cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15154/1524790
title: Substance use onset in high-risk 9–13 year-olds in the ABCD study

description: Aim
A key aim of the Adolescent Brain Cognitive Development℠ (ABCD) Study is to document substance use onset, patterns, and sequelae across adolescent development. However, substance use misreporting can obscure accurate drug use characterization. Hair toxicology provides objective historical substance use data but is rarely used in studies of youth. Here, we compare objective hair toxicology results with self-reported substance use in high-risk youth.

Methods
A literature-based substance use risk algorithm prioritized 696 ABCD Study® hair samples from 677 participants for analysis at baseline, and 1 and 2-year follow-ups (spanning ages 9–13). Chi-square and t-tests assessed differences between participants' demographics, positive and negative hair tests, risk-for-use algorithm scores, and self-reported substance use.

Results
Hair testing confirmed that 17% of at-risk 9–13 year-olds hair samples had evidence of past 3-month use of one (n = 97), two (n = 14), three (n = 2), or four (n = 2) drug classes. After considering prescribed medication and self-reported substance use, 10% had a positive test indicating substance use that was not reported. Participants with any positive hair result reported less sipping of alcohol (p < 0.001) and scored higher on the risk-for-use algorithm (p < 0.001) than those with negative toxicology results.

Conclusions
10% of hair samples from at-risk 9–13 year-olds tested positive for at least one unreported substance, suggesting underreporting in high-risk youth when participating in a research study. As hair testing prioritized youth with risk characteristics, the overall extent of underreporting will be calculated in future studies. Nonetheless, hair toxicology was key to characterizing substance use in high-risk youth.
DOI: 10.15154/1524794
title: Fairness-related performance and explainability effects in deep learning models for brain image analysis

description: Purpose: Explainability and fairness are two key factors for the effective and ethical clinical implementation of deep learning-based machine learning models in healthcare settings. However, there has been limited work on investigating how unfair performance manifests in explainable artificial intelligence (XAI) methods, and how XAI can be used to investigate potential reasons for unfairness. Thus, the aim of this work was to analyze the effects of previously established sociodemographic-related confounders on classifier performance and explainability methods. 
Approach: A convolutional neural network (CNN) was trained to predict biological sex from T1-weighted brain MRI of 4,547 9–10-year-old adolescents from the Adolescent Brain Cognitive Development study. Performance disparities of the trained CNN between White and Black subjects were analyzed and saliency maps were generated for each subgroup at the intersection of sex and race.
Results: The classification model demonstrated a significant difference in the percentage of correctly classified White male (90.3±1.7%) and Black male (81.1±4.5%) subjects. Conversely, slightly higher performance was seen in Black female (89.3±4.8%) compared to White female (86.5±2.0) subjects. Saliency maps showed subgroup-specific differences, corresponding to brain regions previously associated with pubertal development. In line with this finding, average pubertal development scores of subjects used in this study were significantly different between Black and White females (p<0.001) and males (p<0.001).
Conclusions: We demonstrate that a CNN with significantly different sex classification performance between Black and White adolescents can identify different important brain regions when comparing subgroup saliency maps. Importance scores vary substantially between subgroups within brain structures associated with pubertal development, a race-associated confounder for predicting sex. This study illustrates that unfair models can lead to different XAI results between subgroups, and that these results may be able to inform potential reasons for biased performance.
DOI: 10.15154/1524795
title: Effortful control protects against genetic liability for ADHD: Longitudinal results from the ABCD study in the United States

description: Background: Effortful control, the ability to regulate complex and goal-directed behavior, may protect individuals from developing mental health symptoms. This study tested the potential for strong effortful control and executive functioning to buffer the effects of genetic liability for attention deficit hyperactivity disorder (ADHD). 

Methods: Data from the prospectively-collected Adolescent Brain Cognitive Development (ABCD)® study were used to examine whether caregiver-rated effortful control and executive functioning moderated the association between familial ADHD risk and later ADHD symptoms in a sample of children (N = 6,133; ages 9-10 years at baseline). Two independent variables were considered to compare the predictive powers of specific (family ADHD) and broad (family psychopathology) risk factors. Two additional moderating variables (surgency, negative affect) were tested to examine specificity of effortful control and executive functioning as moderators. All variables of interest were measured on a continuum. 

Results: Strong effortful control and executive functioning each negated the association between genetic liability and later ADHD symptoms. Model estimates for ADHD-specific and broad-psychopathology genetic risk were comparable. The moderator effect was specific to effortful control and executive functioning, and was not found for two other temperamental dimensions, surgency and negative affect. 

