Research Publications

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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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With surges in digital technologies, concerns over adolescents’ screen use have intensified. Previous studies often relied on self-reported screen time, neglecting the experiential and motivational aspects of different screen activities (e.g. social media, gaming, and smartphones), possibly leading to heterogeneous associations. This study aimed to examine whether the severity of problematic screen use, conceptualized as a continuous measure of screen-related functional impairment, plays a more central role in development than self-reported screen time or phone-checking frequency, and to explore its influence within the broader adolescent ecosystem (i.e. family conflict, peer involvement, and school participation).

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Childhood adversity can have a lasting negative impact throughout one’s life. Youth with pain conditions consistently report a higher rate of adverse childhood experiences (ACEs) when compared with their healthy peers. Adolescents experiencing pain in more than 1 region tend to have greater symptom burden and reduced quality of life. Research on the association between ACEs and multisite pain in adolescents is sparse.

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Childhood maltreatment significantly heightens the risk of suicide attempt, but the causal mechanisms and underlying pathways are not fully understood. Using genetic instruments for both childhood maltreatment (n = 185,414) and suicide attempt (cases = 29,782; controls = 519,961), we performed two-sample Mendelian randomization analyses. Our results show that higher level of childhood maltreatment is causally associated with an increased risk of suicide attempt (OR = 3.40; 95% CI, 2.34-4.96, P = 1.3e-10). We then conducted a two-step Mendelian randomization mediation analysis, identifying 11 out of 58 potential mediators between childhood maltreatment and suicide attempt. These mediators included neurobiological, psychopathological and behavioral factors. The psychopathological factors had the most significant impact, accounting for 10.4-50.2% the mediation. This study confirms the causal relationship between childhood maltreatment and suicide attempt, highlighting specific mediators-especially within the psychopathological dimension-that can guide targeted interventions to alleviate the adverse effects of childhood maltreatment and prevent suicide attempt.

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Negative life events (NLEs) have been shown to perturb neurodevelopment and are correlated with poor mental health outcomes in adolescence, the most common period of psychopathology onset. Emotion regulation is a critical component of psychological response to NLEs and interacts, neurobiologically and behaviorally, with working memory. This study leveraged an emotional n-back task to examine how NLEs influence emotion- and working memory-related brain activation using data from 2150 youth in the Adolescent Brain Cognitive Development (ABCD) Study. Greater incidence of NLEs was associated with less activation in the amygdala and more pronounced deactivation in other limbic and frontal brain regions previously implicated in emotion-related cognition; however, this association was present only during emotion processing conditions of the task. While NLEs were not significantly associated with task performance in the final sample, behavioural analyses including youth excluded for low task accuracy and poor neuroimaging data quality showed a significant negative association between NLEs and overall task performance. While behavioural findings across the entire sample support prior work, somewhat incongruent with prior literature, imaging results may suggest that during early adolescence the effects of negative experiences on patterns of neural activation are specific to contexts necessitating emotion processing.

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Understanding the relative influences of age, pubertal development, and sex assigned at birth on brain development is a key priority of developmental neuroscience given the complex interplay of these factors in the onset of psychopathology. Previous research has investigated how these factors relate to static (time-averaged) functional connectivity (FC), but little is known about their relationship with dynamic (time-varying) FC. The present study aimed to investigate the unique and overlapping roles of these factors on dynamic FC in children aged approximately 9 to 14 in the ABCD Study using a sample of 5,122 low-motion resting-state scans (from 4,136 unique participants). Time-varying correlations in the frontolimbic, default mode, and dorsal and ventral corticostriatal networks, estimated using the Dynamic Conditional Correlations (DCC) method, were used to calculate variability of within- and between-network connectivity and of graph theoretical measures of segregation and integration. We found decreased variability in global efficiency across the age range, and increased variability within the frontolimbic network driven primarily by those assigned female at birth (AFAB). AFAB youth specifically also showed increased variability in several other networks. Controlling for age, both advanced pubertal development and being AFAB were associated with decreased variability in all within- and between-network correlations and increased variability in measures of network segregation. These results potentially suggest advanced brain maturation in AFAB youth, particularly in key networks related to psychopathology, and lay the foundation for future investigations of dynamic FC.

