Scientific Publications

Abstract

Anxiety and depression in children and adolescents warrant special attention as a public health concern given their devastating and long-term effects on development and mental health. Multiple factors, ranging from genetic vulnerabilities to environmental stressors, influence the risk for the disorders. This study aimed to understand how environmental factors and genomics affect children and adolescents anxiety and depression across three cohorts: Adolescent Brain and Cognitive Development Study (US, age of 9-10; N=11,875), Consortium on Vulnerability to Externalizing Disorders and Addictions (INDIA, age of 6-17; N=4,326) and IMAGEN (EUROPE, age of 14; N=1888). We performed data harmonization and identified the environmental impact on anxiety/depression using a linear mixed-effect model, recursive feature elimination regression, and the LASSO regression model. Subsequently, genome-wide association analyses with consideration of significant environmental factors were performed for all three cohorts by mega-analysis and meta-analysis, followed by functional annotations. The results showed that multiple environmental factors contributed to the risk of anxiety and depression during development, where early life stress and school support index had the most significant and consistent impact across all three cohorts. In both meta, and mega-analysis, SNP rs79878474 in chr11p15 emerged as a particularly promising candidate associated with anxiety and depression, despite not reaching genomic significance. Gene set analysis on the common genes mapped from top promising SNPs of both meta and mega analyses found significant enrichment in regions of chr11p15 and chr3q26, in the function of potassium channels and insulin secretion, in particular Kv3, Kir-6.2, SUR potassium channels encoded by the KCNC1, KCNJ11, and ABCCC8 genes respectively, in chr11p15. Tissue enrichment analysis showed significant enrichment in the small intestine, and a trend of enrichment in the cerebellum. Our findings provide evidences of consistent environmental impact from early life stress and school support index on anxiety and depression during development and also highlight the genetic association between mutations in potassium channels, which support the stress-depression connection via hypothalamic-pituitary-adrenal axis, along with the potential modulating role of potassium channels.

Journal

Published

Authors

Keywords

DOI

Abstract

The association between body mass index (BMI) and binge-eating disorder (BED) is well-established. However, data on the extent to which BMI is associated with progression from binge-eating behavior into BED among adolescents are limited, which was the aim of this investigation. Participants were 9,964 U.S. adolescents from the Adolescent Brain Cognitive Development (ABCD) Study, aged 9-13 at the time of study enrollment. A computerized parent-reported assessment was used to establish adolescents’ binge-eating behaviors and BED. Cox proportional hazards models adjusting for sociodemographic covariates were used to examine prospective associations between BMI and likelihood of BED onset among a) adolescents with binge-eating behavior, and b) adolescents with no binge-eating behavior. Of 975 adolescents who met study criteria for binge-eating behavior, 89 (9.1%) subsequently met study criteria for BED. Of 8,989 adolescents with no binge-eating behavior, 82 (0.9%) subsequently met study criteria for BED. BMI percentile was significantly associated with the likelihood of BED onset in participants with [ adjusted HR =1.03 (1.00, 1.06)] and participants without [adjusted HR =1.05 (1.03, 1.07)] binge-eating behavior. Results were also significant when examining BMI as a dichotomous predictor (above and below 85 percentile) among those with [adjusted HR =2.60 (1.00, 6.68) and those without [adjusted HR =6.01 (3.90, 11.10)] binge-eating behavior. Overall, results indicate that elevated BMI is prospectively associated with a greater risk for BED onset among U.S. adolescents with or without binge-eating behavior. Adolescents with a higher BMI may benefit from screening for binge eating, and prevention/early intervention strategies to mitigate the risk for developing BED.

Journal

Published

Authors

Keywords

DOI

Abstract

Adolescent depression is characterized by diverse symptom trajectories over time and has a strong genetic influence. Research has determined genetic overlap between depression and other psychiatric conditions; investigating the shared genetic architecture of heterogeneous depression trajectories is crucial for understanding disease etiology, prediction, and early intervention.

Journal

Published

Authors

Keywords

DOI

Abstract

Children tend to endorse psychotic-like experiences (PLEs) at higher rates than adults, although little is known about how specific symptom endorsement changes across the span of development. Here we take an observational approach to examine trends in PLE endorsement by age in two non-clinical samples: one of school-aged children and another of late adolescents and early adults.

Journal

Published

Authors

Keywords

DOI

Abstract

Patients and healthcare professionals overestimate the risks of using antidepressants during pregnancy. According to current literature, approximately half of people stop taking an anti-depressant medication when they become pregnant. Discontinuing antidepressants during pregnancy increases risks of postnatal relapses. Factors like socioeconomic status, education, and planned pregnancies play a role in the decision to continue antidepressant medication, which can worsen disparities in maternal and child health. Our aim was to identify the sociodemographic factors associated with antidepressant continuation after awareness of pregnancy.

Journal

Published

Authors

Keywords

DOI

Abstract

Journal

Published

Authors

Keywords

DOI

Abstract

Journal

Published

Authors

Keywords

DOI

Abstract

Impulsivity undergoes a normative developmental trajectory from childhood to adulthood and is thought to be driven by maturation of brain structure. However, few large-scale studies have assessed associations between impulsivity, brain structure, and genetic susceptibility in children. In 9112 children ages 9-10 from the ABCD study, we explored relationships among impulsivity (UPPS-P impulsive behavior scale; delay discounting), brain structure (cortical thickness (CT), cortical volume (CV), and cortical area (CA)), and polygenic scores for externalizing behavior (PGS). Both higher UPPS-P total scores and more severe delay-discounting had widespread, low-magnitude associations with smaller CA in frontal and temporal regions. No associations were seen between impulsivity and CV or CT. Additionally, higher PGS was associated with both higher UPPS-P scores and with smaller CA and CV in frontal and temporal regions, but in non-overlapping cortical regions, underscoring the complex interplay between genetics and brain structure in influencing impulsivity. These findings indicate that, within large-scale population data, CA is significantly yet weakly associated with each of these impulsivity measures and with polygenic risk for externalizing behaviors, but in distinct brain regions. Future work should longitudinally assess these associations through adolescence, and examine associated functional outcomes, such as future substance use and psychopathology.

Journal

Published

Authors

Keywords

DOI

Abstract

In past decades, the positive role of self-control in students’ academic success has attracted plenty of scholarly attention. However, fewer studies have examined the link between adolescents’ neural development of the inhibitory control system and their academic achievement, especially using a longitudinal approach. Moreover, less is known about the role of parents in this link. Using large-scale longitudinal data from the Adolescent Brain Cognitive Development (ABCD) study (N = 9574; mean age = 9.94 years at baseline, SD = .63; 50% girls), the current study took an integrative biopsychosocial approach to explore the longitudinal link between early adolescents’ fronto-striatal connectivity and their academic achievement, with attention to the moderating role of parental warmth. Results showed that weaker intrinsic connectivity between the frontoparietal network and the striatum was associated with early adolescents’ worse academic achievement over 2 years during early adolescence. Notably, parental warmth moderated the association between fronto-striatal connectivity and academic achievement, such that weaker fronto-striatal connectivity was only predictive of worse academic achievement among early adolescents who experienced low levels of parental warmth. Taken together, the findings demonstrate weaker fronto-striatal connectivity as a risk factor for early adolescents’ academic development and highlight parental warmth as a protective factor for academic development among those with weaker connectivity within the inhibitory control system.

Journal

Published

Authors

Keywords

DOI

Abstract

The prevalence, pathophysiology, and long-term outcomes of COVID-19 (post-acute sequelae of SARS-CoV-2 [PASC] or “Long COVID”) in children and young adults remain unknown. Studies must address the urgent need to define PASC, its mechanisms, and potential treatment targets in children and young adults.