Conclusions: Etiological models of heritable psychiatric disorders, such as ADHD, should consider interacting effects of genetic factors and individual traits, such as effortful control and executive functioning. Clinical prevention and intervention efforts may target self-regulation skills in children to buffer against genetic liability for ADHD.
DOI: 10.15154/1526324
title: Brain network coupling associated with high cognitive performance for children in poverty

description: We analyzed resting-state fMRI from children ages 9–10 years in the ABCD dataset. We examined links between resting-state functional coupling between two brain networks, lateral frontoparietal network (LFPN) and default mode network (DMN) and children’s cognitive performance. For children from households defined as being above poverty (family of 4 with income > $25,000, or family of 5+ with income > $35,000), we replicated prior findings; that is, we found that better performance on cognitive tests correlated with weaker LFPN-DMN coupling. For children from households defined as being in poverty, the direction of association was reversed, on average: better performance was instead directionally related to stronger LFPN-DMN connectivity, though there was considerable variability. Among children in households below poverty, the direction of this association was predicted in part by features of their environments, such as school type and parent-reported neighborhood safety. These results highlight the importance of including representative samples in studies of child cognitive development.
DOI: 10.15154/1526345
title: Socioeconomic status, BMI, and brain development in children
DOI: 10.15154/1526346
title: Word Learning and Word Features

description: Vocabulary composition and word-learning biases are closely interrelated in typical development. Learning new words involves attending to certain properties to facilitate word learning. Such word-learning biases are influenced by perceptually and conceptually salient word features, including high imageability, concreteness, and iconicity. This study examined the association of vocabulary knowledge and word features in young children with ASD (n = 280) and typically developing (TD) toddlers (n = 1,054). Secondary analyses were conducted using data from the National Database for Autism Research and the Wordbank database. Expressive vocabulary was measured using the MacArthur-Bates Communicative Development Inventory. Although the trajectories for concreteness, iconicity, and imageability are similar between children with ASD and TD toddlers, divergences were observed. Differences in imageability are seen early but resolve to a common trajectory; differences in iconicity are small but consistent; and differences in concreteness only emerge after both groups reach a simultaneous peak, before converging again. This study reports unique information about the nonlinear growth patterns associated with each word feature for and distinctions in these growth patterns between the groups.
DOI: 10.15154/1526427
title: Metabolism modulates network synchrony in the aging brain

description: Brain aging is associated with hypometabolism and global changes in functional connectivity. Using functional MRI (fMRI), we show that network synchrony, a collective property of brain activity, decreases with age. Applying quantitative methods from statistical physics, we provide a generative (Ising) model for these changes as a function of the average communication strength between brain regions. We ﬁnd that older brains are closer to a critical point of this communication strength, in which even small changes in metabolism lead to abrupt changes in network synchrony. Finally, by experimentally modulating metabolic activity in younger adults, we show how metabolism alone—independent of other changes associated with aging—can provide a plausible candidate mechanism for marked reorganization of brain network topology.
DOI: 10.15154/1526458
title: Variability in cognitive task performance, functional network segregation, and attention problems in early adolescence 

description: Intra-individual variability (IIV) during cognitive task performance is a key behavioral assay of attention. Across the lifespan, lower IIV is associated with higher anticorrelation between the dorsal attention network (DAN) and default mode network (DMN), which is thought to represent effective allocation of attention through functional network segregation. Higher IIV is reported in ADHD, both healthy and neurodegenerative aging, and schizophrenia. However, whether these behavioral and neural markers of sustained attention are (i) related to each other and (ii) can predict future attention-related deficits has not yet been investigated in a developmental, population-based cohort.
DOI: 10.15154/1526462
title: The Mediating Role of Family Acceptance and Conflict on Suicidality among Sexual and Gender Minority Youth

description: Introduction
Prior research suggests sexual and gender minority (SGM) youth are profoundly impacted by levels of parental support. This study assessed mediating effects of generalized family acceptance and conflict on lifetime suicidal behaviors among a large diverse sample comprising both SGM and non-SGM youth in early adolescence, when intervention to optimize family dynamics may be critical.

Materials
Using data from the first-year follow-up of the Adolescent Brain Cognitive Development Study based in the United States, mediation was tested using a binary logistic regression model fitted with a generalized structural equation. Models included SGM status as the independent variable, family acceptance or family conflict sum score as the mediator, and the presence of lifetime suicidal behaviors as the dependent variable. Models adjusted for age, birth-assigned sex (as reported by the parent/guardian), and race/ethnicity.

Results
Of 11,235 youths, lifetime suicidal behaviors were reported by 1.5% (n = 164). Youths with SGM identities reported 40% less parental acceptance and 47% greater family conflict, compared to non-SGM peers. Both parental acceptance and family conflict partially mediated associations between SGM identification and odds of lifetime suicidal behavior (ps = .001).

