Research Publications

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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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Adolescents often do not sleep as much as recommended by most national guidelines, which may impact their brain development. The current study aims to evaluate the relationship between objective assessment of sleep duration measured with actigraphy, and brain network connectivity on functional magnetic resonance imaging (fMRI).

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Exposure to adversity (e.g., negative life events) and socioeconomic disadvantage can increase the risk for internalizing and externalizing symptoms, but many youth demonstrate resilience. Risk and protective factors may vary depending on geographic contexts (i.e., urban vs. rural areas). We hypothesized that community cohesion would mitigate the effects of adversity and disadvantage on youth mental health symptoms, especially among rural communities.

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Distressing psychotic-like experiences (PLEs) in children are associated with an increased risk for psychiatric disorders. Recent studies suggest that different domains of psychotic symptoms could be associated with distinct risk factors, but less is known about PLEs. This study clustered PLEs into subgroups and explored the genetic and environmental characteristics associated with these profiles.

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The relationship between brain asymmetry and inattention, and their heritability is not well understood. Utilizing advanced neuroimaging, we examined brain asymmetry with data from the Adolescent Brain Cognitive Development (ABCD; n = 8943; 9-10 y) and the Human Connectome Project (HCP) cohorts (n = 1033; 5-100 y). Data-driven metrics from resting-state fMRI and morphometrics revealed reproducible and stable brain asymmetry patterns across the lifespan. In children, high levels of inattention were highly heritable (61%) and linked to reduced leftward asymmetry of functional connectivity in the dorsal posterior superior temporal sulcus (dpSTS), a region interconnected with a left-lateralized language network. However, reduced dpSTS asymmetry had low heritability (16%) and was associated with lower cognitive performance suggesting that non-genetic factors, such as those mediating cognitive performance, might underlie its association with dpSTS asymmetry. Interventions that enhance cognition might help optimize brain function and reduce inattention.

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The current study sought to gain a clearer understanding of the impact of child and parent linguistic factors, ethnic identity salience, and acculturation to both mainstream United States of America (USA) culture and their heritage culture on executive functioning task performance among Latin American youth living in the USA.

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Humans are inevitably exposed to multiple physical and social environmental risk factors, potentially contributing to psychiatric problems and cognitive deficits; however, the combined effects of prenatal air pollution and psychosocial environments on youth remain unclear. This longitudinal study aimed to examine how prenatal ozone exposure interacts with psychosocial environments at 9-10 years to affect adolescent limbic system development, cognition, and psychotic-like experiences (PLEs) at 11-13 years.

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Sexual and gender minority (SGM) youth are more susceptible to suicidal ideation and attempts compared to their heterosexual and cisgender peers. Yet, it is unclear how interpersonal and online victimization experiences account for the elevated suicide risks in this population. This study investigates the extent of peer and cyber victimization among SGM youth and its contribution to their higher risks of suicidal ideation and attempts longitudinally.

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Physical environments are linked to adolescents’ well-being in various ways. Green and blue (natural) spaces may protect against psychopathology, while gray (urban) spaces may confer risk. The present study examines how exposure to green, blue, and gray spaces is associated with the growth of psychopathology in early adolescence.

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Idiopathic generalized epilepsy (IGE) is a brain network disease, but the location of this network and its relevance for treatment remain unclear. We combine the locations of brain abnormalities in IGE (131 coordinates from 21 studies) with the human connectome to identify an IGE network. We validate this network by showing alignment with structural brain abnormalities previously identified in IGE and brain areas activated by generalized epileptiform discharges in simultaneous electroencephalogram-functional magnetic resonance imaging. The topography of the IGE network aligns with brain networks involved in motor control and loss of consciousness consistent with generalized seizure semiology. To investigate therapeutic relevance, we analyze data from 21 patients with IGE treated with deep brain stimulation (DBS) for generalized seizures. Seizure frequency reduced a median 90% after DBS and stimulation sites intersect an IGE network peak in the centromedian nucleus of the thalamus. Together, this study helps unify prior findings in IGE and identify a brain network target that can be tested in clinical trials of brain stimulation to control generalized seizures.

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Sleep deficiency is common among youth exposed to adverse childhood experiences (ACEs) and may contribute towards persistent/recurrent pain (PRP). This study tested the hypotheses that sleep deficiency mediates the effect of ACEs on PRP and moderates the effect of ACEs on PRP exerted through anxiety and depression symptoms.

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This study examined the relationships between caffeine intake, screen time, and chronotype/sleep outcomes in adolescents, with a focus on differences between Hispanic and non-Hispanic groups and the influence of peer network health, school environment, and psychological factors, including perceived stress, depression, and anxiety. Data from the Adolescent Brain Cognitive Development (ABCD) study were analyzed using -tests and structural equation modeling (SEM) to assess behavioral, social, and psychological predictors of chronotype, social jet lag, and weekday sleep duration, incorporating demographic covariates. Hispanic adolescents exhibited a later chronotype (Cohen’s  = 0.42), greater social jet lag (Cohen’s  = 0.38), and shorter weekday sleep duration (Cohen’s  = -0.12) compared to non-Hispanic peers. They also reported higher caffeine intake (Cohen’s  = 0.22), though caffeine was not significantly associated with sleep outcomes. Screen time was more prevalent among Hispanic adolescents, particularly on weekday evenings (Cohen’s  = 0.27) and weekend evenings (Cohen’s  = 0.35), and was strongly associated with later chronotype and greater social jet lag. Higher perceived stress was linked to later chronotype and greater social jet lag, while depressive symptoms were associated with earlier chronotype and lower social jet lag. The SEM model explained 12.9% of variance in chronotype, 10.5% in social jet lag, and 6.2% in weekday sleep duration. These findings highlight disparities in adolescent sleep health but should be interpreted cautiously due to methodological limitations, including low caffeine use and assessment timing variability. Targeted interventions addressing screen time, peer relationships, and stress may improve sleep, while longitudinal research is needed to clarify causality.

