Research Publications

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Externalizing psychopathology in childhood is a predictor of poor outcomes across the lifespan. Children exhibiting elevated externalizing symptoms also commonly show emotion dysregulation and callous-unemotional (CU) traits. Examining cross-sectional and longitudinal neural correlates across dimensions linked to externalizing psychopathology during childhood may clarify shared or distinct neurobiological vulnerability for psychopathological impairment later in life. We used tabulated brain structure and behavioural data from baseline, year 1, and year 2 timepoints of the Adolescent Brain Cognitive Development Study (ABCD; baseline n = 10,534). We fit separate linear mixed effect models to examine whether baseline brain structures in frontolimbic and striatal regions (cortical thickness or subcortical volume) were associated with externalizing symptoms, emotion dysregulation, and/or CU traits at baseline and over a two-year period. The most robust relationships found at the cross-sectional level was between cortical thickness in the right rostral middle frontal gyrus and bilateral pars orbitalis was positively associated with CU traits (β = |0.027-0.033|, p = 0.009-0.03). Over the two-year follow-up period, higher baseline cortical thickness in the left pars triangularis and rostral middle frontal gyrus predicted greater decreases in externalizing symptoms ((F = 6.33-6.94, p = 0.014). The results of the current study suggest that unique regions within frontolimbic and striatal networks may be more strongly associated with different dimensions of externalizing psychopathology. The longitudinal findings indicate that brain structure in early childhood may provide insight into structural features that influence behaviour over time.

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The transition from childhood to adolescence presents elevated risks for the onset of psychopathology in youth. Given the multilayered nature of development, the present study leverages the longitudinal, population-based Adolescent Brain Cognitive Development Study to derive ecologically informed risk/resilience profiles based on multilevel influences (e.g., neighborhood and family socioeconomic resources, parenting, school characteristics) and their transition pathways and examine their associations with psychopathology. Latent profile analysis characterized risk/resilience profiles at each time point (i.e., baseline, Year-1, Year-2); latent transition analysis estimated the most likely transition pathway for each individual. Analysis of covariance was used to examine associations between profile membership at baseline (i.e., ages 9-11) and psychopathology, both concurrently and at Year-2 follow-up. Further, we examined the associations between profile transition pathways and Year-2 psychopathology. Four distinct profiles emerged across time – High-SES High-Protective, High-SES Low-Protective, Low-SES High-Family-Risk, and Low-SES High-Protective. Despite reasonably high stability, significant transition over time among profiles was detected. Profile membership at baseline significantly correlated with concurrent psychopathology and predicted psychopathology 2 years later. Additionally, profile transition pathways significantly predicted Year-2 psychopathology, exemplifying equifinality and multifinality. Characterizing and tracing shifts in ecologically informed risk/resilience influences, our findings have the potential to inform more precise intervention efforts in youth.

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Background: Disordered eating in early adolescence impacts development, with long-term health implications. Minoritised adolescents might be at higher risk of disordered eating due to minority stress, but most research has focused on White, heterosexual, cisgender individuals; less is known about disordered eating among minoritised adolescents. We examined sexual, gender, racial, and ethnic identities in relation to disordered eating in early adolescence.

Method: Using 2-year follow-up data from adolescents ages 10-14 in the Adolescent Brain Cognitive Development Study (N = 9385), we examined associations between sexual, gender, racial, and ethnic identities and past-2 week disordered eating (preoccupation with weight, weight control behaviors, and binge eating).

Results: Compared to heterosexual peers, gay/bisexual adolescents had higher odds of all three outcomes (AOR 1.90-3.32); those “questioning” their sexual identity had higher odds of preoccupation with weight (AOR 1.82) and binge eating (AOR 2.53). Compared to cisgender adolescents, transgender adolescents had higher odds of binge eating (AOR 2.62); those “questioning” their gender identity had higher odds of preoccupation with weight (AOR 2.45). Adolescents whose racial identity was categorised as “Another” had higher odds of preoccupation with weight (AOR 1.46) and weight control behaviors (AOR 1.58) compared to White adolescents. Finally, Hispanic adolescents had higher odds of all disordered eating outcomes than non-Hispanic adolescents (AOR 1.25-1.59).

Discussion: This study is among the first to reveal disparities in disordered eating among minoritised early adolescents. Further examination of these disparities can inform future interventions. Healthcare providers are encouraged to screen for disordered eating, recognising that minoritised early adolescents may be at risk.

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Despite the ubiquity of adolescent screen use, there are limited longitudinal studies that examine the prospective relationships between screen time and child behavioral problems in a large, diverse nationwide sample of adolescents in the United States, which was the objective of the current study.

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Mapping of human brain structural connectomes via diffusion magnetic resonance imaging (dMRI) offers a unique opportunity to understand brain structural connectivity and relate it to various human traits, such as cognition. However, head displacement during image acquisition can compromise the accuracy of connectome reconstructions and subsequent inference results. We develop a generative model to learn low-dimensional representations of structural connectomes invariant to motion-induced artifacts, so that we can link brain networks and human traits more accurately, and generate motion-adjusted connectomes. We apply the proposed model to data from the Adolescent Brain Cognitive Development (ABCD) study and the Human Connectome Project (HCP) to investigate how our motion-invariant connectomes facilitate understanding of the brain network and its relationship with cognition. Empirical results demonstrate that the proposed motion-invariant variational autoencoder (inv-VAE) outperforms its competitors in various aspects. In particular, motion-adjusted structural connectomes are more strongly associated with a wide array of cognition-related traits than other approaches without motion adjustment.

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The associations of adverse childhood experiences (ACEs) with blood pressure in adulthood are inconclusive. Similarly, the association between ACEs and blood pressure earlier in the life course is understudied. This study aims to assess the associations of ACEs with blood pressure among early adolescents. We utilized data collected at baseline (age: 9-10 years) and Year 2 follow-up from 4077 participants in the Adolescent Brain Cognitive Development (ABCD) Study. We used adjusted multiple linear regression models to estimate the associations of ACEs (cumulative score and subtypes) at baseline with systolic blood pressure (SBP) and diastolic blood pressure (DBP) at year 2 of follow-up. Experiencing ≥4 ACEs (compared to 0) was significantly associated with higher SBP ( = 3.31, 95 % CI 0.03, 6.57, = 0.048). Of the ACEs subtypes, household substance use ( = 2.28, 95 % CI 0.28, 4.28, = 0.028) and divorce or separation ( = 2.08, 95 % CI 0.01, 4.15, = 0.048) were both significantly associated with a higher SBP while household mental illness ( = 2.57, 95 % CI 1.32, 3.81, < 0.001) was significantly associated with a higher DBP. Our findings suggest that exposure to multiple ACEs is associated with higher blood pressure in adolescence.

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In regression-based analyses of group-level neuroimage data, researchers typically fit a series of marginal general linear models to image outcomes at each spatially referenced pixel. Spatial regularization of effects of interest is usually induced indirectly by applying spatial smoothing to the data during preprocessing. While this procedure often works well, the resulting inference can be poorly calibrated. Spatial modeling of effects of interest leads to more powerful analyses; however, the number of locations in a typical neuroimage can preclude standard computing methods in this setting. Here, we contribute a Bayesian spatial regression model for group-level neuroimaging analyses. We induce regularization of spatially varying regression coefficient functions through Gaussian process priors. When combined with a simple non-stationary model for the error process, our prior hierarchy can lead to more data-adaptive smoothing than standard methods. We achieve computational tractability through a Vecchia-type approximation of our prior that retains full spatial rank and can be constructed for a wide class of spatial correlation functions. We outline several ways to work with our model in practice and compare performance against standard vertex-wise analyses and several alternatives. Finally, we illustrate our methods in an analysis of cortical surface functional magnetic resonance imaging task contrast data from a large cohort of children enrolled in the adolescent brain cognitive development study.