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Air pollution is an emerging novel neurotoxicant during childhood and adolescence. However, little is known regarding how fine particulate matter (PM) components and its sources impact brain morphology. We investigated air pollution exposure-related differences in brain morphology using cross-sectional magnetic resonance imaging data from 10,095 children ages 9-11 years-old enrolled in the United States’ Adolescent Brain Cognitive Development Study [2016-2018]. Air pollution estimates included fifteen PM constituent chemicals and metals, and six major sources of PM (e.g., crustal materials, biomass burning, traffic) identified from prior source apportionment, as well as nitrogen dioxide (NO) and ozone (O). After adjusting for demographic, socioeconomic, and neuroimaging covariates, we used partial least squares analyses to identify associations between simultaneous co-exposures and morphological differences in cortical thickness, surface area, and subcortical volumes. We found that greater exposure to PM and NO was associated with decreases in frontal and increases in inferior temporal surface area. PM component and source analyses linked cortical surface area and thickness to biomass burning (e.g., organic carbon, potassium), crustal material (e.g., calcium, silicon), and traffic (e.g., copper, iron) exposures, while smaller subcortical volumes were linked to greater potassium exposure. This is the first study to show differential effects of several air pollution sources on development of children’s brains. Significant associations were found in brain structures involved in several cognitive and social processes, including lower- and higher-order sensory processing, socioemotional behaviors, and executive functioning. These findings highlight differential effects of several air pollution sources on brain structure in preadolescents across the U.S.

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Adolescence is a critical period marked by significant physical and neurocognitive development as well as increased vulnerability to mental health issues. While the benefits of physical activity (PA) on adult mental health (MH) are well-established, the dose-response relationships and underlying neurobiological mechanisms in adolescents remain elusive. This study investigated the dose-response relationships between wearable-measured PA and MH outcomes in over 7000 adolescents (11-12 years) from the ABCD study through linear and nonlinear modeling. We further examined the genetic influence and mediation effects of brain structure and function underlying the relationships. We found that all intensity levels of PA were associated with reduced internalizing and thought problems but not with externalizing problems. Durations of moderate activity around 90 min and vigorous activity around 120 min each day and frequency of physical exercise four days each week were associated with lowest MH burden. Polygenic risk scores (PRSs) for neuropsychiatric disorders were associated with reduced step count and light activity, while PRS for walking was associated with reduced thought problems. Reduced functional connectivity between cingulo-parietal and auditory networks, and between cingulo-opercular network and left putamen is the common neural pathways mediating the associations between different PA measurements and better mental health. These findings suggest that excessive moderate and vigorous activity may not be always better for adolescent mental health. Brain functional integration and segregation centered on cognitive control as well as genetic interplay may be the potential neurobiological factors underlying the link between PA and MH.

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Behavioral activation (BA) traits mediate responses to positive reinforcement, and then to promote reward-seeking actions. However, few studies have investigated the neurobiological profiles of BA traits in adolescents based on multimodal neuroimaging and machine learning techniques. In this study, a total of 6626 adolescents with both valid multimodal magnetic resonance imaging (MRI) and questionnaire data were included in the Adolescent Brain Cognitive Development Study. Machine learning-based elastic net regression with 5-fold cross-validation (CV) was used to characterize the neurobiological profiles of BA traits using multimodal MRI data as predictors. Using 5-fold CV, the multi-region neurobiological profiles substantively predicted BA traits, and this finding was robust in an out-of-sample. Regarding specific regions, neurobiological profiles were enriched in the bilateral pallidum. Regarding functional networks, functional connectivity of the cingulo-opercular and the fronto-parietal networks with both the pallidum and nucleus accumbens, showed high beta weights. The relationships of the neurobiological profiles with BA traits were further supported by traditional univariate linear mixed effects models, in which many of the profiles identified as part of the neurobiological pattern showed significant univariate associations with BA traits, including the hub region pallidum. In summary, these findings revealed robust machine learning-derived neurobiological profiles of BA traits, those that comprised a key node the pallidum, which is involved in the motivational brain network. These findings suggested that the pallidum might play a vital role in developing BA traits in adolescents.

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Traditional categorical systems for diagnosing psychopathological symptoms, such as the DSM-5, face limitations including high comorbidity rates and insufficient support for transdiagnostic treatment protocols. Dimensional, person-centered approaches can address these limitations by focusing on cross-cutting psychiatric symptoms.