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Brain markers for suicide risk in adulthood may be detected during childhood and used for earlier detection and initiation of preventive interventions. Genetic instrumental variable analyses were used to determine whether there is evidence of lower brain total cortical surface area and thinner average cortical thickness (ACT) causing increased suicide risk in adults and whether lower measures of similar brain measures can cause increased risk of suicidality and related psychopathology in older children.

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Sustained melatonin supplement use may delay pubertal onset, but evidence is limited. In the Adolescent Brain Cognitive Development study, we assessed if melatonin use for 38 months affected the timing of pubertal onset in males (N=3,134) and menarche in females (N=4,424). Pubertal outcomes were parent-reported using the Pubertal Development Scale. We emulated sequential target trials to evaluate the effect of initiating and continuing melatonin supplement use. Findings were contrasted with comparisons of ever- to never-users and initiators to non-initiators using Cox models. In sequentially emulated trials with 1,037,709 person-months among males and 1,818,084 person-months among females, there were 1,872 and 3,377 instances of melatonin use initiation among 186 males and 333 females, respectively. Observational analogues of intention-to-treat and per-protocol effects from target trial emulation showed no difference in risk of pubertal onset in males (end-of-follow-up per-protocol RR=1.00, 95%CI=0.87,1.13) or menarche in females (RR=0.93, 95%CI=0.80,1.07). By contrast, Cox models suggested a delay in menarche among 335(7.74%) melatonin ever-users after adjustment for child, family, and neighborhood characteristics collected at the enrollment visit (HR=0.80, 95%CI=(0.69,0.94)). In large samples, rigorous causal analyses that aligned eligibility criteria with treatment initiation and adjusted for time-varying confounding showed no effect of melatonin supplement use on pubertal timing.

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One of the challenges in the field of neuroimaging is that we often lack knowledge about the underlying truth and whether our methods can detect developmental changes. To address this gap, five research groups around the globe created simulated datasets embedded with their assumptions of the interplay between brain development, cognition, and behavior. Each group independently created the datasets, unaware of the approaches and assumptions made by the other groups. Each group simulated three datasets with the same variables, each with 10,000 participants over 7 longitudinal waves, ranging from 7 to 20 years-of-age. The independently created datasets include demographic data, brain derived variables along with behavior and cognition variables. These datasets and code that were used to generate the datasets can be downloaded and used by the research community to apply different longitudinal models to determine the underlying patterns and assumptions where the ground truth is known.

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Despite the mounting demand for generative population models, their limited generalizability to underrepresented demographic groups hinders widespread adoption in real-world applications. Here we propose a diversity-aware population modeling framework that can guide targeted strategies in public health and education, by estimating subgroup-level effects and stratifying predictions to capture sociodemographic variability. We leverage Bayesian multilevel regression and post-stratification to systematically quantify inter-individual differences in the relationship between socioeconomic status and cognitive development. Post-stratification enhanced the interpretability of model predictions across underrepresented groups by incorporating US Census data to gain additional insights into smaller subgroups in the Adolescent Brain Cognitive Development Study. This ensured that predictions were not skewed by overly heterogeneous or homogeneous representations. Our analyses underscore the importance of combining Bayesian multilevel modeling with post-stratification to validate reliability and provide a more holistic explanation of sociodemographic disparities in our diversity-aware population modeling framework.

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The amygdala, a key limbic structure, is critical to emotional, social, and appetitive behaviors that develop throughout adolescence. Composed of a heterogeneous group of nuclei, questions remain about potential differences in the maturation of its subregions during development. In 3953 9- and 10-year-olds from the Adolescent Brain Cognitive Development℠ Study, the CIT168 Atlas was used to segment nine amygdala subregions. Linear mixed-effects models were used to examine the effects of age, sex, pubertal stage, and body mass index z-score (BMIz) on subregion volumes and their relative apportionment within the amygdala. Distinct associations were observed between age, sex, and BMIz with whole amygdala volume, subregion volumes, and subregion apportionment. Pubertal stage was not related to amygdala subregion volumes. Age was associated with near-global expansion of amygdala subregions during this developmental period. Female sex was linked to smaller volumes in most amygdala subregions, with larger relative apportionment in the dorsal subregions and smaller apportionment in the basolateral ventral paralaminar subregion. Higher BMIz was associated with smaller volumes in large basolateral subregions, with increased relative apportionment in smaller subregions. These findings provide a foundational context for understanding how developmental variables influence amygdala structure, with implications for understanding future risk for brain disorders.

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Early life adversity (ELA) has substantial, lifelong impacts on mental and physical health and development. Data from the ABCD® Study will provide essential insights into these effects. Because the study lacks a unified adversity assessment, our objective was to use a critical, human-driven approach to identify variables that fit ELA domains measured in this study.

