Associations between perinatal risk and physical health in pre-adolescence in the Adolescent Brain Cognitive Development (ABCD) Study®: the unexpected relationship with sleep disruption.

BACKGROUND: To investigate relationships among different physical health problems in a large, sociodemographically diverse sample of 9-to-10-year-old children and determine the extent to which perinatal health factors are associated with childhood physical health problems. METHODS: A cross-sectional study was conducted utilizing the Adolescent Brain Cognitive Development℠ (ABCD) Study (n = 7613, ages 9-to-10-years-old) to determine the associations among multiple physical health factors (e.g., prenatal complications, current physical health problems). Logistic regression models controlling for age, sex, pubertal development, household income, caregiver education, race, and ethnicity evaluated relationships between perinatal factors and childhood physical health problems. RESULTS: There were significant associations between perinatal and current physical health measures. Specifically, those who had experienced perinatal complications were more likely to have medical problems by 9-to-10 years old. Importantly, sleep disturbance co-occurred with several physical health problems across domains and developmental periods. CONCLUSION: Several perinatal health factors were associated with childhood health outcomes, highlighting the importance of understanding and potentially improving physical health in youth. Understanding the clustering of physical health problems in youth is essential to better identify which physical health problems may share underlying mechanisms. IMPACT: Using a multivariable approach, we investigated the associations between various perinatal and current health problems amongst youth. Our study highlights current health problems, such as sleep problems at 9-to-10 years old, that are associated with a cluster of factors occurring across development (e.g., low birth weight, prenatal substance exposure, pregnancy complications, current weight status, lifetime head injury). Perinatal health problems are at large, non-modifiable (in this retrospective context), however, by identifying which are associated with current health problems, we can identify potential targets for intervention and prevention efforts.

FEMA: Fast and efficient mixed-effects algorithm for large sample whole-brain imaging data.

The linear mixed-effects model (LME) is a versatile approach to account for dependence among observations. Many large-scale neuroimaging datasets with complex designs have increased the need for LME; however LME has seldom been used in whole-brain imaging analyses due to its heavy computational requirements. In this paper, we introduce a fast and efficient mixed-effects algorithm (FEMA) that makes whole-brain vertex-wise, voxel-wise, and connectome-wide LME analyses in large samples possible. We validate FEMA with extensive simulations, showing that the estimates of the fixed effects are equivalent to standard maximum likelihood estimates but obtained with orders of magnitude improvement in computational speed. We demonstrate the applicability of FEMA by studying the cross-sectional and longitudinal effects of age on region-of-interest level and vertex-wise cortical thickness, as well as connectome-wide functional connectivity values derived from resting state functional MRI, using longitudinal imaging data from the Adolescent Brain Cognitive DevelopmentSM Study release 4.0. Our analyses reveal distinct spatial patterns for the annualized changes in vertex-wise cortical thickness and connectome-wide connectivity values in early adolescence, highlighting a critical time of brain maturation. The simulations and application to real data show that FEMA enables advanced investigation of the relationships between large numbers of neuroimaging metrics and variables of interest while considering complex study designs, including repeated measures and family structures, in a fast and efficient manner. The source code for FEMA is available via: https://github.com/cmig-research-group/cmig_tools/.

Polygenic profiles define aspects of clinical heterogeneity in attention deficit hyperactivity disorder.

Attention deficit hyperactivity disorder (ADHD) is a complex disorder that manifests variability in long-term outcomes and clinical presentations. The genetic contributions to such heterogeneity are not well understood. Here we show several genetic links to clinical heterogeneity in ADHD in a case-only study of 14,084 diagnosed individuals. First, we identify one genome-wide significant locus by comparing cases with ADHD and autism spectrum disorder (ASD) to cases with ADHD but not ASD. Second, we show that cases with ASD and ADHD, substance use disorder and ADHD, or first diagnosed with ADHD in adulthood have unique polygenic score (PGS) profiles that distinguish them from complementary case subgroups and controls. Finally, a PGS for an ASD diagnosis in ADHD cases predicted cognitive performance in an independent developmental cohort. Our approach uncovered evidence of genetic heterogeneity in ADHD, helping us to understand its etiology and providing a model for studies of other disorders.