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Effective connectivity (EC), which reflects the causal interactions between brain regions, is fundamental to understanding information processing in the brain; however, traditional methods for obtaining EC, which rely on neural responses to stimulation, are often invasive or limited in spatial coverage, making them unsuitable for whole-brain EC mapping in humans. Here, to address this gap, we introduce Neural Perturbational Inference (NPI), a data-driven framework for mapping whole-brain EC. NPI employs an artificial neural network trained to model large-scale neural dynamics, serving as a computational surrogate of the brain. By systematically perturbing all regions in the surrogate brain and analyzing the resulting responses in other regions, NPI maps the directionality, strength and excitatory/inhibitory properties of brain-wide EC. Validation of NPI on generative models with known ground-truth EC demonstrates its superiority over existing methods such as Granger causality and dynamic causal modeling. When applied to resting-state functional magnetic resonance imaging data across diverse datasets, NPI reveals consistent, structurally supported EC patterns. Furthermore, comparisons with cortico-cortical evoked potential data show a strong resemblance between NPI-inferred EC and real stimulation propagation patterns. By transitioning from correlational to causal understandings of brain functionality, NPI marks a stride in decoding the brain’s functional architecture and facilitating both neuroscience studies and clinical applications.

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Although cross-sectional studies have investigated the effects of perceived racial discrimination on suicidality among adolescents, few studies have examined the effects of risk of racism on suicidality among young adolescents using longitudinal data. This study investigated the association between the risk of racism and suicidality among young adolescents. Data for this study came from the Adolescent Brain Cognitive Development (ABCD) study (2017-2020). The sample (n = 10,301) of adolescents aged 11-12 was analyzed with risk of racism at Wave 1 as the main explanatory variable and suicidality at Wave 2 as the outcome variable. The main analysis involves the use of binary logistic regression. Of the 10,301 young adolescents examined, 13.01 % reported experiencing suicidality, 54.58 % were at low risk of racism, 42.54 % were at moderate risk of racism, and 2.88 % were at high risk of racism. Controlling for demographic characteristics, risk and protective factors, the odds of experiencing suicidality were 1.69 times higher for young adolescents at high risk of racism [AOR = 1.69, 95 % CI = 1.23, 2.32] when compared to their counterparts at low risk of racism. Parental acceptance and monitoring emerged as protective factors against the detrimental effects of racism on suicidality. The findings of this study demonstrate that racial discrimination significantly contributes to suicidality. There is the need for targeted interventions and anti-racist policies to combat racism and promote protective familial relationships to mitigate young adolescent suicidality.

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This study examines whether a deep neural network (DNN), trained to predict the general psychopathology factor (p-factor) using functional magnetic resonance imaging (fMRI) data from adolescents in the Adolescent Brain Cognitive Development (ABCD) study, generalizes to Korean adolescents.

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It is unclear how transdiagnostic symptoms including attention, disruptive behavior, and internalizing problems are linked to in-scanner motion in children across structural and functional magnetic resonance imaging (fMRI). In the current study, we examined whether transdiagnostic symptoms of attention, disruptive behavior, and internalizing problems were associated with scanner motion in children during multimodal imaging.

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Understanding the brain mechanisms underlying adolescent sleep patterns and their impact on psychophysiological development is complex. We applied sparse canonical correlation analysis (sCCA) to data from 3,222 adolescents in the Adolescent Brain Cognitive Development (ABCD) study, integrating sleep characteristics with multimodal imaging. This reveals two key sleep-brain dimensions: one linking later sleep onset and shorter duration to decreased subcortical-cortical connectivity and another associating a higher heart rate and shorter light sleep with lower brain volumes and connectivity. Hierarchical clustering identifies three biotypes: biotype 1 has delayed, shorter sleep with a higher heart rate; biotype 3 has earlier, longer sleep with a lower heart rate; and biotype 2 is intermediate. These biotypes also differ in cognitive performance and brain structure and function. Longitudinal analysis confirms these differences from ages 9 to 14, with biotype 3 showing consistent cognitive advantages. Our findings offer insights into optimizing sleep routines for better cognitive development.

