Research Publications

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Alcohol use during adolescence poses a significant public health problem due to its potential long-term consequences on both physical and mental health and increased risk for developing substance use disorders later in life. Both individual (e.g., genetic liability, neural functioning, personality features) and environmental (e.g., parenting, school environment) features play an important role in accelerating or buffering the progression of early alcohol consumption. This study used data from the Adolescent Brain Cognitive Development (ABCD) study (Release 5.1; N = 11,868) to provide a comprehensive examination of how genetic, neural, trait, and environmental factors are associated with risk for first sip of alcohol, first full drink, and the progression from first sip to full drink, both independently and uniquely. Cox proportional hazard models were used to examine the univariable associations between theoretically relevant genetic, neural, trait, and environmental variables and early alcohol use. Then, stepwise model-fitting was used to determine which indicators were uniquely associated with alcohol outcomes. Risk for early alcohol use was distributed across multiple domains highlighting the unique information provided by genetic, trait, and environmental variables. Results also indicated the importance of both environmental and genetic factors on time to first sip of alcohol, but that time to first full drink and the progression from sip to drink was most associated with genetic and trait factors rather than broad environmental influences. These findings highlight both potential etiological pathways driving early alcohol use as well as phenotypic and environmental process that can be targeted for early intervention efforts.

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Resilience to developing emotional disorders is critical for adolescent mental health, especially following childhood trauma. Yet, brain markers of resilience remain poorly understood. By analyzing brain responses to angry faces in a large-scale longitudinal adolescent cohort (IMAGEN), we identified two functional networks located in the orbitofrontal and occipital regions. In girls with high genetic risks for depression, higher orbitofrontal-related network activation was associated with a reduced impact of childhood trauma on emotional symptoms at age 19, whereas in those with low genetic risks, lower occipital-related network activation had a similar association. These findings reveal genetic risk-dependent brain markers of resilience (GRBMR). Longitudinally, the orbitofrontal-related GRBMR predicted subsequent emotional disorders in late adolescence, which were generalizable to an independent prospective cohort (ABCD). These findings demonstrate that high polygenic depression risk relates to activations in the orbitofrontal network and to resilience, with implications for biomarkers and treatment.

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Preterm birth can significantly impact cognitive development, particularly executive functions (EF). This study investigated hot (with emotional/motivational aspects) and cool (purely neutral/cognitive) EF trajectories in preterm and full-term children, examining brain-behavior relationships. It included 3508 participants aged 9-10 years (mean age 10.0 years) at baseline from the Adolescent Brain and Cognitive Development (ABCD®) study, evenly split between preterm and full-term births (54.36 % males; 1.05 % Asian American, 10.69 % Black, 15.68 % Hispanic, 61.57 % White, 11.09 % other). Participants were followed for 4 years, completing MRI scans and a cool EF task at baseline and at the 2-year follow-up, as well as hot/cool and hot EF tasks at the 1- and 3-year follow-ups. Linear mixed models showed varying effects of preterm birth across the different EF tasks. Specifically, preterm children showed persistent cool EF deficits and a catch-up pattern for hot EF, while performance on the hot/cool task showed no association with preterm birth. Brain-behavior bivariate latent change score analyses identified distinct bidirectional relationships in specific regions, suggesting altered cognitive-brain maturation interactions in preterm children. These findings highlight the complex nature of EF development following preterm birth: while cool EF deficits persist, hot EF shows catch-up growth in preterm children during early adolescence. This emphasizes the need for tailored interventions and long-term follow-up in this population.

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Adverse childhood experiences (ACEs) are key risk factors for adolescent mental health problems, including conduct problems (CP). While ACEs may impact CP through neurobiological pathways, it is unclear whether brain functional connectivity acts as the neurobiological link.

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Social functioning difficulties among youth with attention-deficit/hyperactivity disorder (ADHD) have been examined behaviorally; however, limited research has investigated brain networks associated with social difficulties among youth with ADHD. A growing body of literature supports the utility of the NIMH’s Research Domain Criteria (RDoC) framework, which emphasizes broad neurobiological based dimensions, allowing for the integration of models of both neural circuitry and behavior when examining externalizing behaviors in youth. We hypothesized that an ADHD classification system based on social functioning would better predict real-world psychosocial and academic outcomes compared to traditional Diagnostic and Statistical Manual of Mental Disorders (DSM-5) nosology of ADHD presentations. First, using data from the Adolescent Brain Cognitive Development (ABCD) Study, we identified four distinct profiles of youth with ADHD ranging from low social functioning to high social functioning. These social-data-derived profiles were linked to differential social challenges associated with caregiver income and mental health disorders. Next, our neuroimaging findings initially revealed differential patterns of functional connectivity across profiles involving attention-control, cingulo-opercular, sensorimotor networks. However, these connectivity differences were not consistently replicated, indicating that social functioning alone may not define neurobiologically distinct subgroups. Finally, in comparing our social functioning profiles to existing DSM-5 nosology with respect to real-world psychosocial outcomes, our social profiles demonstrated greater explanatory power for outcomes related to peer relationships, family conflict, and mental health. Overall, these findings emphasize the heterogeneity in social functioning among ADHD youth and suggest that while behavioral profiles are clinically meaningful, future work should integrate additional dimensions, such as executive functioning, to more precisely capture the neurobiological underpinnings of ADHD.

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Adolescent digital media use is highly prevalent. However, potential harms are unclear, as prospective studies of outcomes of screen-naïve youth are sparse. This study assessed whether individual differences in 4 domains relevant to addiction, measured in late childhood, prospectively predicted average daily hours of screen time (ST) and problematic screen use (PSU), defined as screen use that is compulsive and distressing, of 3 screen activities in mid-adolescence.

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In adolescence, caffeinated beverage consumption is negatively associated with cognitive functioning. The default mode network and dorsal attention network are anticorrelated brain systems that are essentially implicated in attention. Despite the importance of the anticorrelation of default mode network – dorsal attention network on cognitive functioning, no studies have examined the association between this anticorrelation and recent caffeine consumption among youths. This study analyzed baseline data from the Adolescent Brain Cognitive Development℠ Study, the largest longitudinal study examining brain development and adolescent health in the United States, to explore the associations between caffeinated beverage consumption and the strength of anticorrelation between the default mode network – dorsal attention network.

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To identify associations of past-year witnessing violence with expectancies (anticipated effects) for alcohol and cannabis use in Black, Latinx, and White youth, including possible variations by level of neighborhood advantage and/or race/ethnicity.

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Large, population-based magnetic resonance imaging (MRI) studies of adolescents promise transformational insights into neurodevelopment and mental illness risk. However, youth MRI studies are especially susceptible to motion and other artifacts that introduce non-random noise. After visual quality control of 11,263 T1 MRI scans obtained at age 9-10 years through the Adolescent Brain Cognitive Development study, we uncovered bias in measurements of cortical thickness and surface area in 55.1% of the samples with suboptimal image quality. These biases impacted analyses relating structural MRI and clinical measures, resulting in both false-positive and false-negative associations. Surface hole number, an automated index of topological complexity, reproducibly identified lower-quality scans with good specificity, and its inclusion as a covariate partially mitigated quality-related bias. Closer examination of high-quality scans revealed additional topological errors introduced during image preprocessing. Correction with manual edits reproducibly altered thickness measurements and strengthened age-thickness associations. We demonstrate here that inadequate quality control undermines advantages of large sample size to detect meaningful associations. These biases can be mitigated through additional automated and manual interventions.

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Functional and structural magnetic resonance imaging (fMRI and sMRI) are complementary approaches that can be used to study longitudinal brain changes in adolescents. Each individual modality offers distinct insights into the brain. However each individual modality may overlook crucial aspects of brain analysis. By combining them, we can uncover hidden brain connections and gain a more comprehensive understanding. In previous work, we identified multivariate patterns of change in whole-brain function during adolescence. In this work, we focus on linking functional change patterns (FCPs) to brain structure. We introduced two approaches and applied them to data from the adolescent brain and cognitive development (ABCD) dataset. First, we evaluate voxel-wise sMRI- coupling to identify structural patterns linked to our previously identified FCPs. Our approach revealed multiple interesting patterns in functional network connectivity (FNC) and gray matter volume (GMV) data that were linked to subject-level variation. components 2 and 4 exhibit extensive associations between their loadings and voxel-wise GMV data. Secondly, we leveraged a symmetric multimodal fusion technique called multiset canonical correlation analysis (mCCA) + joint independent component analysis (jICA). Using this approach, we identified structured such as one showing increased connectivity between visual and sensorimotor domains and decreased connectivity between sensorimotor and cognitive control domains, linked to structural change patterns ( ) including alterations in the bilateral sensorimotor cortex. Interestingly, females show stronger connection between brain functional and structural changes than males, highlighting gender-related differences. The combined results from both asymmetric and symmetric multimodal fusion methods underscore the intricate gender-specific nuances in neural dynamics. By utilizing two complementary multimodal approaches, our study enhances our understanding of the evolving nature of whole brain connectivity and structure during the adolescent period, shedding light on the nuanced processes underlying adolescent brain development.