Intelligence Polygenic Score Is More Predictive of Crystallized Measures: Evidence From the Adolescent Brain Cognitive Development (ABCD) Study.

Findings in adults have shown that crystallized measures of intelligence, which are more culturally sensitive than fluid intelligence measures, have greater heritability; however, these results have not been found in children. The present study used data from 8,518 participants between 9 and 11 years old from the Adolescent Brain Cognitive Development (ABCD) Study. We found that polygenic predictors of intelligence test performance (based on genome-wide association meta-analyses of data from 269,867 individuals) and of educational attainment (based on data from 1.1 million individuals) predicted neurocognitive performance. We found that crystallized measures were more strongly associated with both polygenic predictors than were fluid measures. This mirrored heritability differences reported previously in adults and suggests similar associations in children. This may be consistent with a prominent role of gene-environment correlation in cognitive development measured by crystallized intelligence tests. Environmental and experiential mediators may represent malleable targets for improving cognitive outcomes.

Family- and neighborhood-level environmental associations with physical health conditions in 9- and 10-year-olds.

OBJECTIVE: To determine how environmental factors are associated with physical health conditions in 9- to 10-year-old participants in the Adolescent Brain Cognitive Development (ABCD) Study, and how they are moderated by family-level socioeconomic status (SES). METHOD: We performed cross-sectional analyses of 8,429 youth participants in the ABCD Study, in which nine physical health conditions (having underweight or overweight/obesity, not participating in sports activities, short sleep duration, high sleep disturbances, lack of vigorous and strengthening-related physical activity, miscellaneous medical problems, and traumatic brain injury) were regressed on three environmental factors [neighborhood disadvantage (area deprivation index [ADI]), risk of lead exposure, and concentrations of particulate matter 2.5 (PM2.5)] and their interaction with family-level SES (i.e., parent-reported annual household income). Environmental data were geocoded to participants' primary residential addresses at 9- to 10-year-olds. RESULTS: Risk of lead exposure and ADI were positively associated with the odds of having overweight/obesity, not participating in sports activity, and short sleep durations. ADI was also positively associated with high sleep disturbances. PM2.5 was positively associated with the odds of having overweight/obesity and reduced vigorous physical activity. Family-level SES moderated relationships between ADI and both underweight and overweight/obesity, with high SES being associated with more pronounced changes given increased ADI. CONCLUSIONS: Policymakers and public health officials must implement policies and remediation strategies to ensure children are free from exposure to neurotoxicant and environmental factors. Physical health conditions may be less of a product of an individual's choices and more related to environmental influences. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Generalization of cortical MOSTest genome-wide associations within and across samples.

Genome-Wide Association studies have typically been limited to univariate analysis in which a single outcome measure is tested against millions of variants. Recent work demonstrates that a Multivariate Omnibus Statistic Test (MOSTest) is well powered to discover genomic effects distributed across multiple phenotypes. Applied to cortical brain MRI morphology measures, MOSTest has resulted in a drastic improvement in power to discover loci when compared to established approaches (min-P). One question that arises is how well these discovered loci replicate in independent data. Here we perform 10 times cross validation within 34,973 individuals from UK Biobank for imaging measures of cortical area, thickness and sulcal depth (>1,000 dimensionality for each). By deploying a replication method that aggregates discovered effects distributed across multiple phenotypes, termed PolyVertex Score (MOSTest-PVS), we demonstrate a higher replication yield and comparable replication rate of discovered loci for MOSTest (# replicated loci: 242-496, replication rate: 96-97%) in independent data when compared with the established min-P approach (# replicated loci: 26-55, replication rate: 91-93%). An out-of-sample replication of discovered loci was conducted with a sample of 4,069 individuals from the Adolescent Brain Cognitive Development® (ABCD) study, who are on average 50 years younger than UK Biobank individuals. We observe a higher replication yield and comparable replication rate of MOSTest-PVS compared to min-P. This finding underscores the importance of using well-powered multivariate techniques for both discovery and replication of high dimensional phenotypes in Genome-Wide Association studies.