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Prenatal alcohol exposure poses significant risks to offspring mental health. However, the interplay between genetic predispositions to mental health disorders and prenatal alcohol exposure remains incompletely understood, limiting our ability to develop effective interventions for these conditions.

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Along with pubertal development, the transition to adolescence brings about increased risk for sleep disturbances and mental health problems. Functional connectivity of overlapping large-scale brain networks, such as increased connectivity between the default mode and dorsal attention networks, has been reported to relate to both sleep and mental health problems. Clarifying whether pubertal development interacts with sleep disturbances and functional brain networks to predict mental health may provide information to improve the timing and design of interventions targeting sleep disturbances in adolescents.

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Considering the growing threat of climate change and the current youth mental health crisis, data are needed on the relationship between climate and youth mental health. Hot weather contributes to the mental health burden, specifically aggression. We studied associations between extreme heat and externalizing symptoms or suicidal behavior among US preadolescents.

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Structural anomalies in the frontal lobe and basal ganglia have been reported in patients with attention-deficit/hyperactivity disorder (ADHD). However, these findings have been not always consistent because of ADHD diversity. This study aimed to identify ADHD subtypes based on cognitive function and find their distinct brain structural characteristics.

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Postmortem investigations in autism have identified anomalies in neural cytoarchitecture across limbic, cerebellar, and neocortical networks. These anomalies include narrow cell mini-columns and variable neuron density. However, difficulty obtaining sufficient post-mortem samples has often prevented investigations from converging on reproducible measures. Recent advances in processing magnetic resonance diffusion weighted images (DWI) make in vivo characterization of neuronal cytoarchitecture a potential alternative to post-mortem studies. Using extensive DWI data from the Adolescent Brain Cognitive Development (ABCD®) study 142 individuals with an autism diagnosis were compared with 8971 controls using a restriction spectrum imaging (RSI) framework that characterized total neurite density (TND), its component restricted normalized directional diffusion (RND), and restricted normalized isotropic diffusion (RNI). A significant decrease in TND was observed in autism in the right cerebellar cortex (β = -0.005, SE =0.0015, p = 0.0267), with significant decreases in RNI and significant increases in RND found diffusely throughout posterior and anterior aspects of the brain, respectively. Furthermore, these regions remained significant in post-hoc analysis when the autism sample was compared against a subset of 1404 individuals with other psychiatric conditions (pulled from the original 8971). These findings highlight the importance of characterizing neuron cytoarchitecture in autism and the significance of their incorporation as physiological covariates in future studies.

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Exposure to adversity in childhood is a risk factor for lifetime mental health problems. Altered pace of biological aging, as measured through pubertal timing, is one potential explanatory pathway for this risk. This study examined whether pubertal timing mediated the association between adversity (threat and deprivation) and adolescent mental health problems (internalizing and externalizing), and whether this was moderated by sex.

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Adolescent substance use (SU) is often motivated by a desire to alleviate undesirable symptoms. To test the self-medication hypothesis, we examined associations between comorbid psychologic and somatic symptom trajectories across early adolescence and early onset SU.

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We investigate whether neural, cognitive, and psychopathology phenotypes that are more strongly related to genetic differences are less strongly associated with family- and state-level economic contexts (N = 5374 individuals with 1KG-EUR-like genotypes with 870 twins, from the Adolescent Behavior and Cognitive Development study). We estimated the twin- and SNP-based heritability of each phenotype, as well as its association with an educational attainment polygenic index (EA PGI). We further examined associations with family socioeconomic status (SES) and tested whether SES-related differences were moderated by state cost of living and social safety net programs (Medicaid expansion and cash assistance). SES was broadly associated with cognition, psychopathology, brain volumes, and cortical surface areas, even after controlling for the EA PGI. Brain phenotypes that were more heritable or more strongly associated with the EA PGI were not, overall, less related to SES, nor were SES-related differences in these phenotypes less moderated by macroeconomic context and policy. Informing a long-running theoretical debate, and contra to widespread lay beliefs, results suggest that aspects of child brain development that are more strongly related to genetic differences are not, in general, less associated with socioeconomic contexts and policies.

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Parental suicide attempts and suicide death increase suicide risk in their offspring. High levels of impulsivity have been observed in families at high risk for suicide. Impulsivity, a highly heritable trait that is especially elevated in childhood, is frequently measured with the UPPS-P Impulsive Behavior Scale, which includes negative urgency, positive urgency, sensation seeking, premeditation, and perseverance. Our study examined the association between the UPPS-P facets and suicide ideation (without suicide attempts) and suicide attempts at baseline and first-time endorsement within the next two years in childhood. We also examined how the UPPS-P facets mediated the association between parental suicide attempts and suicide death and offspring first-time suicide ideation and attempts at follow-up.

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The previous cross-sectional and prospective studies have reported that psychopathology was associated with the occurrence of psychotic-like experiences (PLEs). However, few of these studies have examined this longitudinal association considering the different developmental trajectories of PLEs, as well as the growth or changes of psychopathology over time.

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To evaluate the prevalence of weight discrimination (the perception of being treated unfairly based on weight) and its sociodemographic associations among early adolescents aged 10 to 13 in the United States.

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Socioeconomic resources (SER) calibrate the developing brain to the current context, which can confer or attenuate risk for psychopathology across the lifespan. Recent multivariate work indicates that SER levels powerfully relate to intrinsic functional connectivity patterns across the entire brain. Nevertheless, the neuroscientific meaning of these widespread neural differences remains poorly understood, despite its translational promise for early risk identification, targeted intervention, and policy reform. In the present study, we leverage graph theory to precisely characterize multivariate and univariate associations between SER across household and neighborhood contexts and the intrinsic functional architecture of brain regions in 5,821 youth (9-10 years) from the Adolescent Brain Cognitive Development Study. First, we establish that decomposing the brain into profiles of integration and segregation captures more than half of the multivariate association between SER and functional connectivity with greater parsimony (100-fold reduction in number of features) and interpretability. Second, we show that the topological effects of SER are not uniform across the brain; rather, higher SER levels are associated with greater integration of somatomotor and subcortical systems, but greater segregation of default mode, orbitofrontal, and cerebellar systems. Finally, we demonstrate that topological associations with SER are spatially patterned along the unimodal-transmodal gradient of brain organization. These findings provide critical interpretive context for the established and widespread associations between SER and brain organization. This study highlights both higher-order and somatomotor networks that are differentially implicated in environmental stress, disadvantage, and opportunity in youth.

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Evidence that breastfeeding impacts the facial features of children is conflicting. Most studies to date have focused on dental and skeletal malocclusion. It currently remains unclear whether such effects are of sufficient magnitude to be detectable on outward facial appearance. Here, we evaluate the extent to which maternally reported breastfeeding is associated with 3D facial shape in a large adolescent cohort. After extracting 3D facial surfaces from MR scans in 2275 9- and 10-year-old children and aligning the surfaces in dense correspondence, we analyzed the effect of breastfeeding on shape as a dichotomous (no/yes) and semi-quantitative (to assess duration in months) variable using partial least squares regression. Our results showed no effect (p = 0.532) when breastfeeding was dichotomized. However, when treated as a semi-quantitative variable, breastfeeding duration was associated with statistically significant changes in shape (p = 3.61x 10-4). The most prominent facial changes included relative retrusion of the central midface, zygomatic arches, and orbital regions along with relative protrusion of forehead, cheek, and mandible. The net effect was that as breastfeeding duration increased, the facial profile in children became flatter (less convex). The observed effects on the face, however, were subtle and likely not conspicuous enough to be noticed by most observers. This was true even when comparing the faces of children breastfed for 19-24 months to children with no reported breastfeeding. Thus, breastfeeding does appear to have detectable effect on outward facial appearance in adolescent children, but its practical impact appears to be minimal.

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Despite the growing epidemic of paediatric obesity, questions remain regarding potential neural mechanisms for individual risk. Delay discounting is a cognitive process of comparison of valuation between immediate and delayed reward, which has been inconsistently linked to weight status. Moreover, central to the brain’s reward system is the nucleus accumbens, a region structurally and functionally altered in obesity.