Journal

Published

Authors

Keywords

DOI

Abstract

Cannabidiol (CBD) is rising in popularity, including as a potential medicinal product. Yet data on use of commercial CBD for medicinal or health reasons in adolescents are lacking. In this study we aim to detail characteristics of adolescents given commercial CBD for health reasons (health CBD [hCBD]) and to investigate predictors of use. The Adolescent Brain Cognitive Development (ABCD) Study is a population-based cohort study following U.S. healthy, community-based adolescents annually, with data from 2018 to 2022 (11- to 15-year-olds; =11,189). Participants and caregivers completed questionnaires, including whether adolescents were given CBD with parent or doctor’s permission. Participants reported past-month pain, attention problems, externalizing symptoms, internalizing symptoms, and total mental health problems. Caregivers reported youth sociodemographics, sleep problems, whether the youth had mental health treatment or sought medical treatment, and rules about recreational cannabis use. We describe youth given hCBD, and run generalized estimating equations predicting odd ratios (ORs) and 95% confidence intervals of adolescents given hCBD by mental health, physical health, or sociodemographics of factors. Of the 11,189 participants across up to three waves of data, 48% were female. Mean age across waves was 12.8 years old (SD=1). In total, 307 (2.8%) were given hCBD. Common administration methods were oil (42%), topical (31%), and edibles (29%). Increased hCBD odds were associated with being older (OR=1.32 [1.17-1.49]), White (relative to Black, OR=05.97 [2.81-12.65] or Hispanic, OR=1.82 [1.17-2.82]), parents with some college (relative to no high school diploma, OR=3.55 [1.09-11.6]), internalizing symptoms (OR=1.81 [1.13-2.91]), mental health treatment (OR=1.76 [1.3-2.38]), pain (OR=1.38 [1.09-1.76]), medical treatment (OR=1.39 [1.08-1.79]), and sleep problems (OR=1.69 [1.27-2.25]). Rules against recreational cannabis decreased odds of hCBD (OR=1.75 [1.30-2.36]). Findings indicate some healthy adolescents are given hCBD, and predictors of use include mental and physical health concerns, being White, older, and parents with some college education. Providers should ask if their youth patients are being given CBD medicinally, and transparently discuss potential benefits, consequences, and unknowns of CBD.

Journal

Published

Authors

Keywords

DOI

Abstract

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.

Journal

Published

Authors

Keywords

DOI

Abstract

To assess the association between transgender or gender-questioning identity and screen use (recreational screen time and problematic screen use) in a demographically diverse national sample of early adolescents in the U.S.

Journal

Published

Authors

Keywords

DOI

Abstract

The purpose of the study was to investigate the association between discrimination by multiple sources (i.e., teachers, students, and other adults) and early adolescents’ behavioral problems (i.e., internalizing, externalizing, and attention problems), also considering the protective role of parental warmth in this association.

Journal

Published

Authors

Keywords

DOI

Abstract

Journal

Published

Authors

Keywords

DOI

Abstract

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.

Journal

Published

Authors

Keywords

DOI

Abstract

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.

Journal

Published

Authors

Keywords

DOI

Abstract

The Adolescent Brain and Cognitive Development (ABCD) Study, involving over 11,000 youth and their families, is a groundbreaking project examining various factors impacting brain and cognitive development. Despite yielding hundreds of publications and counting, the ABCD Study has lacked a centralized help platform to assist researchers in navigating and analyzing the extensive ABCD dataset. To support the ABCD research community, we created NowIKnowMyABCD, the first centralized documentation and communication resource publicly available to researchers using ABCD Study data. It consists of two core elements: a user-focused website and a moderated discussion board. The website serves as a repository for ABCD-related resources, tutorials, and a live feed of relevant updates and queries sourced from social media websites. The discussion board offers a platform for researchers to seek guidance, troubleshoot issues, and engage with peers. Our aim is for NowIKnowMyABCD to grow with participation from the ABCD research community, fostering transparency, collaboration, and adherence to open science principles.

Journal

Published

Authors

Keywords

DOI

Abstract

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.

Journal

Published

Authors

Keywords

DOI

Abstract

Alzheimer’s disease (AD)-related neuropathological changes can occur decades before clinical symptoms. We aimed to investigate whether neurodevelopment and/or neurodegeneration affects the risk of AD, through reducing structural brain reserve and/or increasing brain atrophy, respectively.

Journal

Published

Authors

Keywords

DOI

Abstract

Pet acquisition purportedly increased during the COVID-19 pandemic with individuals acquiring pets during periods of social isolation. Families with children experienced unique challenges during the COVID-19 pandemic, balancing childcare, remote schooling, and other needs and therefore patterns of pet acquisition and loss may differ from the broader population. The goal of this study was to understand patterns of pet ownership within families with adolescents during the pandemic to help identify areas for improved support and programmatic recommendations. Using self-reported survey data from a sample of 7,590 American adolescents from the Adolescent Brain Cognitive Development (ABCD) Study COVID Survey, we found no evidence for large-scale changes in pet acquisition or relinquishment during the first year of the pandemic for families with adolescents in the U.S. Future research should explore the effects of pet acquisition and pet loss on families with adolescents and what resources are needed to support pet ownership during stressors such as the COVID-19 pandemic.

Journal

Published

Authors

Keywords

DOI

Abstract

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.

Journal

Published

Authors

Keywords

DOI

Abstract

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 ( = 10,147, = 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.

Journal

Published

Authors

Keywords

DOI

Abstract

Coarse measures of socioeconomic status, such as parental income or parental education, have been linked to differences in white matter development. However, these measures do not provide insight into specific aspects of an individual’s environment and how they relate to brain development. On the other hand, educational intervention studies have shown that changes in an individual’s educational context can drive measurable changes in their white matter. These studies, however, rarely consider socioeconomic factors in their results. In the present study, we examined the unique relationship between educational opportunity and white matter development, when controlling other known socioeconomic factors. To explore this question, we leveraged the rich demographic and neuroimaging data available in the ABCD study, as well the unique data-crosswalk between ABCD and the Stanford Education Data Archive (SEDA). We find that educational opportunity is related to accelerated white matter development, even when accounting for other socioeconomic factors, and that this relationship is most pronounced in white matter tracts associated with academic skills. These results suggest that the school a child attends has a measurable relationship with brain development for years to come.

Journal

Published

Authors

Keywords

DOI

Abstract

Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviours and although strides have been made using genome-wide association studies to identify risk variants, most variants identified have been for nicotine consumption, rather than TUD. Here we leveraged four US biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records) in 653,790 individuals (495,005 European, 114,420 African American and 44,365 Latin American) and data from UK Biobank (n = 898,680). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviours in children and hundreds of medical outcomes, including HIV infection, heart disease and pain. This work furthers our biological understanding of TUD and establishes electronic health records as a source of phenotypic information for studying the genetics of TUD.

Journal

Published

Authors

Keywords

DOI

Abstract

Why do potentially traumatic events (PTEs) and substance use (SU) so commonly co-occur during adolescence? Causal hypotheses developed from the study of posttraumatic stress disorder (PTSD) and substance use disorder (SUD) among adults have not yet been subject to rigorous theoretical analysis or empirical tests among adolescents with the precursors to these disorders: PTEs and SU. Establishing causality demands accounting for various factors (e.g. genetics, parent education, race/ethnicity) that distinguish youth endorsing PTEs and SU from those who do not, a step often overlooked in previous research.

Journal

Published

Authors

Keywords

DOI

Abstract

Journal

Published

Authors

Keywords

DOI

Abstract

Research on social determinants of health has highlighted the influence of neighborhood characteristics (e.g., neighborhood safety) on adolescents’ health. However, it is less clear how changes in neighborhood environments play a role in adolescent development, and who are more sensitive to such changes. Utilizing the first three waves of data from the Adolescent Brain Cognitive Development (ABCD) project (N = 7932, M (SD) = 9.93 (.63) years at T1; 51% boys), the present study found that increases in neighborhood safety were associated with decreased adolescent externalizing symptoms, internalizing symptoms, but not sleep disturbance over time, controlling for baseline neighborhood safety. Further, adolescents’ insula and anterior cingulate cortex (ACC) reactivity to positive emotional stimuli moderated the association between changes in neighborhood safety and adolescent adjustment. Among youth who showed higher, but not lower, insula and ACC reactivity to positive emotion, increases in neighborhood safety were linked with better adjustment. The current study contributes to the differential susceptibility literature by identifying affective neural sensitivity as a marker of youth’s susceptibility to changes in neighborhood environment. The findings highlight the importance of neighborhood safety for youth during the transition to adolescence, particularly for those with heightened affective neural sensitivity.

