Research Publications

Abstract

Physical Activity (PA) is important for mental, physical, and brain health. Adolescence is marked by increased engagement in risky substance use (SU) behaviors, which can negatively affect brain development. This study aims to determine if PA influences SU experimentation and initiation among adolescents. We predicted higher levels of PA would be associated with less SU, with a larger effect in more vigorous compared to light PA. A sample of 2541 participants from the Adolescent Brain Cognitive Development (ABCD) Study provided three weeks of Fitbit-measured PA data at the 2-year follow-up, and SU outcomes at the 3- and 4-year follow-up. SU outcomes of experimentation (i.e., sip/puff/try of alcohol, nicotine, or cannabis) and initiation (i.e., full drink of alcohol, more than a puff/try of nicotine or cannabis, or anything else) were examined dichotomously (i.e., yes/no). Logistic regression analyses were conducted, controlling for demographics, externalizing, and depressive symptoms endorsed on Child Behavior Checklist (CBCL). Total PA was associated with 24 % decreased odds in SU initiation (OR 0.82, 95 % CI 0.69-0.99,  < .05). After examining PA intensities more closely, light PA predicted 26 % decreased odds of SU initiation (OR 0.73, 95 % CI 0.61-0.88, p = .001). No significant associations emerged between PA and experimentation, or moderate and vigorous PA and initiation. More engagement in total and light PA reduced the odds of SU initiation, suggesting that low-intensity activity, not moderate or vigorous PA, may provide protection against adolescent SU. Future research should examine underlying mechanisms and contextual factors that account for these results.

Journal

Published

Authors

Keywords

DOI

Abstract

Extensive neuroimaging research in temporal lobe epilepsy with hippocampal sclerosis (TLE-HS) has identified brain atrophy as a disease phenotype. While it is also related to a complex genetic architecture, the transition from genetic risk factors to brain vulnerabilities remains unclear. Using a population-based approach, we examined the associations between epilepsy-related polygenic risk for HS (PRS-HS) and brain structure in healthy developing children, assessed their relation to brain network architecture, and evaluated its correspondence with case-control findings in TLE-HS diagnosed patients relative to healthy individuals We used genome-wide genotyping and structural T1-weighted magnetic resonance imaging (MRI) of 3,826 neurotypical children from the Adolescent Brain Cognitive Development (ABCD) study. Surface-based linear models related PRS-HS to cortical thickness measures, and subsequently contextualized findings with structural and functional network architecture based on epicentre mapping approaches. Imaging-genetic associations were then correlated to atrophy and disease epicentres in 785 patients with TLE-HS relative to 1,512 healthy controls aggregated across multiple sites. Higher PRS-HS was associated with decreases in cortical thickness across temporo-parietal as well as fronto-central regions of neurotypical children. These imaging-genetic effects were anchored to the connectivity profiles of distinct functional and structural epicentres. Compared with disease-related alterations from a separate epilepsy cohort, regional and network correlates of PRS-HS strongly mirrored cortical atrophy and disease epicentres observed in patients with TLE-HS, and highly replicable across different studies. Findings were consistent when using statistical models controlling for spatial autocorrelations and robust to variations in analytic methods. Capitalizing on recent imaging-genetic initiatives, our study provides novel insights into the genetic underpinnings of structural alterations in TLE-HS, revealing common morphological and network pathways between genetic vulnerability and disease mechanisms. These signatures offer a foundation for early risk stratification and personalized interventions targeting genetic profiles in epilepsy.

Journal

Published

Authors

Keywords

DOI

Abstract

The global prevalence of cannabis use during pregnancy is increasing, driven by perceived therapeutic benefits and greater societal acceptance. Concurrently, the psychoactive potency of cannabis products has risen significantly, due to increase in concentrations of Tetrahydrocannabinol (THC) from 5% to 30%. THC crosses the placenta, disrupts the endocannabinoid system critical for neurodevelopment, and accumulates in fetal tissues. THC is transferred into breast milk, with breastfed infants receiving ~2.5% of the maternal dose, raising concerns regarding neurodevelopmental consequences. An increasing number of studies and metanalysis have demonstrated association of prenatal cannabis exposure with low birth weight, preterm birth, neonatal intensive care unit admission, and reduced Apgar scores. Longitudinal studies show brain alterations in offspring, affecting memory, attention, and executive function. The inability to conduct randomized controlled trials due to ethical constraints necessitates reliance on observational studies, underscoring the need for rigorous longitudinal research to delineate causality.

Journal

Published

Authors

Keywords

DOI

Abstract

As an increasing realization, many behavioral relationships are interwoven with inherent variations in human populations. Presently, there is no clarity in the biomedical community on which sources of population variation are most dominant. The recent advent of population-scale cohorts like the Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study®) are now offering unprecedented depth and width of phenotype profiling that potentially explains interfamily differences. Here, we leveraged a deep learning framework (conditional variational autoencoder) on the totality of the ABCD Study® phenome (8,902 candidate phenotypes in 11,875 participants) to identify and characterize major sources of population stratification. 80% of the top 5 sources of explanatory stratifications were driven by distinct combinations of 202 available socioeconomic status (SES) measures; each in conjunction with a unique set of non-overlapping social and environmental factors. Several sources of variation across this cohort flagged geographies marked by material poverty interlocked with mental health and behavioral correlates. Deprivation emerged in another top stratification in relation to urbanicity and its ties to immigrant and racial and ethnic minoritized groups. Conversely, two other major sources of population variation were both driven by indicators of privilege: one highlighted measures of access to educational opportunity and income tied to healthy home environments and good behavior, the other profiled individuals of European ancestry leading advantaged lifestyles in desirable neighborhoods in terms of location and air quality. Overall, the disclosed social stratifications underscore the importance of treating SES as a multidimensional construct and recognizing its ties into social determinants of health.

Journal

Published

Authors

Keywords

DOI

Abstract

Functional connectivity is frequently used to assess dynamic brain functioning and predict individual differences in behavioral outcomes, such as psychopathology. Inferences from functional connectivity analyses typically rely on group-averaged model statistics. However, heterogeneity between individuals may lead to group-level models that poorly reflect each individual. Poor individual-level precision may limit the ability to make individual-level predictions, which is necessary for key goals such as clinical translation. This registered report examined between-person heterogeneity in resting-state functional connectivity strength patterns by assessing similarity between group- and individual-level connectivity models in the Adolescent Brain Cognitive Development study. Using intraclass correlation coefficients, we found that a group-averaged region-of-interest-based connectivity model was a poor reflection of every individual. In contrast, a group-averaged model of between- and within-network connectivity was a good representation of most individuals. We then examined how individual-level distinctness from the group moderated predictive performance of several clinical and neurocognitive scales. Hypotheses that group-to-individual dissimilarity would worsen behavioral prediction were not supported with primary clinical outcomes. The little psychopathology reported in this sample was a notable limitation. In contrast, lower similarity to the group worsened prediction of performance on the pattern comparison test, providing minor support for hypotheses. Overall, results suggest that region-of-interest-based functional connectivity networks are highly heterogeneous and group-based models are inappropriate for individual-level inferences, but that network-based connectivity is largely similar across individuals. Additionally, we provide minor evidence of the impacts of heterogeneity on prediction that future studies should build on.

Journal

Published

Authors

Keywords

DOI

Abstract

Pain in youth is a growing public health concern. While research suggests pervasive differences in brain morphology with pain in adulthood, this relationship is less studied in adolescence. To address this gap, the present study explored pain-related associations with gray matter volume across 82 brain regions in a community sample of 7712 youth (mean age = 11.96) by comparing structural brain measures between those with (n = 2668; 34.6%) and without (n = 5044; 65.4%) past-month pain and examining associations with a continuous latent pain factor composed of average pain ratings, worst pain ratings, and pain limitations. Results showed no significant morphological differences between groups with and without past-month pain. Among participants reporting pain, average pain limitations were generally low, despite varied pain intensity, duration, and number of pain locations. Within this group, higher latent pain scores were associated with lower gray matter volume in six cortical regions (bilateral precentral, right postcentral, right inferior parietal, left supramarginal and left lateral occipital gyri; all p < 0.05). However, in secondary analyses adjusting for total intracranial volume (ICV), only the result in the right inferior parietal gyrus remained significant, suggesting this region may represent a more robust and regionally specific correlate of pain, independent of global brain effects. Together, these findings suggest that heightened pain experiences are related to lower gray matter volume in predominantly sensorimotor and parietal regions. Future work exploring the temporal dynamics of these morphological differences is needed to clarify their clinical implications. PERSPECTIVE: This article describes an association between lower gray matter volume in primarily sensorimotor and parietal areas and higher pain scores among youth reporting past-month pain (n = 2668) in a nonclinical community sample (n = 7712). The findings contribute to the understanding of neurobiological correlates of adolescent pain and pain-related neurodevelopmental patterns.

Journal

Published

Authors

Keywords

DOI

Abstract

Psychotic-like experiences (PLEs) may arise from genetic and environmental risk leading to worsening cognitive and morphometry metrics over time, which in turn lead to worsening PLEs. Analyses used three waves of unique longitudinal Adolescent Brain Cognitive Development Study data (ages 9-13) to test whether changes in cognition and global morphometry metrics attenuate associations between genetic and environmental risk with persistent distressing PLEs. Multigroup univariate latent growth models examined three waves of cognitive metrics and global morphometry separately for three PLE groups: persistent distressing PLEs (n=356), transient distressing PLEs (n=408), and low-level PLEs (n=7901). Persistent distressing PLEs showed greater decreases (i.e., more negative slopes) of cognition and morphometry metrics over time compared to those in low-level PLE groups. Analyses also provided novel evidence for extant theories that worsening cognition and global morphometry metrics may partially account for associations between environmental risk with persistent distressing PLEs.

