Adolescent Brain Cognitive Development Study Research Articles

Smaller subcortical volume relates to greater weight gain in girls with initially healthy weight.

Among 3614 youth who were 9 to 12 years old and initially did not have overweight or obesity (12% [n = 385] developed overweight or obesity), we examined the natural progression of weight gain and brain structure development during a 2-year period with a high risk for obesity (e.g., pre- and early adolescence) to determine the following: 1) whether variation in maturational trajectories of the brain regions contributes to weight gain; and/or 2) whether weight gain contributes to altered brain development. Data were gathered from the Adolescent Brain Cognitive Development (ABCD) Study. Linear mixed-effects regression models controlled for puberty, caregiver education, handedness, and intracranial volume (random effects: magnetic resonance scanner [MRI] scanner and participant). Because pubertal development occurs earlier in girls, analyses were stratified by sex. For girls, but not boys, independent of puberty, greater increases in BMI were driven by smaller volumes over time in the bilateral accumbens, amygdala, hippocampus, and thalamus, right caudate and ventral diencephalon, and left pallidum (all p < 0.05). The results suggest a potential phenotype for identifying obesity risk because underlying differences among regions involved in food intake were related to greater weight gain in girls, but not in boys. Importantly, 2 years of weight gain may not be sufficient to alter brain development, highlighting early puberty as a critical time to prevent negative neurological outcomes.

Predictors of Substance Use Initiation by Early Adolescence.

Substance use initiation during early adolescence is associated with later development of substance use and mental health disorders. This study used various domains to predict substance use initiation, defined as trying any nonprescribed substance (e.g., alcohol, tobacco, cannabis), by age 12, using a large longitudinal data set. Substance-naive youths from the Adolescent Brain Cognitive Development Study (ages 9-10; N=6,829) were followed for 3 years. A total of 420 variables were examined as predictors of substance use initiation, using a penalized logistic regression with elastic net; domains spanned demographic characteristics, self and peer involvement with substance use, parenting behaviors, mental and physical health, culture and environment, hormones, neurocognitive functioning, and structural neuroimaging. By age 12, 982 (14.4%) children reported substance initiation, with alcohol being the most common. Models with only self-report predictors had similar prediction performance to models adding hormones, neurocognitive factors, and neuroimaging predictors (AUCtest=0.66). Sociodemographic factors were the most robust predictors, followed by cultural and environmental factors, physical health factors, and parenting behaviors. The top predictor was a religious preference of Mormon (coefficient=-0.87), followed by a religious preference for Jewish (coefficient=0.32), and by Black youths (coefficient=-0.32). Sociodemographic variables were the most robust predictors of substance use initiation. Adding resource-intensive measures, including hormones, neurocognitive assessment, and structural neuroimaging, did not improve prediction of substance use initiation. The application of these large-scale findings in clinical settings could help to streamline and tailor prevention and early intervention efforts.

54. Family Conflict and Neural Markers of Familial Risk for Depression During Preadolescence Predicting Adolescent Psychopathology in the Adolescent Brain Cognitive Development (ABCD) Study

54. Family Conflict and Neural Markers of Familial Risk for Depression During Preadolescence Predicting Adolescent Psychopathology in the Adolescent Brain Cognitive Development (ABCD) Study

Childhood internalizing, externalizing and attention symptoms predict changes in social and nonsocial screen time.