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Predicting substance use in adolescence is a difficult yet important task in developing effective prevention. We aim to extend previous findings on the linear associations between familiarity with (knowledge of) substances in childhood and subsequent substance use in adolescence through a latent class analysis (LCA) to create risk profiles based on substance familiarity.

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Substance use in youth remains a pressing problem in the United States. Existing studies have shown the importance of neuropathways responsible for affective response and reward motivation in adolescents’ substance use initiation and maintenance. However, limited observational studies have explored the relationship between aspects of behavioral motivation traits and the likelihood of substance use initiation in adolescents. In this prospective cohort study, we assessed the associations between behavioral motivation traits based on the Behavioral Inhibition and Approach Systems (BIS-BAS) Scale and substance use initiation using data from the Adolescent Brain Cognitive Development (ABCD) study.

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This study aimed to compare the neuropsychological function in early adolescence between children born small for gestational age (SGA) or large for gestational age (LGA) and those born appropriate for gestational age (AGA).

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Our aim was to examine associations between transgender identity and sleep disturbance in a demographically diverse, national sample of U.S. early adolescents. We conducted a cross-sectional analysis of the Adolescent Brain Cognitive Development Study from Year 3 (2019-2021, = 10,277, 12-13 years) to investigate the association between transgender identity and caregiver-reported measures of their adolescent’s sleep, assessed by the Sleep Disturbance Scale for Children. Transgender adolescents had a higher risk of overall sleep disturbance and symptoms of insomnia and excessive sleepiness. Furthermore, per caregiver report, transgender adolescents were more likely to have shorter sleep duration categories; particularly concerning is the significant risk of <5 hours of sleep for transgender adolescents compared with their cisgender peers. These findings indicate that transgender adolescents had worse caregiver-reported sleep outcomes compared to cisgender peers. This study highlights the need for screenings and interventions targeted at improving sleep among transgender adolescents.

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The Adolescent Brain Cognitive Development (ABCD) study is a longitudinal study of US adolescents with a wide breadth of psychiatric, neuroimaging and genetic data that can be leveraged to better understand psychiatric diseases. The reliability and validity of the psychiatric data collected have not yet been examined. This study aims to explore and optimize the reliability/validity of psychiatric diagnostic constructs in the ABCD study.

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Neural consequences of social disparities are not yet rigorously investigated. How socioeconomic conditions influence children’s connectome development remains unknown. This paper endeavors to gauge how precisely the connectome structure of the brain can predict an individual’s social environment, thereby inversely assessing how social influences are engraved in the neural development of the Adolescent brain. Utilizing Adolescent Brain and Cognition Development (ABCD) data (9099 children residing in the United States), we found that social conditions both at the household and neighborhood levels are significantly associated with specific neural connections. Solely with brain connectome data, we train a linear support vector machine (SVM) to predict socio-economic conditions of those adolescents. The classification performance generally improves when the thresholds of the advantageous and disadvantageous environments compartmentalize the extreme cases. Among the tested thresholds, the 20th and 80th percentile thresholds using the dual combination of household income and neighborhood education yielded the highest Area Under the Precision-Recall Curve (AUPRC) of 0.8224. We identified 8 significant connections that critically contribute to predicting social environments in the parietal lobe and frontal lobe. Insights into social factors that contribute to early brain connectome development is critical to mitigate the disadvantages of children growing up in unfavorable neighborhoods.

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Recent advancements in neuroimaging have led to greater data sharing among the scientific community. However, institutions frequently maintain control over their data, citing concerns related to research culture, privacy, and accountability. This creates a demand for innovative tools capable of analyzing amalgamated datasets without the need to transfer actual data between entities. To address this challenge, we propose a decentralized sparse federated learning (FL) strategy. This approach emphasizes local training of sparse models to facilitate efficient communication within such frameworks. By capitalizing on model sparsity and selectively sharing parameters between client sites during the training phase, our method significantly lowers communication overheads. This advantage becomes increasingly pronounced when dealing with larger models and accommodating the diverse resource capabilities of various sites. We demonstrate the effectiveness of our approach through the application to the Adolescent Brain Cognitive Development (ABCD) dataset.

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Sleep and internalizing problems escalate during adolescence and can negatively impact long-term health. However, the directionality of this risk-relationship remains poorly understood within a developmental context. The current study aimed to determine the directionality of this relationship in adolescents with no history of psychiatric disorder and whether sex at birth played a role in this relationship.

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To deepen the development of positive affect during early adolescence and shed new light on its predictors, this study adopts an exploratory network approach to first identify the main domains that describe the variability of children’s psychological, environmental, and behavioral characteristics, and then use these domains to longitudinally predict positive affect and its development within a latent growth framework. To this aim, we considered 10,904 US participants (9 years old at baseline; 13 years old 42 months later), six measurement occasions of positive affect, and 46 baseline indicators from the ABCD study. Our results not only confirm that positive affect declines between 9 and 13 years old, but also show that among the five domains identified (behavioral dysregulation, cognitive functioning, psychological problems, supportive social environment, and extracurricular activities), only a supportive social environment consistently predicts positive affect. This is crucial for practitioners and policymakers, as it can help them focus on the elements within our complex network of psychological, social, and environmental variability.

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The current study demonstrates that an individual’s resting-state functional connectivity (RSFC) is a dependable biomarker for identifying differential patterns of cognitive and emotional functioning during late childhood. Using baseline RSFC data from the Adolescent Brain Cognitive Development (ABCD) study, which includes children aged 9-11, we identified four distinct RSFC subtypes. We introduce an integrated methodological pipeline for testing the reliability and importance of these subtypes. In the Identification phase, Leiden Community Detection defined RSFC subtypes, with their reproducibility confirmed through a split-sample technique in the Validation stage. The Evaluation phase showed that distinct cognitive and mental health profiles are associated with each subtype, with the Predictive phase indicating that subtypes better predict various cognitive and mental health characteristics than individual RSFC connections. The Replication stage employed bootstrapping and down-sampling methods to substantiate the reproducibility of these subtypes further. This work allows future explorations of developmental trajectories of these RSFC subtypes.

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Since the birth of cognitive science, researchers have used reaction time and accuracy to measure cognitive ability. Although recognition of these two measures is often based on empirical observations, the underlying consensus is that most cognitive behaviors may be along two fundamental dimensions: cognitive processing speed (CPS) and cognitive processing accuracy (CPA). In this study, we used genomic-wide association studies (GWAS) data from 14 cognitive traits to show the presence of those two factors and revealed the specific neurobiological basis underlying them. We identified that CPS and CPA had distinct brain phenotypes (e.g. white matter microstructure), neurobiological bases (e.g. postsynaptic membrane), and developmental periods (i.e. late infancy). Moreover, those two factors showed differential associations with other health-related traits such as screen exposure and sleep status, and a significant causal relationship with psychiatric disorders such as major depressive disorder and schizophrenia. Utilizing an independent cohort from the Adolescent Brain Cognitive Development (ABCD) study, we also uncovered the distinct contributions of those two factors on the cognitive development of young adolescents. These findings reveal two fundamental factors underlying various cognitive abilities, elucidate the distinct brain structural fingerprint and genetic architecture of CPS and CPA, and hint at the complex interrelationship between cognitive ability, lifestyle, and mental health.

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Previous work suggests that cognitive and environmental risk factors may predict conversion to psychosis in individuals at clinical high risk (CHRs) for the disorder. Less clear, however, is whether these same factors are also associated with the initial emergence of the high risk state in individuals who do not meet current threshold criteria for being considered high risk.

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Despite preliminary evidence that links impulsivity to suicide risk among Native American youth, impulsivity has not been directly studied in relation to suicide ideation (SI) or behaviors in this population. We examined indexes of rapid-response impulsivity (RRI) across multiple levels of analysis (self-report, behavioral, neurobiological) and associations with SI among Native American youth ages 9-10 in the Adolescent Brain Cognitive Development Study.