Association of Genetic Variant Linked to Hemochromatosis With Brain Magnetic Resonance Imaging Measures of Iron and Movement Disorders.

Importance: Hereditary hemochromatosis (HH) is an autosomal recessive genetic disorder that leads to iron overload. Conflicting results from previous research has led some to believe the brain is spared the toxic effects of iron in HH. Objective: To test the association of the strongest genetic risk variant for HH on brainwide measures sensitive to iron deposition and the rates of movement disorders in a substantially larger sample than previous studies of its kind. Design, Setting, and Participants: This cross-sectional retrospective study included participants from the UK Biobank, a population-based sample. Genotype, health record, and neuroimaging data were collected from January 2006 to May 2021. Data analysis was conducted from January 2021 to April 2022. Disorders tested included movement disorders (International Statistical Classification of Diseases and Related Health Problems, Tenth Revision [ICD-10], codes G20-G26), abnormalities of gait and mobility (ICD-10 codes R26), and other disorders of the nervous system (ICD-10 codes G90-G99). Exposures: Homozygosity for p.C282Y, the largest known genetic risk factor for HH. Main Outcomes and Measures: T2-weighted and T2* signal intensity from brain magnetic resonance imaging scans, measures sensitive to iron deposition, and clinical diagnosis of neurological disorders. Results: The total cohort consisted of 488 288 individuals (264 719 female; ages 49-87 years, largely northern European ancestry), 2889 of whom were p.C282Y homozygotes. The neuroimaging analysis consisted of 836 individuals: 165 p.C282Y homozygotes (99 female) and 671 matched controls (399 female). A total of 206 individuals were excluded from analysis due to withdrawal of consent. Neuroimaging analysis showed that p.C282Y homozygosity was associated with decreased T2-weighted and T2* signal intensity in subcortical motor structures (basal ganglia, thalamus, red nucleus, and cerebellum; Cohen d >1) consistent with substantial iron deposition. Across the whole UK Biobank (2889 p.C282Y homozygotes, 485 399 controls), we found a significantly increased prevalence for movement disorders in male homozygotes (OR, 1.80; 95% CI, 1.28-2.55; P = .001) but not female individuals (OR, 1.09; 95% CI, 0.70-1.73; P = .69). Among the 31 p.C282Y male homozygotes with a movement disorder, only 10 had a concurrent HH diagnosis. Conclusions and Relevance: These findings indicate increased iron deposition in subcortical motor circuits in p.C282Y homozygotes and confirm an increased association with movement disorders in male homozygotes. Early treatment in HH effectively prevents the negative consequences of iron overload in the liver and heart. Our work suggests that screening for p.C282Y homozygosity in high-risk individuals also has the potential to reduce brain iron accumulation and to reduce the risk of movement disorders among male individuals who are homozygous for this mutation.

Unique prediction of developmental psychopathology from genetic and familial risk.

BACKGROUND: Early detection is critical for easing the rising burden of psychiatric disorders. However, the specificity of psychopathological measurements and genetic predictors is unclear among youth. METHODS: We measured associations between genetic risk for psychopathology (polygenic risk scores (PRS) and family history (FH) measures) and a wide range of behavioral measures in a large sample (n = 5,204) of early adolescent participants (9-11 years) from the Adolescent Brain and Cognitive Development StudySM . Associations were measured both with and without accounting for shared variance across measures of genetic risk. RESULTS: When controlling for genetic risk for other psychiatric disorders, polygenic risk for problematic opioid use (POU) is uniquely associated with lower behavioral inhibition. Attention deficit hyperactivity disorder (ADHD), depression (DEP), and attempted suicide (SUIC) PRS shared many significant associations with externalizing, internalizing, and psychosis-related behaviors. However, when accounting for all measures of genetic and familial risk, these PRS also showed clear, unique patterns of association. Polygenic risk for ASD, BIP, and SCZ, and attempted suicide uniquely predicted variability in cognitive performance. FH accounted for unique variability in behavior above and beyond PRS and vice versa, with FH measures explaining a greater proportion of unique variability compared to the PRS. CONCLUSION: Our results indicate that, among youth, many behaviors show shared genetic influences; however, there is also specificity in the profile of emerging psychopathologies for individuals with high genetic risk for particular disorders. This may be useful for quantifying early, differential risk for psychopathology in development.

