Declining Gaze to Faces in Infants Developing Autism Spectrum Disorder: Evidence From Two Independent Cohorts.

Two independent cohorts (N = 155, N = 126) of infants at high and low risk for autism spectrum disorder (ASD) were followed prospectively between 6 and 36 months of age, when n = 46 were diagnosed with ASD. Gaze to adult faces was coded-during a developmental assessment (Cohort 1) or a play interaction (Cohort 2). Across both cohorts, most children developing ASD showed sharp declines in gaze to faces over time, relative to children without ASD. These findings suggest that declining developmental trajectories may be more common than previously recognized by retrospective methods. Trajectory-based screening methods could potentially identify children in the early stages of symptom onset and allow for early intervention before the full disorder has developed.

Real-World Implementation of Infant Behavioral Sleep Interventions: Results of a Parental Survey.

OBJECTIVE: To describe parental practices implementing behavioral sleep intervention (BSI) outside a clinical setting. STUDY DESIGN: Parents (n = 652), recruited through a Facebook group designed as a peer support group for parents using BSI, completed an online survey about their experience using BSI with their infant or toddler. RESULTS: On average, parents implemented BSI when their infant was 5.6 (±2.77) months. Parents most often used modified (49.5%) or unmodified extinction (34.9%), with fewer using a parental presence approach (15.6%). Regardless of BSI type, more parents endorsed "a great deal of stress" during the first night (42.2%) than 1 week later (5.2%). The duration of infant crying was typically greatest the first night (reported by 45%; M = 43 minutes) and was significantly reduced after 1 week (M = 8.54 minutes). Successful implementation of BSI on the first attempt was reported by 83%, with a median and mode of 7 days until completion (79% by 2 weeks). Regardless of BSI type, after intervention parents reported their infant had less difficulty falling asleep, fewer night awakenings, and were more likely to sleep in their room and/or in their own crib/bed. CONCLUSIONS: The majority of parents report successfully implementing BSI, with significantly reduced infant crying by the end of 1 week and success within 2 weeks. Few differences were found between behavioral approaches.

High-Protein and High-Dietary Fiber Breakfasts Result in Equal Feelings of Fullness and Better Diet Quality in Low-Income Preschoolers Compared with Their Usual Breakfast.

Background: In the United States, 17% of children are currently obese. Increasing feelings of fullness may prevent excessive energy intake, lead to better diet quality, and promote long-term maintenance of healthy weight.Objective: The purpose of this study was to develop a fullness-rating tool (aim 1) and to determine whether a high-protein (HP), high-fiber (HF), and combined HP and HF (HPHF) breakfast increases preschoolers' feelings of fullness before (pre) and after (post) breakfast and pre-lunch, as well as their diet quality, as measured by using a composite diet quality assessment tool, the Revised Children's Diet Quality Index (aim 2).Methods: Children aged 4 and 5 y (n = 41; 22 girls and 19 boys) from local Head Start centers participated in this randomized intervention trial. Sixteen percent of boys and 32% of girls were overweight or obese. After the baseline week, children rotated through four 1-wk periods of consuming ad libitum HP (19-20 g protein), HF (10-11 g fiber), HPHF (19-21 g protein, 10-12 g fiber), or usual (control) breakfasts. Food intake at breakfast was estimated daily, and for breakfast, lunch, and snack on day 3 of each study week Student's t tests and ANOVA were used to determine statistical differences.Results: Children's post-breakfast and pre-lunch fullness ratings were ≥1 point higher than those of pre-breakfast (aim 1). Although children consumed, on average, 65 kcal less energy during the intervention breakfasts (P < 0.007) than during the control breakfast, fullness ratings did not differ (P = 0.76). Relative to the control breakfast, improved diet quality (12%) was calculated for the HP and HF breakfasts (P < 0.027) but not for the HPHF breakfast (aim 2).Conclusions: Post-breakfast fullness ratings were not affected by the intervention breakfasts relative to the control breakfast. HP and HF breakfasts resulted in higher diet quality. Serving HP or HF breakfasts may be valuable in improving diet quality without lowering feelings of satiation or satiety. This trial was registered at clinicaltrials.gov as NCT02122224.

Capturing the complexity of autism: Applying a developmental cascades framework.