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Depression is a common consequence of traumatic brain injury. Separately, spontaneous depression-arising without brain injury-has been linked to abnormal responses in motivational neural circuitry to the anticipation or receipt of rewards. It is unknown if post-injury and spontaneously occurring depression share similar phenotypic profiles. This issue is compounded by the fact that nearly all examinations of these psychiatric sequelae are : there are rarely any prospective assessments of mood and neural functioning before and after a brain injury. In this Stage 2 Registered Report, we used the Adolescent Brain Cognitive Development Consortium dataset to examine if a disruption in functional neural responses to rewards is present in patients with depression after a mild traumatic brain injury. Notably, this study provides an unparalleled opportunity to examine the trajectory of neuropsychiatric symptoms longitudinally within-subjects. This allowed us to isolate mild traumatic brain injury-specific variance independent from pre-existing functioning. Here, we focus on a case-control comparison between 43 youth who experienced a mild traumatic brain injury between MRI visits, and 43 well-matched controls. Contrary to pre-registered predictions (https://osf.io/h5uba/), there was no statistically credible increase in depression in mild traumatic brain injury cases relative to controls. Mild traumatic brain injury was associated with subtle changes in motivational neural circuit recruitment during the anticipation of incentives on the Monetary Incentive Delay paradigm. Specifically, changes in neural recruitment appeared to reflect a failure to deactivate ‘task-negative’ brain regions (ventromedial prefrontal cortex), alongside blunted recruitment of ‘task-positive’ regions (anterior cingulate, anterior insula and caudate), during the anticipation of reward and loss in adolescents following mild brain injuries. Critically, these changes in brain activity were not correlated with depressive symptoms at either visit or depression change scores before and after the brain injury. Increased time since injury was associated with a recovery of cognitive functioning-driven primarily by processing speed differences-but depression did not scale with time since injury. These cognitive changes were also uncorrelated with neural changes after mild traumatic brain injury. This report provides evidence that acquired depression may not be observed as commonly after a mild traumatic brain injury in late childhood and early adolescence, relative to findings in adult cases. Several reasons for these differing findings are considered, including sampling enrichment in retrospective cohort studies, under-reporting of depressive symptoms in parent-report data, and neuroprotective factors in childhood and adolescence.

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Emerging research evidence suggests positive relationships between higher screen time and eating disorders. However, few studies have examined the prospective associations between screen use and eating disorder symptoms in early adolescents and how problematic screen use may contribute to symptom development.

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Decades of neuroimaging studies have shown modest differences in brain structure and connectivity in depression, hindering mechanistic insights or the identification of risk factors for disease onset. Furthermore, whereas depression is episodic, few longitudinal neuroimaging studies exist, limiting understanding of mechanisms that drive mood-state transitions. The emerging field of precision functional mapping has used densely sampled longitudinal neuroimaging data to show behaviourally meaningful differences in brain network topography and connectivity between and in healthy individuals, but this approach has not been applied in depression. Here, using precision functional mapping and several samples of deeply sampled individuals, we found that the frontostriatal salience network is expanded nearly twofold in the cortex of most individuals with depression. This effect was replicable in several samples and caused primarily by network border shifts, with three distinct modes of encroachment occurring in different individuals. Salience network expansion was stable over time, unaffected by mood state and detectable in children before the onset of depression later in adolescence. Longitudinal analyses of individuals scanned up to 62 times over 1.5 years identified connectivity changes in frontostriatal circuits that tracked fluctuations in specific symptoms and predicted future anhedonia symptoms. Together, these findings identify a trait-like brain network topology that may confer risk for depression and mood-state-dependent connectivity changes in frontostriatal circuits that predict the emergence and remission of depressive symptoms over time.

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The transition to adolescence is a critical period for mental health development. Socio-experiential environments play an important role in the emergence of depressive symptoms with some adolescents showing more sensitivity to social contexts than others. Drawing on recent developmental neuroscience advances, we examined whether hippocampal volume amplifies social context effects in the transition to adolescence. We analyzed 2-y longitudinal data from the Adolescent Brain Cognitive Development (ABCD) study in a diverse sample of 11,832 youth (mean age: 9.914 y; range: 8.917 to 11.083 y; 47.8% girls) from 21 sites across the United States. Socio-experiential environments (i.e., family conflict, primary caregiver’s depressive symptoms, parental warmth, peer victimization, and prosocial school environment), hippocampal volume, and a wide range of demographic characteristics were measured at baseline. Youth’s symptoms of major depressive disorder were assessed at both baseline and 2 y later. Multilevel mixed-effects linear regression analyses showed that negative social environments (i.e., family conflict, primary caregiver’s depressive symptoms, and peer victimization) and the absence of positive social environments (i.e., parental warmth and prosocial school environment) predicted greater increases in youth’s depressive symptoms over 2 y. Importantly, left hippocampal volume amplified social context effects such that youth with larger left hippocampal volume experienced greater increases in depressive symptoms in more negative and less positive social environments. Consistent with brain-environment interaction models of mental health, these findings underscore the importance of families, peers, and schools in the development of depression during the transition to adolescence and show how neural structure amplifies social context sensitivity.

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This observational study compared children with and without binge eating (BE) on biobehavioral measures of reward responsiveness, inhibitory control, and emotion processes, while accounting for the impact of weight.

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Suicide is a leading cause of death among adolescents, who demonstrate high rates of sleep disturbance. Poor sleep appears to confer risk for suicide, but longitudinal investigation of suicidal behaviors remains rare, particularly in the transition from childhood to early adolescence.

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Major depressive disorder (MDD) in adolescence is a risk factor for poor physical and psychiatric outcomes in adulthood, with earlier age of onset associated with poorer outcomes. Identifying Depression Early in Adolescence Risk Score (IDEA-RS) is a model for predicting MDD in youth aged >15 years, but replication in younger samples (<15 years) is lacking. Here, we tested IDEA-RS in a younger sample (9-11 years) to assess whether IDEA-RS could be applied to earlier onset depression.

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Studies suggest that prosocial behavior, having high empathy and engaging in behaviors intended to benefit others, may predict mental health or vice versa; however, these findings have been mixed. The purpose of the current study was to examine the bidirectional relationships between prosocial behavior and dimensions of psychopathology in children.

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Studies linking mental health with brain function in cross-sectional population-based association studies have historically relied on small, underpowered samples. Given the small effect sizes typical of such brain-wide associations, studies require samples into the thousands to achieve the statistical power necessary for replicability. Here, we detail how small sample sizes have hampered replicability and provide sample size targets given established association strength benchmarks. Critically, while replicability will improve with larger samples, it is not guaranteed that observed effects will meaningfully apply to target populations of interest (i.e., be generalizable). We discuss important considerations related to generalizability in psychiatric neuroimaging and provide an example of generalizability failure due to “shortcut learning” in brain-based predictions of mental health phenotypes. Shortcut learning is a phenomenon whereby machine learning models learn an association between the brain and an unmeasured construct (the shortcut), rather than the intended target of mental health. Given the complex nature of brain-behavior interactions, the future of epidemiological approaches to brain-based studies of mental health will require large, diverse samples with comprehensive assessment.

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The successful implementation and interpretation of machine learning (ML) models in epidemiological studies can be challenging without an extensive programming background. We provide a didactic example of machine learning for risk prediction in this study by determining whether early life factors could be useful for predicting adolescent psychopathology.

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Mental illnesses are a leading cause of disability globally, and functional disability is often in part caused by cognitive impairments across psychiatric disorders. However, studies have consistently reported seemingly opposite findings regarding the association between cognition and psychiatric symptoms.

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To determine whether anxiety and depression symptoms are mechanisms through which adverse childhood experiences (ACEs) contribute toward persistent/recurrent pain (PRP) across early adolescence.