Microstructural development from 9 to 14 years: Evidence from the ABCD Study.

During late childhood behavioral changes, such as increased risk-taking and emotional reactivity, have been associated with the maturation of cortico-cortico and cortico-subcortical circuits. Understanding microstructural changes in both white matter and subcortical regions may aid our understanding of how individual differences in these behaviors emerge. Restriction spectrum imaging (RSI) is a framework for modelling diffusion-weighted imaging that decomposes the diffusion signal from a voxel into hindered, restricted, and free compartments. This yields greater specificity than conventional methods of characterizing diffusion. Using RSI, we quantified voxelwise restricted diffusion across the brain and measured age associations in a large sample (n = 8086) from the Adolescent Brain and Cognitive Development (ABCD) study aged 9-14 years. Older participants showed a higher restricted signal fraction across the brain, with the largest associations in subcortical regions, particularly the basal ganglia and ventral diencephalon. Importantly, age associations varied with respect to the cytoarchitecture within white matter fiber tracts and subcortical structures, for example age associations differed across thalamic nuclei. This suggests that age-related changes may map onto specific cell populations or circuits and highlights the utility of voxelwise compared to ROI-wise analyses. Future analyses will aim to understand the relevance of this microstructural developmental for behavioral outcomes.

Association of Outdoor Ambient Fine Particulate Matter With Intracellular White Matter Microstructural Properties Among Children.

Importance: Outdoor particulate matter 2.5 µm or less in diameter (PM2.5) is a ubiquitous environmental neurotoxicant that may affect the developing brain. Little is known about associations between PM2.5 and white matter connectivity. Objectives: To assess associations between annual residential PM2.5 exposure and white matter microstructure health in a US sample of children 9 to 10 years of age and to examine whether associations are specific to certain white matter pathways or vary across neuroimaging diffusion markers reflective of intracellular and extracellular microstructural processes. Design, Setting, and Participants: This cross-sectional study, the Adolescent Brain and Cognitive Development (ABCD) Study, was composed of 21 study sites across the US and used baseline data collected from children 9 to 10 years of age from September 1, 2016, to October 15, 2018. Data analysis was performed from September 15, 2020, to June 30, 2021. Exposures: Annual mean PM2.5 exposure estimated by ensemble-based models and assigned to the primary residential addresses at baseline. Main Outcomes and Measures: Diffusion-weighted imaging (DWI) and tractography were used to delineate white matter tracts. The biophysical modeling technique of restriction spectrum imaging (RSI) was implemented to examine total hindered diffusion and restricted isotropic and anisotropic intracellular diffusion in each tract. Hierarchical mixed-effects models with natural splines were used to analyze the associations between PM2.5 exposure and DWI. Results: In a study population of 7602 children (mean [SD] age, 119.1 [7.42] months; 3955 [52.0%] female; 160 [ 21.%] Asian, 1025 [13.5%] Black, 1616 [21.3%] Hispanic, 4025 [52.9%] White, and 774 [10.2%] other [identified by parents as American Indian/Native American or Alaska Native; Native Hawaiian, Guamanian, Samoan, other Pacific Islander; Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese, or other Asian; or other race]), associations were seen between annual ambient PM2.5 and hemispheric differences in white matter microstructure. Hemisphere-stratified models revealed significant associations between PM2.5 exposure and restricted isotropic intracellular diffusion in the left cingulum, in the left superior longitudinal fasciculus, and bilaterally in the fornix and uncinate fasciculus. In tracts with strong positive associations, a PM2.5 increase from 8 to 12 µg/m3 was associated with increases of 2.16% (95% CI, 0.49%-3.84%) in the left cingulum, 1.95% (95% CI, 0.43%-3.47%) in the left uncinate, and 1.68% (95% CI, 0.01%-3.34%) in the right uncinate. Widespread negative associations were observed between PM2.5 and mean diffusivity. Conclusions and Relevance: The findings of this cross-sectional study suggest that annual mean PM2.5 exposure during childhood is associated with increased restricted isotropic diffusion and decreased mean diffusivity of specific white matter tracts, potentially reflecting differences in the composition of white matter microarchitecture.