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The associations of family environment with adolescent behavioral health are well established, yet insights into how these associations are moderated by sex, particularly through changes in brain structure, are limited.

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Parents’ internalizing symptoms, such as anxiety and depression, may contribute to similar symptoms in their youth. However, these associations vary, as youth with better emotion regulation may be more protected from negative parental influence. Yet, it remains unclear how youth’s neural correlates of emotion regulation, particularly in prefrontal regions-such as dorsolateral prefrontal cortex (dlPFC), lateral orbitofrontal cortex (lOFC), and medial orbitofrontal cortex (mOFC)-play a role in these associations. To address this gap, this study used two-wave longitudinal data that spanned 2 yr from the nationwide Adolescent Brain Cognitive Development study including 7,932 youth (Mage = 9.96 yr, SD = 7.52; 49% females) and their parents. Results revealed significant longitudinal associations between parents’ and youth’s internalizing symptoms over 2 yr. Moreover, youth’s dlPFC, lOFC, and mOFC activity to negative emotions moderated these links. Youth with higher activity in these regions showed weaker parent-youth associations in internalizing symptoms over time. This study provides robust evidence that dlPFC, lOFC, and mOFC serve as neurobiological protective factors in the longitudinal links between parents and youth’s internalizing symptoms. Findings inform interventions targeting youth’s neural development in emotion regulation to promote emotional adjustment in families where parents face mental health challenges.

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Associations between childhood obesity and brain microstructural differences have been observed. It remains unknown whether these associations are driven by sex-specific excessive weight gain. Restriction spectrum imaging characterizes brain tissue microstructural health via water diffusion, where the restricted normalized isotropic (RNI) compartment assesses neuronal and glial cellularity, which may reflect neuroinflammation, synaptic pruning, or both.

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Although gaming disorder is recognized as a diagnosable behavioral addiction, uncertainty remains regarding its directional association with adolescent psychopathology. Clarifying this association is crucial for refining diagnostic frameworks and developing targeted interventions.

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Classical regression generally assumes that all subjects follow a common model with the same set of parameters. With ever advancing capabilities of modern technologies to collect more subjects and more covariates, it has become increasingly common that there exist subgroups of subjects, and each group follows a different regression model with a different set of parameters. In this article, we propose a new approach for subgroup analysis in regression modeling. Specifically, we model the relation between a response and a set of primary predictors, while we explicitly model the heterogenous association given another set of auxiliary predictors, through the interaction between the primary and auxiliary variables. We introduce penalties to induce the sparsity and group structures within the regression coefficients, and to achieve simultaneous feature selection for both primary predictors that are significantly associated with the response, as well as the auxiliary predictors that define the subgroups. We establish the asymptotic guarantees in terms of parameter estimation consistency and cluster estimation consistency. We illustrate our method with an analysis of the functional magnetic resonance imaging data from the Adolescent Brain Cognitive Development Study.

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Parental psychopathology is a known risk factor for child autistic-like traits. However, symptom-level associations and underlying mechanisms are poorly understood.

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Assessing dimensions of neighborhoods could aid identification of contextual features that influence psychopathology in children and contribute to uncovering mechanisms underlying these associations.

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Recent advancements in understanding the brain’s functional organization related to behavior have been pivotal, particularly in the development of predictive models based on brain connectivity. A major analytical strategy in this domain involves a two-step process by first constructing a connectivity matrix from predefined brain regions, and then linking these connections to behaviors or clinical outcomes. Although some advances considered subject-specific functionally homogeneous nodes without relying on predefined regions of interest (ROIs), all these approaches with unsupervised node partitions predict outcomes inefficiently with independently established connectivity. In this paper, we introduce the Supervised Brain Parcellation (SBP), a brain node parcellation scheme informed by the downstream predictive task. With voxel-level functional time courses generated under resting-state or cognitive tasks as input, our approach clusters voxels into nodes in a manner that maximizes the correlation between inter-node connections and the behavioral outcome, while also accommodating intra-node homogeneity. We rigorously evaluate the SBP approach using resting-state and task-based fMRI data from both the Adolescent Brain Cognitive Development (ABCD) study and the Human Connectome Project (HCP). Our analyses show that SBP significantly improves out-of-sample connectome-based predictive performance compared to conventional step-wise methods under various brain atlases. This advancement holds promise for enhancing our understanding of brain functional architectures with behavior and establishing more informative network neuromarkers for clinical applications.

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Functional brain networks are associated with both behavior and genetic factors. To uncover biological mechanisms of psychopathology, it is critical to define how the spatial organization of these networks relates to genetic risk during development.

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. Recently, US youth of color reported greater use of alcohol, tobacco, and cannabis than White youth. Increased levels of discrimination in recent years may have added to the chronic burden associated with increased use among youth of color. Little is known about this relationship, especially among youth who initiate substance use earlier in adolescence. This study assessed the prevalence of substance susceptibility (willingness and curiosity) and use (alcohol, tobacco and cannabis) among youth by race/ethnicity and ethnic discrimination’s role on this relationship.

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As youth transition into adolescence, their desire for autonomy leads to changes in the family dynamic, resulting in increased family conflict and possible disruptions to children’s psychological health. Previous literature, however, has largely neglected to consider whether the association between family conflict and child behavioral difficulties is uni- or bi-directional. The current study used latent curve growth models with structured residuals (LCMs-SR) to investigate this question in the Adolescent Brain & Cognitive Development (ABCD) study. At four annual waves (baseline through 3-year follow-up), youth ( = 11,868; at Time 1 = 9.48 years; 48% female; 50% White) reported on family conflict while parents reported on youths’ internalizing and externalizing behaviors. Youth reported family conflict levels as increasing over four years. Furthermore, family conflict was bidirectionally associated with externalizing behavior, in that families with greater than expected conflict had children with more externalizing behaviors, and youth with more externalizing behaviors reported greater than expected conflict at home. Internalizing behavior, however, did not predict later family conflict, though family conflict predicted deviations in later internalizing behavior. These findings add to the literature by demonstrating bidirectional influences between children’s behavior and family functioning across emerging adolescence.

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We present the novel Bayesian Regularized and Annotation-Informed Integrative Analysis of Cognition (BRAINIAC) model. BRAINIAC allows for estimation of total variance explained by all features for a given cognitive phenotype, as well as a principled assessment of the impact of annotations on relative enrichment of predictive features compared to others in terms of variance explained, without relying on a potentially unrealistic assumption of sparsity of brain-behavior associations. We validate BRAINIAC in Monte Carlo simulation studies. In real data analyses, we train the BRAINIAC model on resting state functional magnetic resonance imaging (rsMRI) and neuropsychiatric data from the Adolescent Brain Cognitive Development (ABCD) Study and use the trained model in an out-of-study application to harmonized resting-state data from the Human Connectome Project Development (HCP-D), demonstrating a substantial improvement in out-of-study predictive power by incorporating relevant annotations into the BRAINIAC model.

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Subthreshold anxiety (STA) is a significant risk factor for developing anxiety disorder (AX), particularly in adolescence. Understanding the risk and protective factors of the development of STA in early life is essential for early prevention and intervention efforts. However, research on this topic is scarce. We examined the data of 11,876 early adolescents from the Adolescent Brain and Cognitive Development (ABCD) Study to explore the factors influencing the development of STA between ages 9 and 13. The outcomes included developing AX, persistent STA, and remission from STA. Using the Child Behavior Checklist (CBCL), we identified 786 participants with STA. To predict STA transitions, we analyzed 31 diathesis-stress-related variables covering demographics, mental and physical health, and environmental factors, employing logistic regression. Compared to baseline healthy controls (HCs), adolescents with STA showed an odds ratio (OR) of 6.9 for converting to AX. The pivotal risk factors for progression from STA to AX were lack of perseverance and area deprivation, with females being more likely to maintain STA. Protective factors for a favorable prognosis of STA included the absence of traumatic history, lack of premeditation, increased physical activity, and positive school environment. Healing traumatic experiences, increased physical activity, and enhancing school and family environments could help prevent adverse outcomes. By targeting these modifiable factors, adolescents at high risk can be identified and provided with interventions early in life.