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Patients with ADHD evidence elevated reaction time variability (RTV) due to periodic long reaction times (RTs). Even though reaction time variability (RTV) reflects intraindividual differences in RT across time, prior research exploring the neural basis of RTV in ADHD has primarily examined associations between neural activation and summary RTV outcomes (e.g., standard deviation of reaction time, tau). Here, we explore group differences in the neural basis of RTV by examining association between trial-level RTs and fMRI BOLD activation obtained during a Stop Signal Task in a large ( = 5719) sample of 9- to 10-year-old children participating in the Adolescent Brain Cognitive Development (ABCD) study. Children with ADHD demonstrated greater RTV than those without ADHD. ADHD-related group differences were not observed between fMRI BOLD activation and summary RTV outcomes. At the trial level, longer RTs were associated with increased BOLD activation in salience/ventral attention and executive control networks and decreased BOLD activation in the default mode network, consistent with time-on-task effects (i.e., stimulus processing time) in which long RTs require maintaining task-positive activation and DMN suppression for more time than short RTs. Moreover, children with ADHD showed weaker associations between long RTs and BOLD activation in these regions than children without ADHD supporting models that point to dysregulated competition between the DMN and executive network as mechanism of cognitive impairment in ADHD.

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The recent emergence of deep learning methods, particularly convolutional neural networks (CNNs), applied to fMRI data presents a promising avenue in psychiatry research, offering advantages over traditional analyses by requiring minimal assumptions and enabling detection of higher-level patterns and intricate, nonlinear relationships within inherently complex fMRI data. Irritability, defined as a lowered threshold for angry responses to blocked rewards, is a promising neurodevelopmental marker for mental health risk due to its robust, transdiagnostic predictive power in youth. In this study, data from the Adolescent Brain and Cognitive Development (ABCD) baseline sample ( = 6065) were utilized for a novel application of a 3D CNN to whole-brain fMRI data acquired during the reward anticipation period of the monetary incentive delay task to predict parent-reported youth irritability severity, measured dimensionally. Regression activation mapping (RAM) was employed to extract feature maps of brain regions most predictive of irritability severity from the model. The model demonstrated satisfactory accuracy, with a mean squared error (MSE) of 1.82, and predicted irritability severity scores with a mean absolute error (MAE) of 0.48 ± 1.54 SD from the true scores. Notably, feature maps revealed bilateral representation of key regions implicated in emotional response and reward processing, including the caudate nucleus, amygdala, parahippocampal gyrus, and hippocampus. This study underscores the potential for 3D CNNs to predict significant, dimensional clinical outcomes such as irritability severity using fMRI data.

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C-reactive protein (CRP) is a moderately heritable marker of systemic inflammation that is associated with adverse physical and mental health outcomes. Identifying factors associated with genetic liability to elevated CRP in childhood may inform our understanding of variability in CRP that could be targeted to prevent and/or delay the onset of related health outcomes.

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Greenspace exposure is associated with positive mental health and academic outcomes. This preregistered longitudinal study examines whether the influence of greenspace exposure on structural brain development partially explains these associations.

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Racial discrimination drives health disparities among racial/ethnic minority youth, creating chronic stress that affects brain development and contributes to mental and behavioral health issues. This study analyzed data from the Adolescent Brain Cognitive Development (ABCD) Study to examine the neurobiological mechanisms linking discrimination to mental and behavioral health outcomes.

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The red nucleus, a large brainstem structure, coordinates limb movement for locomotion in quadrupedal animals. In humans, its pattern of anatomical connectivity differs from that of quadrupeds, suggesting a different purpose. Here, we apply our most advanced resting-state functional connectivity based precision functional mapping in highly sampled individuals (n = 5), resting-state functional connectivity in large group-averaged datasets (combined n ~ 45,000), and task based analysis of reward, motor, and action related contrasts from group-averaged datasets (n > 1000) and meta-analyses (n > 14,000 studies) to precisely examine red nucleus function. Notably, red nucleus functional connectivity with motor-effector networks (somatomotor hand, foot, and mouth) is minimal. Instead, connectivity is strongest to the action-mode and salience networks, which are important for action/cognitive control and reward/motivated behavior. Consistent with this, the red nucleus responds to motor planning more than to actual movement, while also responding to rewards. Our results suggest the human red nucleus implements goal-directed behavior by integrating behavioral valence and action plans instead of serving a pure motor-effector function.

