Differences in the functional brain architecture of sustained attention and working memory in youth and adults.

Sustained attention (SA) and working memory (WM) are critical processes, but the brain networks supporting these abilities in development are unknown. We characterized the functional brain architecture of SA and WM in 9- to 11-year-old children and adults. First, we found that adult network predictors of SA generalized to predict individual differences and fluctuations in SA in youth. A WM model predicted WM performance both across and within children-and captured individual differences in later recognition memory-but underperformed in youth relative to adults. We next characterized functional connections differentially related to SA and WM in youth compared to adults. Results revealed 2 network configurations: a dominant architecture predicting performance in both age groups and a secondary architecture, more prominent for WM than SA, predicting performance in each age group differently. Thus, functional connectivity (FC) predicts SA and WM in youth, with networks predicting WM performance differing more between youths and adults than those predicting SA.

Air pollution and age-dependent changes in emotional behavior across early adolescence in the U.S.

Recent studies have linked air pollution to increased risk for behavioral problems during development, albeit with inconsistent findings. Additional longitudinal studies are needed that consider how emotional behaviors may be affected when exposure coincides with the transition to adolescence - a vulnerable time for developing mental health difficulties. This study investigates if annual average PM2.5 and NO2 exposure at ages 9-10 years moderates age-related changes in internalizing and externalizing behaviors over a 2-year follow-up period in a large, nationwide U.S. sample of participants from the Adolescent Brain Cognitive Development (ABCD) Study®. Air pollution exposure was estimated based on the residential address of each participant using an ensemble-based modeling approach. Caregivers answered questions from the Child Behavior Checklist (CBCL) at the baseline, 1-year follow-up, and 2-year follow-up visits, for a total of 3 waves of data; from the CBCL we obtained scores on internalizing and externalizing problems plus 5 syndrome scales (anxious/depressed, withdrawn/depressed, rule-breaking behavior, aggressive behavior, and attention problems). Zero-inflated negative binomial models were used to examine both the main effect of age as well as the interaction of age with each pollutant on behavior while adjusting for various socioeconomic and demographic characteristics. Against our hypothesis, there was no evidence that greater air pollution exposure was related to more behavioral problems with age over time.

Evidence and theory for lower rates of depression in larger US urban areas.

It is commonly assumed that cities are detrimental to mental health. However, the evidence remains inconsistent and at most, makes the case for differences between rural and urban environments as a whole. Here, we propose a model of depression driven by an individual's accumulated experience mediated by social networks. The connection between observed systematic variations in socioeconomic networks and built environments with city size provides a link between urbanization and mental health. Surprisingly, this model predicts lower depression rates in larger cities. We confirm this prediction for US cities using four independent datasets. These results are consistent with other behaviors associated with denser socioeconomic networks and suggest that larger cities provide a buffer against depression. This approach introduces a systematic framework for conceptualizing and modeling mental health in complex physical and social networks, producing testable predictions for environmental and social determinants of mental health also applicable to other psychopathologies.

Profiling intra- and inter-individual differences in brain development across early adolescence.

As we move toward population-level developmental neuroscience, understanding intra- and inter-individual variability in brain maturation and sources of neurodevelopmental heterogeneity becomes paramount. Large-scale, longitudinal neuroimaging studies have uncovered group-level neurodevelopmental trajectories, and while recent work has begun to untangle intra- and inter-individual differences, they remain largely unclear. Here, we aim to quantify both intra- and inter-individual variability across facets of neurodevelopment across early adolescence (ages 8.92 to 13.83 years) in the Adolescent Brain Cognitive Development (ABCD) Study and examine inter-individual variability as a function of age, sex, and puberty. Our results provide novel insight into differences in annualized percent change in macrostructure, microstructure, and functional brain development from ages 9-13 years old. These findings reveal moderate age-related intra-individual change, but age-related differences in inter-individual variability only in a few measures of cortical macro- and microstructure development. Greater inter-individual variability in brain development were seen in mid-pubertal individuals, except for a few aspects of white matter development that were more variable between prepubertal individuals in some tracts. Although both sexes contributed to inter-individual differences in macrostructure and functional development in a few regions of the brain, we found limited support for hypotheses regarding greater male-than-female variability. This work highlights pockets of individual variability across facets of early adolescent brain development, while also highlighting regional differences in heterogeneity to facilitate future investigations in quantifying and probing nuances in normative development, and deviations therefrom.

