Research Publications

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Population neuroscience datasets provide an opportunity for researchers to estimate reproducible effect sizes for brain-behavior associations because of their large sample sizes. However, these datasets undergo strict quality control to mitigate sources of noise, such as head motion. This practice often excludes a disproportionate number of minoritized individuals.

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To assess whether specific parent media practices are associated with the consumption of R-rated (restricted) movies and mature-rated video game use in early adolescents.

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Laboratory studies show brain maturation involves synaptic pruning and cognitive development. Human studies suggest links between early cognitive performance and later mental health, but inconsistencies remain. It is unclear if specific brain regions mediate this relationship, and the molecular underpinnings are not well understood. Here, our longitudinal analyses in both the Adolescent Brain Cognitive Development and IMAGEN cohorts establish inverted U-shaped relationships between baseline executive function and subsequent symptom trajectories in the high-symptom individuals, whose externalizing (n = 963) or internalizing (n = 1762) symptoms exceed a clinical threshold at any point during the follow-up period, but not in the control group (n = 4291). Volumetric changes in the left lateral occipital cortex (LOC) mediated the relationship with externalizing symptoms (outwardly directed behaviors such as aggression), while changes in the right LOC and pars triangularis mediated the relationship with internalizing symptoms (inwardly directed emotional problems such as anxiety). Transcriptomic and genomic findings highlighted synaptic biology and particularly the gene ADCY1, which is implicated in synaptic pruning, as underlying both moderate executive function and its associated brain mediators. Notably, preadolescent cognitive performance predicts late-onset externalizing symptoms and remitting internalizing symptoms with high accuracies (area under the curve: 0.87 and 0.79). Our findings highlight the predictive value of cognitive performance for adolescent mental health trajectories, and indicate how this is mediated by specific brain regions, and underpinned by particular molecular pathways.

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Vaping has grown in prevalence among youth populations over the past decade and has been promoted as a safer alternative to smoking despite the potential health risks. There is a dearth of research which has examined the timing of onset of vaping from childhood into adolescence. Childhood predictors vaping onset have also been understudied. This study sought to address gaps in the literature by examining timing of vaping onset, relevance of childhood levels of dual systems model constructs (sensation-seeking, impulse control) for predicting differential onset, and the potential that childhood predictors may vary in the magnitude of their effects depending on age.

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Sports participation in childhood is known to benefit physical health, but its impact on cognitive development, particularly comparing open-skill and closed-skill sports, is less understood.

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Resting-state functional magnetic resonance imaging (rs-fMRI) is a noninvasive technique pivotal for understanding human neural mechanisms of intricate cognitive processes. Most rs-fMRI studies compute a single static functional connectivity matrix across brain regions of interest, or dynamic functional connectivity matrices with a sliding window approach. These approaches are at risk of oversimplifying brain dynamics and lack proper consideration of the goal at hand. While deep learning has gained substantial popularity for modeling complex relational data, its application to uncovering the spatiotemporal dynamics of the brain is still limited. In this study we propose a novel interpretable deep learning framework that learns goal-specific functional connectivity matrix directly from time series and employs a specialized graph neural network for the final classification. Our model, DSAM, leverages temporal causal convolutional networks to capture the temporal dynamics in both low- and high-level feature representations, a temporal attention unit to identify important time points, a self-attention unit to construct the goal-specific connectivity matrix, and a novel variant of graph neural network to capture the spatial dynamics for downstream classification. To validate our approach, we conducted experiments on the Human Connectome Project dataset with 1075 samples to build and interpret the model for the classification of sex group, and the Adolescent Brain Cognitive Development Dataset with 8520 samples for independent testing. Compared our proposed framework with other state-of-art models, results suggested this novel approach goes beyond the assumption of a fixed connectivity matrix, and provides evidence of goal-specific brain connectivity patterns, which opens up potential to gain deeper insights into how the human brain adapts its functional connectivity specific to the task at hand. Our implementation can be found on https://github.com/bishalth01/DSAM.

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Depression is common, burdensome, and is frequently first diagnosed in adolescents. The popular Adolescent Brain Cognitive Development dataset (ABCD) provides an attractive opportunity to research depression in adolescents. The only continuous measure of depression, as defined by DSM-5, in ABCD is the Child Behavior Checklist’s DSM-5-Oriented Affective Problems scale (CBCL-Aff). We validated CBCL-Aff in the ABCD data and confirmed our results on two independent datasets: the Healthy Brain Network (HBN) and the Brazilian High Risk Cohort Study (BHRC).

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This study aimed to investigate associations between sociodemographic factors and dietary intake among a diverse population of early adolescents ages 10-13 years in the United States.

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Parental monitoring is a robust family-level predictor of youth well-being. Identification of variations by gender and/or race/ethnicity in parental monitoring has important implications for tailoring parenting practices. However, valid comparisons can only be conducted if cross-subpopulation measurement equivalence is established. Although measurement equivalence testing is widely used, it rarely (a) assesses intersectional identity (i.e., identity reflecting multiple factors such as race/ethnicity and gender) or (b) involves generating scores adjusted for nonequivalence. This is the first known study to do both with a parental monitoring measure. Measurement equivalence by sex (proxy for gender), race/ethnicity, and intersectional identity (sex by race/ethnicity) was assessed in the five-item Parental Monitoring Questionnaire administered to middle-school-aged Black, Latinx, and White girls and boys. Data were drawn from the second follow-up of the Adolescent Brain Cognitive Development Study ( = 9,082; 47.5% female, 52.5% male; 15.5% Black, 22.9% Latinx, 61.6% White). Moderated nonlinear factor analysis was used to identify group differences in item-level (intercepts and loadings) and factor-level (mean and variance) parameter estimates for a latent parental monitoring variable and subsequently to generate factor scores accounting for measurement nonequivalence. Intercepts or loadings for four items differed by sex, race/ethnicity, and/or intersectional identity. Factor mean and variance differed by race/ethnicity. Comparisons across the six groups using adjusted (factor) scores differed substantially from comparisons using unadjusted scores, underscoring the impact of systematic measurement bias on the valid assessment of parental monitoring in girls and boys who identify with these racial/ethnic groups. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

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Perinatal and childhood periods are sensitive windows of development wherein adversity exposure can result in disadvantageous outcomes. Data-driven dimensional approaches that appreciate the co-occurrence of adversities allow for extending beyond specificity (individual adversities) and cumulative risk (non-specific summation of adversities) approaches to understand how the type and timing of adversities affect outcomes.

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To identify and characterize how race and ethnicity influence the relationship between autism and weight status, across all categories of weight from underweight to severe obesity.

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While the brain continues to develop during adolescence, such development may depend on sex-at-birth. However, the elucidation of such differences may be hindered by analytical decisions (e.g., covariate selection to address brain-size differences) and the typical reporting of cross-sectional data. To further evaluate adolescent cortical development, we analyzed data from the Adolescent Brain Cognitive Development Study, whose cohort of 11,000+ youth participants with biannual neuroimaging data collection can facilitate understanding neuroanatomical change during a critical developmental window. Doubly considering individual differences in the context of group-level effects, we analyzed regional changes in cortical thickness, sulcal depth, surface area, and volume between two timepoints (∼2 years apart) in 9- to 12-year-olds assigned male or female sex-at-birth. First, we conducted linear mixed-effects models to gauge how controlling for intracranial volume, whole-brain volume (WBV), or a summary metric (e.g., mean cortical thickness) influenced interpretations of age-dependent cortical change. Next, we evaluated the relative changes in thickness and surface area as a function of sex-at-birth and age. Here, we showed that WBV (thickness, sulcal depth, volume) and total cortical surface area were more optimal covariates; controlling for different covariates would have substantially altered our interpretations of overall and sex-at-birth-specific neuroanatomical development. Further, we provided evidence to suggest that aggregate change in how cortical thickness is changing relative to surface area is generally comparable across those assigned male or female sex-at-birth, with corresponding change happening at slightly older ages in those assigned male sex-at-birth. Overall, these results help elucidate neuroanatomical developmental trajectories in early adolescence. While most of our brain’s development happens early in life, much of it still happens in adolescence. Because many factors can alter those developmental trajectories, it is important to evaluate the shape/timing of those trajectories (i.e., what generally constitutes typical brain development). Here, we showed that our understanding of those trajectories can be affected by how we choose to analyze them. First, we showed that the way researchers address differences in brain size affects how we interpret regional variation in brain change over time. Further, we showed that it is important to consider how similar patterns of development may simply be happening at different ages in different groups. These results support a relatively novel way of analyzing adolescent brain development.