Journal

Published

Authors

Keywords

DOI

Abstract

Craniosynostosis (CS) is a major birth defect resulting from premature fusion of cranial sutures. Nonsyndromic CS occurs more frequently than syndromic CS, with sagittal nonsyndromic craniosynostosis (sNCS) presenting as the most common CS phenotype. Previous genome-wide association and targeted sequencing analyses of sNCS have identified multiple associated loci, with the strongest association on chromosome 20. Herein, we report the first whole-genome sequencing study of sNCS using 63 proband-parent trios. Sequencing data for these trios were analyzed using the transmission disequilibrium test (TDT) and rare variant TDT (rvTDT) to identify high-risk rare gene variants. Sequencing data were also examined for copy number variants (CNVs) and de novo variants. TDT analysis identified a highly significant locus at 20p12.3, localized to the intergenic region between BMP2 and the noncoding RNA gene LINC01428. Three variants (rs6054763, rs6054764, rs932517) were identified as potential causal variants due to their probability of being transcription factor binding sites, deleterious combined annotation dependent depletion scores, and high minor allele enrichment in probands. Morphometric analysis of cranial vault shape in an unaffected cohort validated the effect of these three single nucleotide variants (SNVs) on dolichocephaly. No genome-wide significant rare variants, de novo loci, or CNVs were identified. Future efforts to identify risk variants for sNCS should include sequencing of larger and more diverse population samples and increased omics analyses, such as RNA-seq and ATAC-seq.

Journal

Published

Authors

Keywords

DOI

Abstract

Human fetal development has been associated with brain health at later stages. It is unknown whether growth in utero, as indexed by birth weight (BW), relates consistently to lifespan brain characteristics and changes, and to what extent these influences are of a genetic or environmental nature. Here we show remarkably stable and lifelong positive associations between BW and cortical surface area and volume across and within developmental, aging and lifespan longitudinal samples (N = 5794, 4-82 y of age, w/386 monozygotic twins, followed for up to 8.3 y w/12,088 brain MRIs). In contrast, no consistent effect of BW on brain changes was observed. Partly environmental effects were indicated by analysis of twin BW discordance. In conclusion, the influence of prenatal growth on cortical topography is stable and reliable through the lifespan. This early-life factor appears to influence the brain by association of brain reserve, rather than brain maintenance. Thus, fetal influences appear omnipresent in the spacetime of the human brain throughout the human lifespan. Optimizing fetal growth may increase brain reserve for life, also in aging.

Journal

Published

Authors

Keywords

DOI

Abstract

Neuroscience is advancing standardization and tool development to support rigor and transparency. Consequently, data pipeline complexity has increased, hindering FAIR (findable, accessible, interoperable and reusable) access. brainlife.io was developed to democratize neuroimaging research. The platform provides data standardization, management, visualization and processing and automatically tracks the provenance history of thousands of data objects. Here, brainlife.io is described and evaluated for validity, reliability, reproducibility, replicability and scientific utility using four data modalities and 3,200 participants.

Journal

Published

Authors

Keywords

DOI

Abstract

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.

Journal

Published

Authors

Keywords

DOI

Abstract

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.

Journal

Published

Authors

Keywords

DOI

Abstract

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 9-10 years 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 evidence of 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.

Journal

Published

Authors

Keywords

DOI

Abstract

Early adverse experiences or exposures have a profound impact on neurophysiological, cognitive, and somatic development. Evidence across disciplines uncovers adversity-induced alternations in cortical structures, cognitive functions, and related behavioral manifestations, as well as an energetic trade-off between the brain and body. Based on the life history (LH) framework, the present research aims to explore the adversity-adapted cognitive-behavioral mechanism and investigate the relation between cognitive functioning and somatic energy reserve (i.e., body mass index; BMI). A structural equation modeling (SEM) analysis was performed with longitudinal self-reported, anthropometric, and task-based data drawn from a cohort of 2,607 8- to 11-year-old youths and their primary caregivers recruited by the Adolescent Brain Cognitive Development (ABCD) study. The results showed that early environmental adversity was positively associated with fast LH behavioral profiles and negatively with cognitive functioning. Moreover, cognitive functioning mediated the relationship between adversity and fast LH behavioral profiles. Additionally, we found that early environmental adversity positively predicted BMI, which was inversely correlated with cognitive functioning. These results revealed an adversity-adapted cognitive-behavioral mechanism and energy-allocation pathways, and add to the existing knowledge of LH trade-off and developmental plasticity.

Journal

Published

Authors

Keywords

DOI

Abstract

Depression is an incapacitating psychiatric disorder with increased risk through adolescence. Among other factors, children with family history of depression have significantly higher risk of developing depression. Early identification of pre-adolescent children who are at risk of depression is crucial for early intervention and prevention. In this study, we used a large longitudinal sample from the Adolescent Brain Cognitive Development (ABCD) Study (2658 participants after imaging quality control, between 9-10 years at baseline), we applied advanced machine learning methods to predict depression risk at the two-year follow-up from the baseline assessment, using a set of comprehensive multimodal neuroimaging features derived from structural MRI, diffusion tensor imaging, and task and rest functional MRI. Prediction performance underwent a rigorous cross-validation method of leave-one-site-out. Our results demonstrate that all brain features had prediction scores significantly better than expected by chance, with brain features from rest-fMRI showing the best classification performance in the high-risk group of participants with parental history of depression (N = 625). Specifically, rest-fMRI features, which came from functional connectomes, showed significantly better classification performance than other brain features. This finding highlights the key role of the interacting elements of the connectome in capturing more individual variability in psychopathology compared to measures of single brain regions. Our study contributes to the effort of identifying biological risks of depression in early adolescence in population-based samples.

Journal

Published

Authors

Keywords

DOI

Abstract

Journal

Published

Authors

Keywords

DOI

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.

Journal

Published

Authors

Keywords

DOI

Abstract

Adolescence heralds the onset of much psychopathology, which may be conceptualized as an emergence of altered covariation between symptoms and brain measures. Multivariate methods can detect such modes of covariation or latent dimensions, but none specifically relating to psychopathology have yet been found using population-level structural brain data. Using voxel-wise (instead of parcellated) brain data may strengthen latent dimensions’ brain-psychosocial relationships, but this creates computational challenges.

Journal

Published

Authors

Keywords

DOI

Abstract

Magnetic 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.

Journal

Published

Authors

Keywords

DOI

Abstract

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.

Journal

Published

Authors

Keywords

DOI

Abstract

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.

Journal

Published

Authors

Keywords

DOI

Abstract

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.

Journal

Published

Authors

Keywords

DOI

Abstract

Youth 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.

Journal

Published

Authors

Keywords

DOI

Abstract

Journal

Published

Authors

Keywords

DOI

Abstract

One fundamental challenge in diffusion magnetic resonance imaging (dMRI) harmonization is to disentangle the contributions of scanner-related effects from the variable brain anatomy for the observed imaging signals. Conventional harmonization methods rely on establishing an atlas space to resolve anatomical variability and generate a unified inter-site mapping function. However, this approach is limited in accounting for the misalignment of neuroanatomy that still widely persists even after registration, especially in regions close to cortical boundaries. To overcome this challenge, we propose a personalized framework in this paper to more effectively address the confounding from the misalignment of neuroanatomy in dMRI harmonization. Instead of using a common template representing site-effects for all subjects, the main novelty of our method is the adaptive computation of personalized templates for both source and target scanning sites to estimate the inter-site mapping function. We integrate our method with the rotation invariant spherical harmonics (RISH) features to achieve the harmonization of dMRI signals between sites. In our experiments, the proposed approach is applied to harmonize the dMRI data acquired from two scanning platforms: Siemens Prisma and GE MR750 from the Adolescent Brain Cognitive Development dataset and compared with a state-of-the-art method based on RISH features. Our results indicate that the proposed harmonization framework achieves superior performance not only in reducing inter-site variations due to scanner differences but also in preserving sex-related biological variability in original cohorts. Moreover, we assess the impact of harmonization on the estimation of fiber orientation distributions and show the robustness of the personalized harmonization procedure in preserving the fiber orientation of original dMRI signals.