Effects of the physical and social environment on youth cognitive performance.

Individual differences in children's cognitive abilities impact life and health outcomes. What factors influence these individual differences during development? Here, we test whether children's environments predict cognitive performance, independent of well-characterized socioeconomic effects. We analyzed data from 9002 9- to 10-year olds from the Adolescent Brain Cognitive Development Study, an ongoing longitudinal study with community samples across the United States. Using youth- and caregiver-report questionnaires and national database registries (e.g., neighborhood crime, walkability), we defined principal components summarizing children's home, school, neighborhood, and cultural environments. In two independent samples (ns = 3475, 5527), environmental components explained unique variance in children's general cognitive ability, executive functioning, and learning/memory abilities. Furthermore, increased neighborhood enrichment was associated with an attenuated relationship between sociodemographics and general cognitive abilities. Thus, the environment accounts for unique variance in cognitive performance in children and should be considered alongside sociodemographic factors to better understand brain functioning and behavior across development.

Load-dependent relationships between frontal fNIRS activity and performance: A data-driven PLS approach.

Neuroimaging research frequently demonstrates load-dependent activation in prefrontal and parietal cortex during working memory tasks such as the N-back. Most of this work has been conducted in fMRI, but functional near-infrared spectroscopy (fNIRS) is gaining traction as a less invasive and more flexible alternative to measuring cortical hemodynamics. Few fNIRS studies, however, have examined how working memory load-dependent changes in brain hemodynamics relate to performance. The current study employs a newly developed and robust statistical analysis of task-based fNIRS data in a large sample, and demonstrates the utility of data-driven, multivariate analyses to link brain activation and behavior in this modality. Seventy participants completed a standard N-back task with three N-back levels (N = 1, 2, 3) while fNIRS data were collected from frontal and parietal cortex. Overall, participants showed reliably greater fronto-parietal activation for the 2-back versus the 1-back task, suggesting fronto-parietal fNIRS measurements are sensitive to differences in cognitive load. The results for 3-back were much less consistent, potentially due to poor behavioral performance in the 3-back task. To address this, a multivariate analysis (behavioral partial least squares, PLS) was conducted to examine the interaction between fNIRS activation and performance at each N-back level. Results of the PLS analysis demonstrated differences in the relationship between accuracy and change in the deoxyhemoglobin fNIRS signal as a function of N-back level in eight mid-frontal channels. Specifically, greater reductions in deoxyhemoglobin (i.e., more activation) were positively related to performance on the 3-back task, unrelated to accuracy in the 2-back task, and negatively associated with accuracy in the 1-back task. This pattern of results suggests that the metabolic demands correlated with neural activity required for high levels of accuracy vary as a consequence of task difficulty/cognitive load, whereby more automaticity during the 1-back task (less mid-frontal activity) predicted superior performance on this relatively easy task, and successful engagement of this mid-frontal region was required for high accuracy on a more difficult and cognitively demanding 3-back task. In summary, we show that fNIRS activity can track working memory load and can uncover significant associations between brain activity and performance, thus opening the door for this modality to be used in more wide-spread applications.

The impact of motivation on race-based impression formation.