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In order to transition between a resting state and carrying out cognitively-demanding processes the brain makes a host of subtle changes to its network organization. In adults, less reconfiguration relates to better task performance, suggesting a preconfigured brain organization at rest is beneficial, such that only minute changes are required to execute task demands. Here, we take a developmental lens to this phenomenon, examining reconfiguration in late childhood by leveraging a large sample of 9-11 year olds from the Adolescent Brain and Cognitive Development Study. We find more reconfiguration between the resting state and two executive function tasks is related to better task performance. These relationships hold even when accounting for network segregation, though segregation was negatively related to reconfiguration. Reconfiguration was also related to crystallized intelligence, with diverging effects across tasks. Overall, these findings demonstrate that in contrast to adulthood during late childhood, before functional brain networks are fully mature, greater reconfiguration promotes successful task performance.

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Sleep duration and physical activity have been associated with internalizing problems. However, genetic confounding and measurement error may introduce bias. We assessed genetic confounding in the associations of modifiable lifestyle with internalizing problems using device-based and questionnaire assessments to estimate shared genetic risk across different assessments in adolescents.

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With the widespread adoption of screen-based devices among adolescents, there is growing concern that more screen time could contribute to mental health problems such as depression. It is thus critical to identify potential mediating factors that could help explain this potential risk relationship. Recent evidence indicates that more screen time could impact sleep duration and brain structural connectivity (ie, white matter organization), which are critical for emotional health. Notably, sleep duration is a modifiable behavior that health care providers can easily target.

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Lower parental socioeconomic status (SES) is consistently linked to lower academic achievement among adolescents, with early disparities persisting into adulthood. However, the neurobiological mechanisms underlying these associations are not well understood. This preregistered study investigates the associations between household and neighborhood disadvantage-measured by income-to-needs ratio, parental educational attainment, and neighborhood SES-changes in within-network functional connectivity, and school grades, using longitudinal data from the Adolescent Brain Cognitive Development Study (N = 4745; age at baseline = 119.1 ± 7.5 months; age at 2-year follow up = 143.6 ± 7.8 months; age at 3-year follow up = 154.8 ± 7.7 months). Within-network connectivity changed significantly from baseline to follow-up, increasing in most networks (e.g., default mode, fronto-parietal) and decreasing in a few (e.g., salience, ventral attention). After controlling for other SES indicators, parental education and neighborhood disadvantage, but not income, were associated with changes in connectivity across several brain networks, including reduced increases in default mode, cingulo-opercular, and visual network connectivity and greater increases in within-sensorimotor network connectivity. Further, changes in sensorimotor connectivity mediated the relationship between parental educational attainment and academic achievement three years later. These findings highlight the importance of parental education and neighborhood environments in shaping neurodevelopmental trajectories that influence academic outcomes. Understanding the mechanisms that link socioeconomic disadvantage with academic outcomes could inform interventions aimed at reducing persistent achievement gaps.

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A key step toward understanding psychiatric disorders that disproportionately impact female mental health is delineating the emergence of sex-specific patterns of brain organisation at the critical transition from childhood to adolescence. Prior work suggests that individual differences in the spatial organisation of functional brain networks across the cortex are associated with psychopathology and differ systematically by sex.

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Increasing child and adolescent use of social media, video games, and mobile phones has raised concerns about potential links to youth mental health problems. Prior research has largely focused on total screen time rather than longitudinal addictive use trajectories.

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Pregnancy- and birth-related factors affect offspring brain development, emphasizing the importance of early life exposures. While most previous studies have focused on a few variables in isolation, here we investigated associations between a broad range of pregnancy- and birth-related variables and multivariate cortical brain MRI features. Our sample consisted of 8,396 children aged 8.9 to 11.1 y from the Adolescent Brain Cognitive Development Study. Through multiple correspondence analysis and factor analysis of mixed data, we distilled numerous pregnancy and birth variables into four overarching dimensions; maternal pregnancy complications, maternal substance use, low birth weight and prematurity, and newborn birth complications. Vertex-wise measures of cortical thickness (CT), surface area (SA), and curvature were fused using linked independent component analysis. Linear mixed-effects models showed that maternal pregnancy complications and low birth weight and prematurity were associated with smaller global SA. Additionally, low birth weight and prematurity was associated with complex regional cortical patterns reflecting bidirectional variations in both SA and CT. Newborn birth complications showed multivariate patterns reflecting smaller occipital- and larger temporal area, bidirectional frontal area variations, and reduced CT across the cortex. Maternal substance use showed no associations with child cortical structure. By employing a multifactorial and multivariate morphometric fusion approach, we connected complications during pregnancy and fetal size and prematurity to global SA and specific regional signatures across child cortical MRI features.

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The increased use of screen media has raised unknown effects on mental health among adolescents. This study aimed to examine the correlational and causal association between screen media activity (SMA) and mental health problems, and the mediating role of brain functions and structures in this relationship. Data from 4557 adolescents (mean age = 9.955 ± 0.164 years) in the Adolescent Brain Cognitive Development (ABCD) study were analysed across four time points: baseline, 1-year, 2-year, and 3-year follow-ups. Linear mixed models assessed SMA’s association with mental health indices and the brain’s developmental pattern, respectively. Cross-lagged panel models examined the SMA-mental health problems’ longitudinal and causal relationship. Mediation analyses explored brain functions and structures as mediators on the SMA-mental health correlation. Baseline SMA positively correlated with internalizing, externalizing, and stress problems; and negatively correlated with brain volume, area and diverse sets of resting-state functional connectivity (RSFC) after three years. Higher baseline SMA associated with increased internalizing ( = 0.030, = 0.012, = 0.016), and stress problems ( = 0.026, = 0.012, = 0.037) three years later. The RSFC between the cingulo-opercular network (CON) and the retrosplenial temporal network (RTN) mediated the effects of SMA on externalizing ( = 0.002, = 0.042) and stress problems ( = -0.003, = 0.022). TV watching predicted higher externalizing problems (β = 0.054, pfdr < 0.001), while video watching predicted increased internalizing (β = 0.061, pfdr < 0.001), externalizing (β = 0.033, pfdr = 0.035), and stress problems (β = 0.060, pfdr < 0.001). The findings indicate the negative impact of SMA, particularly TV and video watching, on adolescent mental health, mediated by changes in CON and RTN functional connectivity. Future research can explore the specific risks associated with video streaming and consider the role of emerging technologies such as virtual reality in SMA on adolescent mental health.

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Late childhood is a crucial period for individuals with psychiatric disorders. While common single-nucleotide polymorphisms explain a large proportion of inherited risk, structural variations including copy number variants (CNVs) play a significant role in the genetic architecture of neurodevelopmental disorders. The relevance of CNVs to child psychopathology and cognitive function in the general population remains underexplored. The authors conducted a comprehensive exploration of the CNV architecture underlying dimensions of psychopathology and cognitive phenotypes within the Adolescent Brain Cognitive Development (ABCD) Study.

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Impulsivity in highly heritable attention deficit hyperactivity disorder (ADHD) has been studied using neural activity via fMRI or genetic data, but rarely with multivariate methods linking both. We investigated coupled neural activity and gene expression signatures, using parallel independent component analysis (pICA) and Adolescent Brain Cognitive Development data.

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The current study aimed to determine sociodemographic associations of bedtime screen use behaviors and the sociodemographic differences in the associations between bedtime screen use and sleep outcomes in a national (US) study of early adolescents.

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We examined the independent and joint prospective associations of screen time, sleep disturbance, and sleep duration with body mass index (BMI) and waist circumference (WC) stratified by sex. Data are from 7445 participants (47.3% females) aged 9-10 years at baseline (2016-2018) in the Adolescent Brain Cognitive Development Study. Missing data were imputed, and weighted multivariable linear regression models estimated the independent and joint effects of screen time and sleep disturbance or sleep duration on BMI and WC after 2 years. Joint associations grouped participants by combinations of screen time and sleep, with low screen time and sufficient sleep or no sleep disturbance as the reference groups. Screen time was significantly associated with higher BMI (B = 0.32; 95% CI: 0.19, 0.45; < 0.001) and WC (B = 0.40; 95% CI: 0.23, 0.56; < 0.001). Sleep disturbance was associated with higher BMI (B = 1.23; 95% CI: 0.14, 2.33; 0.026) in males. Insufficient sleep (<9 hours) (B = 1.30; 95% CI: 0.53, 2.07; < 0.001) was associated with higher BMI. Medium screen time without sleep disturbance or insufficient sleep, and medium and high screen time with either sleep problem were associated with higher BMI and WC. Low screen time with insufficient sleep and high screen time with sufficient sleep were associated with higher BMI. Associations were generally stronger among males, particularly with high screen time. Screen time and insufficient sleep were independently and jointly associated with higher BMI and WC 2 years later, especially when both were present.