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The striatum, a core brain structure relevant for schizophrenia, exhibits heterogeneous volumetric changes in this illness. Due to this heterogeneity, its role in the risk of developing schizophrenia following exposure to environmental stress remains poorly understood. Using the putamen (a subnucleus of the striatum) as an indicator for convergent genetic risk of schizophrenia, 63 unaffected first-degree relatives of patients (22.08 ± 4.80 years) with schizophrenia (UFR-SZ) were stratified into two groups. Compared with healthy controls (HC; n = 59), voxel-based and brain-wide volumetric changes and their associations with stressful life events (SLE) were tested. These stratified associations were validated using two large population-based cohorts (the ABCD study; n = 1680, 11.92 ± 0.62 years; and UK Biobank, n = 20547, 55.38 ± 7.43 years). Transcriptomic analysis of brain tissues was used to identify the biological processes associated with the brain mediation effects on the SLE-psychosis relationship. The stratified UFR-SZ subgroup with smaller right putamen had a smaller volume in the left caudate when compared to HC; this caudate volume was associated with both a higher level of SLE and more psychotic symptoms. This caudate-SLE association was replicated in two independent large-scale cohorts, when individuals were stratified by both a higher polygenic burden for schizophrenia and smaller right putamen. In UFR-SZ, the caudate cluster mediated the relationship between SLE and more psychotic symptoms. This mediation was associated with the genes enriched in both glutamatergic synapses and response to oxidative stress. The stratified association between the striatum and stress highlights the differential vulnerability to stress, contributing to the complexity of the gene-by-environment etiology of schizophrenia.

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Societal stressors place a tremendous burden on individuals who identify with a sexual minority identity. While minority stress experienced by racial/ethnic minority groups has been linked to accelerated aging, this link has yet to be examined among sexual minority youth. This study explores whether sexual minority youth who indicate experiencing stress at home or school (Minority Stress) due to their identity show evidence of accelerated aging (pubertal status or tempo) compared to those who do not report such experiences (No Minority Stress).

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Parental depression is associated with offspring depression and sleep problems are prospectively associated with the development of depression. However, little work has examined sleep problems in the offspring of depressed parents and whether these problems partially account for the association between parent and offspring depression. This longitudinal study examined the indirect effect of sleep problems on the association between parent psychopathology and offspring depression in a sample of 10,953 10 to 12-year-old children participating in the Adolescent Brain and Cognitive Development (ABCD) study. Controlling for age, sex, and other forms of parent psychopathology, we found significant indirect effects of parent to offspring depression through parent and youth reports of youth insomnia and hypersomnia. We also found indirect effects of parent history of anxiety and drug use problems to offspring depression through insomnia, and indirect effects of parent history of anxiety, drug use problems, and alcohol use problems to offspring depression through hypersomnia. Our findings show that sleep may be a mechanism of the transmission of parent depression, anxiety, drug use problems, and alcohol use problems to offspring depression. Mitigating sleep problems represents a potential avenue for preventative interventions in youth with a heightened susceptibility to depression.

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Sexual minority adolescents experience puberty earlier than their heterosexual peers. Early puberty is an indicator of premature aging and can be partly driven by chronic stress linked to discrimination. Nonetheless, the neural, cognitive, and social development linked to puberty enables adolescents to explore and understand their sexual identities. For sexual minority youth, does the stress from identity-based discrimination make them more likely to experience advanced pubertal timing, or is early pubertal timing the impetus for their self-identification with a sexual minority identity? To answer this research question, the present study leveraged longitudinal and national data to test the temporal ordering between sexual minority self-identification and pubertal timing among one sample of 7,818 unrelated adolescents and another sample of 4,050 adolescent siblings nested across 1,989 households in the United States. Across both samples, results illustrated significant bidirectional relations between pubertal timing and sexual minority self-identification. Adolescents who self-identified as sexual minorities experienced more advanced pubertal timing 1 year later, and adolescents who experienced more advanced pubertal timing were more likely to identify as sexual minorities 1 year later. While the longitudinal link between pubertal timing and later sexual minority self-identification may be a normal developmental process, the longitudinal link between sexual minority self-identification and subsequent advanced pubertal timing may be attributable to heterosexist stigma. The present findings underscore the need to mitigate prejudice so that all adolescents have the freedom to explore their identities without risks to their development. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

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Although racially and ethnically minoritized youth are more likely to experience adverse effects of substance use, and substance use before age 14 is strongly associated with an elevated risk of later substance use disorders, there is limited research identifying risk factors for early substance use. The study examined the role of experiencing ethnic discrimination from teachers, other adults outside of school, and other students in predicting early substance use (measured with hair toxicology reports).

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Previous studies suggest school ethnic density is associated with less internalizing problems in Black and Latine adolescents in high school. Here, we assessed associations between school ethnic density and internalizing, externalizing, and thought problems in Black, Latine, and White pre-adolescent children (mean age=9.9 years) in elementary school. We additionally examined if associations differed by family generational status.

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Attention deficit hyperactivity disorder (ADHD), a prevalent neurodevelopmental disorder influenced by both genetic and environmental factors, remains poorly understood regarding how its polygenic risk score (PRS) impacts functional networks and symptomology. This study capitalized on data from 11,430 children in the Adolescent Brain Cognitive Development study to explore the interplay between PRS, brain function, and behavioral problems, along with their interactive effects. The results showed that children with a higher PRS exhibited more severe attention deficits and rule-breaking problems, and experienced sleep disturbances, particularly in initiating and maintaining sleep. We also identified the central executive network, default mode network, and sensory-motor network as the functional networks most associated with PRS and symptoms in ADHD cases, with potential mediating roles. Particularly, the impact of PRS was enhanced in children experiencing heightened sleep disturbances, emphasizing the need for early intervention in sleep issues to potentially mitigate subsequent ADHD symptoms.

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Little data exist to guide suicide assessment protocols in preadolescent youth. Using the Adolescent Brain Cognitive Development (ABCD) data (N = 10,010) at baseline (ages 9-10) and 24-month follow-up (ages 11-12), this report investigates informant agreement/disagreement in caregiver- and youth- reports of suicidal ideation and their associations with youth sex assigned at birth and symptomatology across preadolescence. Using the Kiddie Schedule for Affective Disorders and Schizophrenia (K-SADS) at both timepoints, four informant discrepancy groups were created from caregiver- and youth- reported suicidal ideation: (1) Concordant No; (2) Concordant Yes; (3) Discordant Caregiver Yes, Youth No; (4) Discordant Caregiver No, Youth Yes. Internalizing and externalizing symptoms were measured at the 24-month follow-up using the caregiver-report Child Behavior Checklist and the youth-report ABCD Brief Problem Monitor. Results indicated low-to-fair caregiver-youth agreement for youth suicidal ideation across preadolescence. Suicidal ideation reported by youth, but not caregivers, demonstrated a shift in prevalence at the follow-up, with females surpassing males in self-reported endorsements. Finally, informant groups at both time points were associated with caregiver- and youth-reported youth symptomatology at the 24-month follow-up, and associations varied by reporter. Findings demonstrate the importance of leveraging both caregiver and youth reports to assess preadolescent suicidal ideation and highlight the clinical utility of informant discrepancies in assessing suicide risk. The accurate assessment of suicidal ideation in preadolescents is essential to curb the increasing rates of preadolescent suicide and identify at-risk youth for interventions prior to even larger uptick of suicide in adolescence.