Affective biases toward racial out-group members, characterized by White perceivers' negative evaluations of Black individuals, prevail in U.S. culture. Such affective associations have been found to guide race-based impression formation. Accordingly, individuals may strive to resolve inconsistencies when perceiving targets violating their expectations. The current study focuses on the impact of evaluative incongruence on the activity of the dorsomedial prefrontal cortex (dmPFC) - a brain region previously shown to support impression formation. When asking participants to form impressions of positively and negatively evaluated Black and White individuals, we found preferential dmPFC activity in response to individuals paired with information that violates race-based affective associations. Importantly, individual differences in internal motivation to respond without prejudice (IMS) were found to shape the extent to which dmPFC activity indexes the interactive effects of race and affective associations during impression formation. Specifically, preferential dmPFC activity in response to evaluatively incongruent targets (i.e., Black-positive & White-negative) was present among participants with lower, but not those with higher, levels of IMS. Implications and future directions are discussed in the context of dmPFC involvement in social cognition.

Recommendations for the responsible use and communication of race and ethnicity in neuroimaging research.

The growing availability of large-population human biomedical datasets provides researchers with unique opportunities to conduct rigorous and impactful studies on brain and behavioral development, allowing for a more comprehensive understanding of neurodevelopment in diverse populations. However, the patterns observed in these datasets are more likely to be influenced by upstream structural inequities (that is, structural racism), which can lead to health disparities based on race, ethnicity and social class. This paper addresses the need for guidance and self-reflection in biomedical research on conceptualizing, contextualizing and communicating issues related to race and ethnicity. We provide recommendations as a starting point for researchers to rethink race and ethnicity choices in study design, model specification, statistical analysis and communication of results, implement practices to avoid the further stigmatization of historically minoritized groups, and engage in research practices that counteract existing harmful biases.

Prenatal and childhood air pollution exposure, cellular immune biomarkers, and brain connectivity in early adolescents.

Introduction: Ambient air pollution is a neurotoxicant with hypothesized immune-related mechanisms. Adolescent brain structural and functional connectivity may be especially vulnerable to ambient pollution due to the refinement of large-scale brain networks during this period, which vary by sex and have important implications for cognitive, behavioral, and emotional functioning. In the current study we explored associations between air pollutants, immune markers, and structural and functional connectivity in early adolescence by leveraging cross-sectional sex-stratified data from the Adolescent Brain Cognitive Development℠ Study®. Methods: Pollutant concentrations of fine particulate matter, nitrogen dioxide, and ozone were assigned to each child's primary residential address during the prenatal period and childhood (9-10 years-old) using an ensemble-based modeling approach. Data collected at 11-13 years-old included resting-state functional connectivity of the default mode, frontoparietal, and salience networks and limbic regions of interest, intracellular directional and isotropic diffusion of available white matter tracts, and markers of cellular immune activation. Using partial least squares correlation, a multivariate data-driven method that identifies important variables within latent dimensions, we investigated associations between 1) pollutants and structural and functional connectivity, 2) pollutants and immune markers, and 3) immune markers and structural and functional connectivity, in each sex separately. Results: Air pollution exposure was related to white matter intracellular directional and isotropic diffusion at ages 11-13 years, but the direction of associations varied by sex. There were no associations between pollutants and resting-state functional connectivity at ages 11-13 years. Childhood exposure to nitrogen dioxide was negatively correlated with white blood cell count in males. Immune biomarkers were positively correlated with white matter intracellular directional diffusion in females and both white matter intracellular directional and isotropic diffusion in males. Lastly, there was a reliable negative correlation between lymphocyte-to-monocyte ratio and default mode network resting-state functional connectivity in females, as well as a compromised immune marker profile associated with lower resting-state functional connectivity between the salience network and the left hippocampus in males. In post-hoc exploratory analyses, we found that the PLSC-identified white matter tracts and resting-state networks related to processing speed and cognitive control performance from the NIH Toolbox. Conclusions: We identified novel links between childhood nitrogen dioxide and cellular immune activation in males, and brain network connectivity and immune markers in both sexes. Future research should explore the potentially mediating role of immune activity in how pollutants affect neurological outcomes as well as the potential consequences of immune-related patterns of brain connectivity in service of improved brain health for all.