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Poverty and systemic racism within rare intertwined. Children of marginalized racial and ethnic identities experience higher levels of poverty and adverse psychiatric outcomes. Thus, in models of poverty and neurodevelopment, race and ethnicity-as proxies for exposure to systemic disadvantage-are regularly considered confounders. Recently, however, some researchers claimed that using race and ethnicity as confounders is statistically dubious, and potentially socially damaging. Instead, they argue for the use of variables measuring other social determinants of health (SDoH). We explore this approach.

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Inter-individual brain differences likely precede the emergence of mood and anxiety disorders, however, the specific brain alterations remain unclear. While many studies focus on a single imaging modality in isolation, recent advances in multimodal image analysis allow for a more comprehensive understanding of the complex neurobiology that underlies mental health.

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Large-scale GWAS studies have uncovered hundreds of genomic loci linked to facial and brain shape variation, but only tens associated with cranial vault shape, a largely overlooked aspect of the craniofacial complex. Surrounding the neocortex, the cranial vault plays a central role during craniofacial development and understanding its genetics are pivotal for understanding craniofacial conditions. Experimental biology and prior genetic studies have generated a wealth of knowledge that presents opportunities to aid further genetic discovery efforts. Here, we use the conditional FDR method to leverage GWAS data of facial shape, brain shape, and bone mineral density to enhance SNP discovery for cranial vault shape. This approach identified 120 independent genomic loci at 1% FDR, nearly tripling the number discovered through unconditioned analysis and implicating crucial craniofacial transcription factors and signaling pathways. These results significantly advance our genetic understanding of cranial vault shape and craniofacial development more broadly.

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Adequate sleep is essential for adolescents’ physical, emotional, and cognitive well-being. However, accurately capturing the complex components of sleep in this demographic is challenging, especially with retrospective self-report measures. This study aims to compare sleep data obtained from youth reports, caregiver reports, and Fitbit devices among early adolescents.

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The present study utilized structural equation models to investigate the association between brain activation and level of executive function in participants in the Adolescent Brain Cognitive Development (ABCD) study at the baseline assessment and the two-year follow-up. The results indicated that increasing levels of a latent factor reflecting activation across multiple regions of the frontoparietal network (FPN) for the contrast of a 2 vs. 0 back condition in the emotional N-back task were significantly associated with higher levels of a latent factor of common executive functioning (cEF) drawn from a variety of behavioral measures, while the opposite was true for a latent factor of activation drawn from somatomotor regions. Moreover, these relationships were specific to cEF as they held even when a latent measure of general intelligence was included. In addition, these effects were observed at each of the two distinct time points 2 years apart. cEF scores at baseline predicted FPN scores at the Year 2 follow-up after controlling for FPN scores at baseline. These results provide for the possibility that increased levels of cEF during late childhood may provide a strong substrate for continued development of the FPN and decreased reliance on somatomotor regions.

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Advanced diffusion magnetic resonance imaging (dMRI) allows one to probe and assess brain white matter (WM) organisation and microstructure in vivo. Various dMRI models with different theoretical and practical assumptions have been developed, representing partly overlapping characteristics of the underlying brain biology with potentially complementary value in the cognitive and clinical neurosciences. To which degree the different dMRI metrics relate to clinically relevant geno- and phenotypes is still debated. Hence, we investigate how tract-based and whole WM skeleton parameters from different dMRI approaches associate with clinically relevant and white matter-related phenotypes (sex, age, pulse pressure (PP), body-mass-index (BMI), brain asymmetry) and genetic markers in the UK Biobank (UKB, n=52,140) and the Adolescent Brain Cognitive Development (ABCD) Study (n=5,844). In general, none of the imaging approaches could explain all examined phenotypes, though the approaches were overall similar in explaining variability of the examined phenotypes. Nevertheless, particular diffusion parameters of the used dMRI approaches stood out in explaining some important phenotypes known to correlate with general human health outcomes. A multi-compartment Bayesian dMRI approach provided the strongest WM associations with age, and together with diffusion tensor imaging, the largest accuracy for sex-classifications. We find a similar pattern of metric and tract-dependent asymmetries across datasets, with stronger asymmetries in ABCD data. The magnitude of WM associations with polygenic scores as well as PP depended more on the sample, and likely age, than dMRI metrics. However, kurtosis was most indicative of BMI and potentially of bipolar disorder polygenic scores. We conclude that WM microstructure is differentially associated with clinically relevant pheno- and genotypes at different points in life.

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The rising prevalence of youth depression underscores the need to identify modifiable factors for prevention and intervention. This study aims to investigate the protective role of Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) diet on depressive symptoms in adolescents.

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Socioeconomic status (SES) is associated with widespread differences in structure of temporal, parietal, occipital, and frontal cortices. Development of sensory processing regions-in particular visual association cortex (VAC) and auditory association cortex (AAC)-may scaffold development of the prefrontal cortex (PFC). Experiences that correlate with SES like cognitive stimulation and language may influence VAC and AAC development, in turn allowing the PFC to resolve conflicts between similar stimuli. SES-related differences in these regions may partly explain differences in executive function (EF) skills. Here, we use structural equation modeling of longitudinal data from the Adolescent Brain and Cognitive Development study to test the hypothesis that SES-related differences in AAC and VAC are associated with differences in structure of the PFC and development of the PFC over time, which in turn are associated with development of EF. We found partial support for this model, demonstrating that SES-related differences in PFC structure are mediated by differences in sensory cortex structure, and that SES-related differences in sensory cortex structure mediate the association between SES and EF. These findings highlight the role sensory processing regions play in SES-related differences in PFC development. Future studies should explore proximal environmental factors driving SES-related differences to inform interventions.