Journal

Published

Authors

Keywords

DOI

Abstract

Journal

Published

Authors

Keywords

DOI

Abstract

Journal

Published

Authors

Keywords

DOI

Abstract

Humans and nonhuman primate studies suggest that timing and tempo of cortical development varies neuroanatomically along a sensorimotor-to-association (S-A) axis. Prior human studies have reported a principal S-A axis across various modalities but largely rely on cross-sectional samples with wide age-ranges. Here, we investigate developmental changes and individual variability in cortical organization along the S-A axis between the ages of 9-13 years using a large, longitudinal sample (N = 2487-3747, 46-50% female) from the Adolescent Brain Cognitive Development Study (ABCD Study®). This work assesses multiple aspects of neurodevelopment indexed by changes in cortical thickness, cortical microarchitecture, and resting-state low-frequency oscillations. First, we evaluated S-A organization in age-related changes and then, computed individual-level S-A alignment in brain changes and assessing differences therein due to age, sex, and puberty. Varying degrees of linear and quadratic age-related brain changes were identified along the S-A axis. Yet, these patterns of cortical development were overshadowed by considerable individual variability in S-A alignment. Even within individuals, there was little correspondence between S-A patterning across the different aspects of neurodevelopment investigated (i.e., cortical morphology, microarchitecture, function). Some of the individual variation in developmental patterning of cortical morphology and microarchitecture was explained by age, sex, and pubertal development. Altogether, this work contextualizes prior findings that regional age differences do progress along an S-A axis at a group level, while highlighting broad variation in developmental change between individuals and between aspects of cortical development, in part due to sex and puberty. Understanding normative patterns of adolescent brain change, and individual variability therein, is crucial for disentangling healthy and abnormal development. We used longitudinal human neuroimaging data to study several aspects of neurodevelopment during early adolescence and assessed their organization along a sensorimotor-to-association (S-A) axis across the cerebral cortex. Age differences in brain changes were linear and curvilinear along this S-A axis. However, individual-level sensorimotor-association alignment varied considerably, driven in part by differences in sex and pubertal development.

Journal

Published

Authors

Keywords

DOI

Abstract

Journal

Published

Authors

Keywords

DOI

Abstract

Journal

Published

Authors

Keywords

DOI

Abstract

Machine learning (ML) has significantly transformed biomedical research, leading to a growing interest in model development to advance classification accuracy in various clinical applications. However, this progress raises essential questions regarding how to rigorously compare the accuracy of different ML models. In this study, we highlight the practical challenges in quantifying the statistical significance of accuracy differences between two neuroimaging-based classification models when cross-validation (CV) is performed. Specifically, we propose an unbiased framework to assess the impact of CV setups (e.g., the number of folds) on the statistical significance. We apply this framework to three publicly available neuroimaging datasets to re-emphasize known flaws in current computation of p-values for comparing model accuracies. We further demonstrate that the likelihood of detecting significant differences among models varies substantially with the intrinsic properties of the data, testing procedures, and CV configurations of choice. Given that many of the above factors do not typically fall into the evaluation criteria of ML-based biomedical studies, we argue that such variability can potentially lead to p-hacking and inconsistent conclusions on model improvement. The obtained results from this study underscore that more rigorous practices in model comparison are urgently needed in order to mitigate the reproducibility crisis in biomedical ML research.

Journal

Published

Authors

Keywords

DOI

Abstract

Non-suicidal self-injury (NSSI) is common in adolescence and is strongly associated with depressive disorders (DDs), necessitating targeted screening and interventions for NSSI among depressed adolescents. This study aimed to build longitudinal predictive models to identify psychosocial factors distinguishing depressed adolescents who begin engaging in NSSI from those who do not and to compare these predictors with those in youth without DDs.

Journal

Published

Authors

Keywords

DOI

Abstract

To investigate the neurodevelopmental associations of moderate to late preterm (MLP) birth during late childhood.

Journal

Published

Authors

Keywords

DOI

Abstract

Journal

Published

Authors

Keywords

DOI

Abstract

Impulsivity, often operationalized as delay discounting (DD) and as impulsive personality traits via the UPPS-P scales, is a key transdiagnostic construct across psychiatric disorders. Recent genome-wide association studies (GWAS) have studied the genetic basis of impulsivity in adults, but it remains unclear how similar the genetic architecture of DD is in children. The present study conducted GWAS of DD and impulsivity traits in 5548 children (ages 9-10 years old) of genetically inferred European ancestry from the Adolescent Brain Cognitive Development (ABCD) Study. Heritability estimates for DD (h = 0.20, S.E. = 0.10) and UPPS-P subscales (h = 0.08-0.11 S.E. = 0.05) were comparable to adult estimates. Genetic correlations between adult and child impulsivity were modest (r = 0.28-0.46), with positive urgency showing the strongest correlation (r = 0.83). While no genome-wide significant associations were identified, the top associated variants were mapped to genes previously linked to smoking initiation (rs3820908; p = 6.5 × 10) and UPPS-P Lack of Premeditation (rs17292179; p = 4.2 × 10). Polygenic score (PGS) associations were used to compare the genetic signals in children with those reported in adults. Adult PGSs for DD and positive and negative urgency indicators explained small but significant variance in the respective child impulsivity phenotypes (0.36%-0.44%, p < 7.5 × 10). Additionally, UPPS-P indices were broadly associated with PGSs derived from adult externalizing (0.42%-1.02%) and ADHD (0.23%-0.79%). This first GWAS of impulsivity in children offers a developmentally informed comparison of genetic influences, revealing both similarities and differences by developmental stage.

Journal

Published

Authors

Keywords

DOI

Abstract

Many communities in the United States are delaying school start times to improve youth sleep. Racial disparities exist in sleep. The extent to which school start times are associated with racial disparities in sleep is unclear, especially in early adolescent populations that are not the focus of research on school start times. This study examined the associations between school start times and actigraphy-assessed sleep, including duration, onset, and offset times among a national sample of racially diverse early adolescents.

Journal

Published

Authors

Keywords

DOI

Abstract

Journal

Published

Authors

Keywords

DOI

Abstract

The present study examined the longitudinal, bidirectional associations between early adolescents’ electronic media use and family conflict across 3 years using data from the ABCD study (T1; = 11,787). Findings indicated that more overall electronic media use was related to later increases in family conflict, whereas the reverse association was not supported. Further analyses examined associations by unique types of electronic media. Social electronic media use at T1 in girls was related to less family conflict at T2, yet more family conflict at later timepoints. These findings suggest that more overall electronic media use promotes later conflict throughout early adolescence and that girls’ use of social types of media may be especially disruptive in families as they progress through early adolescence. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Journal

Published

Authors

Keywords

DOI

Abstract

Persistent and/or distressing psychotic-like experiences (PLEs) during adolescence are associated with poorer subsequent psychiatric outcomes. Modifiable lifestyle factors (such as sleep quality or regular exercise) may improve mental health outcomes; however, it is unknown how lifestyle factors are linked to trajectories of PLEs.

Journal

Published

Authors

Keywords

DOI

Abstract

Adolescence is a pivotal stage for brain development and a critical window for the emergence and transition of self-injury thoughts and behaviours (SITBs). However, the genetic and neurobiological mechanisms underlying SITBs transition during this developmental period are poorly understood.

Journal

Published

Authors

Keywords

DOI

Abstract

Although moderate-to-vigorous physical activity (MVPA) is a widely used construct in physical activity (PA) research, the lack of standardized assessment methods- particularly with the growing use of consumer-grade wearable activity trackers- poses challenges for comparability. Consumer-grade devices tend to rely on heart rate (HR)-based estimation methods to classify PA intensity, which contrasts with traditional research-grade accelerometers that use count- or raw-acceleration metrics. Comparability issues are particularly salient across individuals with varying weight status. In this commentary, we discuss systematic discrepancies between HR-based (relative intensity) and acceleration-based (absolute intensity) classifications of MVPA among individuals with differing weight statuses. Using Fitbit data from the Adolescent Brain Cognitive Development Study, we illustrate how HR-based PA intensity classification may indicate higher MVPA in youth with greater adiposity despite lower step counts and light PA levels. We highlight implications for research design, public health surveillance, messaging, policy, and interventions. We also call for greater transparency, standardized methodologies, and integrative measurement approaches to ensure more accurate assessment of PA behavior.

Journal

Published

Authors

Keywords

DOI

Abstract

The long-term impact of prenatal substance exposure (PSE) on obesity remains inconclusive. Few studies have explored the trajectories of Tri-Ponderal Mass Index (TMI), despite its greater accuracy and reliability in assessing adolescent adiposity. The aim of this study was to examine adiposity trajectories assessed by TMI from pre- to early adolescence and the influence of PSE on these patterns.

Journal

Published

Authors

Keywords

DOI

Abstract

Substance use has been associated with differences in adult brain morphology; however, it is unclear whether these differences precede or are a result of substance use substance use. We investigated the impact of polygenic risk scores (PRSs) for cannabis use disorder (CUD) and general substance use and substance use disorder liability (SU/SUD) on brain morphology in drug-naïve adolescents. Baseline data were used from 1874 European-descent participants (ages 9-11) comprising 222, 328 and 387 pairs of MZ twins, DZ twins, and Non-Twin Siblings, respectively, in the Adolescent Brain Cognitive Development Study. We fitted multivariate twin models to estimate the putative effects of CUD, SU/SUD, and brain region-specific PRSs. These models assessed their influence on six subcortical and two cortical phenotypes. PRS for CUD and SU/SUD were created based on GWAS conducted by Johnson et al. (Lancet Psychiatry 7:1032, 2020) and Hatoum et al. (Nat Ment Health 1:210-223, 2023), respectively. When decomposing variance in each brain region of interest (ROI), we used the corresponding ROI-specific PRS. Brain morphometry in drug-naive subjects was unrelated to CUD PRS. The variance explained in each ROI by its corresponding PRS ranged from 0.8 to 4.4%. The SU/SUD PRS showed marginally significant effects (0.2-0.4%) on cortical surface area and nucleus accumbens volume, but overall effect sizes were small. This study failed to reject the null hypothesis of no association between genetic risk for substance use and brain morphometry among baseline drug-naive adolescents. Genetic risk for CUD was not associated with brain morphometry among drug-naive adolescents, but a weak association with general addiction and substance use risk (SU/SUD) particularly in nucleus accumbens volume and total cortical surface area, was observed.