Lifetime residential history collection and processing for environmental data linkages in the ABCD study.

By using geospatial information such as participants' residential history along with external datasets of environmental exposures, ongoing studies can enrich their cohorts to investigate the role of the environment on brain-behavior health outcomes. However, challenges may arise if clear guidance and key quality control steps are not taken at the outset of data collection of residential information. Here, we detail the protocol development aimed at improving the collection of lifetime residential address information from the Adolescent Brain Cognitive Development (ABCD) Study. This protocol generates a workflow for minimizing gaps in residential information, improving data collection processes, and reducing misclassification error in exposure estimates.

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.

Air pollution from biomass burning disrupts early adolescent cortical microarchitecture development.

Exposure to outdoor particulate matter (PM 2.5 ) represents a ubiquitous threat to human health, and particularly the neurotoxic effects of PM 2.5 from multiple sources may disrupt neurodevelopment. Studies addressing neurodevelopmental implications of PM exposure have been limited by small, geographically limited samples and largely focus either on macroscale cortical morphology or postmortem histological staining and total PM mass. Here, we leverage residentially assigned exposure to six, data-driven sources of PM 2.5 and neuroimaging data from the longitudinal Adolescent Brain Cognitive Development Study (ABCD Study®), collected from 21 different recruitment sites across the United States. To contribute an interpretable and actionable assessment of the role of air pollution in the developing brain, we identified alterations in cortical microstructure development associated with exposure to specific sources of PM 2.5 using multivariate, partial least squares analyses. Specifically, average annual exposure (i.e., at ages 8-10 years) to PM 2.5 from biomass burning was related to differences in neurite development across the cortex between 9 and 13 years of age.

Air pollution from biomass burning disrupts early adolescent cortical microarchitecture development.

Exposure to outdoor particulate matter (PM2.5) represents a ubiquitous threat to human health, and particularly the neurotoxic effects of PM2.5 from multiple sources may disrupt neurodevelopment. Studies addressing neurodevelopmental implications of PM exposure have been limited by small, geographically limited samples and largely focus either on macroscale cortical morphology or postmortem histological staining and total PM mass. Here, we leverage residentially assigned exposure to six, data-driven sources of PM2.5 and neuroimaging data from the longitudinal Adolescent Brain Cognitive Development Study (ABCD Study®), collected from 21 different recruitment sites across the United States. To contribute an interpretable and actionable assessment of the role of air pollution in the developing brain, we identified alterations in cortical microstructure development associated with exposure to specific sources of PM2.5 using multivariate, partial least squares analyses. Specifically, average annual exposure (i.e., at ages 8-10 years) to PM2.5 from biomass burning was related to differences in neurite development across the cortex between 9 and 13 years of age.

Building towards an adolescent neural urbanome: Expanding environmental measures using linked external data (LED) in the ABCD study.

Many recent studies have demonstrated that environmental contexts, both social and physical, have an important impact on child and adolescent neural and behavioral development. The adoption of geospatial methods, such as in the Adolescent Brain Cognitive Development (ABCD) Study, has facilitated the exploration of many environmental contexts surrounding participants' residential locations without creating additional burdens for research participants (i.e., youth and families) in neuroscience studies. However, as the number of linked databases increases, developing a framework that considers the various domains related to child and adolescent environments external to their home becomes crucial. Such a framework needs to identify structural contextual factors that may yield inequalities in children's built and natural environments; these differences may, in turn, result in downstream negative effects on children from historically minoritized groups. In this paper, we develop such a framework - which we describe as the "adolescent neural urbanome" - and use it to categorize newly geocoded information incorporated into the ABCD Study by the Linked External Data (LED) Environment & Policy Working Group. We also highlight important relationships between the linked measures and describe possible applications of the Adolescent Neural Urbanome. Finally, we provide a number of recommendations and considerations regarding the responsible use and communication of these data, highlighting the potential harm to historically minoritized groups through their misuse.

Transparency and reproducibility in the Adolescent Brain Cognitive Development (ABCD) study.