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Difficulty with emotion regulation is a transdiagnostic problem associated with a variety of psychological disorders. The biosocial model suggests that early biological vulnerability, including impulsivity, may potentiate across development by transacting with environmental risk factors leading to the development of emotional dysregulation. During transition from late childhood to early adolescence, family may be a prominent source of environmental influences. The primary aim of this study was to examine whether trait impulsivity and family conflict influence each other in a transactional fashion over the span of two years (from age 9-10 to 11-12) using data collected from 6112 children and their caregivers through the Adolescent Brain Cognitive Development study. In an exploratory manner, the study also aimed to test whether the transactional process was different among children with high, moderate, or low levels of emotion regulation difficulties at age 12-13. Results supported a cross lagged transaction between trait impulsivity and family conflict among this sample of children but a lack of reciprocal paths among those with higher levels of emotion dysregulation. These results provided partial support for the biosocial model.

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There is limited understanding on how polygenic scores derived from genome-wide association studies of adult and child psychopathology may uniquely predict childhood traits. The current study took a developmental approach to examine the interplay between adult-based and child-based polygenic scores with family processes in predicting trajectories of externalizing behaviors from late childhood to early adolescence among racially-ethnically diverse youth.

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People with early-life experiences of deprivation are more likely to develop psychotic symptoms. While the mechanisms of this relationship are poorly understood, research suggests a role of cortical development.

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Little research has examined early life risk for symptoms of cognitive disengagement syndrome (CDS) despite a well-established literature regarding co-occurring outcomes (e.g., attention-deficit/hyperactivity disorder). The current study estimated bivariate associations between early life risk factors and CDS in a large and representative sample of U.S. children. We conducted secondary analyses of baseline data from the Adolescent Brain Cognitive Development (ABCD) study (N = 8,096 children, 9-10 years old). Birthing parents reported early life risk factors on a developmental history questionnaire, including parental, prenatal, delivery and birth, and developmental milestone information. They also completed the Child Behavior Checklist, which includes a CDS subscale that was dichotomized to estimate the odds of elevated CDS symptoms (i.e., T-score > 70) in children related to risk indices. We observed significantly elevated odds of CDS related to parental risk factors (i.e., unplanned pregnancy, pregnancy awareness after 6 weeks, teenage parenthood), birthing parent illnesses in pregnancy (i.e., severe nausea, proteinuria, pre-eclampsia/toxemia, severe anemia, urinary tract infection), pregnancy complications (i.e., bleeding), prenatal substance exposures (i.e., prescription medication, tobacco, illicit drugs), delivery and birth risk factors (i.e., child blue at delivery, child not breathing, jaundice, incubation after delivery), and late motor and speech milestones in children. Several early-life risk factors were associated with elevated odds of CDS at ages 9-10 years; study design prevents the determination of causality. Further investigation is warranted regarding early life origins of CDS with priority given to risk indices that have upstream commonalities (i.e., that restrict fetal growth, nutrients, and oxygen).

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: Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent, heterogeneous neurodevelopmental disorder. : This study presents, for the first time, a comprehensive investigation of white matter microstructural differences between familial ADHD (ADHD-F) and non-familial ADHD (ADHD-NF) using advanced diffusion tensor imaging analyses in a large community-based sample. : Children with ADHD-F exhibited significantly greater volume in the right anterior thalamic radiations and the left inferior fronto-occipital fasciculus compared to controls, and greater volume in the left inferior longitudinal fasciculus relative to ADHD-NF. The ADHD-NF group showed reduced fractional anisotropy in the left inferior longitudinal fasciculus compared to the controls. In both the ADHD-F and ADHD-NF groups, a greater volume of anterior thalamic radiation significantly contributed to reduced ADHD symptoms. : Our findings suggest that white matter microstructural alterations along the frontal-thalamic pathways may play a critical role in hereditary factors among children with ADHD-F and significantly contribute to elevated inattentive and hyperactive/impulsive behaviors in the affected children.

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Adolescence is a period of growth in cognitive performance and functioning. Recently, data-driven measures of brain-age gap, which can index cognitive decline in older populations, have been utilized in adolescent data with mixed findings. Instead of using a data-driven approach, here we assess the maturation status of the brain functional landscape in early adolescence by directly comparing an individual’s resting-state functional connectivity (rsFC) to the canonical early-life and adulthood communities. Specifically, we hypothesized that the degree to which a youth’s connectome is better captured by adult networks compared to infant/toddler networks is predictive of their cognitive development. To test this hypothesis across individuals and longitudinally, we utilized the Adolescent Brain Cognitive Development (ABCD) Study at baseline (9-10 years; n = 6469) and 2-year-follow-up (Y2: 11-12 years; n = 5060). Adjusted for demographic factors, our anchored rsFC score (AFC) was associated with better task performance both across and within participants. AFC was related to age and aging across youth, and change in AFC statistically mediated the age-related change in task performance. In conclusion, we showed that a model-fitting-free index of the brain at rest that is anchored to both adult and baby connectivity landscapes predicts cognitive performance and development in youth.