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The human brain experiences functional changes through childhood and adolescence, shifting from an organizational framework anchored within sensorimotor and visual regions into one that is balanced through interactions with later-maturing aspects of association cortex. Here, we link this profile of functional reorganization to the development of ventral attention network connectivity across independent datasets. We demonstrate that maturational changes in cortical organization link preferentially to within-network connectivity and heightened degree centrality in the ventral attention network, whereas connectivity within network-linked vertices predicts cognitive ability. This connectivity is associated closely with maturational refinement of cortical organization. Children with low ventral attention network connectivity exhibit adolescent-like topographical profiles, suggesting that attentional systems may be relevant in understanding how brain functions are refined across development. These data suggest a role for attention networks in supporting age-dependent shifts in cortical organization and cognition across childhood and adolescence.

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The neurobiological basis of working memory and delay discounting are theorized to overlap, but few studies have empirically examined these relations in large samples. To address this, we investigated the association of neural activation during an fMRI N-Back working memory task with delay discounting area, as well as in- and out-of-scanner working memory measures. These analyses were conducted in two large task fMRI datasets, the Human Connectome Project and the Adolescent Brain Cognitive Development Study. Although in- and out-of-scanner working memory performance were significantly associated with N-back task brain activation regions, contrary to our hypotheses, there were no significant associations between working memory task activation and delay discounting scores. These findings call into question the extent of the neural overlap in delay discounting and working memory and highlight the need for more investigations directly interrogating overlapping and distinct brain regions across cognitive neuroscience tasks.

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Persistent distressing psychotic-like experiences (PLE) are associated with impaired functioning and future psychopathology. Prior research suggests that physical activities may be protective against psychopathology. However, it is unclear whether physical activities may interact with genetics in the development of psychosis.

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Preterm-born (PTB) children are at an elevated risk for neurocognitive difficulties in general and language difficulties more specifically. Environmental factors such as socio-economic status (SES) play a key role for Term children’s language development. SES has been shown to predict PTB children’s behavioral developmental trajectories, sometimes surpassing its role for Term children. However, the role of SES in the neurocognitive basis of PTB children’s language development remains uncharted. Here, we aimed to evaluate the role of SES in the neural basis of PTB children’s language performance. Leveraging the Adolescent Brain Cognitive Development (ABCD) Study, the largest longitudinal study of adolescent brain development and behavior to date, we showed that prematurity status (PTB versus Term) and multiple aspects of SES additively predict variability in cortical thickness, which is in turn related to children’s receptive vocabulary performance. We did not find evidence to support the differential role of environmental factors for PTB versus Term children, underscoring that environmental factors are significant contributors to development of both Term and PTB children. Taken together, our results suggest that the environmental factors influencing language development might exhibit similarities across the full spectrum of gestational age.

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Most research to understand postacute sequelae of SARS-CoV-2 infection (PASC), or long COVID, has focused on adults, with less known about this complex condition in children. Research is needed to characterize pediatric PASC to enable studies of underlying mechanisms that will guide future treatment.

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It is unclear how family factors affect health care utilization among youth with persistent or recurrent pain, despite potential relevance to interventions targeting treatment barriers.

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Many psychopathologies tied to internalizing symptomatology emerge during adolescence, therefore identifying neural markers of internalizing behavior in childhood may allow for early intervention. We utilized data from the Adolescent Brain and Cognitive Development (ABCD) Study® to evaluate associations between cortico-amygdalar functional connectivity, polygenic risk for depression (PRS), traumatic events experienced, internalizing behavior, and internalizing subscales: withdrawn/depressed behavior, somatic complaints, and anxious/depressed behaviors. Data from 6371 children (ages 9-11) were used to analyze amygdala resting-state fMRI connectivity to Gordon parcellation based whole-brain regions of interest (ROIs). Internalizing behaviors were measured using the parent-reported Child Behavior Checklist. Linear mixed-effects models were used to identify patterns of cortico-amygdalar connectivity associated with internalizing behaviors. Results indicated left amygdala connections to auditory, frontoparietal network (FPN), and dorsal attention network (DAN) ROIs were significantly associated with withdrawn/depressed symptomatology. Connections relevant for withdrawn/depressed behavior were linked to social behaviors. Specifically, amygdala connections to DAN were associated with social anxiety, social impairment, and social problems. Additionally, an amygdala connection to the FPN ROI and the auditory network ROI was associated with social anxiety and social problems, respectively. Therefore, it may be important to account for social behaviors when looking for brain correlates of depression.

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Irritability, or an increased proneness to frustration and anger, is common in youth; however, few studies have examined neurostructural correlates of irritability in children. The purpose of the current study was to examine concurrent and longitudinal associations between brain structure and irritability in a large sample of 9-10-year-old children. Participants included 10,647 children from the Adolescent Brain Cognitive Development Study (ABCD Study). We related a latent irritability factor to gray matter volume, cortical thickness, and surface area in 68 cortical regions and to gray matter volume in 19 subcortical regions using structural equation modeling. Multiple comparisons were adjusted for using the false discovery rate (FDR). After controlling for age, sex, race/ethnicity, scanner model, parent’s highest level of education, medication use, and total intracranial volume, irritability was associated with smaller volumes in primarily temporal and parietal regions at baseline. Longitudinal analyses showed that baseline gray matter volume did not predict irritability symptoms at the 3rd-year follow-up. No significant associations were found for cortical thickness or surface area. The current study demonstrates inverse associations between irritability and volume in regions implicated in emotional processing/social cognition, attention allocation, and movement/perception. We advance prior research by demonstrating that neurostructural differences associated with irritability are already apparent by age 9-10 years, extending this work to children and supporting theories positing socioemotional deficits as a key feature of irritability.

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Elevated pediatric irritability is a transdiagnostic symptom that predicts multiple mental health problems in adolescence and adulthood. Altered top-down regulatory networks, such as inhibitory control networks that suppress an impulse in favor of goal-directed behavior, are thought to contribute to high levels of youth irritability. Nevertheless, little work has examined links between youth irritability and neural processes supporting inhibitory control in large diverse samples, nor have they focused on the key period ramping up to adolescence (i.e., preadolescence).

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Adolescents encounter a complex digital environment, yet existing data on youth technology use rarely differentiates technology subtypes. This study maps the evolution and intricacies of youth engagement with technology subtypes.

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Cannabis legalization has triggered an increase in prenatal cannabis use. Given that tobacco is commonly co-used with cannabis, determining outcomes associated with prenatal cannabis and tobacco co-exposure is crucial. While literature exists regarding the individual effects of prenatal cannabis and tobacco exposure on childhood behaviour, there is a gap regarding their combined use, which may have interactive effects. Therefore, we investigated whether prenatal cannabis and tobacco co-exposure was associated with greater externalizing and internalizing problems in middle childhood compared to prenatal exposure to either substance alone or no exposure.

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Preterm birth poses a major public health challenge, with significant and heterogeneous developmental impacts. Latent profile analysis was applied to the National Institutes of Health Toolbox performance of 1891 healthy prematurely born children from the Adolescent Brain and Cognitive Development study (970 boys, 921 girls; 10.00 ± 0.61 years; 1.3% Asian, 13.7% Black, 17.5% Hispanic, 57.0% White, 10.4% Other). Three distinct neurocognitive profiles emerged: consistently performing above the norm (19.7%), mixed scores (41.0%), and consistently performing below the norm (39.3%). These profiles were associated with lasting cognitive, neural, behavioral, and academic differences. These findings underscore the importance of recognizing diverse developmental trajectories in prematurely born children, advocating for personalized diagnosis and intervention to enhance care strategies and long-term outcomes for this heterogeneous population.

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Prospective associations between preadolescent neurocognitive structure and onset of substance use in adolescence have not been examined. This study investigated associations between cognitive structure among youth aged 9 – 10 years and the likelihood of experimentation with tobacco and alcohol by ages 13-14 years.