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Addressing the disproportionate use of school detentions and suspensions among Black youth is crucial for reducing educational and health disparities across the lifespan. Yet, few studies have explored external factors beyond school or individual characteristics as potential contributors to school discipline disparities, such as state-level racial bias and neighborhood opportunity.

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Accurate prediction of the brain’s task reactivity from resting-state functional magnetic resonance imaging (fMRI) data remains a significant challenge in neuroscience. Traditional statistical approaches often fail to capture the complex, nonlinear spatiotemporal patterns of brain function. This study introduces SwiFUN (Swin fMRI UNet Transformer), a novel deep learning framework designed to predict 3D task activation maps directly from resting-state fMRI scans. SwiFUN leverages advanced techniques such as shifted window-based self-attention, which helps to understand complex patterns by focusing on varying parts of the data sequentially, and a contrastive learning strategy to better capture individual differences among subjects. When applied to predicting emotion-related task activation in adults (UK Biobank, n = 7,038) and children (ABCD, n = 4,944), SwiFUN consistently achieved higher overall prediction accuracy than existing methods across all contrasts; it demonstrated an improvement of up to 27% for the FACES-PLACES contrast in ABCD data. The resulting task activation maps revealed individual differences across cortical regions associated with sex, age, and depressive symptoms. This scalable, transformer-based approach potentially reduces the need for task-based fMRI in clinical settings, marking a promising direction for future neuroscience and clinical research that enhances our ability to understand and predict brain function.

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Although children with marginalized sociodemographic characteristics are exposed to increased health risk and disparities, there is a paucity of population-based research on health status of children occupying multiple social marginalities. The present study investigated implications of children’s intersectional sociodemographic characteristics on health risk indicators. In this longitudinal cohort study, we used longitudinal data from the ongoing Adolescent Brain Cognitive Development study. The study used a population-based sample of 9- to 10-year-old children attending private and public schools in 21 U.S.-based study sites between 2016 and 2018. In the present analytic sample of 9,854 children and adolescents, eight social strata groups were identified based on children’s ethnicity/race, assigned sex at birth, and sexual orientation. Five health risk indicators were included in the study: depressed mood, suicidal ideation, self-injurious behaviors, alcohol sipping, and overweight status. Results showed that compared to White heterosexual boys (referent group), sexual minority (SM) children including White and ethnic/racial minority, boys and girls were at greater risk of having depressed mood, self-injurious behavior, and suicidal ideation. White SM children, including boys and girls, were also at greater risk of sipping alcohol, whereas heterosexual ethnically/racially minoritized children, including boys and girls, were at less risk of sipping alcohol. Although no change was found in overweight status over time across social groups, children with marginalized social categories were more likely to report being overweight. Intersectional marginality accounted for an increased health risk and disparities among children from marginalized sociodemographic background. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

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Subthreshold depression refers to a condition involving clinically significant depressive symptoms that fall short of meeting the diagnostic criteria for major depressive disorder (MDD). Identifying risk and protective factors associated with the progression of subthreshold depression in early life is essential for timely prevention. However, there is limited research on this topic among early adolescents.

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The association between family environment factors, such as family conflict and parental monitoring, and attention-deficit/hyperactivity disorder (ADHD) behaviors is well established. However, it is unclear whether ADHD behaviors precede changes in familial functioning, whether certain family dynamics increase ADHD behaviors, or if the association is reciprocal.

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Early life stress (ELS) increases the risk of substance use disorder (SUD) in adulthood. The pathway from ELS to SUD is hypothesized to be influenced by sex. We examine the impact of ELS on adolescent first substance use, a common precursor to adult SUDs, and test for sex differences in the relationship between ELS and risk of first use of alcohol, nicotine, and marijuana.

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To describe patterns of social media use, including underage (under 13 years) use and sex differences, in a diverse, national sample of early adolescents in the U.S.

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Among a large sample of youth (9-10 years old at baseline) from the Adolescent Brain Cognitive Development (ABCD) Study® (n = 11,661) we modeled trajectories of psychopathology over three years and associated risk and protective factors. Growth mixture modeling characterized latent classes with distinct psychopathology trajectories. Results indicated four different internalizing trajectories: a high-decreasing class, a moderate-decreasing class, a moderate-increasing class, and a low-stable class. There were also four externalizing trajectories: a moderate-decreasing class, a high-decreasing class, a moderate-increasing class, and a low-decreasing class. We used parallel process growth analysis to examine the co-development of internalizing and externalizing symptoms and characterized five trajectory classes with distinct patterns of co-development. These classes were differentially associated with negative life events, neighborhood safety, and parental acceptance. Together, the findings characterize general developmental patterns of psychopathology, quantify the proportion of youth that follow each pattern, and identify key predictors that discriminate these patterns.

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The aim of this study was to determine whether advanced puberty at age 9 to 10 years, relative to that in same-aged peers, predicts current and/or new-onset self-injurious thoughts and behaviors (SITBs). New predictors of SITBs in preadolescence are urgently needed to address this escalating public health crisis of youth self-harm and suicidality.

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Specific modifiable factors (e.g., screen time [ST], sleep duration, physical activity, or social connections) are targets for reducing depression risk in adults. However, research in adolescents lacks causal inference implementations, as prevention trials are costly and often prohibitive. Emulating randomized trials with observational data enables inference regarding hypothetical interventions on modifiable factors that reduce depression risk, in general and at-risk populations.

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Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder in childhood, characterized by symptoms of inattention, hyperactivity, and impulsivity. Impaired inhibitory control is observed in the majority of individuals with ADHD. Understanding the relationship between inhibitory control and the developmental trajectory of ADHD is essential for informing clinical prognosis and guiding early interventions.

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Suicide attempts and deaths among children are increasing in the United States, yet suicide in this preadolescent population remains understudied. A clearer understanding of which youth experience early onset of suicidal behavior is crucial for predicting risk and identifying youth best suited to early intervention. This paper examines how intersectional marginalized identities may predict the onset of suicidal behaviors among preadolescent youth.

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Adverse childhood experiences (ACEs) may increase the risk for adolescent sleep disturbances, though the impact of race, ethnicity, and socioeconomic status (SES) remains unclear.

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The brain is always intrinsically active, using energy at high rates while cycling through global functional modes. Awake brain modes are tied to corresponding behavioural states. During goal-directed behaviour, the brain enters an action-mode of function. In the action-mode, arousal is heightened, attention is focused externally and action plans are created, converted to goal-directed movements and continuously updated on the basis of relevant feedback, such as pain. Here, we synthesize classical and recent human and animal evidence that the action-mode of the brain is created and maintained by an action-mode network (AMN), which we had previously identified and named the cingulo-opercular network on the basis of its anatomy. We discuss how rather than continuing to name this network anatomically, annotating it functionally as controlling the action-mode of the brain increases its distinctiveness from spatially adjacent networks and accounts for the large variety of the associated functions of an AMN, such as increasing arousal, processing of instructional cues, task general initiation transients, sustained goal maintenance, action planning, sympathetic drive for controlling physiology and internal organs (connectivity to adrenal medulla), and action-relevant bottom-up signals such as physical pain, errors and viscerosensation. In the functional mode continuum of the awake brain, the AMN-generated action-mode sits opposite the default-mode for self-referential, emotional and memory processing, with the default-mode network and AMN counterbalancing each other as yin and yang.