Journal

Published

Authors

Keywords

DOI

Abstract

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.

Journal

Published

Authors

Keywords

DOI

Abstract

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 ~15 months 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 3 months 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.

Journal

Published

Authors

Keywords

DOI

Abstract

Community structure is a fundamental topological characteristic of optimally organized brain networks. Currently, there is no clear standard or systematic approach for selecting the most appropriate community detection method. Furthermore, the impact of method choice on the accuracy and robustness of estimated communities (and network modularity), as well as method-dependent relationships between network communities and cognitive and other individual measures, are not well understood. This study analyzed large datasets of real brain networks (estimated from resting-state fMRI from = 5251 pre/early adolescents in the adolescent brain cognitive development [ABCD] study), and = 5338 synthetic networks with heterogeneous, data-inspired topologies, with the goal to investigate and compare three classes of community detection methods: (i) modularity maximization-based (Newman and Louvain), (ii) probabilistic (Bayesian inference within the framework of stochastic block modeling (SBM)), and (iii) geometric (based on graph Ricci flow). Extensive comparisons between methods and their individual accuracy (relative to the ground truth in synthetic networks), and reliability (when applied to multiple fMRI runs from the same brains) suggest that the underlying brain network topology plays a critical role in the accuracy, reliability and agreement of community detection methods. Consistent method (dis)similarities, and their correlations with topological properties, were estimated across fMRI runs. Based on synthetic graphs, most methods performed similarly and had comparable high accuracy only in some topological regimes, specifically those corresponding to developed connectomes with at least quasi-optimal community organization. In contrast, in densely and/or weakly connected networks with difficult to detect communities, the methods yielded highly dissimilar results, with Bayesian inference within SBM having significantly higher accuracy compared to all others. Associations between method-specific modularity and demographic, anthropometric, physiological and cognitive parameters showed mostly method invariance but some method dependence as well. Although method sensitivity to different levels of community structure may in part explain method-dependent associations between modularity estimates and parameters of interest, method dependence also highlights potential issues of reliability and reproducibility. These findings suggest that a probabilistic approach, such as Bayesian inference in the framework of SBM, may provide consistently reliable estimates of community structure across network topologies. In addition, to maximize robustness of biological inferences, identified network communities and their cognitive, behavioral and other correlates should be confirmed with multiple reliable detection methods.

Journal

Published

Authors

Keywords

DOI

Abstract

There remains little consensus about the relationship between sex and brain structure, particularly in early adolescence. Moreover, few pediatric neuroimaging studies have analyzed both sex and gender as variables of interest-many of which included small sample sizes and relied on binary definitions of gender. The current study examined gender diversity with a continuous felt-gender score and categorized sex based on X and Y allele frequency in a large sample of children ages 9-11 years old (N = 7195). Then, a statistical model-building approach was employed to determine whether gender diversity and sex independently or jointly relate to brain morphology, including subcortical volume, cortical thickness, gyrification, and white matter microstructure. Additional sensitivity analyses found that male versus female differences in gyrification and white matter were largely accounted for by total brain volume, rather than sex per se. The model with sex, but not gender diversity, was the best-fitting model in 60.1% of gray matter regions and 61.9% of white matter regions after adjusting for brain volume. The proportion of variance accounted for by sex was negligible to small in all cases. While models including felt-gender explained a greater amount of variance in a few regions, the felt-gender score alone was not a significant predictor on its own for any white or gray matter regions examined. Overall, these findings demonstrate that at ages 9-11 years old, sex accounts for a small proportion of variance in brain structure, while gender diversity is not directly associated with neurostructural diversity.

Journal

Published

Authors

Keywords

DOI

Abstract

Employing a developmental psychopathology framework, we tested the utility of the hormesis model in examining the strengthening of children and youth through limited levels of adversity in relation to internalizing and externalizing outcomes within a brain-by-development context.

Journal

Published

Authors

Keywords

DOI

Abstract

Puberty depicts a period of profound and multifactorial changes ranging from social to biological factors. While brain development in youths has been studied mostly from an age perspective, recent evidence suggests that pubertal measures may be more sensitive to study adolescent neurodevelopment, however, studies on pubertal timing in relation to brain development are still scarce.

Journal

Published

Authors

Keywords

DOI

Abstract

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.

Journal

Published

Authors

Keywords

DOI

Abstract

Genetic pleiotropy is abundant across spatially distributed brain characteristics derived from one neuroimaging modality (e.g. structural, functional or diffusion magnetic resonance imaging [MRI]). A better understanding of pleiotropy across modalities could inform us on the integration of brain function, micro- and macrostructure. Here we show extensive genetic overlap across neuroimaging modalities at a locus and gene level in the UK Biobank (N = 34,029) and ABCD Study (N = 8607). When jointly analysing phenotypes derived from structural, functional and diffusion MRI in a genome-wide association study (GWAS) with the Multivariate Omnibus Statistical Test (MOSTest), we boost the discovery of loci and genes beyond previously identified effects for each modality individually. Cross-modality genes are involved in fundamental biological processes and predominantly expressed during prenatal brain development. We additionally boost prediction of psychiatric disorders by conditioning independent GWAS on our multimodal multivariate GWAS. These findings shed light on the shared genetic mechanisms underlying variation in brain morphology, functional connectivity, and tissue composition.

Journal

Published

Authors

Keywords

DOI

Abstract

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.

Journal

Published

Authors

Keywords

DOI

Abstract

Parents play a notable role in the development of child psychopathology. In this study we investigate the role of parent psychopathology and behaviors on child brain-symptom networks to understand the role of intergenerational transmission of psychopathology. Few studies have documented the interaction of child psychopathology, parent psychopathology, and child neuroimaging.

Journal

Published

Authors

Keywords

DOI

Abstract

Black youth are disproportionately exposed to school exclusionary discipline. We examined the impact of race on age at the onset of school disciplinary actions and police contact, and the rate of receiving increasingly severe disciplinary actions.

Journal

Published

Authors

Keywords

DOI

Abstract

To investigate child-parent concordance in reporting social victimization experiences and whether parent concordance with child report of victimization was associated with child behavioral symptoms.

Journal

Published

Authors

Keywords

DOI

Abstract

Although posttraumatic stress disorder (PTSD) has been well characterized in adults, its epidemiology in children is unclear. The current study provides the first population-based examination of the prevalence of PTSD, sociodemographic and psychiatric correlates, clinical sequelae, and associations with psychiatric treatment in preadolescents 9-10 years old in the United States. Data from the Adolescent Brain and Cognitive Development (ABCD) Study (release 5.0) was analyzed. Participants (unweighted n = 11,875) were recruited from 21 sites across the United States. Current and lifetime PTSD prevalence were estimated, as was treatment use among children with PTSD. Sociodemographic, psychiatric correlates and sequelae of PTSD were analyzed using logistic regression, as was the association between PTSD and psychiatric treatment. After the application of propensity weights, lifetime prevalence of PTSD was 2.17%. Sexual minority status, being multiracial, having unmarried parents, and family economic insecurity were associated with greater odds of PTSD. Among psychiatric disorders, separation anxiety was most strongly associated with PTSD, although general comorbid psychopathology was associated with greater odds of PTSD. Prior history of PTSD predicted a new onset of other psychiatric disorders after PTSD remission. Nearly one in three children with lifetime PTSD did not receive psychiatric treatment, despite negative long-term outcomes of PTSD and significant psychiatric comorbidity. Even among preadolescents who experience full remission of PTSD, a significant risk for future psychiatric illness remains. Further, the current findings underscore the need for improved efforts to reduce unmet treatment needs among those with PTSD at this age.