Conclusions
Identification of modifiable risk factors for suicidality in this vulnerable population, including parental acceptance and family conflict, is critical to improving health outcomes. Clinicians should work with SGM youth and their families starting in childhood to optimize family dynamics and bolster acceptance to potentially reduce adverse health outcomes.
DOI: 10.15154/1526509
title: Association between mild traumatic brain injury, brain structure, and mental health outcomes in the Adolescent Brain Cognitive Development Study

description: Background: Children that experience a mild traumatic brain injury (mTBI) are at an increased risk of neural alterations that can deteriorate mental health. We test the hypothesis that mTBI is associated with psychopathology and that structural brain metrics (e.g., volume, area) meaningfully mediate the relation in an adolescent population.
Methods: We analyzed behavioral and brain MRI data from 11,876 children who participated in the Adolescent Brain Cognitive Development (ABCD) Study. Mixed-effects models were used to examine the longitudinal association between mTBI and mental health outcomes. Bayesian methods were used to investigate brain regions that are intermediate between mTBI and symptoms of poor mental health.   
Results: There were 199 children with mTBI and 527 with possible mTBI across the three ABCD Study visits. There was a 7% (IRR = 1.07, 95% CI: 1.01, 1.13) and 15% (IRR = 1.16, 95% CI: 1.05, 1.26) increased risk of emotional or behavioral problems in children that experienced possible mTBI or mTBI, respectively. Possible mTBI  was associated with a 17% (IRR: 1.17, 95% CI: 0.99, 1.40) increased risk of experiencing distress following a psychotic-like experience. We did not find any brain regions that meaningfully mediated the relationship between mTBI and mental health outcomes. Analysis of volumetric measures found that approximately 2% to 5% of the total effect of mTBI on mental health outcomes operated through total cortical volume. Image intensity measure analyses determined that approximately 2% to 5% of the total effect was mediated through the left-hemisphere of the dorsolateral prefrontal cortex. 
Conclusion: Results indicate an increased risk of emotional and behavioral problems in children that experienced possible mTBI or mTBI. Mediation analyses did not elucidate the mechanisms underlying the association between mTBI and mental health outcomes.
DOI: 10.15154/1526524
title: Disparities in Sleep Duration Among American Children: Effects of Race and Ethnicity, Income, Age, and Sex

description: Children in the United States sleep less than the recommended amount and sleep deficiencies may be worse among disadvantaged children. Prior studies that compared sleep time in children of different race/ethnic groups mostly relied on questionnaires or were limited to small sample sizes. Our study takes advantage of the Adolescent Brain Cognitive DevelopmentSM (ABCD) study to compare total sleep time using a week of actigraphy data among American children (n=4207, 9-13 y/o) of different racial/ethnic and income groups. We also assessed the effects of neighborhood deprivation, experience of discrimination, parent’s age at child’s birth, BMI, and time the child fell asleep on sleep times. Daily total sleep time for the sample was 7.45 hours and race/ethnicity, income, sex, age, BMI, were all significant predictors of total sleep time. Black children slept less than White children (≈34 min; Cohen’s d=.95), children from lower income families slept less than those from higher incomes (≈16 min; Cohen’s d=.44), boys slept less than girls (≈7 min; Cohen’s d=.18), and older children slept less than younger ones (≈32 min; Cohen’s d=.91); mostly due to later sleep times. Children with higher BMI also had shorter sleep times. Neither area deprivation index, experience of discrimination, or parent’s age at child’s birth significantly contributed to sleep time. Our findings indicate that children in the United States sleep significantly less than the recommended amount for healthy development and identifies significant racial and income disparities. Interventions to improve sleep hygiene in children will help improve health and ameliorate racial disparities in health outcomes.
DOI: 10.15154/1527628
title: The Role of School Environment in Brain Structure, Connectivity, and Mental Health in Children: A Multimodal Investigation

description: Background
Much work has been dedicated to understanding the effects of adverse home environments on brain development. While the school social and learning environment plays a role in child development, little work has been done to investigate the impact of the school environment on the developing brain. The goal of the present study was to examine associations between the school environment, brain structure and connectivity, and mental health.

Methods
In this preregistered study we investigated these questions in a large sample of adolescents (9–10 years of age) from the Adolescent Brain Cognitive Development (ABCD) Study. We examined the association between school environment and gray matter (n = 10,435) and white matter (n = 10,770) structure and functional connectivity (n = 9528). We then investigated multivariate relationships between school-associated brain measures and mental health.

Results
School environment was associated with connectivity of the auditory and retrosplenial temporal network as well as of higher-order cognitive networks like the cingulo-opercular, default mode, ventral attention, and frontoparietal networks. Multivariate analyses revealed that connectivity of the cingulo-opercular and default mode networks was also associated with mental health.