Developmental change emerges from dynamic interactions among networks of neural activity, behavior systems, and experience-dependent processes. A developmental cascades framework captures the sequential, multilevel, cross-domain nature of human development and is ideal for demonstrating how interconnected systems have far-reaching effects in typical and atypical development. Neurodevelopmental disorders represent an intriguing application of this framework. Autism spectrum disorder (ASD) is complex and heterogeneous, with biological and behavioral features that cut across multiple developmental domains, including those that are motor, cognitive, sensory, and bioregulatory. Mapping developmental cascades in ASD can be transformational in elucidating how seemingly unrelated behaviors (e.g., those emerging at different points in development and occurring in multiple domains) are part of an interconnected neurodevelopmental pathway. In this article, we review evidence for specific developmental cascades implicated in ASD and suggest that theoretical and empirical advances in etiology and change mechanisms can be accelerated using a developmental cascades framework.

Sleep, cerebrospinal fluid, and the glymphatic system: A systematic review.

Current theories of the glymphatic system (GS) hypothesize that it relies on cerebrospinal fluid (CSF) circulation to disseminate growth factors and remove metabolic waste from the brain with increased CSF production and circulation during sleep; thereby, linking sleep disturbance with elements of CSF circulation and GS exchange. However, our growing knowledge of the relations between sleep, CSF, and the GS are plagued by variability in sleep and CSF measures across a wide array of pathologies. Hence, this review aims to summarize the dynamic relationships between sleep, CSF-, and GS-related features in samples of typically developing individuals and those with autoimmune/inflammatory, neurodegenerative, neurodevelopmental, sleep-related, neurotraumatic, neuropsychiatric, and skull atypicalities. One hundred and ninety articles (total n = 19,129 participants) were identified and reviewed for pathology, CSF circulation and related metrics, GS function, and sleep. Numerous associations were documented between sleep problems and CSF metabolite concentrations (e.g., amyloid-beta, orexin, tau proteins) and increased CSF volumes or pressure. However, these relations were not universal, with marked differences across pathologies. It is clear that elements of CSF circulation/composition and GS exchange represent pathways influenced by sleep; however, carefully designed studies and advances in GS measurement are needed to delineate the nuanced relationships.

Coupling between cerebrovascular oscillations and CSF flow fluctuations during wakefulness: An fMRI study.

It is commonly believed that cerebrospinal fluid (CSF) movement is facilitated by blood vessel wall movements (i.e., hemodynamic oscillations) in the brain. A coherent pattern of low frequency hemodynamic oscillations and CSF movement was recently found during non-rapid eye movement (NREM) sleep via functional MRI. This finding raises other fundamental questions: 1) the explanation of coupling between hemodynamic oscillations and CSF movement from fMRI signals; 2) the existence of the coupling during wakefulness; 3) the direction of CSF movement. In this resting state fMRI study, we proposed a mechanical model to explain the coupling between hemodynamics and CSF movement through the lens of fMRI. Time delays between CSF movement and global hemodynamics were calculated. The observed delays between hemodynamics and CSF movement match those predicted by the model. Moreover, by conducting separate fMRI scans of the brain and neck, we confirmed the low frequency CSF movement at the fourth ventricle is bidirectional. Our finding also demonstrates that CSF movement is facilitated by changes in cerebral blood volume mainly in the low frequency range, even when the individual is awake.

Human CSF movement influenced by vascular low frequency oscillations and respiration.

Cerebrospinal fluid (CSF) movement through the pathways within the central nervous system is of high significance for maintaining normal brain health and function. Low frequency hemodynamics and respiration have been shown to drive CSF in humans independently. Here, we hypothesize that CSF movement may be driven simultaneously (and in synchrony) by both mechanisms and study their independent and coupled effects on CSF movement using novel neck fMRI scans. Caudad CSF movement at the fourth ventricle and hemodynamics of the major neck blood vessels (internal carotid arteries and internal jugular veins) was measured from 11 young, healthy volunteers using novel neck fMRI scans with simultaneous measurement of respiration. Two distinct models of CSF movement (1. Low-frequency hemodynamics and 2. Respiration) and possible coupling between them were investigated. We show that the dynamics of brain fluids can be assessed from the neck by studying the interrelationships between major neck blood vessels and the CSF movement in the fourth ventricle. We also demonstrate that there exists a cross-frequency coupling between these two separable mechanisms. The human CSF system can respond to multiple coupled physiological forces at the same time. This information may help inform the pathological mechanisms behind CSF movement-related disorders.

An mCARE study on patterns of risk and resilience for children with ASD in Bangladesh.