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Early adolescence is a dynamic period of social and brain development amid rapid hormonal and puberty changes. We examined how differences and changes in positive social experiences and cortical thickness co-develop from age 9-11 and 11-13 years in the ABCD cohort (N~12,000). We used bivariate latent change score models to capture cortical development (modeling mean whole-brain cortical thickness) and positive social experiences (modeling caregiver monitoring, family cohesion, prosocial behavior, number of friends, school engagement, school involvement, and neighborhood safety). We found evidence for correlated change, such that a greater reduction in positive social experiences was associated with a greater decrease in cortical thickness (est = 2.54SE = .54, z = 4.74,< .001, standardized effect size = .08), which did not differ between males and females in early and late puberty stages. We found mixed evidence for sex-specific relationships between puberty stage and social experiences, highlighting the need to better understand males’ puberty and social experiences in early adolescence. The evidence supports a transactional model of development in that positive social experiences and cortical thickness change together throughout early adolescence. The findings also highlight the importance of supporting youth in early adolescence through school transitions.

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What role do our genes play in shaping the structural organisation of the living human brain? Across a sample of 2,153 children (9-11 years old), we address this question, focusing on common genetic variants associated with cognitive ability and diffusion-based structural neuroimaging. Using polygenic scores, we test how variability in the genetic signal associated with cognitive ability is linked to simulated structural network properties, such as network efficiency. We fit a computational model to each connectome that simulates the emergence of high-level network properties. Central to the model is an economic trade-off between the “cost” of forming a given connection (a distance penalty) and the topological “value” that connection brings to the network. To simulate the network properties of those with the highest genetic propensity for cognitive ability, we had to use a significantly weakerpenalty. This softer distance penalty produces more stochastic, diverse, and efficient simulated networks. Further, those with a high genetic propensity for cognitive ability exhibited a more randomised simulated topology. Finally, we took a different approach to exploring the relationships between genes and model parameters by linking theof those parameters with post-mortem gene expression data, with a comparative pathway enrichment analysis. Across the sample, overlapping biological and cellular pathways between polygenic scores and each child’s optimal cost-value trade-off emerged. Together, the generative wiring distance term, which varied maximally across participants but minimally across the cortex, was enriched for more ontologies than the wiring value term, which varied maximally across the cortex. However, the overlap in enriched ontologies between polygenic scores and the wiringterm was greater than that of polygenic scores and the wiringterm. This application of computational modelling demonstrates that the underlying economic trade-offs needed to simulate the higher-order topological properties of networks vary according to genetic propensity for cognitive ability.

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One in ten children experiences sleep-disordered breathing (SDB). Untreated SDB is associated with poor cognition, but the underlying mechanisms are less understood.

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Outdoor air pollution exposure is associated with structural and functional brain differences and an increased risk for psychopathology. Although the neural mechanisms remain unclear, air pollutants may impact mental health by altering brain regions implicated in psychopathology, such as the amygdala. Here, we examined the association between ambient air pollution exposure and amygdala subregion volumes in 9- to 10-year-olds.

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A delay in brain maturation is a hypothesized pathomechanism of attention-deficit/hyperactivity disorder (ADHD). Differences in emotion regulation are associated with phenotypic and prognostic heterogeneity in ADHD. The development of emotion regulation is driven, in part, by brain maturation. Whether the difference between an individual’s brain age predicted by machine-learning algorithms trained on neuroimaging data and that individual’s chronological age, i.e. brain-predicted age difference (brain-PAD) predicts differences in emotion regulation, and whether ADHD problems add to this prediction is unknown. Using data from the Adolescent Brain Cognitive Development Study, we examined, in 2711 children (M = 120.09 months, SD = 7.61; 54.15% female; 61.23% white), whether adjusting for action cancellation (inhibition), age, sex assigned at birth, psychotropic treatment, and pubertal status, brain-PAD in late childhood predicts self-reported emotion regulation in early adolescence (at 3-year follow-up), and whether parent-reported ADHD problems predict self-reported emotion regulation above and beyond brain-PAD. Greater brain-PAD predicted greater expressive suppression (b = 0.172, SE = 0.051, p = 0.004), whereas ADHD problems did not (b = 0.041, SE = 0.022, p = 0.124), model marginal R = 0.020. This pattern of results was replicated across sensitivity tests. Neither brain-PAD, nor ADHD problems predicted cognitive reappraisal, ps = 0.734. Clinically, consistent with earlier findings linking greater brain-PAD to psychopathology, we observed that greater brain-PAD in childhood-but not ADHD problems-predicted expressive suppression in early adolescence. Expressive suppression is implicated in the etiology, maintenance, and treatment of numerous psychopathologies, highlighting the relevance of brain-PAD in understanding developmental risk mechanisms. Conceptually, these findings further validate brain-PAD as a valuable tool for advancing developmental neuroscience.

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Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that is commonly associated with sleep disturbances. Sleep disruption can contribute to difficulties in a child’s life and, therefore, can be an important determinant of their quality of life. This study uses data from the large multisite Adolescent Brain Cognitive Development (ABCD) database to examine the relationship between sleep and behavior in children with ADHD. We hypothesized that shorter and more interrupted sleep would relate to increased problem behaviors such as inattention and social difficulties. Sleep data was obtained using commercially available actigraphy (Fitbit) measures, and the Sleep Disturbance Scale for Children (SDSC) for 212 children ages 10 to 13 years, with ADHD and an age and sex matched control group (n = 212). Behavioral and emotional subscores were obtained from the Child Behavior Checklist (CBCL). SDSC sleep data was significantly different between ADHD and control groups, while wearable actigraphy data was not. ADHD diagnosis, family income, sleep latency (measured by wearable device), and 3 out of 6 of the SDSC subscores were significantly related to problem behavior scores measured by the CBCL.

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Financial adversity has been associated with altered subcortical neurodevelopment and obesity risk. However, no studies have examined these relationships in tandem. Food intake is influenced by the subcortex; thus, we examined whether financial adversity moderated bidirectional relationships between neurodevelopment and body mass index (BMI) in early adolescence.

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Rates of prenatal cannabis exposure (PCE) are rising with increasingly permissive legislation, which may be a risk factor for psychosis. Disrupted reward-related neural circuitry may underlie this relationship. We aim to elucidate neural mechanisms involved in the association between PCE and youth-onset psychotic-like experiences (PLEs) by probing correlates of reward anticipation, a neurobehavioral marker of endocannabinoid-mediated dopaminergic function.

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Multilevel regression and poststratification (MRP) is a popular method for addressing selection bias in subgroup estimation, with broad applications across fields from social sciences to public health. In this paper, we examine the inferential validity of MRP in finite populations, exploring the impact of poststratification and model specification. The success of MRP relies heavily on the availability of auxiliary information that is strongly related to the outcome. To enhance the fitting performance of the outcome model, we recommend modeling the inclusion probabilities conditionally on auxiliary variables and incorporating flexible functions of estimated inclusion probabilities as predictors in the mean structure. We present a statistical data integration framework that offers robust inferences for probability and nonprobability surveys, addressing various challenges in practical applications. Our simulation studies indicate the statistical validity of MRP, which involves a tradeoff between bias and variance, with greater benefits for subgroup estimates with small sample sizes, compared to alternative methods. We have applied our methods to the Adolescent Brain Cognitive Development (ABCD) Study, which collected information on children across 21 geographic locations in the U.S. to provide national representation, but is subject to selection bias as a nonprobability sample. We focus on the cognition measure of diverse groups of children in the ABCD study and show that the use of auxiliary variables affects the findings on cognitive performance.

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Prior studies show that neighborhood disadvantage negatively impacts children’s cognitive function and brain volume. However, despite their co-occurrence, there is a lack of cohesive examination of the joint effects of environmental and social factors on brain volumes.

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The associations of prenatal alcohol exposure (PAE) and prenatal tobacco exposure (PTE) with adolescent neuroanatomical development are typically evaluated cross-sectionally. It is unclear whether observed effects persist throughout life or reflect different developmental trajectories.

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Bipolar disorder (BD) is a severe, persistent disorder that causes functional impairment. Besides heritability, environmental factors, such as traumatic experience, impact the development of BD. Little is known about the early developmental signs of this disorder; therefore, this study aims to look at the impact of interpersonal trauma on the early developmental signs of BD. Specifically, differences in psychopathological behaviours were investigated between (1) at-risk children and controls and (2) at-risk children who experienced an interpersonal traumatic event and those who did not.