While accumulating research has tested the hypothesis that screen time causes psychiatric symptoms in children, less attention has been paid to the hypothesis that children with psychiatric symptoms change their patterns of screen time and digital media use. We aimed to test whether children with psychiatric symptoms subsequently change their patterns of screen time and digital media use. N = 9,066 children primarily aged 9-10 in the Adolescent Brain Cognitive Development Study at baseline and 1-year later. Psychiatric symptoms included internalizing, attention, and externalizing symptoms. Screen time was measured as ordinally defined weekday and weekend time on social and nonsocial [e.g., YouTube] digital media). Models assessed psychiatric symptoms as predictors of screen time, and screen time as predictors of psychiatric symptoms, controlled for baseline measures of each, sex, age, race/ethnicity, and income. Children with psychiatric symptoms spent more time on non-social media one year later compared with peers. Considering total psychiatric problems, clinical levels of problems predicted higher levels of weekday (OR = 1.22, 95% CI 1.22-1.23) and weekend (OR = 1.10, 95% CI 1.09-1.11) nonsocial screen time. For nearly all analyses of psychiatric symptoms predicting screen time, associations were highest for a non-social screen time outcome rather than a social screen time outcome (Highest OR = 1.65, 95% CI 1.63-1.67, clinical rule breaking predicting weekday nonsocial screen time). Comparable magnitude associations were observed for social and nonsocial media use predicting future psychiatric symptoms, suggesting bidirectionality. Children with psychiatric symptoms have different subsequent media use patterns, including higher rates of subsequent nonsocial engagement. Ensuring that ongoing data collection and analysis efforts attend to temporality and transitions in the relation between media use and psychiatric symptoms will accelerate progress in the field.

Screen time, sleep, brain structural neurobiology, and sequential associations with child and adolescent psychopathology: Insights from the ABCD study.

The precise roles of screen media activity (SMA) and sleep problems in relation to child/adolescent psychopathology remain ambiguous. We investigated temporal relationships among sleep problems, SMA, and psychopathology and potential involvement of thalamus-prefrontal-cortex (PFC)-brainstem structural covariation. This study utilized data from the Adolescent Brain Cognitive Development study (n = 4,641 ages 9-12) at baseline, Year1, and Year2 follow-up. Cross-Lagged Panel Models (CLPMs) investigated reciprocal predictive relationships between sleep duration/problems, SMA, and psychopathology symptoms. A potential mediating role of baseline Thalamus-PFC-brainstem covariation on SMA-externalizing relationships was examined. Participants were divided into discovery (n = 2,359, 1,054 girls) and replication (n = 2,282, 997 girls) sets. CLPMs showed 1) bidirectional associations between sleep duration and SMA in late childhood, with higher frequency SMA predicting shorter sleep duration (β = -0.10 [95%CI: -0.16, -0.03], p = 0.004) and vice versa (β= -0.11 [95%CI: -0.18, -0.05], p < 0.001); 2) externalizing symptoms at age 10-11 predicting sleep problems (β = 0.11 [95%CI: 0.04, 0.19], p = 0.002), SMA (β = 0.07 [95%CI: 0.01, 0.13], p = 0.014), and internalizing symptoms (β = 0.09 [95%CI: 0.05, 0.13], p < 0.001) at age 11-12; and 3) externalizing behavior at age 10-11 partially mediating the relationship between baseline thalamus-PFC-brainstem covariation and SMA at age 11-12 (indirect effect = 0.032 [95%CI: 0.003, 0.067], p-value = 0.030). Findings were replicable. We found bi-directional SMA-sleep-duration associations in late childhood. Externalizing symptoms preceded future SMA and sleep disturbances and partially mediated relationships between structural brain covariation and SMA. The findings emphasize the need for understanding individual differences and developing and implementing integrated strategies addressing both sleep concerns and screen time to mitigate potential impacts on psychopathology.

Probing the digital exposome: associations of social media use patterns with youth mental health