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School shooting events and lockdowns have increased in the United States, raising concerns about their impact on youth mental health.

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Analysis of resting state fMRI (rs-fMRI) typically excludes images substantially degraded by subject motion. However, data quality, including degree of motion, relates to a broad set of participant characteristics, particularly in pediatric neuroimaging. Consequently, when planning quality control (QC) procedures researchers must balance data quality concerns against the possibility of biasing results by eliminating data. In order to explore how researcher QC decisions might bias rs-fMRI findings and inform future research design, we investigated how a broad spectrum of participant characteristics in the Adolescent Brain and Cognitive Development (ABCD) study were related to participant inclusion/exclusion across versions of the dataset (the ABCD Community Collection and ABCD Release 4) and QC choices (specifically, motion scrubbing thresholds). Across all these conditions, we found that the odds of a participant’s exclusion related to a broad spectrum of behavioral, demographic, and health-related variables, with the consequence that rs-fMRI analyses using these variables are likely to produce biased results. Consequently, we recommend that missing data be formally accounted for when analyzing rs-fMRI data and interpreting results. Our findings demonstrate the urgent need for better data acquisition and analysis techniques which minimize the impact of motion on data quality. Additionally, we strongly recommend including detailed information about quality control in open datasets such as ABCD.

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Using data from the Adolescent Brain Cognitive Development study (n = 3928), we examined how police contact relates to sleep problems, anxiety, and depressive symptoms during middle adolescence (M age = 14.09; SD = 0.68). Consistent with racialized disparities in the presence of police in schools and communities, descriptive data revealed that Black children, particularly boys, reported more positive and negative contact with police than other children. Results of regression analyses that adjusted for potential selection factors further revealed that negative interactions with police were associated with increased risk for sleep disturbances and/or internalizing symptoms among White boys, Black girls, and Hispanic youth. Contact with police was not, however, associated with outcomes assessed here for White girls or Black boys, findings that likely reflect fundamentally different lived experiences with police, gendered racial socialization processes, and access to social support that warrant continued investigation in future research.

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Recent years have seen a shift toward alternative nosologies of psychopathology, which frequently include a dimension of externalizing psychopathology. The Hierarchical Taxonomy of Psychopathology is one such framework. Research using data from the Adolescent Brain and Cognitive Development (ABCD) Study has identified a broad-based externalizing dimension, but no research to date has sought to empirically identify finer-grained externalizing subdimensions despite the research benefits associated with the use of homogenous dimensions. Furthermore, no work to date has examined whether externalizing dimensions are invariant over time. Thus, the current study had two primary aims: Aim 1-identify the hierarchical structure of externalizing psychopathology and examine evidence of discriminant validity of identified dimensions and Aim 2-assess the longitudinal measurement invariance of a broad externalizing dimension in the ABCD Study, as well as specific underlying subdimensions. The results for Aim 1 analyses identified a coherent factor structure comprising a broad externalizing dimension and three subdimensions (conduct problems, irritability, and neurodevelopmental problems), and these factors showed important similarities and differences in relation to external correlates. Aim 2 analyses showed that strong invariance was supported for the conduct problems and irritability dimensions, while partial strong invariance was supported for broad externalizing and neurodevelopmental problems. Quantification of measurement (non)invariance revealed small effect sizes. The results highlight important directions for future research on externalizing psychopathology in the ABCD Study. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

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This editorial focuses on the issue of data misuse that is increasingly evidenced in social media as well as some premiere scientific journals. This issue is of critical importance to open science projects in general, and ABCD in particular, given the broad array of biological, behavioural and environmental information collected on this American sample of 12,000 youth and parents. ABCD data are already widely used with over 1,200 publications and twice as many citations per year as expected (relative citation index based on year, field and journal). However, the adverse consequences of misuse of data and inaccurate interpretation of emergent findings from this precedent setting study may have a profound impact on disadvantaged populations and perpetuate biases and societal injustices.

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Black adolescents in the United States face disproportionate poor nutrition and obesity risk due to racism. Intersections of larger structural contexts that pose differential access to Black adolescents’ health resources, such as state-level racism and neighborhood-level disadvantage, may govern these risks. The purpose of this correlational study was to examine the associations between state-level racism, neighborhood disadvantage, and their intersection with nutrition and obesity for Black adolescents in a longitudinal study.

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Online social interactions increase into adolescence. Although cross-sectional studies have positively associated online social activity (OSA) time and attention-deficit/hyperactivity disorder (ADHD) problems, the directionality remains unclear. Therefore, we examined longitudinal associations between OSA time and ADHD problems using data from the Adolescent Brain Cognitive Development (ABCD) study. Four waves of ABCD data from 11,819 youth participants (52.1% boys; Baseline: M = 9.92 years, SD = 0.62) were utilized. Random-intercepts cross-lagged panel models (RI-CLPMs) adjusting for potential confounds were employed to estimate longitudinal bidirectional associations. Multiple-group RI-CLPM analyses examined potential moderation effects of OSA content type and child’s sex. The results revealed that greater OSA time was associated with more ADHD problems in early adolescence, while more ADHD problems did not predict greater OSA time. In moderation analyses, the cross-lagged effects of OSA time on ADHD problems were only significant for girls, and boys showed an inverse relation between ADHD problems and subsequent OSA time. No moderation effect of OSA content type was observed. These findings highlight the potential detrimental effect of OSA time on the development of attentional processes, especially for girls, thereby offering insights that could guide the development and targeting of interventions to mitigate future risks for ADHD problems during adolescence.

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Low socioeconomic status is associated with lower cognitive performance and long-term disparities in achievement and success. However, not all children from low-income backgrounds exhibit lower cognitive performance. Characterizing the factors that promote such resilience in youth from low-income households is of crucial importance.

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Setting rules about alcohol use and minimizing its availability in the home are known effective parent-level strategies for reducing underage drinking risk. However, parents’ restrictions and their perceptions of their child’s alcohol access have rarely been considered in combination (e.g., determining if rule-setting consistently accompanies perceived easy access), despite the potential to inform targeted prevention. The current study identified patterns in six parent-reported indicators of their child’s alcohol restrictions and access and characterized them with respect to race/ethnicity, socioeconomic status, community type (urban, suburban, or rural), and neighborhood (dis)advantage.

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Psychiatric disorders are influenced by genetic and environmental factors. However, their study is hindered by limitations on precisely characterizing human behavior. New technologies such as wearable sensors show promise in surmounting these limitations in that they measure heterogeneous behavior in a quantitative and unbiased fashion. Here, we analyze wearable and genetic data from the Adolescent Brain Cognitive Development (ABCD) study. Leveraging >250 wearable-derived features as digital phenotypes, we show that an interpretable AI framework can objectively classify adolescents with psychiatric disorders more accurately than previously possible. To relate digital phenotypes to the underlying genetics, we show how they can be employed in univariate and multivariate genome-wide association studies (GWASs). Doing so, we identify 16 significant genetic loci and 37 psychiatric-associated genes, including ELFN1 and ADORA3, demonstrating that continuous, wearable-derived features give greater detection power than traditional case-control GWASs. Overall, we show how wearable technology can help uncover new linkages between behavior and genetics.