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Psychopathology is associated with features of the family, neighborhood, and school environments. During adolescence, increased autonomy and novel social relationships may influence the strength of these associations over time. Characterizing these processes is key to understanding how and when different factors may contribute to psychopathology. Participants in the Adolescent Brain Cognitive Development (ABCD) Study (n = 11,823) were 9-10 years old at baseline and 12-13 years old at the three-year follow-up. At each time point, internalizing symptoms (INT) and externalizing symptoms (EXT), family features (e.g., conflict, parental monitoring, acceptance, and financial hardship), neighborhood safety, and school supportiveness were assessed. Fixed effect regression models were estimated separately for male and female youth to examine the age-varying, within-individual associations between symptoms and family, neighborhood, and school factors. INT and EXT significantly decreased among male adolescents over time, while female adolescents exhibited increases in INT and decreases in EXT. Family conflict, financial hardship, neighborhood safety, and school support predicted INT and EXT, with some variation by sex (e.g., neighborhood safety only predicted INT and EXT for male adolescents). Many of these associations were consistent over time. However, for male adolescents, the association between financial hardship and EXT weakened over time, while the family conflict and EXT association strengthened. Understanding how timing and specific environmental factors interact to shape adolescent mental health is critical to identifying periods of heightened sensitivity to risk or protective influences.

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Neurodevelopmental disorders have significant public health impacts, and novel approaches to understanding these disorders are greatly needed. Social connectedness, including relationships with parents and peers as well as family and school environments, may serve as a protective factor for neurodivergent youth. Neural networks that support social processing could also influence outcomes for these individuals.

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Differences in sensitivity to substances are important for understanding variability in addiction propensity. The value of modeling subjective response to nicotine, particularly e-cigarettes, at first use as a predictor of future use remains largely untested.

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The adolescent brain is vulnerable to ambient air pollution. Importantly, community-level factors – such as neighborhood disadvantage – that co-occur with air pollution may further enhance this vulnerability and impact brain development. The current study investigated if neighborhood disadvantage moderates the association between residential fine particulate matter (PM) pollution and adolescent brain development, including longitudinal changes in cortical thickness, surface area, and subcortical/white matter volume from ages 9-13 years (n = 8321 participants from the ABCD Study®; 12,634 observations). We found that, in more disadvantaged neighborhoods, higher PM levels were associated with greater age-related cortical thinning in temporal areas and in most regions of the occipital lobe. Furthermore, independent of neighborhood disadvantage, higher PM exposure was associated with larger age-related surface area decreases in parietal, occipital, and temporal regions, but smaller age-related increases in right cerebral white matter volume and frontal and temporal region surface area. Similarly, higher PM exposure was independently associated with greater age-related cortical thinning in the frontal regions, cingulate, and insula, but smaller age-related cortical thickening in temporal regions. Findings have policy implications for air quality improvements alongside investment in disadvantaged neighborhoods to bolster adolescent brain development.

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Variability in associations between socioeconomic status and cortical gray matter may be due in part to the common, functional brain-derived neurotrophic factor (BDNF) Val66Met polymorphism, which alters BDNF signaling. In this study, we examined whether BDNF Val66Met genotype moderated the associations between socioeconomic factors (family income, parental education) and cortical surface area (SA) and thickness (CT) in two large independent samples of typically-developing children and adolescents. Participants were 3- to 21-year-olds (N = 383; 47% female) from the Pediatric Imaging, Neurocognition, and Genetics (PING) study and 11- to 14-year-olds (N = 2566; 46% female) in the Adolescent Brain Cognitive Development (ABCD) study. High-resolution, T1-weighted magnetic resonance imaging data were acquired in both studies. Analyses were conducted on global and regional SA and CT. In the PING sample, BDNF Val66Met genotype significantly moderated the association between family income and total SA and SA in the left fusiform gyrus. In the ABCD sample, there were no significant interactions for global or regional SA or CT. Collectively, these results suggest that BDNF Val66Met genotype may not explain variability in associations between socioeconomic factors and SA or CT in children and adolescents.

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Parental history of problematic substance use (PH) increases the risk for early adolescent substance use (SU), potentially due to premorbid differences in reward-processing brain regions (e.g., striatum). However, no studies have prospectively examined the separate contributions of parental history of alcohol (PHA) and drug (PHD) use or the impact of PH density (PH, PH, PH) on reward processing in preadolescents. This study analyzed data from 10,235 participants (ages 9-14) in the Adolescent Brain Cognitive Development Study (ABCD). Reward processing was assessed using the Monetary Incentive Delay Task (MID) at baseline and two-year follow-up. Regions of interest included bilateral striatal activation elicited by neutral vs. anticipation of large rewards. Linear mixed-effect models evaluated PH, PHA, PHD, and PH density on ROI activation, controlling for relevant covariates. Results showed that youth with PHA had greater nucleus accumbens activation during reward anticipation than those with no history (PHA), but no significant differences were found between PHA and PHA or PHA and PHA. PHD and PH were not significantly associated with BOLD activation in striatal regions, nor were there changes over time. These findings highlight the need to consider both PH and environmental factors when assessing neurodevelopmental risk for early substance use.

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Intra-individual variability in reaction times (IIVRT), which generally occurs as a result of episodic long reaction times (RTs), is a marker for impaired attention. Multiple functional neuroimaging studies have attempted to discern neurofunctional correlates of IIVRT, but few use models that account for trial-level IIVRT. Neurofunctional correlates of IIVRT differ depending on the method applied, and few studies have used multiple methods in the same sample. This study utilized Stop-Signal Task functional magnetic resonance imaging (fMRI) data from 8,066 children (9-10 years old) in the Adolescent Brain Cognitive Development (ABCD) study. IIVRT was modeled using multiple methods, including converting RTs to z-scores, variance time course modeling, and a novel machine-learning technique (i.e., hidden Markov model) to compute the probability of a trial reflecting good or poor attentional states. Across all three methods, lower IIVRT was associated with greater activation in the default mode network (DMN), while higher IIRVT was associated with greater activation in the dorsal attention network (DAN). Although all models yielded similar neural correlates, z-score modeling demonstrated the strongest effect sizes in task-related networks. Our findings are congruent with previous work in adults and demonstrate the reproducibility and developmental stability of the neural correlates of trial-level IIVRT. Higher effect sizes for brain-IIVRT associations using the z-score method suggest that this approach is a simple and promising candidate for investigating neural mechanisms related to IIVRT.

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Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder with a complex etiology. The current diagnostic process for ADHD is often time-intensive and subjective. Recent advancements in machine learning offer new opportunities to improve ADHD diagnosis using diverse data sources. This study explores the potential of Fitbit-derived physical activity data to enhance ADHD diagnosis.

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Black and Latinx youth experience earlier pubertal timing relative to their non-stigmatized peers. Research on determinants of this increased risk has largely focused on aspects of individuals (e.g., body mass index) or their proximal environment (e.g., socioeconomic status), to the exclusion of broader macro-social factors. Using 2 years of Adolescent Brain Cognitive Development Study data, we examined whether structural stigma (e.g., state-level policies, aggregated prejudicial attitudes) was associated with hormonal and physical markers of pubertal development. Baseline results documented earlier pubertal timing among Black girls (hormones) and Latinx girls and boys (youth and/or caregiver report) in states with higher (vs. lower) levels of structural racism and xenophobia, respectively. Observed associations were comparable in effect size to a well-established correlate of pubertal development, body mass index, and remained 1 year later among these stigmatized (vs. non-stigmatized) groups. Findings suggest the need to broaden the study of determinants of pubertal development to include macro-social factors.

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Executive functions (EF) have been found to differentiate from a single component to three distinct components (i.e., updating, shifting, and inhibition) during development. However, there is still much debate regarding when such differentiation takes place and biological evidence is needed. Here we used the longitudinal and multimodality data from the ABCD study to address this question at two age groups (9-10 and 13-14). Three tasks (i.e., List, Card and Flanker tasks) were used to represent the three EF components respectively at baseline, and two tasks (Flanker and List) at 4 year follow up. Genes associated with each task were identified by whole genome and transcriptome association analyses and were then used for genetic similarity calculation; structural and functional brain indices related to each task were identified and used to assess neural similarity. We found that at baseline (9~10 years old), the three EF components were behaviorally highly inter-correlated and were associated with many of the same genes and the same brain regions. Four years later, the follow-up data (with Flanker and List tasks only) still showed significant but smaller behavioral/genetic/neural similarity. This study is the first to chart the path of EF differentiation during adolescence by combining behavioral, genetic, and neural data, and this approach may be relevant to the study of development of other cognitive abilities.