Journal

Published

Authors

Keywords

DOI

Abstract

The neighborhood context is increasingly recognized as a significant determinant of health. Advances in geospatial analysis and neuroimaging have facilitated an emerging field of research investigating how neighborhood conditions influence brain development. We conducted a systematic review, identifying 37 studies that examined associations between neighborhood conditions and brain structure in children and adolescents. We highlight key findings and research gaps across multiple domains of neighborhood conditions – socioeconomic status, demographic composition, social environment, built environment, physical environment, and health resources. Our review suggests that adverse neighborhood socioeconomic conditions are linked to structural brain differences, including reduced brain volume and white matter, and smaller surface areas. Additionally, observed race-related disparities in brain structures may be partially explained by residence in low-resourced neighborhoods, underscoring the role of structural inequities in shaping neurodevelopment. The majority of studies relied on the Adolescent Brain Cognitive Development Study dataset, limiting the generalizability of findings. Critically, neighborhood conditions beyond socioeconomic status remain understudied, offering opportunities for future research to examine how positive conditions (e.g., social cohesion, greenspace, health resources) may foster neurodevelopment. This review emphasizes the urgent need for policies to reduce structural inequities while leveraging protective neighborhood conditions to promote equity and youth neurodevelopment.

Journal

Published

Authors

Keywords

DOI

Abstract

Journal

Published

Authors

Keywords

DOI

Abstract

The human cortex exhibits remarkable morphometric similarity between regions; however, the form and extent of lifespan network remodeling remain unknown. Here, we show the spatiotemporal maturation of morphometric brain networks, using multimodal neuroimaging data from 33,937 healthy participants aged 0-80 years. Global architecture matures from birth to early adulthood through enhanced modularity and small worldness. Early development features cytoarchitecturally distinct remodeling: sensory cortices exhibit increased morphometric differentiation, paralimbic cortices show increased morphometric similarity, and association cortices retain stable hub roles. Morphology-function coupling peaks in early adolescence and then decreases, supporting protracted functional maturation. These growth patterns of morphometric networks are correlated with gene expression related to synaptic signaling, neurodevelopment, and metabolism. Normative models based on morphometric networks identify person-specific, connectivity-phenotypic deviations in 1,202 patients with brain disorders. These data provide a blueprint for elucidating the principle of cortical network reconfiguration and a benchmark for quantifying interindividual network variations.

Journal

Published

Authors

Keywords

DOI

Abstract

Childhood behavioral problems are associated with significant long-term consequences, yet the underlying cognitive mechanisms remain poorly understood. In this study, we employed computational modeling alongside traditional reaction time (RT) measures to investigate cognitive control during a flanker task. We evaluated the predictive utility of these methods in explaining variance across eight transdiagnostic symptom domains in late childhood (mean age = 10.0 years; n = 10,343) from the Adolescent Brain Cognitive Development study. We compared simultaneous regression models across congruent and incongruent conditions using an RT-only model and a drift-diffusion model (DDM) that incorporated boundary separation, bias, drift rate, and non-decision time parameters. Results from the RT-only models indicated that slower reaction times across both task conditions were associated with higher scores on most symptom subscales, suggesting more behavioral problems. For both task conditions, DDM regressions accounted for more total variance across symptom domains compared to RT models. Additionally, DDM regressions demonstrated that impoverished evidence accumulation emerged as a shared feature of both internalizing and externalizing behaviors, while reductions in non-decision time, indicative of increased impulsiveness, were unique to rule-breaking and aggressive behaviors. These findings suggest that different aspects of cognitive control are associated with specific behavioral problems in children, rather than just overall response speed. Present results provide new insights into cognitive control dynamics and suggest that targeting ineffective cognitive control could be crucial for the prevention and intervention of childhood psychopathology.

Journal

Published

Authors

Keywords

DOI

Abstract

The purpose of this study was to: 1) examine the co-occurrence of household and community adverse childhood experiences (ACEs) among preadolescent youth using latent class analysis (LCA), and 2) examine the association of ACE latent clusters to clinical-range scores on the Child Behavior Checklist (CBCL). Data came from the baseline and year 1 survey of the Adolescent Brain Cognitive Development (ABCD) Study with 10,915 youth recruited from school-based catchment areas in the United States. We used LCA to examine 6 types of household adversity and 7 types of community adversity, including 4 types of discrimination. We identified 5 latent classes of household/community ACEs. The class with high levels of household and community ACEs together was most strongly associated with clinical-range CBCL scores in adjusted models. Assessing adversity comprehensively may improve identification of youth with elevated risk for behavioral symptoms, who are greatest in need of intervention.

Journal

Published

Authors

Keywords

DOI

Abstract

Early life stress (ELS) is associated with an increased risk of substance use in adolescence. The interaction of puberty with neurodevelopment during adolescence increases the sensitivity of the brain to both sex and stress hormones. This sensitivity may result in sex-specific pathways from ELS to adolescent alcohol use initiation. The current study examines the effect of ELS on alcohol initiation by age 13 via pubertal mediators, separated by sex and adjusted for the independent effects of age.

Journal

Published

Authors

Keywords

DOI

Abstract

Our genetic makeup, together with environmental and social influences, shape our brain’s development. Yet, the imaging-genetics field has struggled to integrate all these modalities to investigate the interplay between genetic blueprint, brain architecture, environment, human health and daily living skills. Here we interrogate the Adolescent Brain Cognitive Development (ABCD) cohort to outline the effects of rare high-effect genetic variants on brain architecture and their corresponding implications on cognitive, behavioural, psychosocial and socioeconomic traits. We design a holistic pattern-learning framework that quantitatively dissects the impacts of copy number variations (CNVs) on brain structure and 938 behavioural variables spanning 20 categories in 7,338 adolescents. Our results reveal associations between genetic alterations, higher-order brain networks and specific parameters of the family wellbeing, including increased parental and child stress, anxiety and depression, or neighbourhood dynamics such as decreased safety. We thus find effects extending beyond the impairment of cognitive ability or language capacity which have been previously reported. Our investigation spotlights the interplay between genetic variation and subjective life quality in adolescents and their families.

Journal

Published

Authors

Keywords

DOI

Abstract

Fluid and crystallized intelligence are acknowledged as distinct facets of cognitive ability during brain development, but the specific neural substrates and molecular mechanisms underlying them remain unclear. This study used a sample comprising 7471 young adolescents (mean age 9.87 ± 0.62 years) from the ABCD cohort to elucidate the differential neural correlates of fluid and crystallized intelligence. Our findings indicated that micro-level brain MRI phenotypes such as water diffusivity were closely associated with fluid intelligence, whereas macro-level brain MRI phenotypes such as gray matter cortical thickness were indicative of crystallized intelligence. We further investigated the molecular mechanisms underlying fluid and crystallized intelligence by correlating the characteristic MRI markers with spatial transcriptome profiles and PET imaging. Results showed that fluid intelligence had significant associations with serotonin and glutamate system, while crystallized intelligence was related to serotonin, dopamine and acetylcholine system. Furthermore, we examined the impacts of lifestyle factors on these two forms of intelligence and how the molecular pathways mediated these impacts. Our investigation suggested that physical activities, screen use and sleep duration influenced fluid intelligence mainly through mGlu5 receptors and crystallized intelligence through 5HT1a and D2 receptors. In conclusion, these findings illustrated a distinct neural basis between fluid and crystallized intelligence from the perspectives of neuroimaging, neurotransmitters, and lifestyles in young adolescents.

Journal

Published

Authors

Keywords

DOI

Abstract

Maternal tobacco use during pregnancy (MTDP) remains a global and domestic public health issue. This study seeks to investigate the long-term impact of MTDP on brain morphology during late childhood and early adolescence using the Adolescent Brain Cognitive Development (ABCD) dataset. Children aged 9-10 were enrolled using the ABCD school selection probability sample method for national representation. Participants and their parents or guardians underwent interviews and surveys, and children underwent Magnetic Resonance Imaging (MRI) at baseline and 2-year follow-up. Morphometric brain measures of cortical thickness and sulcal depth across 34 regions of interest on T1-weighted MRI images were analyzed. Of 11,448 at baseline, 1,607 children fell into the MTDP group. Intracranial volume (p<0.001), total cortical surface area, and volume (p<0.0001) were significantly lower among MTDP children (vs. control) at both waves 1 and 2. A sustained difference was found in mean cortical thickness at the parahippocampal gyrus as well as sulcal depth at the isthmus cingulate, parahippocampal, lateral occipital, and lingual gyri. Several regions of interest demonstrated differences in the cortical thickness and sulcal depth at single time points. An association between MTDP and long-term outcomes of regional morphometric differences in cortical thickness and sulcal depth on MRI was found at both baseline among 9-10 years old and at 2-year follow-ups. Taken together with NIH cognitive testing from the same population comparison, the results suggest longstanding cognitive deficits corresponding to specific brain regions.