BACKGROUND: Transparency can build trust in the scientific process, but scientific findings can be undermined by poor and obscure data use and reporting practices. The purpose of this work is to report how data from the Adolescent Brain Cognitive Development (ABCD) Study has been used to date, and to provide practical recommendations on how to improve the transparency and reproducibility of findings. METHODS: Articles published from 2017 to 2023 that used ABCD Study data were reviewed using more than 30 data extraction items to gather information on data use practices. Total frequencies were reported for each extraction item, along with computation of a Level of Completeness (LOC) score that represented overall endorsement of extraction items. Univariate linear regression models were used to examine the correlation between LOC scores and individual extraction items. Post hoc analysis included examination of whether LOC scores were correlated with the logged 2-year journal impact factor. RESULTS: There were 549 full-length articles included in the main analysis. Analytic scripts were shared in 30 % of full-length articles. The number of participants excluded due to missing data was reported in 60 % of articles, and information on missing data for individual variables (e.g., household income) was provided in 38 % of articles. A table describing the analytic sample was included in 83 % of articles. A race and/or ethnicity variable was included in 78 % of reviewed articles, while its inclusion was justified in only 41 % of these articles. LOC scores were highly correlated with extraction items related to examination of missing data. A bottom 10 % of LOC score was significantly correlated with a lower logged journal impact factor when compared to the top 10 % of LOC scores (ß=-0.77, 95 % -1.02, -0.51; p-value < 0.0001). CONCLUSION: These findings highlight opportunities for improvement in future papers using ABCD Study data to readily adapt analytic practices for better transparency and reproducibility efforts. A list of recommendations is provided to facilitate adherence in future research.

Transparency and Reproducibility in the Adolescent Brain Cognitive Development (ABCD) Study.

Background: Transparency can build trust in the scientific process, but scientific findings can be undermined by poor and obscure data use and reporting practices. The purpose of this work is to report how data from the Adolescent Brain Cognitive Development (ABCD) Study has been used to date, and to provide practical recommendations on how to improve the transparency and reproducibility of findings. Methods: Articles published from 2017 to 2023 that used ABCD Study data were reviewed using more than 30 data extraction items to gather information on data use practices. Total frequencies were reported for each extraction item, along with computation of a Level of Completeness (LOC) score that represented overall endorsement of extraction items. Univariate linear regression models were used to examine the correlation between LOC scores and individual extraction items. Post hoc analysis included examination of whether LOC scores were correlated with the logged 2-year journal impact factor. Results: There were 549 full-length articles included in the main analysis. Analytic scripts were shared in 30% of full-length articles. The number of participants excluded due to missing data was reported in 60% of articles, and information on missing data for individual variables (e.g., household income) was provided in 38% of articles. A table describing the analytic sample was included in 83% of articles. A race and/or ethnicity variable was included in 78% of reviewed articles, while its inclusion was justified in only 41% of these articles. LOC scores were highly correlated with extraction items related to examination of missing data. A bottom 10% of LOC score was significantly correlated with a lower logged journal impact factor when compared to the top 10% of LOC scores (ß=-0.77, 95% -1.02, -0.51; p-value < 0.0001). Conclusion: These findings highlight opportunities for improvement in future papers using ABCD Study data to readily adapt analytic practices for better transparency and reproducibility efforts. A list of recommendations is provided to facilitate adherence in future research.

Gray space and default mode network-amygdala connectivity.