Journal

Published

Authors

Keywords

DOI

Abstract

Brain networks are continuously modified throughout development, yet this plasticity can also make functional networks vulnerable to early life stress. Little is currently known about the effect of early life stress on the functional organization of the brain. The current study investigated the association between environmental stressors and network topology using data from the Adolescent Brain Cognitive Development (ABCD®) Study. Hierarchical modeling identified a general factor of environmental stress, representing the common variance across multiple stressors, as well as four subfactors including familial dynamics, interpersonal support, neighborhood SES deprivation, and urbanicity. Functional network topology metrics were obtained using graph theory at rest and during tasks of reward processing, inhibition, and affective working memory. The general factor of environmental stress was associated with less specialization of networks, represented by lower modularity at rest. Local metrics indicated that general environmental stress was also associated with less efficiency in the subcortical-cerebellar and visual networks while showing greater efficiency in the default mode network at rest. Subfactors of environmental stress were associated with differences in specialization and efficiency in select networks. The current study illustrates that a wide range of stressors in a child’s environment are associated with differences in brain network topology.

Journal

Published

Authors

Keywords

DOI

Abstract

Journal

Published

Authors

Keywords

DOI

Abstract

Obsessive-compulsive symptoms (OCS) are relatively common during adolescence although most individuals do not meet diagnostic criteria for obsessive-compulsive disorder (OCD). Nonetheless, OCS during adolescence are associated with comorbid psychopathologies and behavioral problems. Heightened levels of environmental stress and greater functional connectivity between the somatomotor network and putamen have been previously associated with elevated OCS in OCD patients relative to healthy controls. However, the interaction of these factors within the same sample of individuals has been understudied. This study examined somatomotor-putamen resting state connectivity, stress, and their interaction on OCS in adolescents from 9-12 years of age. Participants (n = 6,386) were drawn from the ABCD Study 4.0 release. Multilevel modeling was used to account for nesting in the data and to assess changes in OCS in this age range. Stress moderated the association between somatomotor-putamen connectivity and OCS (β = 0.35, S.E. = 0.13, p = 0.006). Participants who reported more stress than their average and had greater somatomotor-left putamen connectivity reported more OCS, whereas participants who reported less stress than their average and had greater somatomotor-left putamen connectivity reported less OCS. These data suggest that stress differentially affects the direction of association between somatomotor-putamen connectivity and OCS. Individual differences in the experience or perception of stress may contribute to more OCS in adolescents with greater somatomotor-putamen connectivity.

Journal

Published

Authors

Keywords

DOI

Abstract

Mild traumatic brain injury (mTBI) is common in children. Long-term cognitive and behavioral outcomes as well as underlying structural brain alterations following pediatric mTBI have yet to be determined. In addition, the effect of age-at-injury on long-term outcomes is largely unknown.

Journal

Published

Authors

Keywords

DOI

Abstract

Handedness develops early in life, but the structural and functional brain connectivity patterns associated with it remains unknown. Here we investigate associations between handedness and the asymmetry of brain connectivity in 9- to 10-years old children from the Adolescent Brain Cognitive Development (ABCD) study. Compared to right-handers, left-handers had increased global functional connectivity density in the left-hand motor area and decreased it in the right-hand motor area. A connectivity-based index of handedness provided a sharper differentiation between right- and left-handers. The laterality of hand-motor connectivity varied as a function of handedness in unimodal sensorimotor cortices, heteromodal areas, and cerebellum (P < 0.001) and reproduced across all regions of interest in Discovery and Replication subsamples. Here we show a strong association between handedness and the laterality of the functional connectivity patterns in the absence of differences in structural connectivity, brain morphometrics, and cortical myelin between left, right, and mixed handed children.

Journal

Published

Authors

Keywords

DOI

Abstract

Alcohol expectancies predict subsequent alcohol use and related problems among adolescents, although predictors of alcohol expectancies remain unclear. This study examined the longitudinal association between family conflict, a sociocultural factor strongly implicated in adolescent alcohol use, and positive and negative alcohol expectancies of adolescents of diverse racial/ethnic backgrounds.

Journal

Published

Authors

Keywords

DOI

Abstract

Sex differences in psychopathology are well-established, with females demonstrating higher rates of internalizing (INT) psychopathology and males demonstrating higher rates of externalizing (EXT) psychopathology. Using two waves of data from the Adolescent Brain Cognitive Development Study ( = 6,778 at each wave), the current study tested whether the relations between sex and psychopathology might be accounted for by structural brain differences. In general, we found robust, relatively consistent relations between sex and structural morphometry across waves. Relatively few morphometric brain variables were significantly related to INT or EXT across waves, however, with very small effect sizes when present. Next, we tested the extent to which each morphometric brain variable could account for the associations of sex with INT and EXT psychopathology. We found a total of 26 brain regions that accounted for significant portions of the associations between sex and psychopathology across both waves (almost all related to EXT), although the effects present were very small. The current evidence suggests that in children aged 9-12, multiple whole-brain and regional brain variables appear to statistically account for small portions of the sex-psychopathology links, especially for externalizing. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Journal

Published

Authors

Keywords

DOI

Abstract

The study aimed to investigate longitudinal, bidirectional associations between discrimination due to multiple reasons (race/ethnicity, sexual orientation, weight; termed multiple discrimination) and substance use (SU) intention in late childhood. These associations were compared across youth with no, single, and multiple (i.e., intersecting) marginalized identities based on race/ethnicity, sexual orientation, and overweight status.

Journal

Published

Authors

Keywords

DOI

Abstract

A large body of functional MRI research has examined a potential role for subcortico-cortical loops in the pathogenesis of attention deficit hyperactivity disorder (ADHD), but has produced inconsistent findings. The authors performed a mega-analysis of six neuroimaging data sets to examine associations between ADHD diagnosis and traits and subcortico-cortical connectivity.

Journal

Published

Authors

Keywords

DOI

Abstract

Attention and executive function (EF) dysregulation are common in a number of disorders including autism and attention-deficit/hyperactivity disorder (ADHD). Better understanding of the relationship between indirect and direct measures of attention and EF and common neurodevelopmental diagnoses may contribute to more efficient and effective diagnostic assessment in childhood. We obtained cognitive (NIH Toolbox, Little Man Task, Matrix Reasoning Task, and Rey Delayed Recall) and symptom (CBCL, and BPMT) assessment data from the Adolescent Brain and Cognitive Development (ABCD) database for three groups, autistic (N = 110), ADHD (N = 878), and control without autism or ADHD diagnoses (N = 9130) and used ridge regression to determine which attention and EF assessments were most strongly associated with autism or ADHD. More variance was accounted for in the model for the ADHD group (31%) compared to the autism group (2.7%). Finally, we ran odds ratios (using clinical cutoffs where available and 2 standard deviations below the mean when not) for each assessment measure, which generally demonstrated a greater significance within the indirect measures when compared to the direct measures. These results add to the growing literature of symptom variably across diagnostic groups allowing for better understanding of presentations in autism and ADHD and how best to assess diagnosis. It also highlights the increased difficulty in differentiating autism and controls when compared to ADHD and controls and the importance of indirect measures of attention and EF in this differentiation.

Journal

Published

Authors

Keywords

DOI

Abstract

The Sensitivity to Threat and Affiliative Reward (STAR) model proposes low threat sensitivity and low affiliation as risk factors for callous-unemotional (CU) traits. Preliminary evidence for the STAR model comes from work in early childhood. However, studies are needed that explore the STAR dimensions in late childhood and adolescence when severe conduct problems (CP) emerge. Moreover, it is unclear how variability across the full spectrum of threat sensitivity and affiliation gives rise to different forms of psychopathology beyond CU traits.

