD, and AD), primarily in the corpus callosum. For example, FA analyses identified a cluster of 4179 voxels (TFCE FEW corrected P < .05) in posterior portions of the corpus callosum. Dimensional analyses revealed associations between ASD severity and FA, RD, and MD in more extended portions of the corpus callosum and beyond (eg, corona radiata and inferior longitudinal fasciculus) across all individuals, regardless of diagnosis. For example, FA analyses revealed clusters overall encompassing 12121 voxels (TFCE FWE corrected P < .05) with a significant association with parent ratings in the social responsiveness scale. Similar results were evident using an independent measure of ASD traits (ie, children communication checklist, second edition). Total severity of ADHD-traits was not significantly related to DTI metrics but inattention scores were related to AD in corpus callosum in a cluster sized 716 voxels. All these findings were robust to algorithmic correction of motion artifacts with the DTIPrep software. Conclusions and Relevance: Dimensional analyses provided a more complete picture of associations between ASD traits and inattention and indexes of white matter organization, particularly in the corpus callosum. This transdiagnostic approach can reveal dimensional relationships linking white matter structure to neurodevelopmental symptoms.

Enhancing studies of the connectome in autism using the autism brain imaging data exchange II.

The second iteration of the Autism Brain Imaging Data Exchange (ABIDE II) aims to enhance the scope of brain connectomics research in Autism Spectrum Disorder (ASD). Consistent with the initial ABIDE effort (ABIDE I), that released 1112 datasets in 2012, this new multisite open-data resource is an aggregate of resting state functional magnetic resonance imaging (MRI) and corresponding structural MRI and phenotypic datasets. ABIDE II includes datasets from an additional 487 individuals with ASD and 557 controls previously collected across 16 international institutions. The combination of ABIDE I and ABIDE II provides investigators with 2156 unique cross-sectional datasets allowing selection of samples for discovery and/or replication. This sample size can also facilitate the identification of neurobiological subgroups, as well as preliminary examinations of sex differences in ASD. Additionally, ABIDE II includes a range of psychiatric variables to inform our understanding of the neural correlates of co-occurring psychopathology; 284 diffusion imaging datasets are also included. It is anticipated that these enhancements will contribute to unraveling key sources of ASD heterogeneity.