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Few studies have explored the interplay of how individual identity, parental, familial, and contextual factors impact associations between Latinx adolescent adversities and psychopathology. This study aimed to examine if these factors mediate the relationship between adversities and psychopathology in Latinx youth.

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To determine disparities in adverse childhood experiences (ACEs) by sexual identity in a national cohort of early adolescents.

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Positive and negative alcohol expectancies (PAEs and NAEs, respectively) and impulsivity are key risk factors for the onset of alcohol use. While both factors independently contribute to alcohol initiation, the developmental aspects of AEs and their nuanced relationship with impulsivity are not adequately understood. Understanding these relationships is imperative for developing targeted interventions to prevent or delay alcohol use onset in youth.

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The prevalence of internalizing psychopathology rises precipitously from early to mid-adolescence, yet the underlying neural phenotypes that give rise to depression and anxiety during this developmental period remain unclear.

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This study used latent transition analysis to examine the stability and change in perceived threats in youth’s primary social contexts-neighborhoods, schools, and families-and associations with emotional and behavioral problems when youth transitioned from childhood to adolescence. The sample included 8208 racially and ethnically diverse youth enrolled in the Adolescent Brain Cognitive Development Study (47.4% female, M = 9.83, M = 11.99). Results revealed that while perceived threats in youth’s neighborhoods were considerably stable, perceived threats in youth’s families fluctuated in relation to stressful life events. Further, subgroups of youth characterized by elevated perceived threat experiences in different contexts showed differential associations with emotional and behavioral problems. Overall, findings highlight the importance of considering the stability of perceived threats to direct appropriate interventions.

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Chronotype refers to individual preference in circadian cycles and is associated with psychiatric problems. It is mainly classified into early (those who prefer to be active in the morning and sleep and wake up early) and late (those who prefer to be active in the evening and sleep and wake up late) chronotypes. Although previous research has demonstrated associations between chronotype and cognitive function and brain structure in adults, little is known regarding these associations in children. Here, we aimed to investigate the relationship between chronotype and cognitive function in children. Moreover, based on the significant association between chronotype and specific cognitive functions, we extracted regions-of-interest (ROI) and examined the association between chronotype and ROI volumes.

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Exposure to high levels of fine particulate matter (PM) with aerodynamic diameter () via air pollution may be a risk factor for psychiatric disorders during adulthood. Yet few studies have examined associations between exposure and the trajectory of symptoms across late childhood and early adolescence.

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Youth screen media activity is a growing concern, though few studies include objective usage data. Through the longitudinal, U.S.-based Adolescent Brain Cognitive Development (ABCD) Study, youth (m = 14; n = 1415) self-reported their typical smartphone use and passively recorded three weeks of smartphone use via the ABCD-specific Effortless Assessment Research System (EARS) application. Here we describe and validate passively-sensed smartphone keyboard and app use measures, provide code to harmonize measures across operating systems, and describe trends in adolescent smartphone use. Keyboard and app-use measures were reliable and positively correlated with one another (r = 0.33) and with self-reported use (rs = 0.21-0.35). Participants recorded a mean of 5 h of daily smartphone use, which is two more hours than they self-reported. Further, females logged more smartphone use than males. Smartphone use was recorded at all hours, peaking on average from 8 to 10 PM and lowest from 3 to 5 AM. Social media and texting apps comprised nearly half of all use. Data are openly available to approved investigators ( https://nda.nih.gov/abcd/ ). Information herein can inform use of the ABCD dataset to longitudinally study health and neurodevelopmental correlates of adolescent smartphone use.

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Although psychotic behaviors can be difficult to assess in children, early identification of children at high risk for the emergence of psychotic symptoms may facilitate the prevention of related disorders. Psychotic-like experiences (PLEs), or subthreshold thought and perceptual disturbances, could be early manifestations of psychosis that may predict a future diagnosis of a psychosis-related disorder or nonspecific correlates of a wide range of psychological problems. Additional research is needed regarding how PLEs map onto dimensions of psychopathology in children.

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Conduct disorder is associated with the highest burden of any mental disorder in childhood, yet its neurobiology remains unclear. Inconsistent findings limit our understanding of the role of brain structure alterations in conduct disorder. This study aims to identify the most robust and replicable brain structural correlates of conduct disorder.

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Air pollution is ubiquitous, yet questions remain regarding its impact on the developing brain. Large changes occur in white matter microstructure across adolescence, with notable differences by sex.

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Brain-phenotype predictive models seek to identify reproducible and generalizable brain-phenotype associations. External validation, or the evaluation of a model in external datasets, is the gold standard in evaluating the generalizability of models in neuroimaging. Unlike typical studies, external validation involves two sample sizes: the training and the external sample sizes. Thus, traditional power calculations may not be appropriate. Here we ran over 900 million resampling-based simulations in functional and structural connectivity data to investigate the relationship between training sample size, external sample size, phenotype effect size, theoretical power and simulated power. Our analysis included a wide range of datasets: the Healthy Brain Network, the Adolescent Brain Cognitive Development Study, the Human Connectome Project (Development and Young Adult), the Philadelphia Neurodevelopmental Cohort, the Queensland Twin Adolescent Brain Project, and the Chinese Human Connectome Project; and phenotypes: age, body mass index, matrix reasoning, working memory, attention problems, anxiety/depression symptoms and relational processing. High effect size predictions achieved adequate power with training and external sample sizes of a few hundred individuals, whereas low and medium effect size predictions required hundreds to thousands of training and external samples. In addition, most previous external validation studies used sample sizes prone to low power, and theoretical power curves should be adjusted for the training sample size. Furthermore, model performance in internal validation often informed subsequent external validation performance (Pearson’s r difference <0.2), particularly for well-harmonized datasets. These results could help decide how to power future external validation studies.

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Children’s brains dynamically adapt to the stimuli from the internal state and the external environment, allowing for changes in cognitive and mental behavior. In this work, we performed a large-scale analysis of dynamic functional connectivity (DFC) in children aged 9~11 years, investigating how brain dynamics relate to cognitive performance and mental health at an early age. A hybrid independent component analysis framework was applied to the Adolescent Brain Cognitive Development (ABCD) data containing 10,988 children. We combined a sliding-window approach with k-means clustering to identify five brain states with distinct DFC patterns. Interestingly, the occurrence of a strongly connected state with the most within-network synchrony and the anticorrelations between networks, especially between the sensory networks and between the cerebellum and other networks, was negatively correlated with cognitive performance and positively correlated with dimensional psychopathology in children. Meanwhile, opposite relationships were observed for a DFC state showing integration of sensory networks and antagonism between default-mode and sensorimotor networks but weak segregation of the cerebellum. The mediation analysis further showed that attention problems mediated the effect of DFC states on cognitive performance. This investigation unveils the neurological underpinnings of DFC states, which suggests that tracking the transient dynamic connectivity may help to characterize cognitive and mental problems in children and guide people to provide early intervention to buffer adverse influences.

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Trauma exposure (TE) and cognitive flexibility (CF) are risk factors for self-injurious thoughts and behaviors (SITBs). However, it is unknown whether these risk factors contribute to mechanisms associated with distinct categories of SITBs. The current study examined the potential moderating role of TE in the relationships between CF and multiple SITBs, including active suicidal ideation (SI), passive SI, non-suicidal self-injury (NSSI), and history of suicide attempt (SA), among pre-adolescent children.

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Different types of early-life adversity have been associated with children’s brain structure and function. However, understanding the disparate influence of distinct adversity exposures on the developing brain remains a major challenge.