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The Adolescent Brain Cognitive Development (ABCD) Study is the largest longitudinal study on brain development and adolescent health in the United States. The study includes a sociodemographically diverse cohort of nearly 12,000 youth born 2005-2009, with an open science model of making data rapidly available to the scientific community. The ABCD Study® data has been used in over 1100 peer-reviewed publications since its first data release in 2018. The dataset contains a broad scope and comprehensive set of measures of youths’ behavioral, health, and brain outcomes, as well as extensive contextual and environmental measures that map onto the social determinants of health (SDOH). Understanding the impact of SDOH on the developmental trajectories of youth will help to address early lifecourse health inequities that lead to disparities later in life. However, the open science model and extensive use of ABCD data highlight the need for guidance on appropriate, responsible, and equitable use of the data.

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This study examined the relative impact of earlier versus proximal childhood exposures to family adversities (parental health problems, family conflict, financial hardship, abuse, violence) and supportive caregiving (warm and supportive parenting behaviors) on youths’ symptom trajectories across early adolescence. We used parent-reported survey data to differentiate co-occurring Pain, Psychological, and Somatic Symptom (Pain-PSS) trajectories among youth in the longitudinal Adolescent Brain Cognitive Development Study® (2016-2022). Family adversities and supportive caregiving were derived from youth and parent surveys and coded as occurring earlier (by age 9-11yrs; baseline) or proximally (occurring during study follow-up years 1-4; by age 11-15yrs). Sequential modeling determined whether proximal exposures mediated the effects of earlier exposures on youths’ Pain-PSS trajectories (data reflect adjusted relative risk ratios (adj. RRR [95% confidence interval]). Four Pain-PSS trajectories were differentiated among 7,546 youth, 14.3% of whom were classified with High Pain/High PSS. Earlier exposure to any family adversity increased the risk for higher Pain-PSS relative to the lowest symptom trajectory (e.g., parental mental health or somatic problems increased the relative risk for a High Pain/High PSS trajectory to 3.85 [2.84, 5.22] and 5.75 [4.36, 7.58], respectively). Most proximal exposures increased the risk for higher symptom trajectories, fully or partially mediating effects of earlier exposures. Higher proximal supportive caregiving lowered the risk for the High Pain/High PSS trajectory by 80%, fully mediating the impact of earlier caregiving. Findings suggest that family adversities and supportive caregiving may be important interventional targets to lower the risk for co-occurring symptom persistence across early adolescence.

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Various psychosocial factors like collaboration inherent to team sports might provide a more dynamic environment for cognitive challenges that could foster enhanced neurocognitive development compared to individual sports. We investigated the impact of different organised sports on neurocognitive development in children (N = 11,878; aged 9-11) from the Adolescent Brain Cognitive Development (ABCD) study. Participants were classified into four categories based on their sports involvement at baseline and two years later: none, individual-based, team-based, or both. Cross-sectional and longitudinal analyses were conducted on 11 cognitive tests and neuroimaging metrics (i.e., resting-state functional connectivity and various grey matter (GM) and white matter (WM) measurements) between sport groups. A comparison between team and individual sports yielded no significant differences in cognitive measures at baseline and follow-up. Similarly, although WM microstructural differences were significant, the effect size was small. However, participation in any sport at baseline was associated with superior performance in various cognitive domains (i.e. inhibition, processing speed, and others), greater subcortical GM volume (i.e. cerebellum cortex, amygdala, hippocampus, and others), and whole-brain WM integrity compared to non-participants. Results suggest a positive association between organised sports participation, specifically individual and team-based sports, and neurocognitive development. However, further investigation is warranted to determine the nuanced effects of different sports on neurocognitive development.

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To determine the association between transgender or gender-questioning identity and cyberbullying victimization in a diverse national sample of early adolescents in the US.

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There is not yet a consensus on the best way to conceptualise adverse childhood experiences (ACEs). We used data-driven methods across two populations to examine (a) if there were meaningful dimensions underlying ACEs and (b) whether dimensions were differentially associated with increased risk of adolescent psychopathology.

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Resting-state functional magnetic resonance imaging (rsfMRI) is a powerful tool for investigating the relationship between brain function and cognitive processes as it allows for the functional organization of the brain to be captured without relying on a specific task or stimuli. In this paper, we present a novel modeling architecture called BrainRGIN for predicting intelligence (fluid, crystallized and total intelligence) using graph neural networks on rsfMRI derived static functional network connectivity matrices. Extending from the existing graph convolution networks, our approach incorporates a clustering-based embedding and graph isomorphism network in the graph convolutional layer to reflect the nature of the brain sub-network organization and efficient network expression, in combination with TopK pooling and attention-based readout functions. We evaluated our proposed architecture on a large dataset, specifically the Adolescent Brain Cognitive Development Dataset, and demonstrated its effectiveness in predicting individual differences in intelligence. Our model achieved lower mean squared errors and higher correlation scores than existing relevant graph architectures and other traditional machine learning models for all of the intelligence prediction tasks. The middle frontal gyrus exhibited a significant contribution to both fluid and crystallized intelligence, suggesting their pivotal role in these cognitive processes. Total composite scores identified a diverse set of brain regions to be relevant which underscores the complex nature of total intelligence. Our GitHub implementation is publicly available on https://github.com/bishalth01/BrainRGIN/.

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Pubertal trends, wherein adolescents today are experiencing puberty earlier than prior generations, have coincided with the expansion of the criminal legal system, which is disproportionately impacting communities of color. However, whether pubertal development and criminal legal system exposure among adolescents are inter-related is unknown. We tested whether family members’ criminal legal system exposure predicted adolescents’ pubertal development, whether family strain explained the relation between criminal legal system exposure and pubertal development, and whether race/ethnicity moderated our results. We used three yearly waves of longitudinal data among a national sample of 9,518 adolescents. Results illustrated that 40% of Black, 20% of Latinx, 16% of Other, and 10% of White adolescents experienced one or more family criminal legal system exposures. In structural equation models within a case-crossover design controlling for measured confounders and unmeasured confounders that do not change over time, including neighborhood-level socioeconomic status and crime, family criminal legal system exposure predicted adolescents’ advanced pubertal development, and family strain explained this relation between family criminal legal system exposure and pubertal development. The United States’ approach to law and order has public health implications that may be perpetuating health inequities, as accelerated pubertal development can have downstream consequences across the life course.

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Major efforts in human neuroimaging strive to understand individual differences and find biomarkers for clinical applications by predicting behavioural phenotypes from brain imaging data. To identify generalisable and replicable brain-behaviour prediction models, sufficient measurement reliability is essential. However, the selection of prediction targets is predominantly guided by scientific interest or data availability rather than psychometric considerations. Here, we demonstrate the impact of low reliability in behavioural phenotypes on out-of-sample prediction performance. Using simulated and empirical data from four large-scale datasets, we find that reliability levels common across many phenotypes can markedly limit the ability to link brain and behaviour. Next, using 5000 participants from the UK Biobank, we show that only highly reliable data can fully benefit from increasing sample sizes from hundreds to thousands of participants. Our findings highlight the importance of measurement reliability for identifying meaningful brain-behaviour associations from individual differences and underscore the need for greater emphasis on psychometrics in future research.

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The National Institutes of Health (NIH) Toolbox Cognition Battery is increasingly being used as a standardized test to examine cognitive functioning in multicentric studies. This study examines the associations between the NIH Toolbox Cognition Battery composite scores with neuroimaging metrics using data from the Adolescent Brain Cognitive Development (ABCD) study to elucidate the neurobiological and neuroanatomical correlates of these cognitive scores.