Community-wide lockdowns in response to COVID-19 influenced many families, but the developmental cascade for children with autism spectrum disorder (ASD) may be especially detrimental. Our objective was to evaluate behavioral patterns of risk and resilience for children with ASD across parent-report assessments before (from November 2019 to February 2020), during (March 2020 to May 2020), and after (June 2020 to November 2020) an extended COVID-19 lockdown. In 2020, our study Mobile-based care for children with ASD using remote experience sampling method (mCARE) was inactive data collection before COVID-19 emerged as a health crisis in Bangladesh. Here we deployed "Cohort Studies", where we had in total 300 children with ASD (150 test group and 150 control group) to collect behavioral data. Our data collection continued through an extended COVID-19 lockdown and captured parent reports of 30 different behavioral parameters (e.g., self-injurious behaviors, aggression, sleep problems, daily living skills, and communication) across 150 children with ASD (test group). Based on the children's condition, 4-6 behavioral parameters were assessed through the study. A total of 56,290 behavioral data points was collected (an average of 152.19 per week) from parent cell phones using the mCARE platform. Children and their families were exposed to an extended COVID-19 lockdown. The main outcomes used for this study were generated from parent reports child behaviors within the mCARE platform. Behaviors included of child social skills, communication use, problematic behaviors, sensory sensitivities, daily living, and play. COVID-19 lockdowns for children with autism and their families are not universally negative but supports in the areas of "Problematic Behavior" could serve to mitigate future risk.

Informing Developmental Milestone Achievement for Children With Autism: Machine Learning Approach.

BACKGROUND: Care for children with autism spectrum disorder (ASD) can be challenging for families and medical care systems. This is especially true in low- and- middle-income countries such as Bangladesh. To improve family-practitioner communication and developmental monitoring of children with ASD, mCARE (Mobile-Based Care for Children with Autism Spectrum Disorder Using Remote Experience Sampling Method) was developed. Within this study, mCARE was used to track child milestone achievement and family sociodemographic assets to inform mCARE feasibility/scalability and family asset-informed practitioner recommendations. OBJECTIVE: The objectives of this paper are threefold. First, it documents how mCARE can be used to monitor child milestone achievement. Second, it demonstrates how advanced machine learning models can inform our understanding of milestone achievement in children with ASD. Third, it describes family/child sociodemographic factors that are associated with earlier milestone achievement in children with ASD (across 5 machine learning models). METHODS: Using mCARE-collected data, this study assessed milestone achievement in 300 children with ASD from Bangladesh. In this study, we used 4 supervised machine learning algorithms (decision tree, logistic regression, K-nearest neighbor [KNN], and artificial neural network [ANN]) and 1 unsupervised machine learning algorithm (K-means clustering) to build models of milestone achievement based on family/child sociodemographic details. For analyses, the sample was randomly divided in half to train the machine learning models and then their accuracy was estimated based on the other half of the sample. Each model was specified for the following milestones: Brushes teeth, Asks to use the toilet, Urinates in the toilet or potty, and Buttons large buttons. RESULTS: This study aimed to find a suitable machine learning algorithm for milestone prediction/achievement for children with ASD using family/child sociodemographic characteristics. For Brushes teeth, the 3 supervised machine learning models met or exceeded an accuracy of 95% with logistic regression, KNN, and ANN as the most robust sociodemographic predictors. For Asks to use toilet, 84.00% accuracy was achieved with the KNN and ANN models. For these models, the family sociodemographic predictors of "family expenditure" and "parents' age" accounted for most of the model variability. The last 2 parameters, Urinates in toilet or potty and Buttons large buttons, had an accuracy of 91.00% and 76.00%, respectively, in ANN. Overall, the ANN had a higher accuracy (above ~80% on average) among the other algorithms for all the parameters. Across the models and milestones, "family expenditure," "family size/type," "living places," and "parent's age and occupation" were the most influential family/child sociodemographic factors. CONCLUSIONS: mCARE was successfully deployed in a low- and middle-income country (ie, Bangladesh), providing parents and care practitioners a mechanism to share detailed information on child milestones achievement. Using advanced modeling techniques this study demonstrates how family/child sociodemographic elements can inform child milestone achievement. Specifically, families with fewer sociodemographic resources reported later milestone attainment. Developmental science theories highlight how family/systems can directly influence child development and this study provides a clear link between family resources and child developmental progress. Clinical implications for this work could include supporting the larger family system to improve child milestone achievement.

Diversity in pediatric behavioral sleep intervention studies.

Studies designed to assess the efficacy of behavioral sleep interventions for infants and young children often report sleep improvements, but the generalization to children and families of diverse backgrounds is rarely assessed. The present study describes a systematic review of the racial, ethnic, and socioeconomic diversity of behavioral sleep intervention studies for young children. Thirty-two behavioral sleep intervention studies (5474 children) were identified using PRISMA guidelines. Each study was coded for racial and ethnic composition, parental educational attainment (an index of socioeconomic resources), and country of origin. Racial or ethnic information was obtained for 19 studies (60%). Study participants were primarily White and from predominantly White countries. Overall, 21 (66%) of the included studies provided information on parental education. Most of these studies had samples with moderate to high educational attainment. Behavioral sleep intervention studies to date include samples with insufficient diversity. Overall, this study highlights a critical gap in pediatric sleep intervention research and supports a call to further include families from diverse backgrounds when assessing behavioral sleep interventions.