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Although cyberbullying has been linked with adverse health outcomes, most prior studies have been cross-sectional, and there are limited large-scale, prospective analyses examining cyberbullying and mental health and substance use outcomes in early adolescents. Therefore, the aim of this study was to determine prospective associations between cyberbullying, mental health, and substance use experimentation one year later in a US national cohort of early adolescents (11-12 years old).

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Autism Spectrum Disorder (autism) and Attention Deficit/Hyperactivity Disorder (ADHD) often co-occur, although it remains unclear if these conditions share common neurobiological foundations or exhibit distinct alterations in resting-state brain connectivity. We conducted a cross-sectional mega-analytic comparison of functional connectivity patterns linked to autism and ADHD traits in children and adolescents (ages 6-19 years; n=10,168), with follow-up analyses considering autism (n=764 autistic; n=893 neurotypical) and ADHD diagnoses (n=2,026 ADHD; n=2,409 neurotypical). In total, 12,732 unique child and adolescent participants were included: 3,528 in both analyses, 6,640 in the trait analysis only, and 2,564 in the diagnostic analysis only. Autism traits and diagnosis were associated with reduced connectivity between the thalamus, putamen, salience/ventral attention, and frontoparietal networks, while ADHD traits showed the opposite pattern. Hyperconnectivity between the default mode and dorsal attention networks was observed in both autistic and ADHD groups relative to neurotypical individuals and associated with ADHD traits. Despite frequent co-occurrence, autism and ADHD traits exhibit distinct neural signatures, with small effect sizes indicating subtle associations.

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While breastfeeding benefits early child neurocognition, its influences into adolescence, a period of intense brain remodeling and heightened mental health risk, remain unclear.

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To assess longitudinal and geographic variation in perceived discrimination from ages 10-11 to 13-14 years in the Adolescent Brain Cognitive Development cohort, and to examine how these experiences are shaped by contextual factors such as neighborhood segregation and state-level racial bias.

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Early life adversity (ELA) is highly prevalent and has significant detrimental effects on children’s brain development and behavioral outcomes. However, associations of threat, unpredictability, and deprivation in dimensional models of ELA with corticolimbic circuits were unclear. Previous studies have highlighted the effects of proximity, especially the distinctions between interpersonal and socioeconomic ELA, on children’s neurodevelopment. This study first examined the associations between multiple ELA categories (i.e., interpersonal threat, socioeconomic threat, interpersonal unpredictability, socioeconomic unpredictability, interpersonal deprivation, and socioeconomic deprivation) and the developmental changes in resting-state functional connectivity (rsFC) of the frontolimbic and temporal-limbic circuits implicated in cognition and psychopathology, using data from the Adolescent Brain Cognitive Development (ABCD) study, which included four measurements from baseline (mean ± SD age, 119.13 ± 7.51 months; 2815 females) to 3-year follow-up (N = 5885). Controlling for concurrent ELA categories, interpersonal unpredictability and socioeconomic deprivation were associated with accelerated development of rsFC between CON/RTN-amygdala/hippocampus (Cingulo-opercular Network, Retrosplenial Temporal Network). Compared to girls, boys’ corticolimbic circuits development was more sensitive to interpersonal threat. Changes in rsFC mediated the associations between interpersonal unpredictability/socioeconomic deprivation with decreased crystallized cognition, fluid cognition, and internalizing problems. Additionally, socioeconomic deprivation was associated with decreased crystallized cognition through interpersonal unpredictability and changes in rsFC between CON and bilateral amygdala/right hippocampus. This study emphasized interpersonal unpredictability and socioeconomic deprivation as key environmental factors affecting corticolimbic circuit development implicated in cognition and psychopathology. Stable family environments and enriched neighborhoods are crucial for supporting optimal neural and behavioral development in children and adolescents.

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Depression is associated with increased levels of pro-inflammatory biomarkers in children and adolescents. As research to date has primarily focused on inflammatory cytokines, the potential role of white blood cells (WBCs) and platelets in the inflammatory response is not well understood. This study examines the association of blood cell based inflammatory indices, including the systemic immune-inflammation index (SII), and depressive symptoms in participants in the Adolescent Brain Cognitive Development Study.

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Immigrant youth are a large population in the U.S, yet there are limited studies characterizing mental health and unique individual-level risk and protective factors in early adolescent immigrants. Previous studies reveal variable associations between immigration and psychopathology. We aimed to characterize minority stressors, protective factors, and mental health among adolescent immigrants.

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This paper addresses the challenges of managing missing values within expansive longitudinal neuroimaging datasets, using the specific example of data derived from the Adolescent Brain and Cognitive Development (ABCD) Study. The conventional listwise deletion method, while widely used, is not recommended due to the risk that substantial bias can potentially be introduced with this method. Unfortunately, recommended alternative practices can be challenging to implement with large datasets. In this paper, we advocate for the adoption of more sophisticated statistical methodologies, including multiple imputation, propensity score weighting, and full information maximum likelihood (FIML). Through practical examples and code using ABCD Study data, we illustrate some of the benefits and challenges of these methods, with a review of how these advanced methodologies bolster the robustness of analyses and contribute to the integrity of research findings in the field of developmental cognitive neuroscience.

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The current study aimed to identify possible measurement non-equivalence (i.e., bias) with respect to sex (proxy for gender), race/ethnicity, and intersectional identity (sex by race/ethnicity) and generate adjusted scores for the Alcohol Expectancy Questionnaire-Adolescent, Brief (AEQ-AB) in a sample of middle-school-aged Black, Latinx, and White youth.

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Cerebral asymmetry, fundamental to various cognitive functions, is often disrupted in neuropsychiatric disorders. While brain growth has been extensively studied, the maturation of brain asymmetry in children and the factors influencing it in adolescence remain poorly understood. We analyze longitudinal data from 11,270 children aged 10-14 years in the Adolescent Brain Cognitive Development (ABCD) study. Our analysis maps the developmental trajectory of structural brain asymmetry. We identify significant age-related, modality-specific development patterns. These patterns link to crystallized intelligence and mental health problems, but with weak correlations. Genetically, structural asymmetry relates to synaptic processes and neuron projections, likely through asymmetric synaptic pruning. At the microstructural level, corpus callosum integrity emerged as a key factor modulating the developing asymmetry. Environmentally, favorable perinatal conditions were associated with prolonged corpus callosum development, which affected future asymmetry patterns and cognitive outcomes. These findings underscore the dynamic yet predictable interactions between brain asymmetry, its structural determinants, and cognitive and psychiatric outcomes during a pivotal developmental stage. Our results provide empirical support for the adaptive plasticity theory in cerebral asymmetry and offer insights into both cognitive maturation and potential risk for early-onset mental health problems.

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Given mounting literature linking environmental adversity with neurobiological alterations, other evidence has shown association between excess adiposity and attenuated brain development, leading to our current question of how the developing brain interacts with change in body composition in response to environmental challenges. Using data from the Adolescent Brain Cognitive Development (ABCD®) Study, we conducted mediation analyses and demonstrated that socioeconomic deprivation (SED) was associated with lower total brain and cortical volumes via the mediation of higher waist-to-height ratio (WHtR), and that WHtR likewise mediated the association of SED with global brain structures. The prefrontal structures showed region- and direction-specific pathways, with bilateral superior and middle frontal gyrus being most consistently related with WHtR in addition to the impact of SED. These findings reveal a functional trade-off between brain development and fat deposition in response to environmental deprivation, and may have implications for understanding neurocognitive and somatic development among children and adolescents in different socioeconomic contexts.

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The prescription of stimulant medications for young people with attention-deficit/hyperactivity disorder is common and increasing. Concerns have been raised about potentially psychotogenic effects of stimulants, and previous observational research has documented an increased risk of psychotic experiences in young people prescribed stimulants. Our aim was to estimate the causal effect of stimulants on psychotic experiences.

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Background
Urban green space exposure (GSE) benefits mental health and cognition; however, the underlying neural mechanisms in children, a population especially sensitive to environmental influences, remain unclear.

Methods
This cross-sectional study analyzed baseline data from the ABCD study, involving 9-10-year-old children across 21 U.S. sites. GSE included nine indicators, such as Normalized Difference Vegetation Index and tree canopy. Brain structure (BS) and white matter microstructure (WMM) were assessed using MRI. Group Factor Analysis (GFA) was conducted to identify patterns linking GSE with brain metrics. Mental health was evaluated via internalizing and externalizing T-scores, while cognition was assessed using fluid and crystallized intelligence scores.