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Quantitative global or regional brain imaging measurements, known as imaging-specific or -derived phenotypes (IDPs), are commonly used in genotype-phenotype association studies to explore the genomic architecture of the brain and how it may be affected by neurological diseases (e.g., Alzheimer’s disease), mental health (e.g., depression), and neurodevelopmental disorders (e.g., attention-deficit hyperactivity disorder [ADHD]). For this purpose, medical images have been used as IDPs using a voxel-wise or global approach via principal component analysis. However, these methods have limitations related to multiple testing or the inability to isolate high variation regions, respectively.

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High-resolution (HR) 3D MR images provide detailed soft-tissue information that is useful in assessing long-term side-effects after treatment in childhood cancer survivors, such as morphological changes in brain structures. However, these images require long acquisition times, so routinely acquired follow-up images after treatment often consist of 2D low-resolution (LR) images (with thick slices in multiple planes).

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Video games are a common form of entertainment in adolescents, which may result in gaming habits characterized by impairment to reward-related decision-making. The aim of the current study was to investigate the relationship between reward processing and symptoms of gaming addiction in adolescents.

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Insomnia is the most prevalent sleep disturbance during childhood and can result in extensively detrimental effects. Children’s insomnia involves a complex interplay of biological, neurodevelopmental, social-environmental, and behavioral variables, yet remains insufficiently addressed. This study aimed to investigate the multifactorial etiology of childhood insomnia from its genetic architecture and social-environmental variables to its neural instantiation and the relationship to mental health. This cohort study uses 4340 participants at baseline and 2717 participants at 2-year follow-up from the Adolescent Brain Cognitive Development (ABCD) Study. We assessed the joint effects of polygenic risk score (PRS) and socioeconomic status (SES) on insomnia symptoms and then investigated the underlying neurodevelopmental mechanisms. Structural equation model (SEM) was applied to investigate the directional relationships among these variables. SES and PRS affected children’s insomnia symptoms independently and additively (SES: β = -0.089, P = 1.91 × 10; PRS: β = 0.041, P = 0.008), which was further indirectly mediated by the deviation of inferior precentral sulcus (β = 0.0027, P = 0.0071). SEM revealed that insomnia (β = 0.457, P < 0.001) and precentral development (β = -0.039, P = 0.009) significantly mediated the effect of SES_PRS (accumulated risks of PRS and SES) on psychopathology symptoms. Furthermore, baseline insomnia symptoms, SES_PRS, and precentral deviation significantly predicted individual total psychopathology syndromes (r = 0.346, P < 0.001). These findings suggest the additive effects of genetic and socioenvironmental factors on childhood insomnia via precentral development and highlight potential targets in early detection and intervention for childhood insomnia.

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The primary aim of this study was to assess and adjust for measurement non-equivalence (bias) by sex, race/ethnicity, and co-occurring social identities (sex x race/ethnicity) for the Marijuana Effect Expectancies Questionnaire-Brief (MEEQ-B) among Black, Latinx, and Non-Latinx white youth. The second aim was to determine how group comparisons change after accounting for possible measurement bias.

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Converging evidence indicates that the heterogeneity of cognitive profiles may arise through detectable alternations in brain functional connectivity. Despite an unprecedented opportunity to uncover neurobiological subtypes through clustering or subtyping analyses on multi-state functional connectivity, few existing approaches are applicable to accommodate the network topology and unique biological architecture. To address this issue, we propose an innovative Bayesian nonparametric network-variate clustering analysis to uncover subgroups of individuals with homogeneous brain functional network patterns under multiple cognitive states. In light of the existing neuroscience literature, we assume there are unknown state-specific modular structures within functional connectivity. Concurrently, we identify informative network features essential for defining subtypes. To further facilitate practical use, we develop a computationally efficient variational inference algorithm to approximate posterior inference with satisfactory estimation accuracy. Extensive simulations show the superiority of our method. We apply the method to the Adolescent Brain Cognitive Development (ABCD) study, and identify neurodevelopmental subtypes and brain sub-network phenotypes under each state to signal neurobiological heterogeneity, suggesting promising directions for further exploration and investigation in neuroscience.

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To examine the association between multiple dimensions of gender diversity and physical activity (daily steps) in a diverse national sample of early adolescents in the United States.

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Depression and pain co-occur, even during adolescence. However, there is limited knowledge on the association between pain and lifetime depression, and which biopsychosocial measures are associated with this co-occurrence.

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Complex structural and functional changes occurring in typical and atypical development necessitate multidimensional approaches to better understand the risk of developing psychopathology. Here, we simultaneously examined structural and functional brain network patterns in relation to dimensions of psychopathology in the Adolescent Brain Cognitive Development dataset. Several components were identified, recapitulating the psychopathology hierarchy, with the general psychopathology () factor explaining most covariance with multimodal imaging features, while the internalizing, externalizing, and neurodevelopmental dimensions were each associated with distinct morphological and functional connectivity signatures. Connectivity signatures associated with the factor and neurodevelopmental dimensions followed the sensory-to-transmodal axis of cortical organization, which is related to the emergence of complex cognition and risk for psychopathology. Results were consistent in two separate data subsamples and robust to variations in analytical parameters. Although model parameters yielded statistically significant brain-behavior associations in unseen data, generalizability of the model was rather limited for all three latent components ( change from within- to out-of-sample statistics: LC1=0.36, LC1=0.03; LC2=0.34, LC2=0.05; LC3=0.35, LC3=0.07). Our findings help in better understanding biological mechanisms underpinning dimensions of psychopathology, and could provide brain-based vulnerability markers.

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Human craniofacial shape is highly variable yet highly heritable with numerous genetic variants interacting through multiple layers of development. Here, we hypothesize that Mendelian phenotypes represent the extremes of a phenotypic spectrum and, using achondroplasia as an example, we introduce a syndrome-informed phenotyping approach to identify genomic loci associated with achondroplasia-like facial variation in the general population. We compare three-dimensional facial scans from 43 individuals with achondroplasia and 8246 controls to calculate achondroplasia-like facial scores. Multivariate GWAS of the control scores reveals a polygenic basis for facial variation along an achondroplasia-specific shape axis, identifying genes primarily involved in skeletal development. Jointly modeling these genes in two independent control samples, both human and mouse, shows craniofacial effects approximating the characteristic achondroplasia phenotype. These findings suggest that both complex and Mendelian genetic variation act on the same developmentally determined axes of facial variation, providing insights into the genetic intersection of complex traits and Mendelian disorders.

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Maternal tobacco use during pregnancy (MTDP) remains a major public health challenge. However, the complete spectrum of effects of MTDP is not fully understood.

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Although racial and ethnic disparities are well documented in children’s mean levels of sleep, particularly duration, evidence is mixed for sleep variability, an important sleep dimension of growing interest. Most research has also focused on comparisons of Black and White children, with limited attention to sleep variability disparities among other racially and ethnically minoritized groups such as Asian, Latinx, and multiracial children.

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The extent to which neuroanatomical variability associated with early substance involvement, which is associated with subsequent risk for substance use disorder development, reflects preexisting risk and/or consequences of substance exposure remains poorly understood.