Journal

Published

Authors

Keywords

DOI

Abstract

A pervasive dilemma in brain-wide association studies (BWAS) is whether to prioritize functional magnetic resonance imaging (fMRI) scan time or sample size. We derive a theoretical model showing that individual-level phenotypic prediction accuracy increases with sample size and total scan duration (sample size × scan time per participant). The model explains empirical prediction accuracies well across 76 phenotypes from nine resting-fMRI and task-fMRI datasets (R = 0.89), spanning diverse scanners, acquisitions, racial groups, disorders and ages. For scans of ≤20 min, accuracy increases linearly with the logarithm of the total scan duration, suggesting that sample size and scan time are initially interchangeable. However, sample size is ultimately more important. Nevertheless, when accounting for the overhead costs of each participant (such as recruitment), longer scans can be substantially cheaper than larger sample size for improving prediction performance. To achieve high prediction performance, 10 min scans are cost inefficient. In most scenarios, the optimal scan time is at least 20 min. On average, 30 min scans are the most cost-effective, yielding 22% savings over 10 min scans. Overshooting the optimal scan time is cheaper than undershooting it, so we recommend a scan time of at least 30 min. Compared with resting-state whole-brain BWAS, the most cost-effective scan time is shorter for task-fMRI and longer for subcortical-to-whole-brain BWAS. In contrast to standard power calculations, our results suggest that jointly optimizing sample size and scan time can boost prediction accuracy while cutting costs. Our empirical reference is available online for future study design ( https://thomasyeolab.github.io/OptimalScanTimeCalculator/index.html ).

Journal

Published

Authors

Keywords

DOI

Abstract

Suicide is one of the leading causes of death among youth worldwide, yet existing studies that aimed to predict the first onset of suicidal thoughts or behaviors (STB) included a limited number of data modalities, and/or focused on adult populations. We aimed to prospectively predict first-onset STB across four-year follow-ups in adolescents using (1) an existing STB history classification model that was previously applied to baseline data, and (2) a new machine learning model with 195 biopsychosocial features.

Journal

Published

Authors

Keywords

DOI

Abstract

Various multilevel, multidomain factors at the individual-, family-, and environmental-level, and changes in neurobiology have been associated with the likelihood of developing alcohol use disorder (AUD) or binge drinking later in life. Prior studies have examined only limited subsets of these factors, typically focusing on cross-sectional associations with alcohol initiation, binge drinking, or AUD rather than exploring longitudinal alcohol use trajectories. Our study addresses these gaps by applying machine learning methods to a comprehensive set of multilevel, multidomain factors and multimodal brain imaging features (including brain structure and functional connectivity) to prospectively predict early alcohol sipping trajectories. Using data from the Adolescent Brain Cognitive Development Study, we identified functional connectivity features and multilevel factors that distinguish youth with an increasing alcohol sipping trajectory from those who initially experimented with alcohol but reduced their consumption over time. Moreover, structural and functional features predicted differences between youth who increasingly sipped over time and those who did not engage in alcohol experimentation. Interactions between age, socioeconomical status and positive attitudes towards drinking could predict a pattern of increasing alcohol sipping over time. These trends could inform how individual, family, environmental and neurobiological factors impact the development of different alcohol sipping trajectories over time.

Journal

Published

Authors

Keywords

DOI

Abstract

Journal

Published

Authors

Keywords

DOI

Abstract

Sleep disturbances and mental health challenges often arise during adolescence, with a greater prevalence among females and individuals experiencing obesity. In this study, we examined the intricate relationships between sleep problems, obesity, and biological sex, and their combined relationship with well-being in a large, diverse cohort of US adolescents.

Journal

Published

Authors

Keywords

DOI

Abstract

Psychiatric conditions, known for their hereditary nature, exert significant impacts on various life domains. Leveraging this heritability, we examine the relations between genetic susceptibility to major psychiatric disorders and the multifaceted aspects of quality of life in two population-based cohorts, the Adolescent Brain Cognitive Development (ABCD) study (N = 3909 preadolescent children) and the UK Biobank (N = 269,293 adults). Genetic susceptibility to seven major psychiatric disorders was quantified by polygenic scores derived from extensive genome-wide association studies (N = 21,000-413,000). Pervasive associations were found between genetic risk for all seven major psychiatric disorders investigated and age-relevant real-life quality of life indices, with varied patterns of associations for different life domains. We especially highlight the role of genetic risks for ADHD and major depressive disorders. Our findings emphasize the continuous nature of psychiatric traits, extending their influence on daily life experiences and societal functioning beyond symptomatology and diagnostic classifications.

Journal

Published

Authors

Keywords

DOI

Abstract

Alcohol use during adolescence poses a significant public health problem due to its potential long-term consequences on both physical and mental health and increased risk for developing substance use disorders later in life. Both individual (e.g., genetic liability, neural functioning, personality features) and environmental (e.g., parenting, school environment) features play an important role in accelerating or buffering the progression of early alcohol consumption. This study used data from the Adolescent Brain Cognitive Development (ABCD) study (Release 5.1; N = 11,868) to provide a comprehensive examination of how genetic, neural, trait, and environmental factors are associated with risk for first sip of alcohol, first full drink, and the progression from first sip to full drink, both independently and uniquely. Cox proportional hazard models were used to examine the univariable associations between theoretically relevant genetic, neural, trait, and environmental variables and early alcohol use. Then, stepwise model-fitting was used to determine which indicators were uniquely associated with alcohol outcomes. Risk for early alcohol use was distributed across multiple domains highlighting the unique information provided by genetic, trait, and environmental variables. Results also indicated the importance of both environmental and genetic factors on time to first sip of alcohol, but that time to first full drink and the progression from sip to drink was most associated with genetic and trait factors rather than broad environmental influences. These findings highlight both potential etiological pathways driving early alcohol use as well as phenotypic and environmental process that can be targeted for early intervention efforts.

Journal

Published

Authors

Keywords

DOI

Abstract

Resilience to developing emotional disorders is critical for adolescent mental health, especially following childhood trauma. Yet, brain markers of resilience remain poorly understood. By analyzing brain responses to angry faces in a large-scale longitudinal adolescent cohort (IMAGEN), we identified two functional networks located in the orbitofrontal and occipital regions. In girls with high genetic risks for depression, higher orbitofrontal-related network activation was associated with a reduced impact of childhood trauma on emotional symptoms at age 19, whereas in those with low genetic risks, lower occipital-related network activation had a similar association. These findings reveal genetic risk-dependent brain markers of resilience (GRBMR). Longitudinally, the orbitofrontal-related GRBMR predicted subsequent emotional disorders in late adolescence, which were generalizable to an independent prospective cohort (ABCD). These findings demonstrate that high polygenic depression risk relates to activations in the orbitofrontal network and to resilience, with implications for biomarkers and treatment.

Journal

Published

Authors

Keywords

DOI

Abstract

Preterm birth can significantly impact cognitive development, particularly executive functions (EF). This study investigated hot (with emotional/motivational aspects) and cool (purely neutral/cognitive) EF trajectories in preterm and full-term children, examining brain-behavior relationships. It included 3508 participants aged 9-10 years (mean age 10.0 years) at baseline from the Adolescent Brain and Cognitive Development (ABCD®) study, evenly split between preterm and full-term births (54.36 % males; 1.05 % Asian American, 10.69 % Black, 15.68 % Hispanic, 61.57 % White, 11.09 % other). Participants were followed for 4 years, completing MRI scans and a cool EF task at baseline and at the 2-year follow-up, as well as hot/cool and hot EF tasks at the 1- and 3-year follow-ups. Linear mixed models showed varying effects of preterm birth across the different EF tasks. Specifically, preterm children showed persistent cool EF deficits and a catch-up pattern for hot EF, while performance on the hot/cool task showed no association with preterm birth. Brain-behavior bivariate latent change score analyses identified distinct bidirectional relationships in specific regions, suggesting altered cognitive-brain maturation interactions in preterm children. These findings highlight the complex nature of EF development following preterm birth: while cool EF deficits persist, hot EF shows catch-up growth in preterm children during early adolescence. This emphasizes the need for tailored interventions and long-term follow-up in this population.

Journal

Published

Authors

Keywords

DOI

Abstract

Adverse childhood experiences (ACEs) are key risk factors for adolescent mental health problems, including conduct problems (CP). While ACEs may impact CP through neurobiological pathways, it is unclear whether brain functional connectivity acts as the neurobiological link.

Journal

Published

Authors

Keywords

DOI

Abstract

Social functioning difficulties among youth with attention-deficit/hyperactivity disorder (ADHD) have been examined behaviorally; however, limited research has investigated brain networks associated with social difficulties among youth with ADHD. A growing body of literature supports the utility of the NIMH’s Research Domain Criteria (RDoC) framework, which emphasizes broad neurobiological based dimensions, allowing for the integration of models of both neural circuitry and behavior when examining externalizing behaviors in youth. We hypothesized that an ADHD classification system based on social functioning would better predict real-world psychosocial and academic outcomes compared to traditional Diagnostic and Statistical Manual of Mental Disorders (DSM-5) nosology of ADHD presentations. First, using data from the Adolescent Brain Cognitive Development (ABCD) Study, we identified four distinct profiles of youth with ADHD ranging from low social functioning to high social functioning. These social-data-derived profiles were linked to differential social challenges associated with caregiver income and mental health disorders. Next, our neuroimaging findings initially revealed differential patterns of functional connectivity across profiles involving attention-control, cingulo-opercular, sensorimotor networks. However, these connectivity differences were not consistently replicated, indicating that social functioning alone may not define neurobiologically distinct subgroups. Finally, in comparing our social functioning profiles to existing DSM-5 nosology with respect to real-world psychosocial outcomes, our social profiles demonstrated greater explanatory power for outcomes related to peer relationships, family conflict, and mental health. Overall, these findings emphasize the heterogeneity in social functioning among ADHD youth and suggest that while behavioral profiles are clinically meaningful, future work should integrate additional dimensions, such as executive functioning, to more precisely capture the neurobiological underpinnings of ADHD.