Recently, the U.S. Surgeon General issued an advisory highlighting the lack of knowledge about the safety of ubiquitous social media use on adolescent mental health. For many youths, social media use can become excessive and can contribute to frequent exposure to adverse peer interactions (e.g., cyberbullying, and hate speech). Nonetheless, social media use is complex, and although there are clear challenges, it also can create critical new avenues for connection, particularly among marginalized youth. In the current project, we leverage a large nationally diverse sample of adolescents from the Adolescent Brain Cognitive Development (ABCD) Study assessed between 2019–2020 (N = 10,147, Mage = 12.0, 48% assigned female at birth, 20% Black, 20% Hispanic) to test the associations between specific facets of adolescent social media use (e.g., type of apps used, time spent, addictive patterns of use) and overall mental health. Specifically, a data-driven exposome-wide association was applied to generate digital exposomic risk scores that aggregate the cumulative burden of digital risk exposure. This included general usage, cyberbullying, having secret accounts, problematic/addictive use behavior, and other factors. In validation models, digital exposomic risk explained substantial variance in general child-reported psychopathology, and a history of suicide attempt, over and above sociodemographics, non-social screentime, and non-digital adversity (e.g., abuse, poverty). Furthermore, differences in digital exposomic scores also shed insight into mental health disparities, among youth of color and sexual and gender minority youth. Our work using a data-driven approach supports the notion that digital exposures, in particular social media use, contribute to the mental health burden of US adolescents.

Racialized influence of parental education on adolescents’ tobacco and marijuana initiation: Mediating effects of average cortical thickness

Various regions of the cerebral cortex, such as the prefrontal cortex, parahippocampal gyrus, insular cortex, temporal cortex, and anterior cingulate cortex, play critical roles in emotion regulation and executive/cognitive control. Given these regions' involvement, it is hypothesized that average cortical thickness might play a role in mediating the socioeconomic gradient observed in substance use behaviors. However, the mechanisms through which average cortical thickness influences the differential impact of socioeconomic factors, such as parental education, on the initiation of tobacco and marijuana use among youths from diverse backgrounds remain unclear. Recent studies indicate that the effects of socioeconomic factors on substance use and brain development are racialized, often showing weaker associations in racialized populations due to social stratification and racism. Our aim was to examine whether average cortical thickness mediates the racialized effects of parental education as a major socioeconomic determinant on the initiation of tobacco and marijuana use among youth. This longitudinal study, spanning 36 months, utilizes data from the Adolescent Brain Cognitive Development (ABCD) study, which included 10,777 pre-adolescents aged 9–10 years. From this, 8263 (76.67%) were White youth and 2514 (23.33%) were Black. Structural equation modeling was employed to assess the mediating role of average cortical thickness in the relationship between parental education (social determinant), race, and the initiation of tobacco and marijuana use, while considering covariates such as sex and age. Socioeconomic factors were predictive of future substance use. However, the association between these socioeconomic factors and substance use was found to be weaker among Black youths compared to White youths. Average cortical thickness partially mediated the influence of the racialized socioeconomic gradient on substance use, indicating both direct and indirect effects. Average cortical thickness acts as a partial mediator in the racialized impact of socioeconomic determinants on the initiation of adolescent substance use, underscoring the intricate relationship between neurodevelopmental and social factors in influencing substance use behaviors. This observation supports a biopsychosocial model that incorporates the effects of racism, aligning with the theory of minorities’ diminished returns.

Examining neural responses to anticipating or receiving monetary rewards and the development of binge eating in youth. A registered report using data from the Adolescent Brain Cognitive Development (ABCD) study

Binge eating is characterized as eating a large amount of food and feeling a loss of control while eating. However, the neurobiological mechanisms associated with the onset and maintenance of binge eating are largely unknown. Recent neuroimaging work has suggested that increased responsivity within reward regions of the brain to the anticipation or receipt of rewards is related to binge eating; however, limited longitudinal data has precluded understanding of the role of reward responsivity in the development of binge eating. The current study used data from the Adolescent Brain and Cognitive Development® (ABCD) longitudinal study dataset to assess whether heightened neural responses to different phases of reward processing (reward anticipation and receipt) (1) differentiated individuals with binge eating from matched controls, and (2) predicted the onset of binge eating in an "at risk" sample. Consistent with hypotheses, heightened neural responsivity in the right caudate and bilateral VS during reward anticipation differentiated youth with and without binge eating. Moreover, greater VS response to reward anticipation predicted binge eating two years later. Neural responses to reward receipt also were consistent with hypotheses, such that heightened VS and OFC responses differentiated youth with and without binge eating and predicted the presence of binge eating two years later. Findings from the current study suggest that hypersensitivity to rewards may contribute to the development of binge eating during early adolescence.