Sleep in Neurodevelopmental Disorders.

Individuals with intellectual and developmental disabilities (IDD) experience sleep problems at higher rates than the general population. Although individuals with IDD are a heterogeneous group, several sleep problems cluster within genetic syndromes or disorders. This review summarizes the prevalence of sleep problems experienced by individuals with Angelman syndrome, Cornelia de Lange syndrome, Cri du Chat syndrome, Down syndrome, fragile X syndrome, Prader-Willi syndrome, Smith-Magenis syndrome, Williams syndrome, autism spectrum disorder, and idiopathic IDD. Factors associated with sleep problems and the evidence for sleep treatments are reviewed for each neurodevelopmental disorder. Sleep research advancements in neurodevelopmental disorders are reviewed, including the need for consistency in defining and measuring sleep problems, considerations for research design and reporting of results, and considerations when evaluating sleep treatments.

Circadian Sleep Patterns in Toddlers Born Preterm: Longitudinal Associations with Developmental and Health Concerns.

OBJECTIVE: Children born preterm are at elevated risk for several developmental and health concerns. Early sleep patterns may be associated with these concerns. The current study assesses the associations between toddler circadian sleep/activity patterns and later developmental, behavioral, attentional, and health concerns in this at-risk population. METHOD: We examined circadian sleep/activity patterns at 2 years of age in 99 children born preterm. Child cognitive skills were tested at 3 years of age, and behavior, attention, and health concerns were reported at 3 and 6 years of age. First, sleep/activity data collected via actigraphy were assessed using time series analysis (TSA). For this, we assessed how each child's sleep/activity pattern compared to a specified 24-hour circadian cycle (SCC) with an adjustment for daytime napping. Second, in a series of regression models child sleep/activity parameters from the TSA were assessed with child gender, prematurity, and family sociodemographic assets as covariates. RESULTS: Toddlers with patterns that closely aligned with the SCC had higher abbreviated intelligence quotient scores at 3 years of age. Additionally, at 6 years these children had a lower risk for illness-related medical visits. Higher toddler average activity level was associated with fewer teacher-reported attention-deficit hyperactivity disorder symptoms and a lower risk for illness-related medical visits. CONCLUSION: The novel approach used in this study to index child circadian patterns provides a pattern-based analysis of sleep/activity, which may prove to be developmentally consequential. With replication, these findings may help practitioners promote optimal cognitive and health development via circadian sleep supports in infants born preterm.

Behavior and sleep problems in children with a family history of autism.

The present study explores behavioral and sleep outcomes in preschool-age siblings of children with autism spectrum disorders (ASD). This study focuses on behavior problems that are common in children with ASD, such as emotional reactivity, anxiety, inattention, aggression, and sleep problems. Infant siblings were recruited from families with at least one older child with ASD (high-risk group, n = 104) or families with no history of ASD (low-risk group, n = 76). As part of a longitudinal prospective study, children completed the Mullen Scales of Early Learning and the Autism Diagnostic Observation Schedule, and parents completed the Child Behavior Checklist (CBCL) and the Social Communication Questionnaire at 36 months of age. This study focuses on developmental concerns outside of ASD; therefore, only siblings who did not develop an ASD were included in analyses. Negative binomial regression analyses revealed that children in the high-risk group were more likely to have elevated behavior problems on the CBCL Anxious/Depressed and Aggression subscales. To explore sleep problems as a correlate of these behavior problems, a second series of models was specified. For both groups of children, sleep problems were associated with elevated behavior problems in each of the areas assessed (reactivity, anxiety, somatic complaints, withdrawal, attention, and aggression). These findings support close monitoring of children with a family history of ASD for both behavioral and sleep issues.

Causes and correlates of frequent night awakenings in early childhood.

Night awakenings are a normative part of early development. In the first year, night awakenings are associated with birth order, feeding route, sleep aid use, sleep location, infant temperament and development, infant-parent attachment, family socioeconomics, and cultural norms. In the second year, additional factors build on these foundational features, including parenting practices and object attachment. As children grow, contextual factors like preschool entry or changes in family member status may influence the continuation or exacerbation of awakenings. Future research should consider the multitude of factors that influence not only awakenings but also parental perceptions, family dynamics, and cultural norms.