Journal

Published

Authors

Keywords

DOI

Abstract

Adolescent digital media use is highly prevalent. However, potential harms are unclear, as prospective studies of outcomes of screen-naïve youth are sparse. This study assessed whether individual differences in 4 domains relevant to addiction, measured in late childhood, prospectively predicted average daily hours of screen time (ST) and problematic screen use (PSU), defined as screen use that is compulsive and distressing, of 3 screen activities in mid-adolescence.

Journal

Published

Authors

Keywords

DOI

Abstract

In adolescence, caffeinated beverage consumption is negatively associated with cognitive functioning. The default mode network and dorsal attention network are anticorrelated brain systems that are essentially implicated in attention. Despite the importance of the anticorrelation of default mode network – dorsal attention network on cognitive functioning, no studies have examined the association between this anticorrelation and recent caffeine consumption among youths. This study analyzed baseline data from the Adolescent Brain Cognitive Development℠ Study, the largest longitudinal study examining brain development and adolescent health in the United States, to explore the associations between caffeinated beverage consumption and the strength of anticorrelation between the default mode network – dorsal attention network.

Journal

Published

Authors

Keywords

DOI

Abstract

To identify associations of past-year witnessing violence with expectancies (anticipated effects) for alcohol and cannabis use in Black, Latinx, and White youth, including possible variations by level of neighborhood advantage and/or race/ethnicity.

Journal

Published

Authors

Keywords

DOI

Abstract

Large, population-based magnetic resonance imaging (MRI) studies of adolescents promise transformational insights into neurodevelopment and mental illness risk. However, youth MRI studies are especially susceptible to motion and other artifacts that introduce non-random noise. After visual quality control of 11,263 T1 MRI scans obtained at age 9-10 years through the Adolescent Brain Cognitive Development study, we uncovered bias in measurements of cortical thickness and surface area in 55.1% of the samples with suboptimal image quality. These biases impacted analyses relating structural MRI and clinical measures, resulting in both false-positive and false-negative associations. Surface hole number, an automated index of topological complexity, reproducibly identified lower-quality scans with good specificity, and its inclusion as a covariate partially mitigated quality-related bias. Closer examination of high-quality scans revealed additional topological errors introduced during image preprocessing. Correction with manual edits reproducibly altered thickness measurements and strengthened age-thickness associations. We demonstrate here that inadequate quality control undermines advantages of large sample size to detect meaningful associations. These biases can be mitigated through additional automated and manual interventions.

Journal

Published

Authors

Keywords

DOI

Abstract

Functional and structural magnetic resonance imaging (fMRI and sMRI) are complementary approaches that can be used to study longitudinal brain changes in adolescents. Each individual modality offers distinct insights into the brain. However each individual modality may overlook crucial aspects of brain analysis. By combining them, we can uncover hidden brain connections and gain a more comprehensive understanding. In previous work, we identified multivariate patterns of change in whole-brain function during adolescence. In this work, we focus on linking functional change patterns (FCPs) to brain structure. We introduced two approaches and applied them to data from the adolescent brain and cognitive development (ABCD) dataset. First, we evaluate voxel-wise sMRI- coupling to identify structural patterns linked to our previously identified FCPs. Our approach revealed multiple interesting patterns in functional network connectivity (FNC) and gray matter volume (GMV) data that were linked to subject-level variation. components 2 and 4 exhibit extensive associations between their loadings and voxel-wise GMV data. Secondly, we leveraged a symmetric multimodal fusion technique called multiset canonical correlation analysis (mCCA) + joint independent component analysis (jICA). Using this approach, we identified structured such as one showing increased connectivity between visual and sensorimotor domains and decreased connectivity between sensorimotor and cognitive control domains, linked to structural change patterns ( ) including alterations in the bilateral sensorimotor cortex. Interestingly, females show stronger connection between brain functional and structural changes than males, highlighting gender-related differences. The combined results from both asymmetric and symmetric multimodal fusion methods underscore the intricate gender-specific nuances in neural dynamics. By utilizing two complementary multimodal approaches, our study enhances our understanding of the evolving nature of whole brain connectivity and structure during the adolescent period, shedding light on the nuanced processes underlying adolescent brain development.

Journal

Published

Authors

Keywords

DOI

Abstract

The associations of family environment with adolescent behavioral health are well established, yet insights into how these associations are moderated by sex, particularly through changes in brain structure, are limited.

Journal

Published

Authors

Keywords

DOI

Abstract

Journal

Published

Authors

Keywords

DOI

Abstract

Parents’ internalizing symptoms, such as anxiety and depression, may contribute to similar symptoms in their youth. However, these associations vary, as youth with better emotion regulation may be more protected from negative parental influence. Yet, it remains unclear how youth’s neural correlates of emotion regulation, particularly in prefrontal regions-such as dorsolateral prefrontal cortex (dlPFC), lateral orbitofrontal cortex (lOFC), and medial orbitofrontal cortex (mOFC)-play a role in these associations. To address this gap, this study used two-wave longitudinal data that spanned 2 yr from the nationwide Adolescent Brain Cognitive Development study including 7,932 youth (Mage = 9.96 yr, SD = 7.52; 49% females) and their parents. Results revealed significant longitudinal associations between parents’ and youth’s internalizing symptoms over 2 yr. Moreover, youth’s dlPFC, lOFC, and mOFC activity to negative emotions moderated these links. Youth with higher activity in these regions showed weaker parent-youth associations in internalizing symptoms over time. This study provides robust evidence that dlPFC, lOFC, and mOFC serve as neurobiological protective factors in the longitudinal links between parents and youth’s internalizing symptoms. Findings inform interventions targeting youth’s neural development in emotion regulation to promote emotional adjustment in families where parents face mental health challenges.

Journal

Published

Authors

Keywords

DOI

Abstract

Associations between childhood obesity and brain microstructural differences have been observed. It remains unknown whether these associations are driven by sex-specific excessive weight gain. Restriction spectrum imaging characterizes brain tissue microstructural health via water diffusion, where the restricted normalized isotropic (RNI) compartment assesses neuronal and glial cellularity, which may reflect neuroinflammation, synaptic pruning, or both.

Journal

Published

Authors

Keywords

DOI

Abstract

Although gaming disorder is recognized as a diagnosable behavioral addiction, uncertainty remains regarding its directional association with adolescent psychopathology. Clarifying this association is crucial for refining diagnostic frameworks and developing targeted interventions.

Journal

Published

Authors

Keywords

DOI

Abstract

Classical regression generally assumes that all subjects follow a common model with the same set of parameters. With ever advancing capabilities of modern technologies to collect more subjects and more covariates, it has become increasingly common that there exist subgroups of subjects, and each group follows a different regression model with a different set of parameters. In this article, we propose a new approach for subgroup analysis in regression modeling. Specifically, we model the relation between a response and a set of primary predictors, while we explicitly model the heterogenous association given another set of auxiliary predictors, through the interaction between the primary and auxiliary variables. We introduce penalties to induce the sparsity and group structures within the regression coefficients, and to achieve simultaneous feature selection for both primary predictors that are significantly associated with the response, as well as the auxiliary predictors that define the subgroups. We establish the asymptotic guarantees in terms of parameter estimation consistency and cluster estimation consistency. We illustrate our method with an analysis of the functional magnetic resonance imaging data from the Adolescent Brain Cognitive Development Study.

Journal

Published

Authors

Keywords

DOI

Abstract

Parental psychopathology is a known risk factor for child autistic-like traits. However, symptom-level associations and underlying mechanisms are poorly understood.

Journal

Published

Authors

Keywords

DOI

Abstract

Assessing dimensions of neighborhoods could aid identification of contextual features that influence psychopathology in children and contribute to uncovering mechanisms underlying these associations.

Journal

Published

Authors

Keywords

DOI

Abstract

Recent advancements in understanding the brain’s functional organization related to behavior have been pivotal, particularly in the development of predictive models based on brain connectivity. A major analytical strategy in this domain involves a two-step process by first constructing a connectivity matrix from predefined brain regions, and then linking these connections to behaviors or clinical outcomes. Although some advances considered subject-specific functionally homogeneous nodes without relying on predefined regions of interest (ROIs), all these approaches with unsupervised node partitions predict outcomes inefficiently with independently established connectivity. In this paper, we introduce the Supervised Brain Parcellation (SBP), a brain node parcellation scheme informed by the downstream predictive task. With voxel-level functional time courses generated under resting-state or cognitive tasks as input, our approach clusters voxels into nodes in a manner that maximizes the correlation between inter-node connections and the behavioral outcome, while also accommodating intra-node homogeneity. We rigorously evaluate the SBP approach using resting-state and task-based fMRI data from both the Adolescent Brain Cognitive Development (ABCD) study and the Human Connectome Project (HCP). Our analyses show that SBP significantly improves out-of-sample connectome-based predictive performance compared to conventional step-wise methods under various brain atlases. This advancement holds promise for enhancing our understanding of brain functional architectures with behavior and establishing more informative network neuromarkers for clinical applications.

Journal

Published

Authors

Keywords

DOI

Abstract

Functional brain networks are associated with both behavior and genetic factors. To uncover biological mechanisms of psychopathology, it is critical to define how the spatial organization of these networks relates to genetic risk during development.

Journal

Published

Authors

Keywords

DOI

Abstract

. Recently, US youth of color reported greater use of alcohol, tobacco, and cannabis than White youth. Increased levels of discrimination in recent years may have added to the chronic burden associated with increased use among youth of color. Little is known about this relationship, especially among youth who initiate substance use earlier in adolescence. This study assessed the prevalence of substance susceptibility (willingness and curiosity) and use (alcohol, tobacco and cannabis) among youth by race/ethnicity and ethnic discrimination’s role on this relationship.