Results
The study included 8,430 participants with BS data and 8,161 with WMM data. BSGFA 1, associated with higher GSE, positively correlated with surface area, cortical volume, subcortical volume, and most cortical thickness indicators. It predicted lower internalizing (β = -0.08, p < 0.001, 95% CI, −0.13 to −0.04) and externalizing problems (β = -0.10, p < 0.001, 95% CI, −0.15 to −0.06), and greater crystallized intelligence (β = 0.12, p < 0.001, 95% CI, 0.08 to 0.17). WGFA 1, linked to greater GSE, was positively correlated with fractional anisotropy and negatively with mean diffusivity. It predicted lower externalizing problems (β = -0.04, p = 0.01, 95% CI, −0.06 to −0.01) and improved fluid (β = 0.14, p < 0.001, 95% CI, 0.11 to 0.17) and crystallized intelligence (β = 0.04, p = 0.01, 95% CI, 0.01 to 0.06). Forest-related WGFA 2 was negatively associated with fractional anisotropy and fluid intelligence (β = -0.10, p < 0.001, 95% CI, −0.15 to −0.06).

Conclusions
This study highlights the benefits of urban GSE on children’s brain development, mental health, and cognitive function. Notably, forest-related GSE exhibited distinct effects compared to urban green spaces, suggesting that the type and characteristics of green spaces matter significantly. Future research should investigate the long-term impacts of different types of GSE to inform urban designs supporting mental health and cognition.

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Access to essential neighborhood opportunities (e.g., quality education, nutritious foods, clean air) is critical for development, but the influence of these factors on neurocognition remains unclear. Leveraging the ABCD (Adolescent Brain Cognitive Development) Study, we examined associations between neighborhood opportunity, cognitive function, and brain structure.

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E-cigarette expectancies, which may differ by race/ethnicity, play a crucial role in shaping youth e-cigarette use. Observed differences by race/ethnicity, however, may reflect racial/ethnic variations in social determinants of health, such as socioeconomic status (SES). This study examined the extent to which race/ethnicity was uniquely associated with youths’ positive and negative e-cigarette expectancies, after adjusting for SES and neighborhood disadvantage, and individual, family, and peer risk factors.

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Concerns about the accuracy of self-reported screen time persist due to discrepancies with objective measures. This study compared passive smartphone tracking via the “Effortless Assessment of Risk States” (EARS) app with self-reported screen time from 495 adolescents. Based on self-reports, 94.26% of social media use occurred on smartphones. EARS-recorded social media use was higher (1.64 ± 1.93 h) than past-year self-report (1.44 ± 1.97 h; p = 0.037) but similar to post-sensing self-report (1.63 ± 1.93 h; p = 0.835). Higher picture vocabulary scores were associated with lower odds of under-reporting social media use (OR = 0.96, 95% CI: 0.93-0.99). Both self-reported (β = 0.06, 95% CI: 0.01-0.11) and EARS (β = 0.07, 95% CI: 0.03-0.12) measures correlated with externalizing symptoms. They were also correlated with social media addiction (self-reported:β = 0.15, 95% CI: 0.10-0.20; EARS:β = 0.06, 95% CI: 0.01-0.11). However, past-year self-report uniquely correlated with internalizing symptoms (β = 0.05, 95% CI: 0.01-0.09) and video game addiction (β = 0.05, 95% CI: 0.01-0.10). These findings highlight the value of integrating self-report and objective measures in screen media use research.

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Adolescence is a critical period for brain development, yet the impact of peer environments on brain structure, cognition, and psychopathology remains poorly understood. Here, we capitalized on data from 7806 adolescents (age = 12.02 ± 0.67) from the Adolescent Brain Cognitive Development (ABCD) study, to determine associations between two distinct peer environments (proportion of prosocial or delinquent friends) and the structural and functional architecture of the brain, cognition, as well as behavioral and emotional dysregulation. A higher proportion of prosocial friends was associated with fewer behavioral problems and larger fronto-cingulate and striatal regions. In contrast, a higher proportion of delinquent friends was linked to increased behavioral problems, lower neurocognitive performance, and decreased functional connectivity in the default-mode and fronto-striato-limbic circuits, which spatially overlapped with external dopamine density maps. Moreover, the associations between prosocial friends and behaviors were mediated by brain volumes (e.g., pallidum), while the associations between delinquent friends and behaviors were primarily mediated by fronto-striato-limbic connectivity. Prosocial friends also attenuated the development of internalizing problems, whereas delinquent friends promoted externalizing symptoms. These findings underscore the profound influence of peer environments on adolescent brain development and mental health, highlighting the need for early interventions to promote resilience and healthy neuro-maturation.

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Investigate sex-related differences in mild traumatic brain injury (mTBI) risks due to sports among children aged 9 to 10 years and examine whether the benefits of sports participation, specifically in behavioral, neurocognitive, and psychiatric health, differ between boys and girls.

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Preterm infants with very low birth weight are at high risk for long-term neurocognitive deficits. However, whether these neurocognitive deficits are improved or worsened in adolescence remains unclear.

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Autistic children often consume less varied diets, experience sleep difficulties, and have higher rates of mental health problems as compared to neurotypical peers. Yet, the direct relationship between all of these domains is not well characterized. We leveraged the Adolescent Brain Cognitive Development study (ABCD study) dataset to explore whether estimated levels of consumption of specific macro- and micronutrients correlated with the severity of mental health and sleep problems in autistic youth. We found that low vitamin B3, B6, C, and iron intake was associated with more severe psychiatric problems in autistic children in the ABCD cohort, though these findings did not reach statistical significance after correction for multiple comparisons. In a post hoc analysis, we found that the severity of sleep difficulties was correlated with estimated levels of Vitamins B3, B6, C, and iron intake and with the severity of anxiety/depressive symptoms and/or thought problems. Our analysis on a large number of nutrients, psychiatric symptoms, and sleep serves as an exploratory, initial analysis to identify specific nutrients and psychiatric symptoms that could be the focus of future (confirmatory) studies on the relationship between nutrition, sleep, and mental health in autistic individuals.

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Before assuming its role in the mature brain, serotonin modulates early brain development across phylogenetically diverse species. In mice and humans, early-life SSRI exposure alters the offspring’s brain structure and is associated with anxiety and depression-related behaviors beginning in puberty. However, the impact of early-life SSRI exposure on brain circuit function is unknown. To address this question, we examined how developmental SSRI exposure changes fear-related brain activation and behavior in mice and humans. SSRI-exposed mice showed increased defense responses to a predator odor, and stronger fMRI amygdala and extended fear-circuit activation. Likewise, adolescents exposed to SSRIs in utero exhibited higher anxiety and depression symptoms than unexposed adolescents and also had greater activation of the amygdala and other limbic structures when processing fearful faces. These findings demonstrate that increases in anxiety and fear-related behaviors as well as brain circuit activation following developmental SSRI exposure are conserved between mice and humans. These findings have potential implications for the clinical use of SSRIs during human pregnancy and for designing interventions that protect fetal brain development.

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Extant research has focused on the risk factors for alcohol use in adolescence, but little work has examined these in childhood. Early alcohol sipping, defined here as sipping alcohol by ages 9 to 10, may be a unique and informative developmental precursor to future problematic alcohol use. This study employed machine learning to rank risk factors linked to early alcohol sipping by importance.

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The objective of this study is to investigate whether apolipoprotein E (APOE) ε4 genotype is associated with lower cognitive performance in children with habitual snoring and to determine if APOE could stratify children with snoring by their risk for adverse cognitive outcomes.

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To facilitate future research on self-regulation and related brain-behavior associations, we aimed to establish a psychometric model of self-regulation in the largest open neuroimaging dataset to date, the Adolescent Brain and Cognitive Development (ABCD; https://abcdstudy.org/). Given the measures adopted in the ABCD study, we tested three theoretically defensible and applicable psychometric models of self-regulation. The dual-process theory provided the framework for postulating the models to be tested. This theory states that successful self-regulation occurs in case of a balanced state between bottom-up ‘hot’ and top-down ‘cool’ processes in favor of achieving goals. Based on the results, we recommend a measurement model with three correlated first-order factors: Hot, Cool and Executive Functions. The model successfully predicted academic achievement both at the time of self-regulation assessment and two years later, and its robustness across smaller samples was confirmed. Given its factorial and predictive validity, we recommend the adoption of the established model for future research on self-regulation and its neural correlates based on the ABCD dataset. Given the measures adopted in the ABCD study, a theoretically desirable bifactor model with a general self-regulation factor and nested Hot and Cool factors cannot be reliably established.