Childhood adversity is associated with reduced BOLD response in inhibitory control regions amongst preadolescents from the ABCD study

Adolescence is characterized by dynamic neurodevelopment, which poses opportunities for risk and resilience. Adverse childhood experiences (ACEs) confer additional risk to the developing brain, where ACEs have been associated with alterations in functional magnetic resonance imaging (fMRI) BOLD signaling in brain regions underlying inhibitory control. Socioenvironmental factors like the family environment may amplify or buffer against the neurodevelopmental risks associated with ACEs. Using baseline to Year 2 follow-up data from the Adolescent Brain Cognitive Development (ABCD) Study, the current study examined how ACEs relate to fMRI BOLD signaling during successful inhibition on the Stop Signal Task in regions associated with inhibitory control and examined whether family conflict levels moderated that relationship. Results showed that greater ACEs were associated with reduced BOLD response in the right opercular region of the inferior frontal gyrus and bilaterally in the pre-supplementary motor area, which are key regions underlying inhibitory control. Further, greater BOLD response was correlated with less impulsivity behaviorally, suggesting reduced activation may not be behaviorally adaptive at this age. No significant two or three-way interactions with family conflict levels or time were found. Findings highlight the continued utility of examining the relationship between ACEs and neurodevelopmental outcomes and the importance of intervention/prevention of ACES.

Estimating the prevalence of Non-Verbal Learning Disability (NVLD) from the ABCD sample.

Non-Verbal Learning Disability (NVLD) is a neurodevelopmental disorder characterized by deficits in processing visuospatial information but with age-appropriate verbal skills. This cognitive profile has been hypothesized to be associated with atypical white matter, but at the present there is a lack of evidence for this hypothesis. Currently, the condition is not characterized within the main diagnostic systems, in part because no clear set of criteria for characterizing the disorder exists. This report is the first attempt to estimate NVLD prevalence, using two sets of diagnostic criteria, in a large sample of over 11,000 children who were selected without regards to problems of specific nature, either psychological, neurological, physical and/or social. Furthermore, it examined the association between the profile of cognitive abilities and aspects of whole-brain white matter measures in children with and without symptoms associated with NVLD. Participants were drawn from the Adolescent Brain Cognitive Development (ABCD) study, a 10-year longitudinal study of 11,876 children in the U.S. The data used in the present study were drawn from the initial testing point at which the children were 9-10years old. Prevalence of NVLD based on two distinct sets of criteria, correlations between the measures used to create the criteria, correlations between criteria measures and measures of white matter integrity. The cognitive criteria included measures of visuospatial processing, reading, intelligence and social skills. By varying the cut-offs applied to social skills in conjunction with visuo-spatial difficulties, spared reading skills and intelligence scores, we calculated prevalence for two NVLD groups. White matter characteristics were measures of volume, fractional anisotropy and mean diffusivity. Based on the criteria used, the estimated prevalence of NVLD varied from 1 to 8%. Furthermore, children with NVLD showed a dissociation between measures of visuo-spatial processing not observed in non-NVLD children. At the neurological level, findings provide preliminary evidenceof associations between the cognitive profile of NVLD and abnormalities in white matters tracts. The present study documents that exists, within this large non-selected sample, a proportion of youth who show evidence of NVLD. Given those results, it appears essential to establish the best diagnostic criteria, to improve the treatment options and quality of life for children with this disorder.