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Twin births are related with maternal and fetal adverse outcomes. Little was known about the comparability of the cognitive, behavioral development and brain structure between twins and singletons in early adolescence. This retrospective cohort study was based on data from the United States population-based, prospective, longitudinal observational Adolescent Brain Cognitive Development study. Children with complete twin status information were enrolled, and the exposure variable was twin status. Primary outcomes were cognitive, behavioral development and brain structure in early adolescence. Cognitive and behavioral outcomes were assessed by using the NIH Toolbox and Child Behavioral Checklist, respectively. Brain structure was evaluated by the cortical thickness, area, and volume extracted from the magnetic resonance imaging (MRI) data. Subgroup analyses were conducted by prematurity, birth weight, with sibling, genetic profiles, and twin types (zygosity). From 1st September 2016 to 15th November 2018, 11545 children (9477 singletons and 2068 twins) aged 9-10 years were enrolled. Twins showed mildly lower cognitive performance (|t|> 5.104, P-values < 0.001, False Discovery Rate [FDR] < 0.001), better behavioral outcome (|t|> 2.441, P-values < 0.015, FDR < 0.042), such as lower scores for multiple psychiatric disorders and behavioral issues, and smaller cortical volume (t = - 3.854, P-values < 0.001, FDR < 0.001) and cortical area (t = - 3.872, P-values < 0.001, FDR < 0.001). The observed differences still held when stratified for prematurity, birth weight, presence of siblings, genetic profiles, and twin types (zygosity). Furthermore, analyses on the two-year follow-up data showed consistent results with baseline data. Twin status is associated with lower cognitive and better behavioral development in early adolescence accompanied by altered brain structure. Clinicians should be aware of the possible difference when generalizing results from adolescent twin samples to singletons.

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Decades of research document an association between neurocognitive dysfunction and externalizing behaviors, including rule-breaking, aggression, and impulsivity. However, there has been very little work that examines how multiple neurocognitive functions co-occur within individuals and which combinations of neurocognitive functions are most relevant for externalizing behaviors. Moreover, Latent Profile Analysis (LPA), a widely used method for grouping individuals in person-centered analysis, often struggles to balance the tradeoff between good model fit (splitting participants into many latent profiles) and model interpretability (using only a few, highly distinct latent profiles). To address these problems, we implemented a non-parametric Bayesian form of LPA based on the Dirichlet process mixture model (DPM-LPA) and used it to study the relationship between neurocognitive functioning and externalizing behaviors in adolescents participating in the Adolescent Brain Cognitive Development Study. First, we found that DPM-LPA outperformed conventional LPA, revealing more distinct profiles and classifying participants with higher certainty. Second, latent profiles extracted from DPM-LPA were differentially related to externalizing behaviors: profiles with deficits in working memory, inhibition, and/or language abilities were robustly related to different expressions of externalizing. Together, these findings represent a step towards addressing the challenge of finding novel ways to use neurocognitive data to better describe the individual. By precisely identifying and specifying the variation in neurocognitive and behavioral patterns this work offers an innovative empirical foundation for the development of assessments and interventions that address these costly behaviors.

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Attention-deficit/hyperactivity disorder (ADHD) is among the most prevalent, inheritable, and heterogeneous childhood-onset neurodevelopmental disorders. Children with a hereditary background of ADHD have heightened risk of having ADHD and persistent impairment symptoms into adulthood. These facts suggest distinct familial-specific neuropathological substrates in ADHD that may exist in anatomical components subserving attention and cognitive control processing pathways during development. The objective of this study is to investigate the topological properties of the gray matter (GM) structural brain networks in children with familial ADHD (ADHD-F), non-familial ADHD (ADHD-NF), as well as matched controls. A total of 452 participants were involved, including 132, 165 and 155 in groups of ADHD-F, ADHD-NF and typically developed children, respectively. The GM structural brain network was constructed for each group using graph theoretical techniques with cortical and subcortical structures as nodes and correlations between volume of each pair of the nodes within each group as edges, while controlled for confounding factors using regression analysis. Relative to controls, children in both ADHD-F and ADHD-NF groups showed significantly higher nodal global and nodal local efficiencies in the left caudal middle frontal gyrus. Compared to controls and ADHD-NF, children with ADHD-F showed distinct structural network topological patterns associated with right precuneus (significantly higher nodal global efficiency and significantly higher nodal strength), left paracentral gyrus (significantly higher nodal strength and trend toward significantly higher nodal local efficiency) and left putamen (significantly higher nodal global efficiency and trend toward significantly higher nodal local efficiency). Our results for the first time in the field provide evidence of familial-specific structural brain network alterations in ADHD, that may contribute to distinct clinical/behavioral symptomology and developmental trajectories in children with ADHD-F.

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Stress is associated with increased vulnerability to psychosis, yet the mechanisms that contribute to these effects are poorly understood. Substantial literature has linked reduced hippocampal volume to both psychosis risk and early life stress. However, less work has explored the direct and indirect effects of stress on psychosis through the hippocampus in preclinical samples- when vulnerability for psychosis is accumulating. The current paper leverages the Adolescent Brain Cognitive Development (ABCD) Study sample to examine whether objective psychosocial stressors, specifically adverse childhood experiences (ACE), are linked to vulnerability for psychosis, measured by psychotic-like experiences (PLE) severity, in late childhood and early adolescence, both directly and indirectly through the deleterious effects of stress on the hippocampus. Baseline data from 11,728 individuals included previously examined and validated items to assess ACE exposure, hippocampal volume, and PLE severity – a developmentally appropriate metric of risk for psychosis. Objective psychosocial stress exposure in childhood was associated with elevated PLE severity during the transition from childhood to adolescence. Hippocampal volume was significantly reduced in individuals with greater PLE severity and greater childhood stress exposure compared to peers with low symptoms or low stress exposure. These findings are consistent with a hippocampal vulnerability model of psychosis risk. Stress exposure may cumulatively impact hippocampal volume and may also reflect a direct pathway of psychosis risk. Objective psychosocial stress should be considered as a treatment target that may impact neurodevelopment and psychosis risk.

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Parental incarceration is an adverse childhood experience that inequitably burdens families of color and affects millions of U.S. children and adolescents. Although racialized disparities in exposure to parental incarceration are often acknowledged, researchers have yet to examine whether manifestations of racism may affect the link between parental incarceration and youth outcomes. This study provides a first look at how parental incarceration relates to health vulnerabilities in the Adolescent Brain Cognitive Development (ABCD) study, an ongoing, population-based study of U.S. children born between 2006 and 2008. We start by describing exposure to parental incarceration and then examine how parental incarceration, state-level racial prejudice, and discrimination relate to health risks among 9191 White (66%), Black (19%), or Hispanic (15%) youth. Consistent with what we know about pervasive racialized disparities in the U.S. criminal legal system, we find that 19.3% of Black children in our sample have experienced parental incarceration, followed by 7.8% of Hispanic children, and 4.8% of White children. Results of multilevel mixed models further indicate that parental incarceration was associated with increased health risks among White children whereas family economic hardship and discrimination experiences were more robustly associated with health vulnerabilities among Black and Hispanic children. Additional analyses explored whether parental incarceration was associated with other outcomes among Black and Hispanic children, revealing increased risk for behavior problems contingent upon parental incarceration and discrimination for Black children and Hispanic boys. Among Hispanic girls, parental incarceration was associated with increased risk of behavior problems in states with higher levels of racism. Results suggest that parental incarceration contributes to risk among early adolescents across racialized groups, but that the specific toll it takes depends on outcomes assessed and the context in which it occurs.

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The current study investigated the prospective relationships between parental monitoring, family conflict, and screen time across six screen time modalities in early adolescents in the USA.

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Girls and boys presenting disruptive behavior disorders (DBDs) display differences in white matter microstructure (WMM) relative to typically developing (TD) sex-matched peers. Boys with DBDs are at increased risk for traumatic brain injuries (TBIs), which are also known to impact WMM. This study aimed to disentangle associations of WMM with DBDs and TBIs.

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Suicide is the third-leading cause of death among US adolescents. Environmental and lifestyle factors influence suicidal behavior and can inform risk classification, yet quantifying and incorporating them in risk assessment presents a significant challenge for reproducibility and clinical translation.