Journal

Published

Authors

Keywords

DOI

Abstract

As youth transition into adolescence, their desire for autonomy leads to changes in the family dynamic, resulting in increased family conflict and possible disruptions to children’s psychological health. Previous literature, however, has largely neglected to consider whether the association between family conflict and child behavioral difficulties is uni- or bi-directional. The current study used latent curve growth models with structured residuals (LCMs-SR) to investigate this question in the Adolescent Brain & Cognitive Development (ABCD) study. At four annual waves (baseline through 3-year follow-up), youth ( = 11,868; at Time 1 = 9.48 years; 48% female; 50% White) reported on family conflict while parents reported on youths’ internalizing and externalizing behaviors. Youth reported family conflict levels as increasing over four years. Furthermore, family conflict was bidirectionally associated with externalizing behavior, in that families with greater than expected conflict had children with more externalizing behaviors, and youth with more externalizing behaviors reported greater than expected conflict at home. Internalizing behavior, however, did not predict later family conflict, though family conflict predicted deviations in later internalizing behavior. These findings add to the literature by demonstrating bidirectional influences between children’s behavior and family functioning across emerging adolescence.

Journal

Published

Authors

Keywords

DOI

Abstract

We present the novel Bayesian Regularized and Annotation-Informed Integrative Analysis of Cognition (BRAINIAC) model. BRAINIAC allows for estimation of total variance explained by all features for a given cognitive phenotype, as well as a principled assessment of the impact of annotations on relative enrichment of predictive features compared to others in terms of variance explained, without relying on a potentially unrealistic assumption of sparsity of brain-behavior associations. We validate BRAINIAC in Monte Carlo simulation studies. In real data analyses, we train the BRAINIAC model on resting state functional magnetic resonance imaging (rsMRI) and neuropsychiatric data from the Adolescent Brain Cognitive Development (ABCD) Study and use the trained model in an out-of-study application to harmonized resting-state data from the Human Connectome Project Development (HCP-D), demonstrating a substantial improvement in out-of-study predictive power by incorporating relevant annotations into the BRAINIAC model.

Journal

Published

Authors

Keywords

DOI

Abstract

Subthreshold anxiety (STA) is a significant risk factor for developing anxiety disorder (AX), particularly in adolescence. Understanding the risk and protective factors of the development of STA in early life is essential for early prevention and intervention efforts. However, research on this topic is scarce. We examined the data of 11,876 early adolescents from the Adolescent Brain and Cognitive Development (ABCD) Study to explore the factors influencing the development of STA between ages 9 and 13. The outcomes included developing AX, persistent STA, and remission from STA. Using the Child Behavior Checklist (CBCL), we identified 786 participants with STA. To predict STA transitions, we analyzed 31 diathesis-stress-related variables covering demographics, mental and physical health, and environmental factors, employing logistic regression. Compared to baseline healthy controls (HCs), adolescents with STA showed an odds ratio (OR) of 6.9 for converting to AX. The pivotal risk factors for progression from STA to AX were lack of perseverance and area deprivation, with females being more likely to maintain STA. Protective factors for a favorable prognosis of STA included the absence of traumatic history, lack of premeditation, increased physical activity, and positive school environment. Healing traumatic experiences, increased physical activity, and enhancing school and family environments could help prevent adverse outcomes. By targeting these modifiable factors, adolescents at high risk can be identified and provided with interventions early in life.

Journal

Published

Authors

Keywords

DOI

Abstract

In order to transition between a resting state and carrying out cognitively-demanding processes the brain makes a host of subtle changes to its network organization. In adults, less reconfiguration relates to better task performance, suggesting a preconfigured brain organization at rest is beneficial, such that only minute changes are required to execute task demands. Here, we take a developmental lens to this phenomenon, examining reconfiguration in late childhood by leveraging a large sample of 9-11 year olds from the Adolescent Brain and Cognitive Development Study. We find more reconfiguration between the resting state and two executive function tasks is related to better task performance. These relationships hold even when accounting for network segregation, though segregation was negatively related to reconfiguration. Reconfiguration was also related to crystallized intelligence, with diverging effects across tasks. Overall, these findings demonstrate that in contrast to adulthood during late childhood, before functional brain networks are fully mature, greater reconfiguration promotes successful task performance.

Journal

Published

Authors

Keywords

DOI

Abstract

Journal

Published

Authors

Keywords

DOI

Abstract

Sleep duration and physical activity have been associated with internalizing problems. However, genetic confounding and measurement error may introduce bias. We assessed genetic confounding in the associations of modifiable lifestyle with internalizing problems using device-based and questionnaire assessments to estimate shared genetic risk across different assessments in adolescents.

Journal

Published

Authors

Keywords

DOI

Abstract

With the widespread adoption of screen-based devices among adolescents, there is growing concern that more screen time could contribute to mental health problems such as depression. It is thus critical to identify potential mediating factors that could help explain this potential risk relationship. Recent evidence indicates that more screen time could impact sleep duration and brain structural connectivity (ie, white matter organization), which are critical for emotional health. Notably, sleep duration is a modifiable behavior that health care providers can easily target.

Journal

Published

Authors

Keywords

DOI

Abstract

Lower parental socioeconomic status (SES) is consistently linked to lower academic achievement among adolescents, with early disparities persisting into adulthood. However, the neurobiological mechanisms underlying these associations are not well understood. This preregistered study investigates the associations between household and neighborhood disadvantage-measured by income-to-needs ratio, parental educational attainment, and neighborhood SES-changes in within-network functional connectivity, and school grades, using longitudinal data from the Adolescent Brain Cognitive Development Study (N = 4745; age at baseline = 119.1 ± 7.5 months; age at 2-year follow up = 143.6 ± 7.8 months; age at 3-year follow up = 154.8 ± 7.7 months). Within-network connectivity changed significantly from baseline to follow-up, increasing in most networks (e.g., default mode, fronto-parietal) and decreasing in a few (e.g., salience, ventral attention). After controlling for other SES indicators, parental education and neighborhood disadvantage, but not income, were associated with changes in connectivity across several brain networks, including reduced increases in default mode, cingulo-opercular, and visual network connectivity and greater increases in within-sensorimotor network connectivity. Further, changes in sensorimotor connectivity mediated the relationship between parental educational attainment and academic achievement three years later. These findings highlight the importance of parental education and neighborhood environments in shaping neurodevelopmental trajectories that influence academic outcomes. Understanding the mechanisms that link socioeconomic disadvantage with academic outcomes could inform interventions aimed at reducing persistent achievement gaps.

Journal

Published

Authors

Keywords

DOI

Abstract

Journal

Published

Authors

Keywords

DOI

Abstract

A key step toward understanding psychiatric disorders that disproportionately impact female mental health is delineating the emergence of sex-specific patterns of brain organisation at the critical transition from childhood to adolescence. Prior work suggests that individual differences in the spatial organisation of functional brain networks across the cortex are associated with psychopathology and differ systematically by sex.

Journal

Published

Authors

Keywords

DOI

Abstract

Journal

Published

Authors

Keywords

DOI

Abstract

Increasing child and adolescent use of social media, video games, and mobile phones has raised concerns about potential links to youth mental health problems. Prior research has largely focused on total screen time rather than longitudinal addictive use trajectories.

Journal

Published

Authors

Keywords

DOI

Abstract

Pregnancy- and birth-related factors affect offspring brain development, emphasizing the importance of early life exposures. While most previous studies have focused on a few variables in isolation, here we investigated associations between a broad range of pregnancy- and birth-related variables and multivariate cortical brain MRI features. Our sample consisted of 8,396 children aged 8.9 to 11.1 y from the Adolescent Brain Cognitive Development Study. Through multiple correspondence analysis and factor analysis of mixed data, we distilled numerous pregnancy and birth variables into four overarching dimensions; maternal pregnancy complications, maternal substance use, low birth weight and prematurity, and newborn birth complications. Vertex-wise measures of cortical thickness (CT), surface area (SA), and curvature were fused using linked independent component analysis. Linear mixed-effects models showed that maternal pregnancy complications and low birth weight and prematurity were associated with smaller global SA. Additionally, low birth weight and prematurity was associated with complex regional cortical patterns reflecting bidirectional variations in both SA and CT. Newborn birth complications showed multivariate patterns reflecting smaller occipital- and larger temporal area, bidirectional frontal area variations, and reduced CT across the cortex. Maternal substance use showed no associations with child cortical structure. By employing a multifactorial and multivariate morphometric fusion approach, we connected complications during pregnancy and fetal size and prematurity to global SA and specific regional signatures across child cortical MRI features.

Journal

Published

Authors

Keywords

DOI

Abstract

The increased use of screen media has raised unknown effects on mental health among adolescents. This study aimed to examine the correlational and causal association between screen media activity (SMA) and mental health problems, and the mediating role of brain functions and structures in this relationship. Data from 4557 adolescents (mean age = 9.955 ± 0.164 years) in the Adolescent Brain Cognitive Development (ABCD) study were analysed across four time points: baseline, 1-year, 2-year, and 3-year follow-ups. Linear mixed models assessed SMA’s association with mental health indices and the brain’s developmental pattern, respectively. Cross-lagged panel models examined the SMA-mental health problems’ longitudinal and causal relationship. Mediation analyses explored brain functions and structures as mediators on the SMA-mental health correlation. Baseline SMA positively correlated with internalizing, externalizing, and stress problems; and negatively correlated with brain volume, area and diverse sets of resting-state functional connectivity (RSFC) after three years. Higher baseline SMA associated with increased internalizing ( = 0.030, = 0.012, = 0.016), and stress problems ( = 0.026, = 0.012, = 0.037) three years later. The RSFC between the cingulo-opercular network (CON) and the retrosplenial temporal network (RTN) mediated the effects of SMA on externalizing ( = 0.002, = 0.042) and stress problems ( = -0.003, = 0.022). TV watching predicted higher externalizing problems (β = 0.054, pfdr < 0.001), while video watching predicted increased internalizing (β = 0.061, pfdr < 0.001), externalizing (β = 0.033, pfdr = 0.035), and stress problems (β = 0.060, pfdr < 0.001). The findings indicate the negative impact of SMA, particularly TV and video watching, on adolescent mental health, mediated by changes in CON and RTN functional connectivity. Future research can explore the specific risks associated with video streaming and consider the role of emerging technologies such as virtual reality in SMA on adolescent mental health.