Factor Structure of the Difficulties in Emotion Regulation Scale among Early Adolescents: Results from the Adolescent Brain Cognitive Development Study

Abstract Introduction Emotion regulation (ER) deficits in early adolescence are associated with subsequent negative health consequences, including anxiety and depression. Yet, limited work has evaluated the factor structure of measures of ER deficits in early adolescents, leaving a methodological gap for at-risk youths. Method This study examined the Difficulties in Emotion Regulation Scale (DERS) factor structure in early adolescents (N = 2300) recruited from the Adolescent Brain Cognitive Development Study. We randomly split the sample into two sub-samples (n = 1150 each) and implemented an a-priori three-pronged approach: (1) A confirmatory factor analysis (CFA) assessed the fit of the six-factor DERS in Sample 1; (2) An exploratory factor analysis (EFA) identified an alternative factor structure in Sample 1; and (3) A second CFA assessed the new model in Sample 2. A bi-factor model was also used to assess the global structure of the DERS total and subscales. Results The original six-factor model yielded poor-to-adequate fit. EFA results supported an alternative five-factor model with different item mappings and ten omitted items. CFA results supported the five-factor solution with good fit. The bi-factor model, estimating a general factor with the five subscales, also demonstrated good fit. Discussion A five-factor structure of the DERS appears supported in a large community sample of early adolescents. Items from the former Awareness and Clarity subscales were combined into a single factor. Nearly all items from the former Strategies subscale were omitted, suggesting there may be developmental considerations rendering those items less relevant.

Brain volumes, behavioral inhibition, and anxiety disorders in children: results from the adolescent brain cognitive development study

BackgroundMagnetic resonance imaging (MRI) studies have identified brain changes associated with anxiety disorders (ADs), but the results remain mixed, particularly at a younger age. One key predictor of ADs is behavioral inhibition (BI), a childhood tendency for high avoidance of novel stimuli. This study aimed to evaluate the relationships between candidate brain regions, BI, and ADs among children using baseline data from the Adolescent Brain Cognitive Development (ABCD) study.MethodsWe analyzed global and regional brain volumes of 9,353 children (9–10 years old) in relation to BI and current ADs, using linear mixed models accounting for family clustering and important demographic and socioeconomic covariates. We further investigated whether and how past anxiety was related to brain volumes.ResultsAmong included participants, 249 (2.66%) had a current AD. Larger total white matter (Beta = -0.152; 95% CI [-0.281, -0.023]), thalamus (Beta = -0.168; 95% CI [-0.291, -0.044]), and smaller hippocampus volumes (Beta = 0.094; 95% CI [-0.008, 0.196]) were associated with lower BI scores. Amygdala volume was not related to BI. Larger total cortical (OR = 0.751; 95% CI [0.580;0.970]), amygdala (OR = 0.798; 95%CI [0.666;0.956]), and precentral gyrus (OR = 0.802; 95% CI [0.661;0.973]) volumes were associated with lower odds of currently having ADs. Children with past ADs had smaller total white matter and amygdala volumes.ConclusionsThe results show associations between brain volumes and both BI and ADs at an early age. Importantly, results suggest that ADs and BI have different neurobiological correlates and that earlier occurrences of ADs may influence brain structures related to BI and ADs, motivating research that can better delineate the similarities and divergence in the neurobiological underpinnings and building blocks of BI and ADs across their development in early life.

Multiple marginalization, discrimination, and disordered eating among youth aged 10-11.

Although rates of weight discrimination are on-par with racial, ethnic, and gender discrimination, comparatively less work has examined impacts of weight-based discrimination in youth, including on disordered eating. Knowing whether experiences of weight-based discrimination, including in youth with multiply-marginalized identities, are associated with disordered eating could identify vulnerable youth and inform intervention efforts. Youth (N = 11,875) ages 10-11 were recruited through the Adolescent Brain Cognitive Development (ABCD) study. Logistic regressions using cross-sectional data examined discrimination experiences (weight, perceived sexual orientation, race/ethnicity, national origin) and disordered eating (binge-eating, vomiting, weight-gain fear, weight self-worth). Models included race/ethnicity, age, sex, parental income, and degree of elevated weight. Raked poststratification weights were used. Rates of weight-based discrimination (6.2%) were similar to rates of race/ethnicity (4.4%) and sexual orientation discrimination (4.5%). Weight-based discrimination was associated with more disordered eating. Youth reporting multiple experiences of discrimination had significantly increased disordered eating compared to youth who did not report discrimination. Weight-based discrimination is common in youth and associated with disordered eating. Youth with elevated weight are more likely to be multiply marginalized and experience disordered eating. These findings suggest discrimination, including weight-based discrimination, is a critical intervention target to prevent and treat eating disorders. Experiences of discrimination contribute to poorer health; however, weight-based discrimination is relatively understudied. Data from a large sample of youth ages 10-11 showed that youth with elevated weight reported experiencing multiple types of discrimination, and multiply-marginalized youth had increased odds of disordered eating with each additional type of discrimination. Together, this suggests that weight-based discrimination is a critical target to prevent and treat eating disorders, especially in multiply-marginalized youth.