Journal

Published

Authors

Keywords

DOI

Abstract

Coming from a disadvantaged background can have negative impact on an individual’s educational trajectory. Some people however seem unaffected and cope well with the demands and challenges posed by school education, despite growing up in adverse conditions, a phenomenon termed academic resilience. While it is uncertain which underlying factors make some people more likely to circumvent unfavorable odds than others, both socioeconomic status (SES) and cognitive ability have robustly been linked to school performance. The objective of the present work is to investigate if individual cognitive abilities and SES interact in their effect on grades. For this purpose, we analyzed SES, cognitive, and school performance data from 5001 participants from the Adolescent Brain Cognitive Development (ABCD) Study. Ordinal logistic regression models suggest similar patterns of associations between three SES measures (parental education, income-to-needs ratio, and neighborhood deprivation) and grades at two timepoints, with no evidence for interaction effects between SES and time. Parental education and income-to-needs ratio were associated with grades at both timepoints, irrespective of whether cognitive abilities were modeled or not. Neighborhood deprivation, in contrast, was only a statistically significant predictor of reported grades when cognitive abilities were not factored in. Cognitive abilities interacted with parental education level, meaning that they could be a safeguard against effects of SES on school performance.

Journal

Published

Authors

Keywords

DOI

Abstract

Children who experience persistent psychotic-like experiences (PLEs) are at a higher risk of developing psychotic disorder later in life. The developmental trajectories of PLEs are influenced by various factors. Therefore, it is important to identify early characteristics that can distinguish and predict between different developmental trajectories of PLEs.

Journal

Published

Authors

Keywords

DOI

Abstract

Few studies have considered the neural underpinnings of binge eating disorder (BED) in children despite clinical and subclinical symptom presentation occurring in this age group. Symptom presentation at this age is of clinical relevance, as early onset of binge eating is linked to negative health outcomes. Studies in adults have highlighted dysfunction in the frontostriatal reward system as a potential candidate for binge eating pathophysiology although the exact nature of such dysfunction is currently unclear.

Journal

Published

Authors

Keywords

DOI

Abstract

In children, psychotic-like experiences (PLEs) are related to risk of psychosis, schizophrenia, and other mental disorders. Maladaptive cognitive functioning, influenced by genetic and environmental factors, is hypothesized to mediate the relationship between these factors and childhood PLEs. Using large-scale longitudinal data, we tested the relationships of genetic and environmental factors (such as familial and neighborhood environment) with cognitive intelligence and their relationships with current and future PLEs in children. We leveraged large-scale multimodal data of 6,602 children from the Adolescent Brain and Cognitive Development Study. Linear mixed model and a novel structural equation modeling (SEM) method that allows estimation of both components and factors were used to estimate the joint effects of cognitive phenotypes polygenic scores (PGSs), familial and neighborhood socioeconomic status (SES), and supportive environment on NIH Toolbox cognitive intelligence and PLEs. We adjusted for ethnicity (genetically defined), schizophrenia PGS, and additionally unobserved confounders (using computational confound modeling). Our findings indicate that lower cognitive intelligence and higher PLEs are significantly associated with lower PGSs for cognitive phenotypes, lower familial SES, lower neighborhood SES, and less supportive environments. Specifically, cognitive intelligence mediates the effects of these factors on PLEs, with supportive parenting and positive school environments showing the strongest impact on reducing PLEs. This study underscores the influence of genetic and environmental factors on PLEs through their effects on cognitive intelligence. Our findings have policy implications in that improving school and family environments and promoting local economic development may enhance cognitive and mental health in children.

Journal

Published

Authors

Keywords

DOI

Abstract

Further research is needed to understand factors associated with well-being during the COVID-19 pandemic among adolescents who have experienced adverse childhood experiences (ACEs).

Journal

Published

Authors

Keywords

DOI

Abstract

Prenatal and perinatal complications are established risk factors for psychotic disorder, but far less is known about these measures and psychotic experiences (PEs). We investigated the longitudinal effect of prenatal risk factors (maternal behavior, medication complications) and perinatal risk factors (birth weight, medical complications) on frequency of PEs. We also examined the cumulative risk of prenatal/perinatal risk factors, and differences between transient PE, persistent PE, and controls.

Journal

Published

Authors

Keywords

DOI

Abstract

Nearly 50 years of research has focused on faces as a special visual category, especially during development. Yet it remains unclear how spatial patterns of neural similarity of faces and places relate to how information processing supports subsequent recognition of items from these categories. The current study uses representational similarity analysis and functional imaging data from 9- and 10-year-old youth during an emotional n-back task from the Adolescent Brain and Cognitive Development Study 3.0 data release to relate spatial patterns of neural similarity during working memory to subsequent out-of-scanner performance on a recognition memory task. Specifically, we examine how similarities in representations within face categories (neutral, happy, and fearful faces) and representations between visual categories (faces and places) relate to subsequent recognition memory of these visual categories. Although working memory performance was higher for faces than places, subsequent recognition memory was greater for places than faces. Representational similarity analysis revealed category-specific patterns in face-and place-sensitive brain regions (fusiform gyrus, parahippocampal gyrus) compared with a nonsensitive visual region (pericalcarine cortex). Similarity within face categories and dissimilarity between face and place categories in the parahippocampus was related to better recognition of places from the n-back task. Conversely, in the fusiform, similarity within face categories and their relative dissimilarity from places was associated with better recognition of new faces, but not old faces. These findings highlight how the representational distinctiveness of visual categories influence what information is subsequently prioritized in recognition memory during development.

Journal

Published

Authors

Keywords

DOI

Abstract

The early prediction of adolescent depression recurrence poses a significant challenge in the field. This study aims to investigate and compare the abilities of the general psychopathology factor () and the specific internalizing factor, in predicting depression recurrence over a 2-year course, as well as identifying remitted depressed adolescents from healthy adolescents. Longitudinal changes of these two factors in different trajectory groups were also tracked to examine their sensitivity to sustained remission and relapse.

Journal

Published

Authors

Keywords

DOI

Abstract

Predictive modeling is a central technique in neuroimaging to identify brain-behavior relationships and test their generalizability to unseen data. However, data leakage undermines the validity of predictive models by breaching the separation between training and test data. Leakage is always an incorrect practice but still pervasive in machine learning. Understanding its effects on neuroimaging predictive models can inform how leakage affects existing literature. Here, we investigate the effects of five forms of leakage-involving feature selection, covariate correction, and dependence between subjects-on functional and structural connectome-based machine learning models across four datasets and three phenotypes. Leakage via feature selection and repeated subjects drastically inflates prediction performance, whereas other forms of leakage have minor effects. Furthermore, small datasets exacerbate the effects of leakage. Overall, our results illustrate the variable effects of leakage and underscore the importance of avoiding data leakage to improve the validity and reproducibility of predictive modeling.

Journal

Published

Authors

Keywords

DOI

Abstract

Multivariate machine learning techniques are a promising set of tools for identifying complex brain-behavior associations. However, failure to replicate results from these methods across samples has hampered their clinical relevance. Here we aimed to delineate dimensions of brain functional connectivity that are associated with child psychiatric symptoms in two large and independent cohorts: the Adolescent Brain Cognitive Development (ABCD) Study and the Generation R Study (total n = 6935). Using sparse canonical correlations analysis, we identified two brain-behavior dimensions in ABCD: attention problems and aggression/rule-breaking behaviors. Importantly, out-of-sample generalizability of these dimensions was consistently observed in ABCD, suggesting robust multivariate brain-behavior associations. Despite this, out-of-study generalizability in Generation R was limited. These results highlight that the degrees of generalizability can vary depending on the external validation methods employed as well as the datasets used, emphasizing that biomarkers will remain elusive until models generalize better in true external settings.

