IntroductionRegular cannabis use is associated with attenuated neural reward signaling, primarily measured through monetary or drug-cue tasks. Yet, minimal research has studied functional positive face processing in inhibitory control contexts, particularly amongst cannabis-using adolescent and young adults. The present study seeks to investigate functional response differences in whole-brain and ventral striatal activation, and ventral striatal functional context-dependent connectivity during positive (i.e., happy) face conditions during an emotional Go/No-go task in abstinent regular cannabis-using adolescent and young adults compared to controls.MethodsParticipants (age 16-26; cannabis-using=35; control=33) underwent at least two-weeks of monitored abstinence before completing an emotional Go/No-go fMRI task. Whole-brain analyses examined blood-oxygen-level-dependent (BOLD) differences for positive (minus neutral) face conditions between groups. Bilateral ventral striatal activity was investigated in region-of-interest and task-dependent functional connectivity analysis.ResultsCannabis-using participants displayed increased left middle cingulum and decreased left supplemental motor area BOLD response during positive Go conditions. Decreased BOLD response was seen in left superior frontal region during positive No-go for cannabis-using participants. Ventral striatum activity was increased during Go and decreased during No-go conditions for cannabis-using group, with null connectivity findings.DiscussionClusters of aberrant functional response within cannabis-using adolescents and young adults aligns with previous, but sparse, literature on positive face engagement and inhibition. Here, we demonstrate variable ventral striatum activity consistent with reward-eliciting BOLD investigations—representing importance of reward-related affective investigations—yet no connectivity differences in this sample. These findings may represent a risk for or consequence of cannabis use, as differences are still notable after two-weeks of abstinence.

BACKGROUND AND AIMS:Adolescent substance use is a significant public health concern, though the scope of the problem is difficult to ascertain given reliance on self-reported substance use information. Recent, large cohort studies in adolescents and young adults suggest underreporting of substance use. Analyses here aimed to determine concordance between self-reported substance use and biochemical verification through hair samples and to estimate prevalence of the three most reported substances used by adolescents. DESIGN:Observational cohort longitudinal study design. Liquid chromatography and gas chromatography tandem mass spectrometry (LC or GC/MS-MS) were used to test hair samples for biochemically verified substance use, with results compared with self-reported substance use. Multi-step weighting methods estimated prevalence trends of cannabis, alcohol and nicotine use over time, adjusting for discrepancies in sample representation due to recruitment demography, missed visits and hair sample testing. SETTING AND PARTICIPANTS:Data came from the United States nationwide Adolescent Brain Cognitive Development Study (n = 11 868; age 9-10 at baseline, age 15-16 at wave 6). Participants were followed annually, with data here from 2016 to 2024. MEASUREMENTS:Hair samples objectively detected at least several days of substance use in a subsample of participants (nsamples = 11 865; n = 6133 unique participants). Participants self-reported past 3-month substance use. Sociodemographic, individual and environmental-level factors were included in inverse propensity weights to estimate prevalence rates of cannabis, alcohol and nicotine use in teens. FINDINGS:Concordance between self-report and toxicological data improved with age (for cannabis, ages 11-12 = <1%; ages 15-16 = 45%). Weighted estimates of biochemically verified substance use indicated 7.1% [95% confidence interval (CI) = 6.0-8.3] of 15-16 year olds engaged in biochemically detected cannabis use, 0.2% (95% CI = 0.1-0.4) used alcohol and 4.7% (95% CI = 3.7-6.0) used nicotine. CONCLUSIONS:In United States youth, the concordance between self-reported substance use patterns and biochemical verification improves with age. Biochemical verification reflects substantive cannabis and nicotine use by United States youth aged 15-16, supporting combining toxicological and self-report data to improve identification of substance use in youth when possible.