Lifetime residential data collection protocol for the Adolescent Brain Cognitive Development (ABCD) Study

Understanding the impacts of environmental exposures on health outcomes during development is an important area of research for plenty of reasons. Collecting retrospective and prospective residential history can enrich observational studies through eventual linkages to external sources. Augmenting participant health outcome data with environmental data can better inform on the role of the environment, thereby enhancing prevention and intervention efforts. However, collecting the geospatial information needed for this type of research can be difficult, especially when data are collected directly from participants. Participants’ residential histories are unique and often complex. Collecting residential history data often involves capturing precise spatial locations along specific timeframes as well as contending with recall bias and unique, complex living arrangements. When trying to assess lifetime environmental exposures, researchers must consider the many changes in location a person goes through and the timeframes in which these changes occur, ultimately creating a multidimensional and dynamic dataset. Creating data collection protocols that are feasible to administer, result in accurate data, and minimize data missingness is a major challenge to undertake. Here, we provide an overview of the protocol developed to collect the lifetime residential address information of participants in the Adolescent Brain Cognitive Development (ABCD) Study.

Longitudinal associations of screen time, physical activity, and sleep duration with body mass index in U.S. youth

BackgroundYouth use different forms of screen time (e.g., streaming, gaming) that may be related to body mass index (BMI). Screen time is non-independent from other behaviors, including physical activity and sleep duration. Statistical approaches such as isotemporal substitution or compositional data analysis (CoDA) can model associations between these non-independent behaviors and health outcomes. Few studies have examined different types of screen time, physical activity, and sleep duration simultaneously in relation to BMI.MethodsData were baseline (2017–2018) and one-year follow-up (2018–2019) from the Adolescent Brain Cognitive Development Study, a multi-site study of a nationally representative sample of U.S. youth (N = 10,544, mean [SE] baseline age = 9.9 [0.03] years, 48.9% female, 45.4% non-White). Participants reported daily minutes of screen time (streaming, gaming, socializing), physical activity, and sleep. Sex-stratified models estimated the association between baseline behaviors and follow-up BMI z-score, controlling for demographic characteristics, internalizing symptoms, and BMI z-score at baseline.ResultsIn females, isotemporal substitution models estimated that replacing 30 min of socializing (β [95% CI] = -0.03 [-0.05, -0.002]), streaming (-0.03 [-0.05, -0.01]), or gaming (-0.03 [-0.06, -0.01]) with 30 min of physical activity was associated with a lower follow-up BMI z-score. In males, replacing 30 min of socializing (-0.03 [-0.05, -0.01]), streaming (-0.02 [-0.03, -0.01]), or gaming (-0.02 [-0.03, -0.01]) with 30 min of sleep was associated with a lower follow-up BMI z-score. In males, replacing 30 min of socializing with 30 min of gaming was associated with a lower follow-up BMI z-score (-0.01 [-0.03, -0.0001]). CoDA estimated that in males, a greater proportion of time spent in baseline socializing, relative to the remaining behaviors, was associated with a higher follow-up BMI z-score (0.05 [0.02, 0.08]). In females, no associations between screen time and BMI were observed using CoDA.ConclusionsOne-year longitudinal associations between screen time and BMI may depend on form of screen time, what behavior it replaces (physical activity or sleep), and participant sex. The alternative statistical approaches yielded somewhat different results. Experimental manipulation of screen time and investigation of biopsychosocial mechanisms underlying the observed sex differences will allow for causal inference and can inform interventions.