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We examined the relationship between parenting, suicidal ideation (SI), and the transition from SI to suicide attempt (SA), and whether parenting behaviors moderate the associations of genetic liability for SA and/or painful and provocative events (PPEs) with SA risk. Participants included 6153 adolescents (48.3 % female, M at baseline = 9.47 years, followed over 3 years) from the Adolescent Brain Cognitive Development Study (ABCD) and 5942 adolescents (52.1 % female, M at baseline = 15.55 years, followed over 1 year) from the National Longitudinal Study of Adolescent to Adult Health (Add Health). We used logistic regression to test associations between parenting and SI/SA. Genetic liability and PPEs were included as potential predictors of SA. In ABCD, higher parental acceptance and monitoring were associated with lower risk for SI (odds ratios [ORs] = 0.7-0.9, ps < .01) but not SA (ORs = 0.9, ps > .05). Non-suicidal self-injury and parental knowledge of child SI were associated with elevated risk for SA (ORs = 2.6-2.8, ps < .01), but their interaction was non-significant (OR = 0.9, p = .85). In Add Health, maternal support was related to reduced SI risk (OR = 0.8, p < .01), but paternal support, and both parents’ involvement and presence at home, were not (ORs = 0.9-1.0, ps > .05). Several PPEs were associated with higher SA risk (ORs = 1.3-2.0, ps < .05). These findings suggest that the parent-adolescent relationship may be more relevant to SI, rather than the transition from SI to SA.

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This study examines the social epidemiology of sports and extracurricular activities in early adolescents (9-14 years) using a diverse national U.S.

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Pain experiences in adolescence are increasing and represent a major public health concern. However, little is known about the neurobiological phenotype of pain experiences in adolescents, particularly outside of a clinical setting. A better neurobiological understanding of pain experiences in community youth may shed light on potential vulnerabilities present before clinical diagnoses of chronic pain. This study utilized an exploratory region-of-interest approach, in a large community sample (n = 7332) of youth (ages 11-12), to examine the association between white matter microstructure, fractional anisotropy (FA) and mean diffusivity (MD), and pain experiences. Bayesian multilevel modeling was used to explore group differences (between those reporting past-month pain and those who did not), and continuous associations between pain experiences (average pain intensity, worst pain intensity, and pain-related limitations) and FA and MD. Sex differences in these effects were also explored. Analyses revealed widespread associations between pain-related limitations and lower FA and greater MD in male but not female youth. Furthermore, average pain intensity was associated with greater superior corticostriate and superior longitudinal fasciculus MD in all youth, and worst pain intensity was associated with lower inferior fronto-occipital fasciculus FA in male youth. There were no group differences in FA or MD between those with or without past-month pain. These findings suggest that white matter microstructural alterations in youth may be more related to the severity of the pain experience than to the presence or absence of pain itself, with male youth showing stronger neurobiological associations with pain-related outcomes.

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Existing research highlights interpersonal ethnic-racial discrimination as a contributing factor to sleep disparities among ethnic-racial minoritized adolescents. However, limited research has examined the impact of structural racism, the root cause of interpersonal discrimination, on sleep disturbances. The current study examined how structural racism within the state where an adolescent resided influenced sleep disturbances among ethnic-racial minoritized adolescents, both conjointly and interactively with their experiences of interpersonal discrimination.

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Early initiation of substance use (  14 years old) constitutes a key target for intervention strategies. This study investigated associations between exposure to adverse childhood experiences (ACEs) and risk for future substance use among young adolescents in the United States (US); the moderating effect of family conflict was also explored.

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The present study examined default mode network (DMN) neural connectivity patterns among adolescents. Next, we tested two critical markers of sleep health-duration and efficiency, in predicting neural connectivity patterns. Last, we investigated the latent DMN profiles’ predictive utility of internalizing and externalizing symptoms in youth.

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In 2023, the US Surgeon General issued the Advisory on Social Media and Youth Mental Health, identifying critical research gaps that preclude evidence-based guidance given that most studies of social media and mental health have been cross-sectional rather than longitudinal and have focused on young adults or older adolescents rather than on younger adolescents.

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Genome-wide association studies (GWAS) have uncovered genetic variants associated with suicide attempt (SA) risk and regional brain volumes (RBVs). However, the extent of their genetic overlap remains unclear. To address this, we investigated whether the genetic architecture of SA and various RBVs (i.e., caudate nucleus, hippocampus, brainstem, ventral diencephalon, thalamus, globus pallidus, putamen, nucleus accumbens, amygdala and intracranial volume (ICV)) was shared. We leveraged GWAS summary statistics from the largest available datasets on SA (N = 958,896) and intracranial and subcortical RBVs (N = 74,898). Using linkage disequilibrium score regression, we estimated genome-wide genetic correlations between SA and individual RBVs. GWAS-pairwise analyses identified genomic segments associated with both SA and RBVs, followed by functional annotation. Additionally, we examined whether polygenic scores (PGS) for SA were associated with ICV and subcortical brain structure phenotypes in youth of European ancestry (N = 5276) in the Adolescent Brain Cognitive Development (ABCD) study. Linkage disequilibrium score regression results indicated a significant genetic correlation between SA and ICV (rG = -0.10, p-value = 1.9 × 10-3). GWAS-pairwise analyses and functional annotation revealed 10 genomic segments associated with SA and at least one RBV (thalamus, putamen and caudate nucleus). After adjusting for multiple tests, PGS association analysis indicated that a higher PGS for SA was significantly associated with a smaller volume of the right nucleus accumbens (b = -7.05, p = 0.018). Our findings highlight a negative genetic correlation between SA and ICV amongst adults and suggest different neural correlates associated with genetic risk for SA across developmental periods. This study advances our understanding of the shared genetic underpinnings of SA and brain structure, potentially informing future research and clinical interventions.

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Children are disproportionately exposed to sexual orientation-based discrimination and ethnic or racial discrimination due to intersections of sexual orientation, ethnicity, race, and assigned sex at birth. Yet, there is sparse evidence in clinical settings.

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Differences in adolescent temperament are associated with innumerable psychological outcomes in the developmental literature and can help link adult personality-based nosology to earlier development. The Early Adolescent Temperament Questionnaire-Revised is one important measure of adolescent temperament designed to capture constructs within the influential Rothbart temperament model. Yet conflicting factor structures and minimal evidence for measurement invariance across samples and clinical groups have limited its ability to further temperament-based understanding of psychopathology. The goal of the present study was to identify reproducible measurement structures for the parent-rated and self-rated Early Adolescent Temperament Questionnaire-Revised in multiple large independent samples and to evaluate how that structure corresponded to their proposed theoretical structure. We also tested measurement invariance and compared temperament characteristics in youth with and without attention-deficit/hyperactivity disorder. Findings support the lower order theoretical structure using a reduced set of items in the parent-rated form, including evidence for measurement invariance across samples and clinical groups. Findings confirm important patterns of temperament variation associated with attention-deficit/hyperactivity disorder diagnosis, including lower effortful control and differences in expression of negative affect and surgency. The self-rated form demonstrated poor structural validity and could not be reliably replicated in a confirmatory sample. Parent-reported temperament may help link personality-based models of psychopathology to earlier developmental periods where psychopathology often emerges. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

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Sleep is critical for healthy brain development and emotional well-being, especially during adolescence, when sleep, behavior, and neurobiology are rapidly evolving. Theoretical reviews and empirical research have historically focused on how sleep influences mental health through its impact on higher-order brain systems. No studies have leveraged data-driven network neuroscience methods to uncover interpretable, brainwide signatures of sleep duration in adolescence, their socioenvironmental origins, and their consequences for cognition and psychopathology.

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Potential health consequences of adolescent smartphone use are a growing public concern. Improving upon existing, largely self-report-based research, this study investigated relationships between adolescent smartphone use, sleep, and physical activity using passive sensor measures.

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Mental health problems are the major cause of disability among adolescents. Personalized prevention may help to mitigate the development of mental health problems, but no tools are available to identify individuals at risk before they require mental health care.

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Depression is characterized by diverse symptom combinations that can be represented as dynamic networks. While previous research has focused on central symptoms for targeted interventions, less attention has been given to whole-network properties. Here we show that ‘network temperature’, a novel measure of psychological network stability, captures symptom alignment across adolescence-a critical period for depression onset. Network temperature reflects system stability, with higher values indicating less symptom alignment and greater variability. In three large longitudinal adolescent cohorts (total  = 35,901), we found that network temperature decreases across adolescence, with the steepest decline during early adolescence, particularly in males. This suggests that depression symptom networks stabilize throughout development via increased symptom alignment, potentially explaining why adolescence is a crucial period for depression onset. These findings highlight early adolescence as a key intervention window and underscore the importance of sex-specific and personalized interventions.

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