Journal

Published

Authors

Keywords

DOI

Abstract

The Adolescent Brain Cognitive Development (ABCD) Study® has collected data from over 10,000 children across 21 sites, providing insights into adolescent brain development. However, site-specific scanner variability has made it challenging to use diffusion MRI (dMRI) data from this study. To address this, a dataset of harmonized and processed ABCD dMRI data (from release 3) has been created, comprising quality-controlled imaging data from 9,345 subjects, focusing exclusively on the baseline session, i.e., the first time point of the study. This resource required substantial computational time (approx. 50,000 CPU hours) for harmonization, whole-brain tractography, and white matter parcellation. The dataset includes harmonized dMRI data, 800 white matter clusters, 73 anatomically labeled white matter tracts in full and low resolution, and 804 different dMRI-derived measures per subject (72.3 TB total size). Accessible via the NIMH Data Archive, it offers a large-scale dMRI dataset for studying structural connectivity in child and adolescent neurodevelopment. Additionally, several post-harmonization experiments were conducted to demonstrate the success of the harmonization process on the ABCD dataset.

Journal

Published

Authors

Keywords

DOI

Abstract

The endocannabinoid system modulates neural activity throughout the lifespan. In adults, neuroimaging studies link a common genetic variant in fatty acid amide hydrolase (FAAH C385A)-an enzyme that regulates endocannabinoid signaling-to reduced risk of anxiety and depression, and altered threat- and reward-related neural activity. However, limited research has investigated these associations during the transition into adolescence, a period of substantial neurodevelopment and increased psychopathology risk.

Journal

Published

Authors

Keywords

DOI

Abstract

Children with ADHD show abnormal brain function and structure. Neuroimaging studies found that stimulant medications may improve brain structural abnormalities in children with ADHD. However, prior studies on this topic were conducted with relatively small sample sizes and wide age ranges and showed inconsistent results. In this cross-sectional study, we employed latent class analysis and linear mixed-effects models to estimate the impact of stimulant medications using demographic, clinical measures, and brain structure in a large and diverse sample of children aged 9-11 from the Adolescent Brain and Cognitive Development Study. We studied 273 children with low ADHD symptoms and received stimulant medication (Stim Low-ADHD), 1002 children with high ADHD symptoms and received no medications (No-Med ADHD), and 5378 typically developing controls (TDC). After controlling for the covariates, compared to Stim Low-ADHD and TDC, No-Med ADHD showed lower cortical thickness in the right insula (INS, d = 0.340, P = 0.003) and subcortical volume in the left nucleus accumbens (NAc, d = 0.371, P = 0.003), indicating that high ADHD symptoms were associated with structural abnormalities in these brain regions. In addition, there was no difference in brain structural measures between Stim Low-ADHD and TDC children, suggesting that the stimulant effects improved both ADHD symptoms and ADHD-associated brain structural abnormalities. These findings together suggested that children with ADHD appear to have structural abnormalities in brain regions associated with saliency and reward processing, and treatment with stimulant medications not only improve the ADHD symptoms but also normalized these brain structural abnormalities.

Journal

Published

Authors

Keywords

DOI

Abstract

Preterm infants with low birthweight are at heightened risk of developmental sequelae, including neurological and cognitive dysfunction that can persist into adolescence or adulthood. In addition, preterm birth and low birthweight can provoke changes in endocrine and metabolic processes that likely impact brain health throughout development. However, few studies have examined associations among birthweight, pubertal endocrine process, long-term neurological and cognitive development.

Journal

Published

Authors

Keywords

DOI

Abstract

Due to limitations of categorical definitions of mental illness, there is a need for quantitative empirical investigations of the dimensional structure of psychopathology. Using exploratory bifactor methods, this study investigated a comprehensive and representative structure of psychopathology in children to better understand how psychotic-like experiences (PLEs), autism spectrum disorder (ASD) symptoms, impulsivity, and sensitivity to reward and punishment, may be integrated into extant general factor models of psychopathology.

Journal

Published

Authors

Keywords

DOI

Abstract

Individual differences in cognitive performance in childhood are a key predictor of significant life outcomes such as educational attainment and mental health. Differences in cognitive ability are governed in part by variations in brain structure. However, studies commonly focus on either grey or white matter metrics in humans, leaving open the key question as to whether grey or white matter microstructure play distinct or complementary roles supporting cognitive performance.To compare the role of grey and white matter in supporting cognitive performance, we used regularized structural equation models to predict cognitive performance with grey and white matter measures. Specifically, we compared how grey matter (volume, cortical thickness and surface area) and white matter measures (volume, fractional anisotropy and mean diffusivity) predicted individual differences in cognitive performance. The models were tested in 11,876 children (ABCD Study, 5680 female; 6196 male) at 10 years old.We found that grey and white matter metrics bring partly non-overlapping information to predict cognitive performance. The models with only grey or white matter explained respectively 15.4% and 12.4% of the variance in cognitive performance, while the combined model explained 19.0%. Zooming in we additionally found that different metrics within grey and white matter had different predictive power, and that the tracts/regions that were most predictive of cognitive performance differed across metric.These results show that studies focusing on a single metric in either grey or white matter to study the link between brain structure and cognitive performance are missing a key part of the equation. This paper enriches the recent debates on the challenges of linking variation in brain structure to phenotypic differences (Marek et al., 2022). We demonstrate that using latent variables (to improve power), structural equation modelling (to allow greater flexibility in linking brain to behaviour), and by simultaneously incorporating multiple measures of grey and white matter in a large sample, we demonstrate relatively strong and robust brain-behaviour associations, which highlight the complementarity of grey and white matter metrics in predicting cognitive performance as well as the importance of incorporating the full complexity of these associations over 1-to-1 linkages. This finding should lead researchers to consider integrating both grey and white matter measures when demonstrating a more comprehensive picture of brain-cognition relationships.

Journal

Published

Authors

Keywords

DOI

Abstract

Over the past 30 years there have been numerous large-scale and longitudinal psychiatric research efforts to improve our understanding and treatment of mental health conditions. However, despite the huge effort by the research community and considerable funding, we still lack a causal understanding of most mental health disorders. Consequently, the majority of psychiatric diagnosis and treatment still operates at the level of symptomatic experience, rather than measuring or addressing root causes. This results in a trial-and-error approach that is a poor fit to underlying causality with poor clinical outcomes. Here we discuss how a research framework that originates from exploration of causal factors, rather than symptom groupings, applied to large scale multi-dimensional data can help address some of the current challenges facing mental health research and, in turn, clinical outcomes. Firstly, we describe some of the challenges and complexities underpinning the search for causal drivers of mental health conditions, focusing on current approaches to the assessment and diagnosis of psychiatric disorders, the many-to-many mappings between symptoms and causes, the search for biomarkers of heterogeneous symptom groups, and the multiple, dynamically interacting variables that influence our psychology. Secondly, we put forward a causal-orientated framework in the context of two large-scale datasets arising from the Adolescent Brain Cognitive Development (ABCD) study, the largest long-term study of brain development and child health in the United States, and the Global Mind Project which is the largest database in the world of mental health profiles along with life context information from 1.4 million people across the globe. Finally, we describe how analytical and machine learning approaches such as clustering and causal inference can be used on datasets such as these to help elucidate a more causal understanding of mental health conditions to enable diagnostic approaches and preventative solutions that tackle mental health challenges at their root cause.

Journal

Published

Authors

Keywords

DOI

Abstract

Public genomic datasets like the 1000 Genomes project (1KGP), Human Genome Diversity Project (HGDP), and the Adolescent Brain Cognitive Development (ABCD) study are valuable public resources that facilitate scientific advancements in biology and enhance the scientific and economic impact of federally funded research projects. Regrettably, these datasets have often been developed and studied in ways that propagate outdated racialized and typological thinking, leading to fallacious reasoning among some readers that social and health disparities among the so-called races are due in part to innate biological differences between them. We highlight how this framing has set the stage for the racist exploitation of these datasets in two ways: First, we discuss the use of public biomedical datasets in studies that claim support for innate genetic differences in intelligence and other social outcomes between the groups identified as races. We further highlight recent instances of this which involve unauthorized access, use, and dissemination of public datasets. Second, we discuss the use of simple figures meant for quick dissemination among lay audiences, of population genetic data to argue for a biological basis for purported human racial groups. We close with recommendations for scientists, to preempt the exploitation and misuse of their data, and for funding agencies, to better enforce violations of data use agreements.