A general exposome factor explains individual differences in functional brain network topography and cognition in youth

Childhood environments are critical in shaping cognitive neurodevelopment. With the increasing availability of large-scale neuroimaging datasets with deep phenotyping of childhood environments, we can now build upon prior studies that have considered relationships between one or a handful of environmental and neuroimaging features at a time. Here, we characterize the combined effects of hundreds of inter-connected and co-occurring features of a child’s environment (“exposome”) and investigate associations with each child’s unique, multidimensional pattern of functional brain network organization (“functional topography”) and cognition. We apply data-driven computational models to measure the exposome and define personalized functional brain networks in pre-registered analyses. Across matched discovery (n=5139, 48.5% female) and replication (n=5137, 47.1% female) samples from the Adolescent Brain Cognitive Development study, the exposome was associated with current (ages 9–10) and future (ages 11–12) cognition. Changes in the exposome were also associated with changes in cognition after accounting for baseline scores. Cross-validated ridge regressions revealed that the exposome is reflected in functional topography and can predict performance across cognitive domains. Importantly, a single measure capturing a child’s exposome could more accurately and parsimoniously predict cognition than a wealth of personalized neuroimaging data, highlighting the importance of children’s complex, multidimensional environments in cognitive neurodevelopment.

Strength and resilience of developing brain circuits predict adolescent emotional and stress responses during the COVID-19 pandemic.

The COVID-19 pandemic has had profound but incompletely understood adverse effects on youth. To elucidate the role of brain circuits in how adolescents responded to the pandemic's stressors, we investigated their prepandemic organization as a predictor of mental/emotional health in the first ~15months of the pandemic. We analyzed resting-state networks from n = 2,641 adolescents [median age (interquartile range) = 144.0 (13.0) months, 47.7% females] in the Adolescent Brain Cognitive Development study, and longitudinal assessments of mental health, stress, sadness, and positive affect, collected every 2 to 3months from May 2020 to May 2021. Topological resilience and/or network strength predicted overall mental health, stress and sadness (but not positive affect), at multiple time points, but primarily in December 2020 and May 2021. Higher resilience of the salience network predicted better mental health in December 2020 (β = 0.19, 95% CI = [0.06, 0.31], P = 0.01). Lower connectivity of left salience, reward, limbic, and prefrontal cortex and its thalamic, striatal, amygdala connections, predicted higher stress (β = -0.46 to -0.20, CI = [-0.72, -0.07], P < 0.03). Lower bilateral robustness (higher fragility) and/or connectivity of these networks predicted higher sadness in December 2020 and May 2021 (β = -0.514 to -0.19, CI = [-0.81, -0.05], P < 0.04). These findings suggest that the organization of brain circuits may have played a critical role in adolescent stress and mental/emotional health during the pandemic.

