Research Publications

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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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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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