Conclusions
Findings shed light on the neural mechanisms through which favorable school environments may contribute to positive mental health outcomes in children. Our findings have implications for interventions targeted at promoting positive youth functioning through improving school environments.
DOI: 10.15154/1527711
title: Characterizing the dimensional structure of early-life adversity in the Adolescent Brain Cognitive Development (ABCD) Study

description: Increasing evidence suggests that different dimensions of early-life adversity may be associated with unique neurodevelopmental mechanisms and behavioral outcomes. We sought to characterize the underlying dimensional structure of co-occurring adverse experiences among a community sample of youth (ages 9-10) from a subset of the Adolescent Brain Cognitive Development (ABCD) Study (N = 7,115). We identified 60 environmental and experiential variables that reflect adverse experiences. Exploratory factor analysis identified 10 early-life adversity dimensions of co-occurrence corresponding to conceptual domains such as caregiver substance use and biological caregiver separation, caregiver psychopathology, caregiver lack of support, and socioeconomic disadvantage / neighborhood lack of safety. These dimensions demonstrated distinct associations with internalizing problems, externalizing problems, cognitive flexibility, and inhibitory control. Non-metric multidimensional scaling characterized the qualitative similarity among the 10 identified dimensions. Results supported a nonlinear three-dimensional structure representing early-life adversity, including continuous gradients of “perspective”, “environmental uncertainty”, and “acts of omission/commission”. Our findings suggest that there are 10 dimensions of early-life adversity in the ABCD sample at baseline, and the resulting dimensions may have unique implications for neurodevelopment and youth behavior.
DOI: 10.15154/1527726
title: Sex-specific Factors that Predict Early Substance Initiation in the ABCD Sample

description: Objective: Studies addressing childhood risk factors for the development of substance use disorders (SUDs) have focused mostly on males. Few studies have examined the risk for early substance use in males or females. We generated sex-specific subgroups defined by environmental, cognitive, and behavioral characteristics, to identify predictors of substance use at age 9-10. Method: A machine learning approach identified risk factors in males (n = 371) and females (n = 281), that predict drug or alcohol use at age 9-10 among subjects in the Adolescent Brain Cognitive Development (ABCD) study. First, twenty-nine variables with “low importance” (< 50% importance) were excluded by Random Forest analysis (RF). Then, the remaining candidate predictors were entered in Classification and Regression Trees (CART) analysis. CART was used to identify risk factors and their synergistic interactions, classifying children into “user” and “non-user” groups, independently for males and females. Results: CART analysis identified negative urgency, lack of perseverance, abstract reasoning, sensation seeking, and reward sensitivity as the most useful predictors for males, while abstract reasoning and family history of SUDs were the best predictors for females. Conclusions: The machine learning model identified different factors for males and females to classify them as substance “users” or “non-users”. While several personality and cognitive variables were crucial to classify males as “users”, for females the only optimal classifiers were abstract reasoning and familial SUD. These results suggest that the predictive utility of risk factors is largely unique to each sex.
DOI: 10.15154/1527737
title: An open-access accelerated adult equivalent of the ABCD Study neuroimaging dataset (a-ABCD).

description: As public access to longitudinal developmental datasets like the Adolescent Brain Cognitive Development StudySM (ABCD Study®) increases, so too does the need for resources to benchmark time-dependent effects. Scan-to-scan changes observed with repeated imaging may reflect development but may also reflect practice effects, day-to-day variability in psychological states, and/or measurement noise. Resources that allow disentangling these time-dependent effects will be useful in quantifying actual developmental change. We present an accelerated adult equivalent of the ABCD Study dataset (a-ABCD) using an identical imaging protocol to acquire magnetic resonance imaging (MRI) structural, diffusion-weighted, resting-state and task-based data from eight adults scanned five times over five weeks. We report on the task-based imaging data (n = 7). In-scanner stop-signal (SST), monetary incentive delay (MID), and emotional n-back (EN-back) task behavioral performance did not change across sessions. Post-scan recognition memory for emotional n-back stimuli, however, did improve as participants became more familiar with the stimuli. Functional MRI analyses revealed that patterns of task-based activation reflecting inhibitory control in the SST, reward success in the MID task, and working memory in the EN-back task were more similar within individuals across repeated scan sessions than between individuals. Within-subject, activity was more consistent across sessions during the EN-back task than in the SST and MID task, demonstrating differences in fMRI data reliability as a function of task. The a-ABCD dataset provides a unique testbed for characterizing the reliability of brain function, structure, and behavior across imaging modalities in adulthood and benchmarking neurodevelopmental change observed in the open-access ABCD Study.