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Having multiple previous generations with depression in the family increases offspring risk for psychopathology. Parental depression has been associated with smaller subcortical brain volumes in their children, but whether two prior generations with depression is associated with further decreases is unclear.

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A single dose of psilocybin, a psychedelic that acutely causes distortions of space-time perception and ego dissolution, produces rapid and persistent therapeutic effects in human clinical trials. In animal models, psilocybin induces neuroplasticity in cortex and hippocampus. It remains unclear how human brain network changes relate to subjective and lasting effects of psychedelics. Here we tracked individual-specific brain changes with longitudinal precision functional mapping (roughly 18 magnetic resonance imaging visits per participant). Healthy adults were tracked before, during and for 3 weeks after high-dose psilocybin (25 mg) and methylphenidate (40 mg), and brought back for an additional psilocybin dose 6-12 months later. Psilocybin massively disrupted functional connectivity (FC) in cortex and subcortex, acutely causing more than threefold greater change than methylphenidate. These FC changes were driven by brain desynchronization across spatial scales (areal, global), which dissolved network distinctions by reducing correlations within and anticorrelations between networks. Psilocybin-driven FC changes were strongest in the default mode network, which is connected to the anterior hippocampus and is thought to create our sense of space, time and self. Individual differences in FC changes were strongly linked to the subjective psychedelic experience. Performing a perceptual task reduced psilocybin-driven FC changes. Psilocybin caused persistent decrease in FC between the anterior hippocampus and default mode network, lasting for weeks. Persistent reduction of hippocampal-default mode network connectivity may represent a neuroanatomical and mechanistic correlate of the proplasticity and therapeutic effects of psychedelics.

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Resting-state functional connectivity (RSFC) is widely used to predict phenotypic traits in individuals. Large sample sizes can significantly improve prediction accuracies. However, for studies of certain clinical populations or focused neuroscience inquiries, small-scale datasets often remain a necessity. We have previously proposed a “meta-matching” approach to translate prediction models from large datasets to predict new phenotypes in small datasets. We demonstrated a large improvement over classical kernel ridge regression (KRR) when translating models from a single source dataset (UK Biobank) to the Human Connectome Project Young Adults (HCP-YA) dataset. In the current study, we propose two meta-matching variants (“meta-matching with dataset stacking” and “multilayer meta-matching”) to translate models from multiple source datasets across disparate sample sizes to predict new phenotypes in small target datasets. We evaluate both approaches by translating models trained from five source datasets (with sample sizes ranging from 862 participants to 36,834 participants) to predict phenotypes in the HCP-YA and HCP-Aging datasets. We find that multilayer meta-matching modestly outperforms meta-matching with dataset stacking. Both meta-matching variants perform better than the original “meta-matching with stacking” approach trained only on the UK Biobank. All meta-matching variants outperform classical KRR and transfer learning by a large margin. In fact, KRR is better than classical transfer learning when less than 50 participants are available for finetuning, suggesting the difficulty of classical transfer learning in the very small sample regime. The multilayer meta-matching model is publicly available athttps://github.com/ThomasYeoLab/Meta_matching_models/tree/main/rs-fMRI/v2.0.

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Adolescents exhibit remarkable heterogeneity in the structural architecture of brain development. However, due to limited large-scale longitudinal neuroimaging studies, existing research has largely focused on population averages, and the neurobiological basis underlying individual heterogeneity remains poorly understood. Here we identify, using the IMAGEN adolescent cohort followed up over 9 years (14-23 y), three groups of adolescents characterized by distinct developmental patterns of whole-brain gray matter volume (GMV). Group 1 show continuously decreasing GMV associated with higher neurocognitive performances than the other two groups during adolescence. Group 2 exhibit a slower rate of GMV decrease and lower neurocognitive performances compared with Group 1, which was associated with epigenetic differences and greater environmental burden. Group 3 show increasing GMV and lower baseline neurocognitive performances due to a genetic variation. Using the UK Biobank, we show these differences may be attenuated in mid-to-late adulthood. Our study reveals clusters of adolescent neurodevelopment based on GMV and the potential long-term impact.

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Lack of sleep has been found to be associated with cognitive impairment in children, yet the neural mechanism underlying this relationship remains poorly understood. To address this issue, this study utilized the data from the Adolescent Brain Cognitive Development (ABCD) study ( = 4930, aged 9-10), involving their sleep assessments, cognitive measures, and functional magnetic resonance imaging (fMRI) during an emotional n-back task. Using partial correlations analysis, we found that the out-of-scanner cognitive performance was positively correlated with sleep duration. Additionally, the activation of regions of interest (ROIs) in frontal and parietal cortices for the 2-back versus 0-back contrast was positively correlated with both sleep duration and cognitive performance. Mediation analysis revealed that this activation significantly mediated the relationship between sleep duration and cognitive function at both individual ROI level and network level. After performing analyses separately for different sexes, it was revealed that the mediation effect of the task-related activation was present in girls ( = 2546). These findings suggest that short sleep duration may lead to deficit in cognitive function of children, particularly in girls, through the modulation of frontoparietal activation during working memory load.

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Both cannabis use and depressive symptomology increase in prevalence throughout adolescence. Concurrently, the brain is undergoing neurodevelopment in important limbic regions, such as the amygdala. Prior research indicates the amygdala may also be related to cannabis use and depressive symptoms. We aimed to investigate the effects of adolescent cannabis use on amygdala volumes as well as the interaction of cannabis use and amygdala morphometry on depressive symptoms in youth.

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To progress adolescent mental health research beyond our present achievements – a complex account of brain and environmental risk factors without understanding neurobiological embedding in the environment – we need methods to unveil relationships between the developing brain and real-world environmental experiences.

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Sex and gender are associated with human behavior throughout the life span and across health and disease, but whether they are associated with similar or distinct neural phenotypes is unknown. Here, we demonstrate that, in children, sex and gender are uniquely reflected in the intrinsic functional connectivity of the brain. Somatomotor, visual, control, and limbic networks are preferentially associated with sex, while network correlates of gender are more distributed throughout the cortex. These results suggest that sex and gender are irreducible to one another not only in society but also in biology.

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Sex and gender differences exist in the prevalence and clinical manifestation of common brain disorders. Identifying their neural correlates may help improve clinical care.

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The human subcortex plays a pivotal role in cognition and is widely implicated in the pathophysiology of many psychiatric disorders. However, the heritability of functional gradients based on subcortico-cortical functional connectivity remains elusive. Here, leveraging twin functional MRI (fMRI) data from both the Human Connectome Project (n = 1023) and the Adolescent Brain Cognitive Development study (n = 936) datasets, we construct large-scale subcortical functional gradients and delineate an increased principal functional gradient pattern from unimodal sensory/motor networks to transmodal association networks. We observed that this principal functional gradient is heritable, and the strength of heritability exhibits a heterogeneous pattern along a hierarchical unimodal-transmodal axis in subcortex for both young adults and children. Furthermore, employing a machine learning framework, we show that this heterogeneous pattern of the principal functional gradient in subcortex can accurately discern the relationship between monozygotic twin pairs and dizygotic twin pairs with an accuracy of 76.2% (P < 0.001). The heritability of functional gradients is associated with the anatomical myelin proxied by MRI-derived T1-weighted/T2-weighted (T1w/T2w) ratio mapping in subcortex. This study provides new insights into the biological basis of subcortical functional hierarchy by revealing the structural and genetic properties of the subcortical functional gradients.

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This study aimed to investigate the relationships between four types of perceived discrimination (based on race/ethnicity, nationality/country of origin, gender identity, weight/body size), individually and cumulatively; positive childhood experiences (PCEs); and behavioral symptoms among pre-adolescent youth.

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Research has documented that adolescent sleep is impacted by various stressors, including interpersonal experiences and structural disadvantage. This study extends existing knowledge by empirically examining interconnected individual experiences of structural inequity and assessing its association with subjective and objective sleep outcomes.

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