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To estimate associations between sociodemographic factors and cardiometabolic risk factors among a demographically diverse sample of U.S. adolescents aged 10-14 years.

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Prospective prediction of mental health risk in adolescence can facilitate early preventive interventions. Here, using psychosocial questionnaires and neuroimaging measures from over 11,000 children in the Adolescent Brain and Cognitive Development Study, we trained neural network models to stratify general psychopathology risk. The model trained on current symptoms accurately predicted which participants would convert into the highest psychiatric illness risk group in the following year (area under the receiver operating characteristic curve = 0.84). The model trained solely on potential etiologies or disease mechanisms achieved an area under the receiver operating characteristic curve of 0.75 without relying on the child’s current symptom burden. Sleep disturbances emerged as the most influential predictor of high-risk status, surpassing adverse childhood experiences and family mental health history. Including neuroimaging measures did not enhance predictive performance. These findings suggest that artificial intelligence models trained on readily available psychosocial questionnaires can effectively predict future psychiatric risk while highlighting potential targets for intervention. This is a promising step toward artificial intelligence-based mental health screening for clinical decision support systems.

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Cyberbullying has been linked to various adverse psychological outcomes, but prospective associations with manic symptoms in early adolescents remain unexplored. We examined the prospective relationship between cyberbullying victimisation and manic symptoms in a diverse cohort of American children and adolescents.

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Exposure to trauma in childhood is associated with an increased risk for internalising symptoms. Alterations in pubertal development has been proposed as a potential mechanism underpinning this association. However, longitudinal studies, which are needed to examine pubertal development over time, are scarce. The goal of this pre-registered study was to examine how trauma exposure shapes the timing and tempo of pubertal development, and in turn contributes to risk for internalising symptoms in female youth.

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Food selectivity and mood problems and disorders are commonly described independently in individuals with autism spectrum disorder (ASD). However, little is known about the relationship between food selectivity and mood problems and disorders in ASD.

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Pubertal development is theorized to shape the brain’s response to socio-emotional information in the environment. Large-scale longitudinal studies, such as the Adolescent Brain Cognitive Development (ABCD) study, provide the opportunity to examine the association between pubertal maturation and within-person changes in neural activation to emotional stimuli over time. Leveraging ABCD data (n = 9648), the current study examines the coupling between parent-reported pubertal development and changes in youth’s brain response to emotional faces in an emotional n-back task (during functional magnetic resonance imaging) across two timepoints (2 years apart). Bivariate latent change score models were fit to regions of interest canonically involved in face processing (fusiform), emotional/motivational salience (amygdala, nucleus accumbens, orbitofrontal cortex [OFC]), and social cognition (temporoparietal junction [TPJ]) to determine the associations between baseline pubertal status and neural response, and rate of change in either variable across time. Results point to both concurrent and longitudinal associations between pubertal maturation and neural activation to emotional faces in regions involved in processing emotional and social information (amygdala, TPJ, accumbens, OFC) but not basic facial processing (fusiform). These findings highlight pubertal maturation as a potential mechanism for change in neural response to emotional information during the transition from childhood to adolescence.

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Emerging evidence suggests that ambient air pollution may affect the developing brain and contribute to an increased risk of mental health problems. However, most studies have focused on prenatal or early postnatal periods of exposure, with less attention given to the dynamic neurodevelopment period of early adolescence. Moving forward, it is necessary to consider additional periods of exposure, such as adolescence, and the biological mechanisms that may drive potential neurotoxicological effects. This project aimed to investigate whether 1-year exposure to ambient fine particulate matter (PM) and nitrogen dioxide (NO) at 9-10 years of age was associated with (1) concurrent prefrontal white matter connectivity at ages 9-10 years and (2) emotional health problems at ages 9-10 years as well as 1 year later. Lastly, we hypothesized that poor prefrontal white matter connectivity might be an intermediate marker (i.e., mediator) for the association between 1-year ambient exposure and mental health outcomes.

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Disparities in health or well-being experienced by minority groups can be difficult to study using the traditional exposure-outcome paradigm in causal inference, since potential outcomes in variables such as race or sexual minority status are challenging to interpret. Causal decomposition analysis addresses this gap by positing causal effects on disparities under interventions to other intervenable exposures that may play a mediating role in the disparity. While invoking weaker assumptions than causal mediation approaches, decomposition analyses are often conducted in observational settings and require uncheckable assumptions that eliminate unmeasured confounders. Leveraging the marginal sensitivity model, we develop a sensitivity analysis for weighted causal decomposition estimators and use the percentile bootstrap to construct valid confidence intervals for causal effects on disparities. We also propose a two-parameter reformulation that enhances interpretability and facilitates an intuitive understanding of the plausibility of unmeasured confounders and their effects. We illustrate our framework on a study examining the effect of parental support on disparities in suicidal ideation among sexual minority youth. We find that the effect is small and sensitive to unmeasured confounding, suggesting that further screening studies are needed to identify mitigating interventions in this vulnerable population.