Demographic and mental health assessments in the adolescent brain and cognitive development study: Updates and age-related trajectories.

The Adolescent Brain Cognitive Development (ABCD) Study of 11,880 youth incorporates a comprehensive range of measures assessing predictors and outcomes related to mental health across childhood and adolescence in participating youth, as well as information about family mental health history. We have previously described the logic and content of the mental health assessment battery at Baseline and 1-year follow-up. Here, we describe changes to that battery and issues and clarifications that have emerged, as well as additions to the mental health battery at the 2-, 3-, 4-, and 5-year follow-ups. We capitalize on the recent release of longitudinal data for caregiver and youth report of mental health data to evaluate trajectories of dimensions of psychopathology as a function of demographic factors. For both caregiver and self-reported mental health symptoms, males showed age-related decreases in internalizing and externalizing symptoms, while females showed an increase in internalizing symptoms with age. Multiple indicators of socioeconomic status (caregiver education, family income, financial adversity, neighborhood poverty) accounted for unique variance in both caregiver and youth-reported externalizing and internalizing symptoms. These data highlight the importance of examining developmental trajectories of mental health as a function of key factors such as sex and socioeconomic environment.

A Comprehensive Overview of the Physical Health of the Adolescent Brain Cognitive Development Study Cohort at Baseline.

Physical health in childhood is crucial for neurobiological as well as overall development, and can shape long-term outcomes into adulthood. The landmark, longitudinal Adolescent Brain Cognitive Development StudySM (ABCD study®), was designed to investigate brain development and health in almost 12,000 youth who were recruited when they were 9-10 years old and will be followed through adolescence and early adulthood. The overall goal of this paper is to provide descriptive analyses of physical health measures in the ABCD study at baseline, including but not limited to sleep, physical activity and sports involvement, and body mass index. Further this summary will describe how physical health measures collected from the ABCD cohort compare with current normative data and clinical guidelines. We propose this data set has the potential to facilitate clinical recommendations and inform national standards of physical health in this age group. This manuscript will also provide important information for ABCD users and help guide analyses investigating physical health including new avenues for health disparity research as it pertains to adolescent and young adult development.

Vertex-wise multivariate genome-wide association study identifies 780 unique genetic loci associated with cortical morphology.

Brain morphology has been shown to be highly heritable, yet only a small portion of the heritability is explained by the genetic variants discovered so far. Here we extended the Multivariate Omnibus Statistical Test (MOSTest) and applied it to genome-wide association studies (GWAS) of vertex-wise structural magnetic resonance imaging (MRI) cortical measures from N=35,657 participants in the UK Biobank. We identified 695 loci for cortical surface area and 539 for cortical thickness, in total 780 unique genetic loci associated with cortical morphology robustly replicated in 8,060 children of mixed ethnicity from the Adolescent Brain Cognitive Development (ABCD) Study®. This reflects more than 8-fold increase in genetic discovery at no cost to generalizability compared to the commonly used univariate GWAS methods applied to region of interest (ROI) data. Functional follow up including gene-based analyses implicated 10% of all protein-coding genes and pointed towards pathways involved in neurogenesis and cell differentiation. Power analysis indicated that applying the MOSTest to vertex-wise structural MRI data triples the effective sample size compared to conventional univariate GWAS approaches. The large boost in power obtained with the vertex-wise MOSTest together with pronounced replication rates and highlighted biologically meaningful pathways underscores the advantage of multivariate approaches in the context of highly distributed polygenic architecture of the human brain.