394 A Machine Learning Approach to Predicting High-Risk Irritability Trajectories Across the Transition to Adolescence

OBJECTIVES/GOALS: Irritability, a proneness to anger and frustration, is a transdiagnostic symptom associated with poor mental health outcomes. Levels of irritability vary across development and high-risk trajectories have been observed. This study aims to use machine learning to predict irritability trajectories across the transition to adolescence. METHODS/STUDY POPULATION: Data were from the Adolescent Brain Cognitive Development (ABCD) Study, which is a 10-year longitudinal study that tracks the brain development, cognitive skills, physical health, and psychosocial functioning of a large, national sample starting from preadolescence. The baseline sample consisted of 11,861 9-10-year-old preadolescent youth. Irritability was parent-rated at baseline, 1-year, 2-year, 3-year, and 4-year follow-ups on the Child Behavior Checklist (CBCL) irritability index. Latent class growth analysis (LCGA) was used to determine developmental trajectories of irritability. Two machine learning approaches were applied to develop predictive models of youth irritability developmental trajectories. We used baseline (preadolescent) variables that spanned a wide range of domains. RESULTS/ANTICIPATED RESULTS: Preliminary results fromthe LCGA indicated best support for a four-class model that differentiated growth trajectories in irritability across the transition to adolescence: 1) persistent low irritability (n = 8691, 73.27%), 2) moderate irritability and decreasing (n = 1257, 10.60%), 3) low to moderate irritability and increasing (n = 1295, 10.92%), and 4) chronic high irritability (n = 618, 5.21%). We expect the machine learning analyses to generate predictive models with acceptable accuracy. We hypothesize that the most important predictors in the models will originate from the youth mental health domain, including baseline youth irritability, externalizing symptoms, internalizing symptoms, and oppositional behaviors, and the parent psychopathology domain, particularly parent irritability. DISCUSSION/SIGNIFICANCE: The present study elucidates unique developmental trajectories of irritability and generates predictive models to classify high-risk irritability trajectories using machine learning approaches. Clinicians can use these predictive models to identify at-risk youth and provide early intervention to preadolescents at high risk.

A precision functional atlas of personalized network topography and probabilities.

Although the general location of functional neural networks is similar across individuals, there is vast person-to-person topographic variability. To capture this, we implemented precision brain mapping functional magnetic resonance imaging methods to establish an open-source, method-flexible set of precision functional network atlases-the Masonic Institute for the Developing Brain (MIDB) Precision Brain Atlas. This atlas is an evolving resource comprising 53,273 individual-specific network maps, from more than 9,900 individuals, across ages and cohorts, including the Adolescent Brain Cognitive Development study, the Developmental Human Connectome Project and others. We also generated probabilistic network maps across multiple ages and integration zones (using a new overlapping mapping technique, Overlapping MultiNetwork Imaging). Using regions of high network invariance improved the reproducibility of executive function statistical maps in brain-wide associations compared to group average-based parcellations. Finally, we provide a potential use case for probabilistic maps for targeted neuromodulation. The atlas is expandable to alternative datasets with an online interface encouraging the scientific community to explore and contribute to understanding the human brain function more precisely.

Gray matter volume associations in youth with ADHD features of inattention and hyperactivity/impulsivity.

Prior research has shown smaller cortical and subcortical gray matter volumes among individuals with attention-deficit/hyperactivity disorder (ADHD). However, neuroimaging studies often do not differentiate between inattention and hyperactivity/impulsivity, which are distinct core features of ADHD. The present study uses an approach to disentangle overlapping variance to examine the neurostructural heterogeneity of inattention and hyperactivity/impulsivity dimensions. We analyzed data from 10,692 9- to 10-year-old children from the Adolescent Brain Cognitive Development (ABCD) Study. Confirmatory factor analysis was used to derive factors representing inattentive and hyperactive/impulsive traits. We employed structural equation modeling to examine these factors' associations with gray matter volume while controlling for the shared variance between factors. Greater endorsement of inattentive traits was associated with smaller bilateral caudal anterior cingulate and left parahippocampal volumes. Greater endorsement of hyperactivity/impulsivity traits was associated with smaller bilateral caudate and left parahippocampal volumes. The results were similar when accounting for socioeconomic status, medication, and in-scanner motion. The magnitude of these findings increased when accounting for overall volume and intracranial volume, supporting a focal effect in our results. Inattentive and hyperactivity/impulsivity traits show common volume deficits in regions associated with visuospatial processing and memory while at the same time showing dissociable differences, with inattention showing differences in areas associated with attention and emotion regulation and hyperactivity/impulsivity associated with volume differences in motor activity regions. Uncovering such biological underpinnings within the broader disorder of ADHD allows us to refine our understanding of ADHD presentations.