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Air pollution affects human health and may disrupt brain maturation, including axon myelination, critical for efficient neural signaling. Here, we assess the impact of prenatal and current long-term particulate matter (PM) and nitrogen dioxide (NO) exposure on cortical T1w/T2w ratios – a proxy for myelin content – in school-age children from the Adolescent Brain Cognitive Development (ABCD) Study (United States; N = 2021) and NeuroSmog study (Poland; N = 577), using Siemens scanners. Across both samples, we found that NO and PM were not significantly associated with cortical T1w/T2w except for one association of PM with lower T1w/T2w in the precuneus in NeuroSmog. Superficially, ABCD Study analyses including data from all scanner types (Siemens, GE, Philips; N = 3089) revealed a negative association between NO₂ exposure and T1w/T2w ratios. However, this finding could be an artifact of between-site sociodemographic differences and large scanner-type-related measurement differences. While significant associations between air pollution and cortical myelin were largely absent, these findings do not rule out the possibility that air pollution affects cortical myelin during other exposure periods/stages of neurodevelopment. Future research should examine these relationships across diverse populations and developmental periods using unified analysis methods to better understand the potential neurotoxic effects of air pollution.

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This study investigates the development of mental rotation skills in male and female youth from a longitudinal study at ages 9/10 (baseline), 11/12 (Year 2), and 13/14 (Year 4) using a relatively novel task, the Little Man Task.

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The hippocampus is central in the pathophysiology of depression. Subregions of the hippocampus (head, body, tail) have been implicated in adult depression, though research examining depression and hippocampal subregions in youth has been limited. This study aimed to examine associations between preadolescent hippocampal subregions and depression risk as well as their interactions with factors associated with depression risk, including biological sex and socioeconomic status (SES). Hippocampal subregions were extracted from the Adolescent Brain and Cognitive Development Study baseline sample (N = 10,469, ages 9-10 years). Depression risk factors included maternal lifetime depression, child depressive symptoms, and child internalizing and externalizing symptoms. Maternal depression was measured through the Family History Questionnaire, and child symptoms were measured through the Child Behavioral Checklist. Results identified associations between hippocampal volumes and future increases in internalizing symptoms (N = 9738). Further, associations between hippocampal subregions and depression risk were moderated by biological sex and SES: males, but not females, with maternal depression exhibited lower hippocampal tail volumes (N = 9826), and for preadolescents with low, but not high, SES, greater hippocampal head volumes predicted increased internalizing symptoms at baseline (N = 10,294) and at the 24-month follow up (N = 7069-7086). Together, this study demonstrates the importance of hippocampal subregions within preadolescent depression risk and identifies subgroups, including preadolescent males and those with low SES, that may be at particular risk.

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To determine the prospective associations between sleep disturbance and binge-eating disorder and behaviors in a national sample of early adolescents in the United States (US).

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Low socioeconomic status (SES) during childhood is associated with higher levels of youth psychopathology. However, limited longitudinal work has examined the role of both household and neighborhood SES in shaping mental health trajectories over time using population-based data. The goal of the present study was to characterize associations between SES and changes in mental health problems during early adolescence.

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This report provides a primer to delay discounting data in the context of the Adolescent Brain Cognitive Development (ABCD) Study. Delay discounting describes the tendency for organisms to devalue temporally constrained outcomes. This decision-making framework has garnered attention from multiple fields for its association with various behavioral health conditions like substance use disorder. Importantly, the literature on delay discounting describes many approaches to analyzing and interpreting discounting data. To be most beneficial to the broader scientific audience, consistency and reproducibility in how delay discounting data are operationalized, analyzed, and interpreted is key. We describe relevant data analysis methods for use with the ABCD Study, a large-cohort longitudinal study ( = 11,878) examining delay discounting among youth respondents across child and adolescent development. Particular attention is given to data collected from children and younger populations given their relevance to ABCD research and potential merit for unique analytic considerations (e.g., higher rates of atypical responding). We first provide a background on the broad theoretical and conceptual aspects of discounting research. We then review discounting assessment, describing conventional titration tasks and the more novel algorithm-based approaches to generating descriptive metrics. We conclude with recommendations for best practice modeling, data handling and exclusions based on nonsystematic data, and ensuing interpretations. Analytic pipelines and coding are provided for investigator use. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

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This study aimed to assess the independent and joint associations of genomic and exposomic liabilities for schizophrenia with distressing psychotic experiences (PEs) and their persistence in early adolescence. The Adolescent Brain and Cognitive Development Study data from children with European ancestry were used (N = 5122). The primary outcome was past-month distressing PEs at the 3-year follow-up. Secondary outcomes were distressing PEs at varying cutoffs of persistence. Multilevel logistic regression models were used to test the associations of binary modes (>75th percentile) of polygenic risk score for schizophrenia (PRS-SCZ) and exposome score for schizophrenia (ES-SCZ) on the outcomes. Relative excess risk due to interaction (RERI) calculation indicated additive interaction. When analyzed independently, PRS-SCZ was not significantly associated with past-month distressing PEs but with lifetime (OR 1.29 [95% CI 1.08, 1.53]) and repeating distressing PEs ≥2 waves (OR 1.34 [95% CI 1.08, 1.65]); whereas, ES-SCZ was consistently associated with all outcomes, with increasing strength of association as a function of PEs persistence (one wave: OR 2.77 [95% CI 2.31, 3.31]; two waves: OR 3.16 [95% CI 2.54, 3.93]; three waves: OR 3.93 [95% CI 2.86, 5.40]; four waves: OR 3.65 [95% CI 2.34, 5.70]). When considered jointly, ES-SCZ and PRS-SCZ did not additively interact to predict past-month distressing PEs but showed significant additive interactions for lifetime (RERI = 1.26 [95%CI 0.14, 2.38]) and repeating distressing PEs ≥2 waves (RERI = 1.79 [95%CI 0.35, 3.23]). Genomic and exposomic liabilities for schizophrenia were independently and jointly associated with distressing PEs and their persistence in early adolescence.