Importance:Millions of children worldwide are experiencing prolonged symptoms after SARS-CoV-2 infection, yet social risk factors for developing long COVID are largely unknown. As child health is influenced by the environment in which they live and interact, adverse social determinants of health (SDOH) may contribute to the development of pediatric long COVID. Objective:To identify whether adverse SDOH are associated with increased odds of long COVID in school-aged children and adolescents in the US. Design, Setting, and Participants:This cross-sectional analysis of a multicenter, longitudinal, meta-cohort study encompassed 52 sites (health care and community settings) across the US. School-aged children (6-11 years; n = 903) and adolescents (12-17 years; n = 3681) with SARS-CoV-2 infection history were included. Those with an unknown date of first infection, history of multisystem inflammatory syndrome in children, or symptom surveys with less than 50% of questions completed were excluded. Participants were recruited via health care systems, long COVID clinics, fliers, websites, social media campaigns, radio, health fairs, community-based organizations, community health workers, and existing research cohorts from March 2022 to August 2024, and surveys were completed by caregivers between March 2022 and August 2024. Exposure:Twenty-four individual social determinant of health factors were grouped into 5 Healthy People 2030 domains: economic stability, social and community context, caregiver education access and quality, neighborhood and built environment, and health care access and quality. Latent classes were created within each domain and used in regression models. Main Outcomes and Measures:Presence of long COVID using caregiver-reported, symptom-based, age-specific research indices. Results:The mean (SD) age among 4584 individuals included in this study was 14 (3) years, and 2330 (51%) of participants were male. The number of latent classes varied by domain; the reference group was the class with the least adversity. In unadjusted analyses, most classes in each domain were associated with higher odds of long COVID. After adjusting for many factors, including age group, sex, timing of infection, referral source, and other social determinant of health domains, economic instability characterized by difficulty covering expenses, poverty, receipt of government assistance, and food insecurity were associated with an increased risk of having long COVID (class 2 adjusted odds ratio [aOR], 1.57; 95% CI, 1.18-2.09; class 4 aOR, 2.39; 95% CI, 1.73-3.30); economic instability without food insecurity (class 3) was not (aOR, 0.93; 95% CI, 0.70-1.23). Poorer social and community context (eg, high levels of discrimination and low social support) was also associated with long COVID (aOR, 2.17; 95% CI, 1.77-2.66). Sensitivity analyses stratified by age group and adjusted for race and ethnicity did not alter or attenuate these results. Conclusions and Relevance:In this study, economic instability that included food insecurity and poor social and community context were associated with greater odds of pediatric long COVID. Those with food security, despite experiencing other economic challenges, did not have greater odds of long COVID. Further study is needed to determine if addressing SDOH factors can decrease the rate of pediatric long COVID.

Importance: Despite the importance placed on physical activity throughout childhood to adolescence, the extent to which physical activity is associated with trajectories of brain structure development remains unclear. Objective: To investigate the associations between physical activity on volumetric gray matter morphometry throughout adolescence. Design: The Adolescent Brain Cognitive Development (ABCD) Study is a cohort-based longitudinal design of over 11,880 participants from ages 9-10 followed for 10 years. Setting: Multi-site study design including 21 U.S.-based sites within the continental United States. Participants: 9,291 participants (ages 9-17; 49% female; 55% white/non-Hispanic) with usable neuroimaging and sports activity involvement questionnaire data were analyzed across four longitudinal follow-up visits (i.e., year-0 to year-6). Exposures: Past-year amount of physical activity, from sports and activities, converted to a common metric (metabolic equivalent of task; METs) across late childhood to mid-adolescence. Main Outcomes and Measures: Longitudinal linear mixed effect models evaluated brain structure measured across 84 gray matter volumetric regions-of-interest. The interaction between METs and age was the primary effect investigated; non-linear fits of age were evaluated. Covariates included: total intracranial volume, sex, household income, body mass index, pubertal stage, MRI software version, genetic principal components, and random effects of participant identification, family identification, and MRI serial number. Results: Across 24,929 total observations, participants engaged in an average of 13,858 past-year MET-minutes (i.e., 266 MET-minutes/week) from sports/activities with stepwise increases across time. A quadratic effect of age resulted in optimal model fit. Linear mixed-effect regressions identified significant effects of total past-year METs*age-squared across 23 regions-of-interest with more pronounced trajectories of changes in volume observed for youth with higher past-year METs; standardized beta estimates range from -.005 to -.01 (all FDR-correct p&lt;.05). Significant regions were predominantly frontotemporal, but also included: subcortical, parietal, occipital, and cingulate regions. Conclusions and Relevance: Findings suggest that the volume of physical activity engaged in from sports/activities is linked with brain morphological metrics throughout late childhood into adolescence. Physical activity remains an important modifiable health factor that influences neurodevelopmental trajectories.

Objective Adolescence is characterized by rapid neurobehavioral development. The endocannabinoid (eCB) system modulates several co-developing neurotransmitter systems and is well-implicated in preclinical substance use (SU) models. Few studies, however, have investigated associations between the eCB system and SU in adolescence. The present study evaluated associations between circulating eCB lipids and SU, impulsivity, and behavioral approach endophenotypes. Methods:Concentrations of eCBs [2-arachidonoylglycerol (2-AG) and N-arachidonoylethanolamine (AEA)] and related small bioactive lipids were quantified in serum samples from a substudy of youth (n=432) enrolled in the Adolescent Brain Cognitive Development Study using liquid chromatography-mass spectrometry. Youth completed the UPPS-P Impulsive Behavior and Behavioral Inhibition/Behavioral Approach System Scales, a SU interview, and questionnaire on factors that impact circulating eCBs. Generalized additive models assessed for associations and sex interactions between eCB concentrations and behaviors. Results: 2-AG and 2-oleoylglycerol were broadly associated with behavioral approach and urgency, while AEA and other N-acylethanolamines were associated with higher-order functions like perseverance and planning, with several sex interactions observed. 2-AG and AEA were negatively associated with low-level substance use and full-unit substance use, respectively. Conclusions Although relationships between serum eCBs and concentrations in brain are not known, the associations observed between peripheral eCB concentrations and substance use behaviors could reflect differences in eCB homeostasis in the brain. Observed sex differences may suggest hormonal or sex-specific eCB influences on brain development. Further work using direct measures of eCB concentrations in the brain are needed to validate these speculations. Future studies should investigate these mechanisms longitudinally.