Risk factors associated with curiosity about alcohol use in the ABCD cohort.

Curiosity and intent to use alcohol in pre-adolescence is a risk factor for later experimentation and use, yet we know little of how curiosity about use develops. Here, we examine factors that may influence curiosity about alcohol use, as it may be an important predictor of later drinking behavior. Cross-sectional data on youth ages 10-11 from the ongoing Adolescent Brain Cognitive Development℠ (ABCD) Study Year 1 follow-up were used (n = 2,334; NDA 2.0.1). All participants were substance-naïve at time of assessment. Group factor analysis identified latent factors across common indicators of risk for early substance use (i.e., psychopathology and trait characteristics; substance use attitudes/behaviors; neurocognition; family and environment). Logistic mixed-effect models tested associations between latent factors of risk for early substance use and curiosity about alcohol use, controlling for demographics and study site. Two multidimensional factors were significantly inversely and positively associated with greater curiosity about alcohol use, respectively: 1) low internalizing and externalizing symptomatology coupled with low impulsivity, perceived neighborhood safety, negative parental history of alcohol use problems, and fewer adverse life experiences and family conflict; and 2) low perceived risk of alcohol use coupled with lack of peer disapproval of use. When assessing all risk factors in an overall regression, lack of perceived harm from trying alcohol once or twice was associated with greater likelihood of alcohol curiosity. Taken together, perceptions that alcohol use causes little harm and having peers with similar beliefs is related to curiosity about alcohol use among substance-naïve 10-11-year-olds. General mental health and environmental risk factors similarly increase the odds of curiosity for alcohol. Identification of multidimensional risk factors for early alcohol use may point to novel prevention and early intervention targets. Future longitudinal investigations in the ABCD cohort will determine the extent to which these factors and curiosity predict alcohol use among youth.

Reduced differentiation of emotion-associated bodily sensations in autism.

LAY ABSTRACT: More research has been conducted on how autistic people understand and interpret other people's emotions, than on how autistic people experience their own emotions. The experience of emotion is important however, because it can relate to difficulties like anxiety and depression, which are common in autism. In neurotypical adults and children, different emotions have been associated with unique maps of activity patterns in the body. Whether these maps of emotion are comparable in autism is currently unknown. Here, we asked 100 children and adolescents, 45 of whom were autistic, to color in outlines of the body to indicate how they experienced seven emotions. Autistic adults and children sometimes report differences in how they experience their internal bodily states, termed interoception, and so we also investigated how this related to the bodily maps of emotion. In this study, the autistic children and adolescents had comparable interoception to the non-autistic children and adolescents, but there was less variability in their maps of emotion. In other words, they showed more similar patterns of activity across the different emotions. This was not related to interoception, however. This work suggests that there are differences in how autistic people experience emotion that are not explained by differences in interoception. In neurotypical people, less variability in emotional experiences is linked to anxiety and depression, and future work should seek to understand if this is a contributing factor to the increased prevalence of these difficulties in autism.

Individual Differences in Cognitive Performance Are Better Predicted by Global Rather Than Localized BOLD Activity Patterns Across the Cortex.

Despite its central role in revealing the neurobiological mechanisms of behavior, neuroimaging research faces the challenge of producing reliable biomarkers for cognitive processes and clinical outcomes. Statistically significant brain regions, identified by mass univariate statistical models commonly used in neuroimaging studies, explain minimal phenotypic variation, limiting the translational utility of neuroimaging phenotypes. This is potentially due to the observation that behavioral traits are influenced by variations in neuroimaging phenotypes that are globally distributed across the cortex and are therefore not captured by thresholded, statistical parametric maps commonly reported in neuroimaging studies. Here, we developed a novel multivariate prediction method, the Bayesian polyvertex score, that turns a unthresholded statistical parametric map into a summary score that aggregates the many but small effects across the cortex for behavioral prediction. By explicitly assuming a globally distributed effect size pattern and operating on the mass univariate summary statistics, it was able to achieve higher out-of-sample variance explained than mass univariate and popular multivariate methods while still preserving the interpretability of a generative model. Our findings suggest that similar to the polygenicity observed in the field of genetics, the neural basis of complex behaviors may rest in the global patterning of effect size variation of neuroimaging phenotypes, rather than in localized, candidate brain regions and networks.