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Sleep irregularity are associated with health outcomes, particularly during adolescence. Early adversity may exacerbate sleep irregularity, but longitudinal evidence remains limited.

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Understanding the relationship between subjective and objective sleep measures is essential for evaluating their agreement and utility. This study compared Munich Chronotype Questionnaire (MCTQ) and Fitbit metrics for sleep duration, sleep midpoint and social jetlag in 5252 participants from the Adolescent Brain Cognitive Development (ABCD) study. Linear and nonlinear models assessed relationships between Fitbit-derived and MCTQ-reported metrics, whilst moderation analyses examined the influence of age, sex, household income and BMI. A sensitivity analysis compared results pre- and post-COVID-19 to assess pandemic-related effects (pre-COVID n = 4451). Correlations were weak to moderate: r = 0.15-0.21 for sleep duration, r = 0.37-0.42 for sleep midpoint, and r = 0.12-0.16 for social jetlag. Quadratic and LOESS models confirmed nonlinear trends for sleep midpoint, with greater Fitbit-MCTQ divergence at extreme morningness or eveningness. Fitbit classified 63.2% of participants as having insufficient sleep, compared to 39.45% with MCTQ, suggesting Fitbit underestimates sleep duration. Bland-Altman plots confirmed MCTQ overestimation, especially for shorter sleepers. BMI was significantly associated with sleep duration and social jetlag, with higher BMI linked to shorter sleep and greater variability. Household income and BMI moderated specific sleep metrics, whilst age and sex did not significantly moderate any metric. Sensitivity analyses showed consistent results across pre- and post-COVID periods. Findings highlight stronger agreement for sleep midpoint than for sleep duration or social jetlag, with methodological differences driving discrepancies. The consistency across demographics and time periods supports the complementary use of Fitbit and MCTQ for adolescent sleep assessment.

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White matter develops over the course of childhood in an experience-dependent manner. However, its role in the relationship between the early environment and later cognition is unclear, in part due to focus on changes in specific gray matter regions. This study examines white matter differences across adolescents from diverse environments, evaluating both their extent throughout the brain and their contribution to cognitive outcomes. Using data from the Adolescent Brain Cognitive Development (ABCD) study (N = 9,082, female = 4,327), we found extensive cross-sectional associations with lower white matter fractional anisotropy (FA) and streamline count in the brains of 9- and 10-y-old children exposed to a range of experiences, including prenatal risk factors, interpersonal adversity, household economic deprivation, and neighborhood adversity. Lower values of FA were associated with later difficulties with mental arithmetic and receptive language. Furthermore, white matter FA partially mediated the detrimental relationship between adversity and cognition later in adolescence. These findings advance a white matter-based account of the neural and cognitive effects of adversity, which supports leading developmental theories that place interregional connectivity prior to gray matter maturation.

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Marijuana consumption by pregnant women has been steadily increasing over the past decades. Even though many pregnant women perceive marijuana consumption as safe during pregnancy it has been previously linked to poor maternal and neonatal outcomes. The specific long lasting neurodevelopmental alterations caused by prenatal marijuana exposure in children are still underexplored. Thus, this study aims to determine the effect of prenatal marijuana exposure on brain neurodevelopment at late childhood.

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Suicide is the second leading cause of death among early adolescents, yet the first onset of suicide attempts during this critical developmental period remains poorly understood. This study aimed to identify key characteristics associated with the first suicide attempt in early adolescence and to develop a predictive model for assessing individual risk.

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Delay discounting (DD), which reflects a tendency to devalue rewards as the time to their receipt increases, is associated with health behaviors such as sleep disturbances, obesity, and externalizing behavior among adolescents. Response patterns characterized by inconsistent or unexpected reward valuation, called non-systematic responding (NSR), may also predict health outcomes. Many researchers flag and exclude NSR trials prior to analysis, which could lead to systematic bias if NSR (a) varies by demographic characteristics or (b) predicts health outcomes. Thus, in this study we characterized NSR and examined its potential beyond error by comparing it against DD with a secondary data analysis of the Adolescent Brain Cognitive Development (ABCD) Study-a population-based study that tracked youths (N = 11,948) annually from 8 to 11 years of age over 4 years. We assessed DD and NSR using the Adjusting Delay Discounting Task when youths were approximately 9.48 years old (SD = 0.51). We also examined three maladaptive health outcomes annually: sleep disturbances, obesity, and externalizing psychopathology. Our analysis revealed variations in NSR across races, ethnicities, and body mass index categories, with no significant differences observed by sex or gender. Notably, NSR was a stronger predictor of obesity and externalizing psychopathology than DD and inversely predicted the growth trajectory of obesity. These findings suggest that removing NSR patterns could systematically bias analyses given that NSR may capture unexplored response variability. This study demonstrates the significance of NSR and underscores the necessity for further research on how to manage NSR in future DD studies.