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Recent studies using the diffusion decision model find that performance across many cognitive control tasks can be largely attributed to a task-general efficiency of evidence accumulation (EEA) factor that reflects individuals’ ability to selectively gather evidence relevant to task goals. However, estimates of EEA from an n-back “conflict recognition” paradigm in the Adolescent Brain Cognitive Development (ABCD) Study, a large, diverse sample of youth, appear to contradict these findings. EEA estimates from “lure” trials-which present stimuli that are familiar (i.e., presented previously) but do not meet formal criteria for being a target-show inconsistent relations with EEA estimates from other trials and display atypical v-shaped bivariate distributions, suggesting many individuals are responding based largely on stimulus familiarity rather than goal-relevant stimulus features. We present a new formal model of evidence integration in conflict recognition tasks that distinguishes individuals’ EEA for goal-relevant evidence from their use of goal-irrelevant familiarity. We then investigate developmental, cognitive, and clinical correlates of these novel parameters. Parameters for EEA and goal-irrelevant familiarity-based processing showed strong correlations across levels of n-back load, suggesting they are task-general dimensions that influence individuals’ performance regardless of working memory demands. Only EEA showed large, robust developmental differences in the ABCD sample and an independent age-diverse sample. EEA also exhibited higher test-retest reliability and uniquely meaningful associations with clinically relevant dimensions. These findings establish a principled modeling framework for characterizing conflict recognition mechanisms and have several broader implications for research on individual and developmental differences in cognitive control.

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Mapping differential brain structures for psychiatric problems has been challenging due to a lack of regional convergence and poor replicability in previous brain-behavior association studies. By leveraging two independent large cohorts of neurodevelopment, the ABCD and Generation R Studies (total N = 11271), we implemented an unsupervised machine learning technique with a highly stringent generalizability test to identify reliable brain-behavior associations across diverse domains of child psychiatric problems. Across all psychiatric symptoms measured, one multivariate brain-behavior association was found, reflecting a widespread reduction of cortical surface area correlated with higher child attention problems. Crucially, this association showed marked generalizability across different populations and study protocols, demonstrating potential clinical utility. Moreover, the derived brain dimension score predicted child cognitive and academic functioning three years later and was also associated with polygenic scores for ADHD. Our results indicated that attention problems could be a phenotype for establishing promising multivariate neurobiological prediction models for children across populations. Future studies could extend this investigation into different development periods and examine the predictive values for assessment of functioning, diagnosis, and disease trajectory in clinical samples.

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Sexual orientation discrimination increases the risks of negative health outcomes for sexual minorities. Previous studies have found increased rates of eating disorder symptoms in sexual minority individuals, which is attributable to minority stress and discrimination that they experience. Emerging research suggests relationships between sexual orientation discrimination and eating disorder symptoms. However, there is a lack of studies focusing on early adolescents. The objective of this study was to determine prospective associations between discrimination based on sexual orientation and eating disorder symptoms in a national sample of 10-13-year-old early adolescents in the U.S.

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Decades of research show a clear link between family factors and psychopathology. Family functioning varies across cultures, suggesting potential cultural differences in the association between family factors and psychopathology. In addition, assessing family functioning generally involves tools not systematically validated for diverse cultural backgrounds. Using the Adolescent Brain Cognitive Development data ( = 11,864), this study found: (a) full scalar invariance was tenable for the Children’s Reports of Parental Behavior Inventory (CRPBI) and Prodromal Questionnaire-Brief Child Version (PQ-BC) across race/ethnicity, but not for the Family Environment Scale (FES) and Parental Monitoring Survey (PMQ); (b) the CRPBI and PMQ were significantly associated with the PQ-BC, and (c) all three family scales had equivalent relations with the PQ-BC across groups. This highlights the importance of evaluating scales for measurement invariance across race/ethnicity. Results also help to connect specific family factors to the etiology of psychosis risk among U.S. children and adolescents.

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Brain-wide association studies (BWAS) are a fundamental tool in discovering brain-behaviour associations. Several recent studies have shown that thousands of study participants are required for good replicability of BWAS. Here we performed analyses and meta-analyses of a robust effect size index using 63 longitudinal and cross-sectional MRI studies from the Lifespan Brain Chart Consortium (77,695 total scans) to demonstrate that optimizing study design is critical for increasing standardized effect sizes and replicability in BWAS. A meta-analysis of brain volume associations with age indicates that BWAS with larger variability of the covariate and longitudinal studies have larger reported standardized effect size. Analysing age effects on global and regional brain measures from the UK Biobank and the Alzheimer’s Disease Neuroimaging Initiative, we showed that modifying study design through sampling schemes improves standardized effect sizes and replicability. To ensure that our results are generalizable, we further evaluated the longitudinal sampling schemes on cognitive, psychopathology and demographic associations with structural and functional brain outcome measures in the Adolescent Brain and Cognitive Development dataset. We demonstrated that commonly used longitudinal models, which assume equal between-subject and within-subject changes can, counterintuitively, reduce standardized effect sizes and replicability. Explicitly modelling the between-subject and within-subject effects avoids conflating them and enables optimizing the standardized effect sizes for each separately. Together, these results provide guidance for study designs that improve the replicability of BWAS.

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This study investigated longitudinal relationships between social media usage and binge eating (BE) in early adolescence and explored potential moderating effects of sex and BMI.

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The spatial layout of large-scale functional brain networks exhibits considerable inter-individual variability, especially in the association cortex. Research has demonstrated a link between early socioeconomic status (SES) and variations in both brain structure and function, which are further associated with cognitive and mental health outcomes. However, the extent to which SES is associated with individual differences in personalized functional network topography during childhood remains largely unexplored.

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Adolescence is marked by hormonal, physical, neural, and behavioral changes, including in sleep patterns and, in females, the onset of menarche. Menstrual problems, such as painful menses, are common and contribute to school absences, and could indicate gynecological conditions impacting reproductive health. While studies in adults have shown associations between sleep disturbances and menstrual problems, this relationship is less understood in adolescents. Our study explores the association between sleep, menstrual problems, and menarche in a diverse sample of early adolescent girls in the U.S.

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The purpose of this study was to examine associations between identifying as transgender and attention deficit hyperactivity disorder (ADHD) symptoms in US early adolescents.

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Though caffeine use during pregnancy is common, its longitudinal associations with child behavioral and physical health outcomes remain poorly understood. Here, we estimated associations between prenatal caffeine exposure, body mass index (BMI), and behavior as children enter adolescence.

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Longitudinal studies of the effects of adversity on human brain development are complicated by the association of stressful events with confounding variables. To counter this bias, we apply a propensity-weighted analysis of the first two years of The Adolescent Brain Cognitive Development (ABCD) Study® data, employing a machine learning analysis weighted by individuals’ propensity to experience adversity. Data included 338 resting-state functional connections from 7190 youth (46% female), divided into a training group (80%) and an independent testing group (20%). Propensity scores were computed using 390 variables to balance across two-year adverse life event exposures. Using elastic net regularization with and without inverse propensity weighting, we developed linear models in which changes in functional connectivity of brain connections during the two-year period served as predictors of the number of adverse events experienced during that same period. Haufe’s method was applied to forward-transform the backward prediction models. We also tested whether brain changes associated with adverse events correlated with concomitant changes in internalizing or externalizing behaviors or to academic achievement. In the propensity-weighted analysis, brain development significantly predicted the number of adverse events experienced during that period in both the training group (ρ = 0.14, p < 0.001) and the independent testing group (ρ = 0.10, p < 0.001). The predictor indicated a general pattern of decreased functional connectivity between large-scale networks and subcortical brain regions, particularly for cingulo-opercular and sensorimotor networks. These network-to-subcortical functional connectivity decreases inversely associated with the development of internalizing symptoms, suggesting adverse events promoted adaptive brain changes that may buffer against stress-related psychopathology. However, these same functional connections were also associated with poorer grades at the two-year follow-up. Although cortical-subcortical brain developmental responses to adversity potentially shield against stress-induced mood and anxiety disorders, they may be detrimental to other domains such as academic success.

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Impulsivity has been recognized as an important factor in suicidal thoughts and behaviors (STBs). However, previous research linking impulsivity to STBs has largely relied on cross-sectional designs, considered only a subset of impulsivity measures, and typically focused on middle-to-older adolescents. Here, we explored multiple measures of impulsivity and assessed their predictive relation to suicidal ideation and suicide attempts.