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Generalized anxiety disorder (GAD) frequently emerges during childhood or adolescence, yet, few studies have examined functional connectivity differences in youth GAD. Functional MRI studies of adult GAD have implicated multiple brain regions; however, frequent examination of individual brain seed regions and/or networks has limited a holistic view of GAD-associated differences. The current study therefore used resting-state fMRI data from the Adolescent Brain Cognitive Development study to investigate connectivity in youth with GAD across multiple cortical networks and subcortical regions implicated in adult GAD, considering diagnosis changes across two assessment periods.

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Results of the impact of reading books and viewing television on neurodevelopment have been mixed, without definitive evaluation to date. Using data from 11,875 US adolescents in the Adolescent Brain and Cognitive Development (ABCD) study, we investigated the associations between reading and television viewing on brain morphology and neurocognitive performance. After quality control, 8,125 participants’ MRI scans and cognitive tests were analyzed in relation to their reading and TV habits. Greater reading time was associated with higher cognitive performance and regionally-selective increases in cortical area, while greater TV viewing had a much smaller association with lower cognitive performance and decreased cortical area. Regionally, areas of spatial overlap in associations included the lateral temporal, inferior parietal, and inferior frontal lobes, while significant associations in the ventral and inferior temporal cortex and cingulate cortex were unique to reading habits. These relationships persisted after adjusting for demographics, socioeconomic factors, genetic ancestry, and imaging factors. The magnitude of reading associations exceeded those of TV viewing and was similar to established contributions of parental income and education on neurodevelopment. This study provides a comprehensive evaluation of how these behaviors correlate with early adolescent brain development across a large diverse population.

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Today’s advancements in neuroimaging have been pivotal in enhancing our understanding of brain development and function using various MRI techniques. This study utilizes images from T1-weighted imaging and diffusion-weighted imaging to identify gray matter and white matter coherent growth patterns within 2 years from 9-10-year-old participants in the Adolescent Brain Cognitive Development (ABCD) Study. The motivation behind this investigation lies in the need to comprehend the intricate processes of brain development during adolescence, a critical period characterized by significant cognitive maturation and behavioral change. While traditional methods like canonical correlation analysis (CCA) capture the linear interactions of brain regions, a deep canonical correlation analysis with an autoencoder (DCCAE) nonlinearly extracts brain patterns. The study involves a comparative analysis of changes in gray and white matter over two years, exploring their interrelation based on correlation scores, extracting significant features using both CCA and DCCAE methodologies, and finding an association between the extracted features with cognition and the Child Behavior Checklist. The results show that both CCA and DCCAE components identified similar brain regions associated with cognition and behavior, indicating that brain growth patterns over this two-year period are linear. The variance explained by CCA and DCCAE components for cognition and behavior suggests that brain growth patterns better account for cognitive maturation compared to behavioral changes. This research advances our understanding of neuroimaging analysis and provides valuable insights into the nuanced dynamics of brain development during adolescence.

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This study aimed to examine prospective associations between screen time and manic symptoms in early adolescents, and the extent to which problematic screen use (characterized by addiction, conflict, relapse, and withdrawal) mediates the association.

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Discrimination increases the risk for adverse mental health in minority populations, with studies showing elevated rates of obsessive-compulsive disorder (OCD) in Black adults facing racial discrimination. Yet, there is a lack of longitudinal research on the different forms of discrimination in relation to OCD risk in early adolescence. The objective of this study was to examine the prospective associations between multiple forms of discrimination and OCD in a national sample of U.S. early adolescents.

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Childhood maltreatment stands out as a pivotal risk factor for depression, with gene-by-environment interaction serving as a crucial mechanism. Here we perform genome-wide interaction analyzes of childhood maltreatment in the UK Biobank, integrating methylation evidence through colocalization analysis and identifying associated brain structure abnormalities from childhood to adulthood. A genome-wide significant genomic region interacting with childhood maltreatment is identified at 8p11.21 (IDO2 rs7846217, P = 2.02e-08), implicating the tryptophan-kynurenine pathway. Colocalization analysis reveals that IDO2 rs11777027, rs2340953 and rs28631334 are associated with depression in individuals exposed to childhood maltreatment and colocalize with methylation signals in both blood and brain for IDO2. These interactions affect cortical thickness of the left supramarginal gyrus in children (P = 9.72e-04) and adults (P = 1.34e-04), as well as cortical volume in the right angular gyrus in children (P = 1.02e-04). Furthermore, the interactions significantly predict new-onset depression at a 2-year follow-up in children. Stunted increase in cortical thickness of the left middle-anterior cingulate gyrus and sulcus significantly mediates the interaction between childhood maltreatment and IDO2 on childhood depression. These interactions also moderate antidepressant treatment efficacy at 4-6 weeks.