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Functional connectivity of the human brain changes through life. Here, we assemble task-free functional and structural magnetic resonance imaging data from 33,250 individuals at 32 weeks of postmenstrual age to 80 years from 132 global sites. We report critical inflection points in the nonlinear growth curves of the global mean and variance of the connectome, peaking in the late fourth and late third decades of life, respectively. After constructing a fine-grained, lifespan-wide suite of system-level brain atlases, we show distinct maturation timelines for functional segregation within different systems. Lifespan growth of regional connectivity is organized along a spatiotemporal cortical axis, transitioning from primary sensorimotor regions to higher-order association regions. These findings elucidate the lifespan evolution of the functional connectome and can serve as a normative reference for quantifying individual variation in development, aging and neuropsychiatric disorders.

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To review recent literature based on Adolescent Brain and Cognitive Development (ABCD) Study data of over 11 000 participants about screen time and social media use in early adolescence, including epidemiology, trends, and associations with mental and physical health outcomes.

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The conventional approach to estimating heritability in twin studies implicitly assumes either the absence of measurement error or that any measurement error is incorporated into the nonshared environment component. However, this assumption can be problematic when it does not hold or when measurement error cannot be reasonably classified as part of the nonshared environment. In this study, we demonstrate the need for improvement in the conventional structural equation modeling (SEM) used for estimating heritability when applied to trait data with measurement errors. The critical issue revolves around an assumption concerning measurement errors in twin studies. In cases where traits are measured using samples, data is aggregated during preprocessing, with only a centrality measure (e.g., mean) being used for modeling. Additionally, measurement errors resulting from sampling are assumed to be part of the nonshared environment and are thus overlooked in heritability estimation. Consequently, the presence of intra-individual variability remains concealed. Moreover, recommended sample sizes are typically based on the assumption of no measurement errors. We argue that measurement errors in the form of intra-individual variability are an intrinsic limitation of finite sampling and should not be considered as part of the nonshared environment. Previous studies have shown that the intra-individual variability of psychometric effects is significantly larger than the inter-individual counterpart. Here, to demonstrate the appropriateness and advantages of our hierarchical linear modeling approach in heritability estimation, we utilize simulations as well as a real dataset from the ABCD (Adolescent Brain Cognitive Development) study. Moreover, we showcase the following analytical insights for data containing non-negligible measurement errors: i) The conventional SEM may underestimate heritability. ii) A hierarchical model provides a more accurate assessment of heritability. iii) Large samples, exceeding 100 observations or thousands of twins, may be necessary to reduce imprecision. Our study highlights the impact of measurement error on heritability estimation and introduces a hierarchical model as a more accurate alternative. These findings have significant implications for understanding individual differences and improving the design and analysis of twin studies.

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Both video game addiction (VGA) and social media addiction (SMA) have been linked to dysfunction of the brain reward circuit. However, it remains unclear whether VGA or SMA have a bidirectional relationship with reward circuit dysfunction during development. The current study used a large longitudinal dataset from the Adolescent Brain and Cognitive Development (ABCD) study to explore the association between VGA, SMA, and longitudinal changes in neural processing of rewards and losses during a monetary incentive delay task. Significant VGA × time interactions were observed for loss-related neural activity were observed in left nucleus accumbens, bilateral insula, and right anterior cingulate cortex (ACC). Simple slope analysis revealed an increasing trend in neural responses to losses among participants with high levels of VGA. Additionally, time × neural loss sensitivity interactions predicted later VGA in the right amygdala and right ACC, suggesting that heightened loss sensitivity both influences and is influenced by VGA. In contrast, SMA showed no significant longitudinal associations with reward or loss sensitivity. These findings highlight a bidirectional relationship between VGA and neural loss sensitivity, while SMA was not implicated in similar patterns. These findings may provide valuable insights into the neural mechanisms underlying behavioral addiction.