Journal

Published

Authors

Keywords

DOI

Abstract

Early exposure to neighborhood social fragmentation has been shown to be associated with schizophrenia. The impact of social fragmentation and friendships on distressing psychotic-like experiences (PLE) remains unknown. We investigate the relationships between neighborhood social fragmentation, number of friends, and distressing PLE among early adolescents.

Journal

Published

Authors

Keywords

DOI

Abstract

Sleep disturbances are common in adolescence and associated with a host of negative outcomes. Here we assess associations between multifaceted sleep disturbances and a broad set of psychological, cognitive, and demographic variables using a data-driven approach, canonical correlation analysis (CCA).

Journal

Published

Authors

Keywords

DOI

Abstract

Alcohol intent (the susceptibility to initiating alcohol use) and alcohol sips (the initiation of alcohol) in youth are a multifactorial puzzle with many components. This research aims to examine the connection between genetic and environmental factors across sex, race and ethnicity.

Journal

Published

Authors

Keywords

DOI

Abstract

Screen time has been reported to be associated with binge-eating disorder (BED) among adolescents in the US; however, potential mediators remain unclear. This study aimed to evaluate depression symptoms as a mediator of the prospective association between screen time and BED.

Journal

Published

Authors

Keywords

DOI

Abstract

The complexity of brain signals may hold clues to understand brain-based disorders. Sample entropy, an index that captures the predictability of a signal, is a promising tool to measure signal complexity. However, measurement of sample entropy from fMRI signals has its challenges, and numerous questions regarding preprocessing and parameter selection require research to advance the potential impact of this method. For one example, entropy may be highly sensitive to the effects of motion, yet standard approaches to addressing motion (e.g., scrubbing) may be unsuitable for entropy measurement. For another, the parameters used to calculate entropy need to be defined by the properties of data being analyzed, an issue that has frequently been ignored in fMRI research. The current work sought to rigorously address these issues and to create methods that could be used to advance this field.

Journal

Published

Authors

Keywords

DOI

Abstract

This study aimed to characterize the role of sex and pubertal markers in reward motivation behavior and neural processing in early adolescence. We used baseline and two-year follow-up data from the Adolescent Brain and Cognitive Development study (15844 observations; 52% from boys; age 9-13). Pubertal development was measured with parent-reported Pubertal Development Scale, and DHEA, testosterone, and estradiol levels. Reward motivation behavior and neural processing at anticipation and feedback stages were assessed with the Monetary Incentive Delay task. Boys had higher reward motivation than girls, demonstrating greater accuracy difference between reward and neutral trials and higher task earnings. Girls had lower neural activation during reward feedback than boys in the nucleus accumbens, caudate, rostral anterior cingulate, medial orbitofrontal cortex, superior frontal gyrus and posterior cingulate. Pubertal stage and testosterone levels were positively associated with reward motivation behavior, although these associations changed when controlling for age. There were no significant associations between pubertal development and neural activation during reward anticipation and feedback. Sex differences in reward-related processing exist in early adolescence, signaling the need to understand their impact on typical and atypical functioning as it unfolds into adulthood.

Journal

Published

Authors

Keywords

DOI

Abstract

Identifying neuroimaging risk markers for depression has been an elusive goal in psychopathology research. Despite this, smaller hippocampal volume has emerged as a potential risk marker for depression, with recent research suggesting this association is moderated by family income. The current pre-registered study aimed to replicate and extend these findings by examining the moderating role of family income and three dimensions of environmental experience on the link between hippocampus volume and later depression. Data were drawn from the Adolescent Brain Cognitive Development (ABCD) study and were comprised of 6693 youth aged 9-10 years at baseline. Results indicated that psychosocial threat moderated the association between right hippocampus volume and depression symptoms two years later, such that a negative association was evident in low-threat environments (std. beta=0.15, 95% CI [0.05, 0.24]). This interaction remained significant when baseline depression symptoms were included as a covariate, though only in youth endorsing 1 or more depression symptoms at baseline (β = 0.13, 95% CI = [0.03, 0.22]). These results suggest that hippocampus volume may not be a consistent correlate of depression symptoms in high risk environments and emphasize the importance of including measures of environmental heterogeneity when seeking risk markers for depression.

Journal

Published

Authors

Keywords

DOI

Abstract

Attention deficit hyperactivity disorder (ADHD) has been characterized by impairments among distributed functional brain networks, e.g., the frontoparietal network (FPN), default mode network (DMN), reward and motivation-related circuits (RMN), and salience network (SAL). In the current study, we evaluated the complexity and functional connectivity (FC) of resting state fMRI (rsfMRI) in pre-adolescents with the behavioral symptoms of ADHD, for pathology-relevant networks. We leveraged data from the Adolescent Brain and Cognitive Development (ABCD) Study. The final study sample included 63 children demonstrating the behavioral features of ADHD and 92 healthy control children matched on age, sex, and pubertal development status. For selected regions in the relevant networks, ANCOVA compared multiscale entropy (MSE) and FC between the groups. Finally, differences in the association between MSE and FC were evaluated. We found significantly reduced MSE along with increased FC within the FPN of pre-adolescents demonstrating the behavior symptoms of ADHD compared to matched healthy controls. Significant partial correlations between MSE and FC emerged in the FPN and RMN in the healthy controls however the association was absent in the participants demonstrating the behavior symptoms of ADHD. The current findings of complexity and FC in ADHD pathology support hypotheses of altered function of inhibitory control networks in ADHD.

Journal

Published

Authors

Keywords

DOI

Abstract

Stimulant medication is the primary pharmacological treatment for attention dysregulation and is commonly prescribed for children with Attention-Deficit/Hyperactivity Disorder (ADHD) and Autism. Neuroimaging studies of these groups commonly use a 24-48-hour washout period to mediate the effects of stimulant medication on functional connectivity (FC) metrics. However, the impact of washout on functional connectivity has received limited study.

Journal

Published

Authors

Keywords

DOI

Abstract

Social media can influence alcohol initiation behaviors such as sipping, which can lead to future adverse alcohol-related outcomes. Few studies have examined the role of problematic social media use, characterized by addiction, mood modification, tolerance, withdrawal, conflict, and relapse, especially in early adolescence.

Journal

Published

Authors

Keywords

DOI

Abstract

Behavioral features of binge eating disorder (BED) suggest abnormalities in reward and inhibitory control. Studies of adult populations suggest functional abnormalities in reward and inhibitory control networks. Despite behavioral markers often developing in children, the neurobiology of pediatric BED remains unstudied.

Journal

Published

Authors

Keywords

DOI

Abstract

Prior research suggests that the organization of the language network in the brain is left-dominant and becomes more lateralized with age and increasing language skill. The age at which specific components of the language network become adult-like varies depending on the abilities they subserve. So far, a large, developmental study has not included a language task paradigm, so we introduce a method to study resting-state laterality in the Adolescent Brain Cognitive Development (ABCD) study. Our approach mixes source timeseries between left and right homotopes of the (1) inferior frontal and (2) middle temporal gyri and (3) a region we term “Wernicke’s area” near the supramarginal gyrus. Our large subset sample size of ABCD (n = 6153) allows improved reliability and validity compared to previous, smaller studies of brain-behavior associations. We show that behavioral metrics from the NIH Youth Toolbox and other resources are differentially related to tasks with a larger linguistic component over ones with less (e.g., executive function-dominant tasks). These baseline characteristics of hemispheric specialization in youth are critical for future work determining the correspondence of lateralization with language onset in earlier stages of development.

Journal

Published

Authors

Keywords

DOI