Positive Economic, Psychosocial, and Physiological Ecologies Predict Brain Structure and Cognitive Performance in 9-10-Year-Old Children.

While low socioeconomic status (SES) introduces risk for developmental outcomes among children, there are an array of proximal processes that determine the ecologies and thus the lived experiences of children. This study examined interrelations between 22 proximal measures in the economic, psychosocial, physiological, and perinatal ecologies of children, in association with brain structure and cognitive performance in a diverse sample of 8,158 9-10-year-old children from the Adolescent Brain Cognitive Development (ABCD) study. SES was measured by the income-to-needs ratio (INR), a measure used by federal poverty guidelines. Within the ABCD study, in what is one of the largest and most diverse cohorts of children studied in the United States, we replicate associations of low SES with lower total cortical surface area and worse cognitive performance. Associations between low SES (<200% INR) and measures of development showed the steepest increases with INR, with apparent increases still visible beyond the level of economic disadvantage in the range of 200-400% INR. Notably, we found three latent factors encompassing positive ecologies for children across the areas of economic, psychosocial, physiological, and perinatal well-being in association with better cognitive performance and the higher total cortical surface area beyond the effects of SES. Specifically, latent factors encompassing youth perceived social support and perinatal well-being were positive predictors of developmental measures for all children, regardless of SES. Further, we found a general latent factor that explained relationships between 20 of the proximal measures and encompassed a joint ecology of higher social and economic resources relative to low adversity across psychosocial, physiological, and perinatal domains. The association between the resource-to-adversity latent factor and cognitive performance was moderated by SES, such that for children in higher SES households, cognitive performance progressively increased with these latent factor scores, while for lower SES, cognitive performance increased only among children with the highest latent factor scores. Our findings suggest that both positive ecologies of increased access to resources and lower adversity are mutually critical for promoting better cognitive development in children from low SES households. Our findings inform future studies aiming to examine positive factors that influence healthier development in children.

Sensorimotor beta power reflects the precision-weighting afforded to sensory prediction errors.

It has been proposed that accurate motor control relies on Bayesian inference that integrates sensory input with prior contextual knowledge (Bays and Wolpert, 2007; Körding and Wolpert, 2004; Wolpert et al., 1995). Recent evidence has suggested that modulations in beta power (∼12-30 Hz) measured over sensorimotor cortices using electroencephalography (EEG) may represent parameters of Bayesian inference. While the well characterised post-movement beta synchronisation has been shown to correlate with prediction error (H. Tan, Jenkinson, & Brown, 2014; Huiling Tan, Wade, & Brown, 2016), recent evidence suggests that beta power may also represent uncertainty measures (Tan et al., 2016; Tzagarakis et al., 2015). The current study aimed to measure the neurophysiological correlates of uncertainty mediating Bayesian updating during a visuomotor adaptation paradigm in healthy human participants. In particular, sensory uncertainty was directly modulated to measure its effect on sensorimotor beta power. Participant's behaviour was modelled using the Hierarchical Gaussian Filter (HGF) in order to extract the latent variables involved in learning actions required by the task and correlate these with the measured EEG. We found that sensorimotor beta power correlated with inverse uncertainty afforded to sensory prediction errors both prior to and following a movement. This suggests that sensorimotor beta oscillations may more readily represent relative uncertainty within the sensorimotor system rather than error. Neurophysiological models describing the generation of beta oscillations offer a potential mechanism by which this neural signature may encode latent uncertainty parameters. This is essential for understanding how the brain controls behaviour.