Introduction: Aspects of the built environment relate to health factors and equity in living conditions, and may contribute to racial, ethnic, or economic health disparities. For example, urbanicity is linked with negative factors including exposure to gray space (e.g., impervious surfaces such as concrete, streets, or rooftops). While there is existing research on access to green space and urbanicity on some mental health and cognitive outcomes, there is limited research on the presence of gray space linked with cognitive functioning in youth. The goal of this study was to investigate the link between gray space and amygdala-default mode network (DMN) connectivity. Methods: This study used data from the ABCD Study. Participants (n = 10,144; age M = 119.11 months, female = 47.62%) underwent resting-state fMRI acquisition at baseline. Impervious surfaces (gray space) were measured via the Child Opportunity Index (COI). To examine the relationship between presence of gray space and -amygdala-DMN (left/right) connectivity, we employed linear mixed effects models. Correlations were run between amygdala-DMN connectivity and internalizing and externalizing symptoms. Finally, post hoc sensitivity analyses were run to assess the impact of race. Results: More gray space, adjusting for age, sex, and neighborhood-level variables, was significantly associated with increased left amygdala-DMN connectivity (p = 0.0001). This association remained significant after sensitivity analyses for race were completed (p = 0.01). No significant correlations were observed between amygdala-DMN and internalizing or externalizing symptoms. Discussion: Findings suggest gray space was linked with increased left amygdala-DMN connectivity, circuits that have been implicated in affective processing, emotion regulation, and psychopathology. Thus gray space may be related to alterations in connectivity that may enhance risk for emotion dysregulation. Future investigation of these relationships is needed, as neuroimaging findings may represent early dysregulation not yet observed in the behavioral analyses at this age (i.e., the present study did not find significant relationships with parent-reported behavioral outcomes). These findings can help to inform future public policy on improving lived and built environments.

Sex-specific effects in how childhood exposures to multiple ambient air pollutants affect white matter microstructure development across early adolescence.

Ambient air pollution is ubiquitous, yet questions remain as to how it might impact the developing brain. Large changes occur in the brain's white matter (WM) microstructure across adolescence, with noticeable differences in WM integrity in male and female youth. Here we report sex-stratified effects of fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) on longitudinal patterns of WM microstructure from 9-13 years-old in 8,182 (49% female) participants using restriction spectrum imaging. After adjusting for key sociodemographic factors, multi-pollutant, sex-stratified models showed that one-year annual exposure to PM2.5 and NO2 was associated with higher, while O3 was associated with lower, intracellular diffusion at age 9. All three pollutants also affected trajectories of WM maturation from 9-13 years-old, with some sex-specific differences in the number and anatomical locations of tracts showing altered trajectories of intracellular diffusion. Concentrations were well-below current U.S. standards, suggesting exposure to these criteria pollutants during adolescence may have long-term consequences on brain development.

Atypical Functional Network Properties and Associated Dimensions of Child Psychopathology During Rest and Task Performance.

Background: When brain networks deviate from typical development, this is thought to contribute to varying forms of psychopathology. However, research has been limited by the reliance on discrete diagnostic categories that overlook the potential for psychological comorbidity and the dimensional nature of symptoms. Methods: This study examined the topology of functional networks in association with 4 bifactor-defined psychopathology dimensions-general psychopathology, internalizing symptoms, conduct problems, and attention-deficit/hyperactivity disorder symptoms-via the Child Behavior Checklist in a sample of 3568 children from the ABCD (Adolescent Brain Cognitive Development) Study. Local and global graph theory metrics were calculated at rest and during tasks of reward processing, inhibition, and working memory. Results: Greater attention-deficit/hyperactivity disorder symptoms were associated with reduced modularity across rest and tasks as well as reduced local efficiency in motor networks at rest. Results survived sensitivity analyses for medication and socioeconomic status. Greater conduct problem symptoms were associated with reduced modularity on working memory and reward processing tasks; however, these results did not persist after sensitivity analyses. General psychopathology and internalizing symptoms showed no significant network associations. Conclusions: Our findings suggest reduced efficiency in topology in those with greater attention-deficit/hyperactivity disorder symptoms across 4 critical cognitive states, with conduct problems also showing network deficits, although less consistently. This may suggest that modularity deficits are a neurobiological marker of externalizing behavior in children. Such specificity has not been demonstrated before using graph theory metrics and has the potential to redefine our understanding of network deficits in children with psychopathology symptoms.