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Higher delay discounting (DD) (i.e., propensity to devalue larger, delayed rewards over immediate, smaller rewards) is a transdiagnostic marker underpinning multiple health behaviors. Although genetic influences account for some of the variability in DD among adults, less is known about the genetic contributors to DD among preadolescents. We examined whether polygenic scores (PGS) for DD, educational attainment, and behavioral traits (i.e., impulsivity, inhibition, and externalizing behavior) were associated with phenotypic DD among preadolescents. Participants included youth (N = 8982, 53% male) from the Adolescent Brain Cognitive Development Study who completed an Adjusting Delay Discounting Task at the 1-year follow-up and had valid genetic data. PGS for DD, educational attainment, impulsivity, inhibition, and externalizing behaviors were created based on the largest GWAS available. Separate linear mixed effects models were conducted in individuals most genetically similar to European (EUR; n = 4972), African (AFR; n = 1769), and Admixed American (AMR; n = 2241) reference panels. After adjusting for age, sex, income, and the top ten genetic ancestry principal components, greater PGS for DD and lower educational attainment (but not impulsivity, inhibition, or externalizing) were associated with higher rates of DD (i.e., preference for sooner, smaller rewards) in participants most genetically similar to EUR reference panels. Findings provide insight into the influence of genetic propensity for DD and educational attainment on the discounting tendencies of preadolescents, particularly those most genetically similar to European reference samples, thereby advancing our understanding of the etiology of choice behaviors in this population.

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General cognitive ability (GCA), also called “general intelligence,” is thought to depend on network properties of the brain, which can be quantified through graph theoretic measures such as small worldness and module degree. An extensive set of studies examined links between GCA and graphical properties of resting state connectomes. However, these studies often involved small samples, applied just a few graph theory measures in each study, and yielded inconsistent results, making it challenging to identify the architectural underpinnings of GCA. Here, we address these limitations by systematically investigating univariate and multivariate relationships between GCA and 17 whole-brain and node-level graph theory measures in individuals from the Adolescent Brain Cognitive Development Study (n = 5937). We demonstrate that whole-brain graph theory measures, including small worldness and global efficiency, fail to exhibit meaningful relationships with GCA. In contrast, multiple node-level graphical measures, especially module degree (within-network connectivity), exhibit strong associations with GCA. We establish the robustness of these results by replicating them in a second large sample, the Human Connectome Project (n = 847), and across a variety of modeling choices. This study provides the most comprehensive and definitive account to date of complex interrelationships between GCA and graphical properties of the brain’s intrinsic functional architecture.

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Preterm and early-term births are known risk factors for cognitive impairment, but studies that comprehensively include genetics, prenatal risk, and child-specific factors in high-risk populations are lacking.

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Multisite pain disproportionately affects females starting in adolescence and is associated with central nervous system dysregulation. Understanding the heterogeneity of underlying neural networks and behavioral symptoms is essential.

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The increasing availability of large-scale brain imaging genetics studies enables more comprehensive exploration of the genetic underpinnings of brain functional organizations. However, fundamental analytical challenges arise when considering the complex network topology of brain functional connectivity, influenced by genetic contributions and sample relatedness, particularly in longitudinal studies. In this paper, we propose a novel method named Bayesian Longitudinal Network-Variant Regression (BLNR), which models the association between genetic variants and longitudinal brain functional connectivity. BLNR fills the gap in existing longitudinal genome-wide association studies that primarily focus on univariate or multivariate phenotypes. Our approach jointly models the biological architecture of brain functional connectivity and the associated genetic mixed-effect components within a Bayesian framework. By employing plausible prior settings and posterior inference, BLNR enables the identification of significant genetic signals and their associated brain sub-network components, providing robust inference. We demonstrate the superiority of our model through extensive simulations and apply it to the Adolescent Brain Cognitive Development (ABCD) study. This application highlights BLNR’s ability to estimate the genetic effects on changes in brain network configurations during neurodevelopment, demonstrating its potential to extend to other similar problems involving sample relatedness and network-variate outcomes.

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