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Human adolescence marks a crucial phase of extensive brain development, highly susceptible to environmental influences. Employing brain age estimation to assess individual brain aging, we categorized individuals ( = 7,435, aged 9-10 years old) from the Adolescent Brain and Cognitive Development (ABCD) cohort into groups exhibiting either accelerated or delayed brain maturation, where the accelerated group also displayed increased cognitive performance compared to their delayed counterparts. A 4-way multi-set canonical correlation analysis integrating three modalities of brain metrics (gray matter density, brain morphological measures, and functional network connectivity) with nine environmental factors unveiled a significant 4-way canonical correlation between linked patterns of neural features, air pollution, area crime, and population density. Correlations among the three brain modalities were notably strong (ranging from 0.65 to 0.77), linking reduced gray matter density in the middle temporal gyrus and precuneus to decreased volumes in the left medial orbitofrontal cortex paired with increased cortical thickness in the right supramarginal and bilateral occipital regions, as well as increased functional connectivity in occipital sub-regions. These specific brain characteristics were significantly more pronounced in the accelerated brain aging group compared to the delayed group. Additionally, these brain regions exhibited significant associations with air pollution, area crime, and population density, where lower air pollution and higher area crime and population density were correlated to brain variations more prominently in the accelerated brain aging group.

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Unpredictability is a core but understudied dimension of adversities and has been receiving increasing attention recently. The effects of unpredictability on psychopathology and the underlying neural mechanisms, however, remain unclear. It is also unknown how unpredictability interacts with other dimensions of adversities in predicting brain development and psychopathology of youth.

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Adolescence is a time of increased risk for the onset of internalising problems, particularly in females. However, how individual differences in brain maturation relate to the increased vulnerability for internalising problems in adolescence remains poorly understood due to a scarcity of longitudinal studies.

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Adolescent depression is a growing public health concern, and neuroimaging offers a promising approach to its pathology. We focused on the functional connectivity of the amygdala and subgenual anterior cingulate cortex (sgACC), which is theoretically important in major depressive disorder (MDD), but empirical evidence has remained inconsistent. This discrepancy is likely due to the limited statistical power of small sample sizes.

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Maternal education was strongly correlated with adolescent brain morphology, cognitive performances, and mental health. However, the molecular basis for the effects of maternal education on the structural neurodevelopment remains unknown. Here, we conducted gene-environment-wide interaction study using the Adolescent Brain Cognitive Development cohort. Seven genomic loci with significant gene-environment interactions (G×E) on regional gray matter volumes were identified, with enriched biological functions related to metabolic process, inflammatory process, and synaptic plasticity. Additionally, genetic overlapping results with behavioral and disease-related phenotypes indicated shared biological mechanism between maternal education modified neurodevelopment and related behavioral traits. Finally, by decomposing the multidimensional components of maternal education, we found that socioeconomic status, rather than family environment, played a more important role in modifying the genetic effects on neurodevelopment. In summary, our study provided analytical evidence for G×E effects regarding adolescent neurodevelopment and explored potential biological mechanisms as well as social mechanisms through which maternal education could modify the genetic effects on regional brain development.

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There are limited large-scale, prospective analyses examining contemporary screen use and substance use experimentation in early adolescents. The current study aimed to determine associations between eight forms of contemporary screen modalities and substance use experimentation one year later in a national cohort of 11-12-year-olds in the United States.

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Adverse childhood experiences (ACEs) increase the risk for poor adolescent mental health, yet mediational pathways that connect ACEs with mental health problems remain unaddressed. Our study investigates whether school involvement and disengagement mediate the longitudinal associations between ACEs and adolescent mental health problems.

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Parental mental health is associated with children’s emotion regulation (ER) and risk for psychopathology. The relationship between parental psychopathology and children’s functional ER networks and whether connectivity patterns mediate the relationship between parent and youth psychopathology remains unexplored. Using resting-state functional magnetic resonance imaging data from the Adolescent Brain Cognitive Development Study (N = 4202, mean age = 10.0) and a multilevel approach, we analyzed the relationship between self-reported parental psychopathology and their offsprings’ connectivity of four ER networks, as well as associations with self-reported youth psychopathology at a 3-year follow-up. Parental internalizing and total problems were associated with 1) higher connectivity between a subcortical-cortical integrative and ventrolateral prefrontal cortical (PFC) network, 2) lower connectivity between dorsolateral and ventrolateral PFC networks involved in cognitive aspects of ER, and 3) lower connectivity within a subcortical ER network (β = -0.05-0.04). Parental externalizing and total problems were associated with lower connectivity within the integrative network (β = -0.05; β = -0.04). Mediation analyses yielded direct effects of parental to youth psychopathology, but no mediation effect of ER network connectivity. Overall, our results show that ER network connectivity in youth is related to parental psychopathology, yet do not explain intergenerational transmission of psychopathology.

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Pediatric hypertension is linked to environmental factors like neighborhood noise disrupting sleep, which is crucial for health. The specific interaction between noise and sleep health in causing hypertension still needs to be explored.

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To assess associations between multiple dimensions of gender diversity with eating disorder symptoms in a national cohort of U.S. early adolescents.

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Adolescents with disrupted rest-activity rhythms (RAR) including shorter sleep duration, later sleep timing and low physical activity levels are at a greater risk for mental and behavioral problems. However, it remains unclear whether the same associations can be observed for within-subject changes in RAR.

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Adolescent cannabis use has been consistently posited to contribute to the onset and progression of psychosis. However, alternative causal models may account for observed associations between cannabis use and psychosis risk, including shared vulnerability for both cannabis use and psychosis or efforts to self-medicate distress from psychosis spectrum symptomology.

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Widely prescribed for Attention-Deficit/Hyperactivity Disorder (ADHD), stimulants (e.g., methylphenidate) have been studied for their chronic effects on the brain in prospective designs controlling dosage and adherence. While controlled approaches are essential, they do not approximate real-world stimulant exposure contexts where medication interruptions, dosage non-compliance, and polypharmacy are common. Brain changes in real-world conditions are largely unexplored. To fill this gap, we capitalized on the observational design of the Adolescent Brain Cognitive Development (ABCD) study to examine effects of stimulants on large-scale bilateral cortical networks’ resting-state functional connectivity (rs-FC) with 6 striatal regions (left and right caudate, putamen, and nucleus accumbens) across two years in children with ADHD. Bayesian hierarchical regressions revealed associations between stimulant exposure and change in rs-FC of multiple striatal-cortical networks, affiliated with executive and visuo-motor control, which were not driven by general psychotropic medication. Of these connections, three were selective to stimulants versus stimulant naive: reduced rs-FC between caudate and frontoparietal network, and between putamen and frontoparietal and visual networks. Comparison with typically developing children in the ABCD sample revealed stronger rs-FC reduction in stimulant-exposed children for putamen and frontoparietal and visual networks, suggesting a normalizing effect of stimulants. 14% of stimulant-exposed children demonstrated reliable reduction in ADHD symptoms, and were distinguished by stronger rs-FC reduction between right putamen and visual network. Thus, stimulant exposure for a two-year period under real-world conditions modulated striatal-cortical functional networks broadly, had a normalizing effect on a subset of networks, and was associated with potential therapeutic effects involving visual attentional control.

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Abstract

There is ongoing concern about the impact of increasing use of social media and digital devices on unhealthy behaviors such as substance use in youth. Mobile phone and social media use have been associated with substance use in adolescent and young adult samples, but few studies have evaluated these relationships in younger samples.

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