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Prenatal alcohol and tobacco exposure affects child brain development. Less is known about how neighborhood environment (built, institutional, and social) may be associated with structural brain development and whether prenatal exposure to alcohol or tobacco may modify this relationship. The current study aimed to examine whether neighborhood environment is associated with brain volume at age 9-11, and whether prenatal exposure to alcohol or tobacco modifies this relationship. Baseline data from Adolescent Brain and Cognitive Development (ABCD) study was analyzed ( = 7,887). Neighborhood environment was characterized by 10 variables from the linked external dataset. Prenatal alcohol and tobacco exposures were dichotomized based on the developmental history questionnaire. Bilateral volumes of three regions of interests (hippocampal, parahippocampal, and entorhinal) were examined as outcomes. High residential area deprivation was associated with smaller right hippocampal volume. Prenatal alcohol exposure was associated with larger volume in left parahippocampal and hippocampal regions, while prenatal tobacco exposure was associated with smaller volumes in bilateral parahippocampal, right entorhinal, and right hippocampal regions. In children without prenatal tobacco exposure, high residential area deprivation was associated with smaller right hippocampal volumes. In contrast, neighborhood environment was not significantly associated with brain volumes in children with prenatal tobacco exposure. In summary, neighborhood environment plays a role in child brain development. This relationship may differ by prenatal tobacco exposure. Future studies on prenatal tobacco exposure may need to consider how postnatal neighborhood environment interacts with the teratogenic effect.

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Recent research has demonstrated that domains of social determinants of health (SDOH) (e.g. air pollution and social context) are associated with psychosis. However, SDOHs have often been studied in isolation. This study investigated distinct exposure profiles, estimated their associations with persistent distressing psychotic-like experiences (PLE), and evaluated whether involvement in physical activity partially explains this association.

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Schizophrenia is associated with abnormalities in neurodevelopmental processes. Furthermore, dysfunctional neural circuits involved in reward processing may be linked to the development of symptoms in schizophrenia and are predictive of long-term functional outcome. It is however unknown whether neural signatures of reward anticipation are detectable in children with high psychotic-like experiences.

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Research has rarely examined biobehavioral factors in mitigating substance use (SU) risks associated with discrimination among racially and ethnically minoritized youth. This study investigated sleep duration as a potential moderator of the association between multiple forms of discrimination based on race and ethnicity, sexual orientation, and weight (i.e., multiple discrimination) and subsequent SU intention in this population.

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Cannabis is one of the most widely used drugs in early adolescence, a crucial time for development. Cannabinoids within the cannabis plant (e.g., delta-9-tetrahydrocannabinol [THC], and cannabidiol [CBD]) are suggested to have a range of health implications. These may differ by sex, given sex differences in the endocannabinoid system (ECS). Yet, how aspects of mental and physical health are related to cannabis use as measured by hair concentrations, both within early adolescence and across sexes, is so far inconclusive.

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The Adolescent Brain Cognitive Development® (ABCD) Study provides a unique opportunity to investigate developmental processes in a large, diverse cohort of youths, aged approximately 9-10 at baseline and assessed annually for 10 years. Given the size and complexity of the ABCD Study, researchers analyzing its data will encounter a myriad of methodological and analytical considerations. This review provides an examination of key concepts and techniques related to longitudinal analyses of the ABCD Study data, including: (1) characterization of the factors associated with variation in developmental trajectories; (2) assessment of how level and timing of exposures may impact subsequent development; (3) quantification of how variation in developmental domains may be associated with outcomes, including mediation models and reciprocal relationships. We emphasize the importance of selecting appropriate statistical models to address these research questions. By presenting the advantages and potential challenges of longitudinal analyses in the ABCD Study, this review seeks to equip researchers with foundational knowledge and tools to make informed decisions as they navigate and effectively analyze and interpret the multi-dimensional longitudinal data currently available.

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This study aimed to identify the independent associations of positive childhood experiences (PCEs) on brain health (cognitive function, behavioral and emotional problems) among early adolescents.

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The built physical and social environments are critical drivers of child neural and cognitive development. This study aimed to identify the factor structure and correlates of 29 environmental, education, and socioeconomic indicators of neighborhood resources as measured by the Child Opportunity Index 2.0 (COI 2.0) in a sample of youths aged 9-10 enrolled in the Adolescent Brain Cognitive Development (ABCD) Study. This study used the baseline data of the ABCD Study ( = 9767, ages 9-10). We used structural equation modeling to investigate the factor structure of neighborhood variables (e.g., indicators of neighborhood quality including access to early child education, health insurance, walkability). We externally validated these factors with measures of psychopathology, impulsivity, and behavioral activation and inhibition. Exploratory factor analyses identified four factors: Neighborhood Enrichment, Socioeconomic Attainment, Child Education, and Poverty Level. Socioeconomic Attainment and Child Education were associated with overall reduced impulsivity and the behavioral activation system, whereas increased Poverty Level was associated with increased externalizing symptoms, an increased behavioral activation system, and increased aspects of impulsivity. Distinct dimensions of neighborhood opportunity were differentially associated with aspects of psychopathology, impulsivity, and behavioral approach, suggesting that neighborhood opportunity may have a unique impact on neurodevelopment and cognition. This study can help to inform future public health efforts and policy about improving built and natural environmental structures that may aid in supporting emotional development and downstream behaviors.

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