Journal

Published

Authors

Keywords

DOI

Abstract

Late childhood is a crucial period for individuals with psychiatric disorders. While common single-nucleotide polymorphisms explain a large proportion of inherited risk, structural variations including copy number variants (CNVs) play a significant role in the genetic architecture of neurodevelopmental disorders. The relevance of CNVs to child psychopathology and cognitive function in the general population remains underexplored. The authors conducted a comprehensive exploration of the CNV architecture underlying dimensions of psychopathology and cognitive phenotypes within the Adolescent Brain Cognitive Development (ABCD) Study.

Journal

Published

Authors

Keywords

DOI

Abstract

Impulsivity in highly heritable attention deficit hyperactivity disorder (ADHD) has been studied using neural activity via fMRI or genetic data, but rarely with multivariate methods linking both. We investigated coupled neural activity and gene expression signatures, using parallel independent component analysis (pICA) and Adolescent Brain Cognitive Development data.

Journal

Published

Authors

Keywords

DOI

Abstract

The current study aimed to determine sociodemographic associations of bedtime screen use behaviors and the sociodemographic differences in the associations between bedtime screen use and sleep outcomes in a national (US) study of early adolescents.

Journal

Published

Authors

Keywords

DOI

Abstract

We examined the independent and joint prospective associations of screen time, sleep disturbance, and sleep duration with body mass index (BMI) and waist circumference (WC) stratified by sex. Data are from 7445 participants (47.3% females) aged 9-10 years at baseline (2016-2018) in the Adolescent Brain Cognitive Development Study. Missing data were imputed, and weighted multivariable linear regression models estimated the independent and joint effects of screen time and sleep disturbance or sleep duration on BMI and WC after 2 years. Joint associations grouped participants by combinations of screen time and sleep, with low screen time and sufficient sleep or no sleep disturbance as the reference groups. Screen time was significantly associated with higher BMI (B = 0.32; 95% CI: 0.19, 0.45; < 0.001) and WC (B = 0.40; 95% CI: 0.23, 0.56; < 0.001). Sleep disturbance was associated with higher BMI (B = 1.23; 95% CI: 0.14, 2.33; 0.026) in males. Insufficient sleep (<9 hours) (B = 1.30; 95% CI: 0.53, 2.07; < 0.001) was associated with higher BMI. Medium screen time without sleep disturbance or insufficient sleep, and medium and high screen time with either sleep problem were associated with higher BMI and WC. Low screen time with insufficient sleep and high screen time with sufficient sleep were associated with higher BMI. Associations were generally stronger among males, particularly with high screen time. Screen time and insufficient sleep were independently and jointly associated with higher BMI and WC 2 years later, especially when both were present.

Journal

Published

Authors

Keywords

DOI

Abstract

Early adolescence is a dynamic period of social and brain development amid rapid hormonal and puberty changes. We examined how differences and changes in positive social experiences and cortical thickness co-develop from age 9-11 and 11-13 years in the ABCD cohort (N~12,000). We used bivariate latent change score models to capture cortical development (modeling mean whole-brain cortical thickness) and positive social experiences (modeling caregiver monitoring, family cohesion, prosocial behavior, number of friends, school engagement, school involvement, and neighborhood safety). We found evidence for correlated change, such that a greater reduction in positive social experiences was associated with a greater decrease in cortical thickness (est = 2.54SE = .54, z = 4.74,< .001, standardized effect size = .08), which did not differ between males and females in early and late puberty stages. We found mixed evidence for sex-specific relationships between puberty stage and social experiences, highlighting the need to better understand males’ puberty and social experiences in early adolescence. The evidence supports a transactional model of development in that positive social experiences and cortical thickness change together throughout early adolescence. The findings also highlight the importance of supporting youth in early adolescence through school transitions.

Journal

Published

Authors

Keywords

DOI

Abstract

Genetic risk factors, impulsivity, and exposure to painful and provocative events (PPEs) have each been linked with risk for suicide attempt (SA). However, the degree to which genetic associations with SA are mediated by dimensions of impulsivity and PPEs remains unexplored, particularly in early adolescence.

Journal

Published

Authors

Keywords

DOI

Abstract

What role do our genes play in shaping the structural organisation of the living human brain? Across a sample of 2,153 children (9-11 years old), we address this question, focusing on common genetic variants associated with cognitive ability and diffusion-based structural neuroimaging. Using polygenic scores, we test how variability in the genetic signal associated with cognitive ability is linked to simulated structural network properties, such as network efficiency. We fit a computational model to each connectome that simulates the emergence of high-level network properties. Central to the model is an economic trade-off between the “cost” of forming a given connection (a distance penalty) and the topological “value” that connection brings to the network. To simulate the network properties of those with the highest genetic propensity for cognitive ability, we had to use a significantly weakerpenalty. This softer distance penalty produces more stochastic, diverse, and efficient simulated networks. Further, those with a high genetic propensity for cognitive ability exhibited a more randomised simulated topology. Finally, we took a different approach to exploring the relationships between genes and model parameters by linking theof those parameters with post-mortem gene expression data, with a comparative pathway enrichment analysis. Across the sample, overlapping biological and cellular pathways between polygenic scores and each child’s optimal cost-value trade-off emerged. Together, the generative wiring distance term, which varied maximally across participants but minimally across the cortex, was enriched for more ontologies than the wiring value term, which varied maximally across the cortex. However, the overlap in enriched ontologies between polygenic scores and the wiringterm was greater than that of polygenic scores and the wiringterm. This application of computational modelling demonstrates that the underlying economic trade-offs needed to simulate the higher-order topological properties of networks vary according to genetic propensity for cognitive ability.

Journal

Published

Authors

Keywords

DOI

Abstract

One in ten children experiences sleep-disordered breathing (SDB). Untreated SDB is associated with poor cognition, but the underlying mechanisms are less understood.

Journal

Published

Authors

Keywords

DOI

Abstract

Outdoor air pollution exposure is associated with structural and functional brain differences and an increased risk for psychopathology. Although the neural mechanisms remain unclear, air pollutants may impact mental health by altering brain regions implicated in psychopathology, such as the amygdala. Here, we examined the association between ambient air pollution exposure and amygdala subregion volumes in 9- to 10-year-olds.

Journal

Published

Authors

Keywords

DOI

Abstract

A delay in brain maturation is a hypothesized pathomechanism of attention-deficit/hyperactivity disorder (ADHD). Differences in emotion regulation are associated with phenotypic and prognostic heterogeneity in ADHD. The development of emotion regulation is driven, in part, by brain maturation. Whether the difference between an individual’s brain age predicted by machine-learning algorithms trained on neuroimaging data and that individual’s chronological age, i.e. brain-predicted age difference (brain-PAD) predicts differences in emotion regulation, and whether ADHD problems add to this prediction is unknown. Using data from the Adolescent Brain Cognitive Development Study, we examined, in 2711 children (M = 120.09 months, SD = 7.61; 54.15% female; 61.23% white), whether adjusting for action cancellation (inhibition), age, sex assigned at birth, psychotropic treatment, and pubertal status, brain-PAD in late childhood predicts self-reported emotion regulation in early adolescence (at 3-year follow-up), and whether parent-reported ADHD problems predict self-reported emotion regulation above and beyond brain-PAD. Greater brain-PAD predicted greater expressive suppression (b = 0.172, SE = 0.051, p = 0.004), whereas ADHD problems did not (b = 0.041, SE = 0.022, p = 0.124), model marginal R = 0.020. This pattern of results was replicated across sensitivity tests. Neither brain-PAD, nor ADHD problems predicted cognitive reappraisal, ps = 0.734. Clinically, consistent with earlier findings linking greater brain-PAD to psychopathology, we observed that greater brain-PAD in childhood-but not ADHD problems-predicted expressive suppression in early adolescence. Expressive suppression is implicated in the etiology, maintenance, and treatment of numerous psychopathologies, highlighting the relevance of brain-PAD in understanding developmental risk mechanisms. Conceptually, these findings further validate brain-PAD as a valuable tool for advancing developmental neuroscience.

Journal

Published

Authors

Keywords

DOI

Abstract

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that is commonly associated with sleep disturbances. Sleep disruption can contribute to difficulties in a child’s life and, therefore, can be an important determinant of their quality of life. This study uses data from the large multisite Adolescent Brain Cognitive Development (ABCD) database to examine the relationship between sleep and behavior in children with ADHD. We hypothesized that shorter and more interrupted sleep would relate to increased problem behaviors such as inattention and social difficulties. Sleep data was obtained using commercially available actigraphy (Fitbit) measures, and the Sleep Disturbance Scale for Children (SDSC) for 212 children ages 10 to 13 years, with ADHD and an age and sex matched control group (n = 212). Behavioral and emotional subscores were obtained from the Child Behavior Checklist (CBCL). SDSC sleep data was significantly different between ADHD and control groups, while wearable actigraphy data was not. ADHD diagnosis, family income, sleep latency (measured by wearable device), and 3 out of 6 of the SDSC subscores were significantly related to problem behavior scores measured by the CBCL.

Journal

Published

Authors

Keywords

DOI

Abstract

Financial adversity has been associated with altered subcortical neurodevelopment and obesity risk. However, no studies have examined these relationships in tandem. Food intake is influenced by the subcortex; thus, we examined whether financial adversity moderated bidirectional relationships between neurodevelopment and body mass index (BMI) in early adolescence.