Background:Adolescent substance use is a continued public health concern. The objective of this manuscript is to detail the prevalence of substance use, polysubstance use, and investigate sex differences in the Adolescent Brain Cognitive Development (ABCD) Study from ages 9-17. Methods:11,880 youth across the U.S., recruited at ages 9-10, completed annual study visits from September 2016 to January 2024. The ABCD 6.0 data release comprises baseline to year-6 data. Lifetime and annual substance use prevalence rates, sex differences, and polysubstance use are described and analyzed. Results:Past-year substance use prevalence increased with age; 38% report lifetime use by age 16. Alcohol, cannabis, and nicotine were the most reported substances. There were non-significant differences observed between unweighted trends and census-weighted trends. More boys reported substance use prior to age 12, then from age 13 onward, more girls reported use. Polysubstance use analyses detail the occurrence of the most shared substance use patterns and divergent reports across the sexes. Conclusions:Descriptively, these prevalence rates mirror other national surveys showing increases in reported use across early adolescence, with alcohol, cannabis, and nicotine being the most used substances. Unique sex differences and polysubstance use prevalence rates are contextualized alongside prior national reports of these behaviors in the U.S. Understanding the latest prevalences, specifically in a well-phenotyped cohort, helps to guide knowledge for continued analysis of antecedents and sequelae of substance use on health.

Adolescents experience extensive neurocognitive development, with cannabis use potentially impacting developmental trajectories. Here, we comprehensively assess the influence of adolescent cannabis use onset on neurocognitive trajectories and consider how recent delta-9-tetrahydrocannabinol (THC) and cannabidiol (CBD) may influence neurocognition. We use the large, diverse longitudinal Adolescent Brain Cognitive Development (ABCD) Study dataset, combining self-reported substance use with objective toxicological tests (hair, urine, breath, oral fluid). Longitudinal mixed methods of the full cohort (n=11,036, ages 9-17; 47% Female/53% Male) investigate time-varying cannabis onset on neurocognitive performance. Primary model covariates include sociodemographics, family history of substance use disorder, prenatal substance exposure, early psychopathology, other substance use, and nesting for participant ID, study site, and family ID. Secondarily, in participants with repeat toxicological hair testing (n=645; 38% Female/62% Male) at ages 12-16, we consider the influence of THC v. CBD v. Controls. Primary models included false discovery rate corrections (FDR-p<.05) while secondary models were interpreted at p<.01. Cannabis group interacted with age to show altered neurocognitive trajectories across domains (immediate recall and delayed memory, processing speed, inhibitory control, visuospatial processing, language, and working memory; βs=-0.11- -0.52). Secondary models indicated hair-identified THC exposure*age predicted worse episodic memory than in Controls (β=-0.60, p=.007), with no difference between CBD exposed and Controls. Data suggest those who use cannabis show likely pre-existing better cognitive performance during late childhood, with reduced improvement or flattened trajectories over time. These neurocognitive trajectories in youth (ages 9-17) who initiate cannabis use were demonstrated after accounting for within-person change and numerous known confounds and improving accuracy in identifying cannabis use through incorporating toxicological measures. Continued monitoring of this cohort will clarify cannabinoid-cognition relationships into young adulthood, including the impact of timing of cannabis use initiation.

BACKGROUND:This study relied on previously established factor scores of environmental, education, and socioeconomic-related variables in the Adolescent Brain Cognitive Development Study (ABCD) and their associations with cognitive functioning in youth. METHOD:We used the ABCD Study (n = 9543) linked external data, cognitive task performance, and self-reported data from youth (ages 9-10) and their caregivers. We investigated the links between four previously established factor scores of the Child Opportunity Index 2.0 (COI) (Socioeconomic Attainment, Poverty, Neighborhood Enrichment, and Child Education) and cognitive functioning via the NIH Toolbox subscales. We estimated 36 models that examined all possible relationships between the (a) four COI factors and (b) cognitive functioning indices. RESULTS:Socioeconomic Attainment and Child Education factor scores were significantly positively associated with cognitive performance across all cognitive tasks subscales and composite scores (i.e., crystallized and fluid intelligence). Poverty factor scores were significantly negatively associated with cognitive performance across all subscales and composite scores. Finally, Neighborhood Enrichment factor scores were significantly positively associated with increased Oral Reading Recognition Task scores only, and no other cognitive task. DISCUSSION:Distinct dimensions of neighborhood opportunity were differentially associated with aspects of cognition, which may have a unique impact on brain development and neural outcomes as youth age into adolescence. The present study can help to inform future public health efforts and policy on improving built and natural environmental structures that may aid in supporting childhood cognitive development.