Journal

Published

Authors

Keywords

DOI

Abstract

Rates of prenatal cannabis exposure (PCE) are rising with increasingly permissive legislation, which may be a risk factor for psychosis. Disrupted reward-related neural circuitry may underlie this relationship. We aim to elucidate neural mechanisms involved in the association between PCE and youth-onset psychotic-like experiences (PLEs) by probing correlates of reward anticipation, a neurobehavioral marker of endocannabinoid-mediated dopaminergic function.

Journal

Published

Authors

Keywords

DOI

Abstract

Multilevel regression and poststratification (MRP) is a popular method for addressing selection bias in subgroup estimation, with broad applications across fields from social sciences to public health. In this paper, we examine the inferential validity of MRP in finite populations, exploring the impact of poststratification and model specification. The success of MRP relies heavily on the availability of auxiliary information that is strongly related to the outcome. To enhance the fitting performance of the outcome model, we recommend modeling the inclusion probabilities conditionally on auxiliary variables and incorporating flexible functions of estimated inclusion probabilities as predictors in the mean structure. We present a statistical data integration framework that offers robust inferences for probability and nonprobability surveys, addressing various challenges in practical applications. Our simulation studies indicate the statistical validity of MRP, which involves a tradeoff between bias and variance, with greater benefits for subgroup estimates with small sample sizes, compared to alternative methods. We have applied our methods to the Adolescent Brain Cognitive Development (ABCD) Study, which collected information on children across 21 geographic locations in the U.S. to provide national representation, but is subject to selection bias as a nonprobability sample. We focus on the cognition measure of diverse groups of children in the ABCD study and show that the use of auxiliary variables affects the findings on cognitive performance.

Journal

Published

Authors

Keywords

DOI

Abstract

Prior studies show that neighborhood disadvantage negatively impacts children’s cognitive function and brain volume. However, despite their co-occurrence, there is a lack of cohesive examination of the joint effects of environmental and social factors on brain volumes.

Journal

Published

Authors

Keywords

DOI

Abstract

The associations of prenatal alcohol exposure (PAE) and prenatal tobacco exposure (PTE) with adolescent neuroanatomical development are typically evaluated cross-sectionally. It is unclear whether observed effects persist throughout life or reflect different developmental trajectories.

Journal

Published

Authors

Keywords

DOI

Abstract

Bipolar disorder (BD) is a severe, persistent disorder that causes functional impairment. Besides heritability, environmental factors, such as traumatic experience, impact the development of BD. Little is known about the early developmental signs of this disorder; therefore, this study aims to look at the impact of interpersonal trauma on the early developmental signs of BD. Specifically, differences in psychopathological behaviours were investigated between (1) at-risk children and controls and (2) at-risk children who experienced an interpersonal traumatic event and those who did not.

Journal

Published

Authors

Keywords

DOI

Abstract

Psychopathology is associated with features of the family, neighborhood, and school environments. During adolescence, increased autonomy and novel social relationships may influence the strength of these associations over time. Characterizing these processes is key to understanding how and when different factors may contribute to psychopathology. Participants in the Adolescent Brain Cognitive Development (ABCD) Study (n = 11,823) were 9-10 years old at baseline and 12-13 years old at the three-year follow-up. At each time point, internalizing symptoms (INT) and externalizing symptoms (EXT), family features (e.g., conflict, parental monitoring, acceptance, and financial hardship), neighborhood safety, and school supportiveness were assessed. Fixed effect regression models were estimated separately for male and female youth to examine the age-varying, within-individual associations between symptoms and family, neighborhood, and school factors. INT and EXT significantly decreased among male adolescents over time, while female adolescents exhibited increases in INT and decreases in EXT. Family conflict, financial hardship, neighborhood safety, and school support predicted INT and EXT, with some variation by sex (e.g., neighborhood safety only predicted INT and EXT for male adolescents). Many of these associations were consistent over time. However, for male adolescents, the association between financial hardship and EXT weakened over time, while the family conflict and EXT association strengthened. Understanding how timing and specific environmental factors interact to shape adolescent mental health is critical to identifying periods of heightened sensitivity to risk or protective influences.

Journal

Published

Authors

Keywords

DOI

Abstract

Neurodevelopmental disorders have significant public health impacts, and novel approaches to understanding these disorders are greatly needed. Social connectedness, including relationships with parents and peers as well as family and school environments, may serve as a protective factor for neurodivergent youth. Neural networks that support social processing could also influence outcomes for these individuals.

Journal

Published

Authors

Keywords

DOI

Abstract

Differences in sensitivity to substances are important for understanding variability in addiction propensity. The value of modeling subjective response to nicotine, particularly e-cigarettes, at first use as a predictor of future use remains largely untested.

Journal

Published

Authors

Keywords

DOI

Abstract

The adolescent brain is vulnerable to ambient air pollution. Importantly, community-level factors – such as neighborhood disadvantage – that co-occur with air pollution may further enhance this vulnerability and impact brain development. The current study investigated if neighborhood disadvantage moderates the association between residential fine particulate matter (PM) pollution and adolescent brain development, including longitudinal changes in cortical thickness, surface area, and subcortical/white matter volume from ages 9-13 years (n = 8321 participants from the ABCD Study®; 12,634 observations). We found that, in more disadvantaged neighborhoods, higher PM levels were associated with greater age-related cortical thinning in temporal areas and in most regions of the occipital lobe. Furthermore, independent of neighborhood disadvantage, higher PM exposure was associated with larger age-related surface area decreases in parietal, occipital, and temporal regions, but smaller age-related increases in right cerebral white matter volume and frontal and temporal region surface area. Similarly, higher PM exposure was independently associated with greater age-related cortical thinning in the frontal regions, cingulate, and insula, but smaller age-related cortical thickening in temporal regions. Findings have policy implications for air quality improvements alongside investment in disadvantaged neighborhoods to bolster adolescent brain development.

Journal

Published

Authors

Keywords

DOI

Abstract

Variability in associations between socioeconomic status and cortical gray matter may be due in part to the common, functional brain-derived neurotrophic factor (BDNF) Val66Met polymorphism, which alters BDNF signaling. In this study, we examined whether BDNF Val66Met genotype moderated the associations between socioeconomic factors (family income, parental education) and cortical surface area (SA) and thickness (CT) in two large independent samples of typically-developing children and adolescents. Participants were 3- to 21-year-olds (N = 383; 47% female) from the Pediatric Imaging, Neurocognition, and Genetics (PING) study and 11- to 14-year-olds (N = 2566; 46% female) in the Adolescent Brain Cognitive Development (ABCD) study. High-resolution, T1-weighted magnetic resonance imaging data were acquired in both studies. Analyses were conducted on global and regional SA and CT. In the PING sample, BDNF Val66Met genotype significantly moderated the association between family income and total SA and SA in the left fusiform gyrus. In the ABCD sample, there were no significant interactions for global or regional SA or CT. Collectively, these results suggest that BDNF Val66Met genotype may not explain variability in associations between socioeconomic factors and SA or CT in children and adolescents.

Journal

Published

Authors

Keywords

DOI

Abstract

Journal

Published

Authors

Keywords

DOI

Abstract

Parental history of problematic substance use (PH) increases the risk for early adolescent substance use (SU), potentially due to premorbid differences in reward-processing brain regions (e.g., striatum). However, no studies have prospectively examined the separate contributions of parental history of alcohol (PHA) and drug (PHD) use or the impact of PH density (PH, PH, PH) on reward processing in preadolescents. This study analyzed data from 10,235 participants (ages 9-14) in the Adolescent Brain Cognitive Development Study (ABCD). Reward processing was assessed using the Monetary Incentive Delay Task (MID) at baseline and two-year follow-up. Regions of interest included bilateral striatal activation elicited by neutral vs. anticipation of large rewards. Linear mixed-effect models evaluated PH, PHA, PHD, and PH density on ROI activation, controlling for relevant covariates. Results showed that youth with PHA had greater nucleus accumbens activation during reward anticipation than those with no history (PHA), but no significant differences were found between PHA and PHA or PHA and PHA. PHD and PH were not significantly associated with BOLD activation in striatal regions, nor were there changes over time. These findings highlight the need to consider both PH and environmental factors when assessing neurodevelopmental risk for early substance use.

Journal

Published

Authors

Keywords

DOI

Abstract

Intra-individual variability in reaction times (IIVRT), which generally occurs as a result of episodic long reaction times (RTs), is a marker for impaired attention. Multiple functional neuroimaging studies have attempted to discern neurofunctional correlates of IIVRT, but few use models that account for trial-level IIVRT. Neurofunctional correlates of IIVRT differ depending on the method applied, and few studies have used multiple methods in the same sample. This study utilized Stop-Signal Task functional magnetic resonance imaging (fMRI) data from 8,066 children (9-10 years old) in the Adolescent Brain Cognitive Development (ABCD) study. IIVRT was modeled using multiple methods, including converting RTs to z-scores, variance time course modeling, and a novel machine-learning technique (i.e., hidden Markov model) to compute the probability of a trial reflecting good or poor attentional states. Across all three methods, lower IIVRT was associated with greater activation in the default mode network (DMN), while higher IIRVT was associated with greater activation in the dorsal attention network (DAN). Although all models yielded similar neural correlates, z-score modeling demonstrated the strongest effect sizes in task-related networks. Our findings are congruent with previous work in adults and demonstrate the reproducibility and developmental stability of the neural correlates of trial-level IIVRT. Higher effect sizes for brain-IIVRT associations using the z-score method suggest that this approach is a simple and promising candidate for investigating neural mechanisms related to IIVRT.

Journal

Published

Authors

Keywords

DOI