The built physical and social environments are critical drivers of child neural and cognitive development. This study aimed to identify the factor structure and correlates of 29 environmental, education, and socioeconomic indicators of neighborhood resources as measured by the Child Opportunity Index 2.0 (COI 2.0) in a sample of youths aged 9–10 enrolled in the Adolescent Brain Cognitive Development (ABCD) Study. This study used the baseline data of the ABCD Study (n = 9767, ages 9–10). We used structural equation modeling to investigate the factor structure of neighborhood variables (e.g., indicators of neighborhood quality including access to early child education, health insurance, walkability). We externally validated these factors with measures of psychopathology, impulsivity, and behavioral activation and inhibition. Exploratory factor analyses identified four factors: Neighborhood Enrichment, Socioeconomic Attainment, Child Education, and Poverty Level. Socioeconomic Attainment and Child Education were associated with overall reduced impulsivity and the behavioral activation system, whereas increased Poverty Level was associated with increased externalizing symptoms, an increased behavioral activation system, and increased aspects of impulsivity. Distinct dimensions of neighborhood opportunity were differentially associated with aspects of psychopathology, impulsivity, and behavioral approach, suggesting that neighborhood opportunity may have a unique impact on neurodevelopment and cognition. This study can help to inform future public health efforts and policy about improving built and natural environmental structures that may aid in supporting emotional development and downstream behaviors.

Study Objectives: Early exposure to mature content is linked to high-risk behaviors. This study aims to prospectively investigate how sleep and sensation-seeking behaviors influence the consumption of mature video games and R-rated movies in early adolescents. A secondary analysis examines the bidirectional relationships between sleep patterns and mature screen usage. Methods: Data were obtained from a subsample of 3687 early adolescents (49.2% female; mean age: 11.96 years) participating in the Adolescent Brain and Cognitive Development study. At year 2 follow-up, participants wore Fitbit wearables for up to 21 nights to assess objective sleep measures and completed a scale about sensation-seeking traits. At year 3 follow-up, they answered questions about mature screen usage. Results: Of the sample, 41.8% of the sample reported playing mature-rated video games and 49% reported watching R-rated movies. Sensation-seeking traits were associated with R-rated movie watching 1 year later. Shorter sleep duration, later bedtime, more bedtime variability, and more social jetlag (discrepancy between the mid-sleep on weekdays and weekends) were associated with mature-rated video gaming and R-rated movie watching 1 year later. Sleep duration variability was associated with mature-rated video gaming. There was also an interaction effect: those with higher sensation-seeking scores and shorter sleep duration reported more frequent R-rated movie usage than those with longer sleep duration. Secondary analyses showed bidirectional associations between later bedtimes, more variability in bedtimes, and more social jetlag with mature screen usage. Conclusions: Early adolescents with sensation-seeking traits and poorer sleep health were more likely to engage in mature screen usage.

Objectives/Goals: The neighborhoods children grow up in are critical drivers of social, emotional, and cognitive development. This study utilized factor scores of environment, education, and socioeconomic variables in the Adolescent Brain Cognitive Development Study (ABCD) and its association with cognitive functioning in youth. Methods/Study Population: This study used ABCD (n = 9,543) linked external data, cognitive performance, and self-reported data from youth (ages 9–10) and their caregivers. We utilized four factor scores of the Child Opportunity Index 2.0 (COI), including socioeconomic attainment, poverty, neighborhood enrichment, and child education. Furthermore, this study investigated the association between the COI factors and youth cognitive functioning via the NIH Toolbox. Covariates included age, sex, county level crime rates, perceptions of neighborhood threat, parent education, and family income; site and family relationship were held as random effects. Results/Anticipated Results: Increased Socioeconomic Attainment and Child Education factor scores were distinctly associated with increased cognitive performance across all subscales and composite scores that include aspects of overall cognitive ability, executive functioning, and learning and memory. Increased poverty factor scores were significantly associated with decreased cognitive performance across all substances and composite scores. Finally, increased neighborhood enrichment factor scores were significantly associated with increased oral reading recognition task scores only and no other cognitive task. Discussion/Significance of Impact: Findings suggest distinct dimensions of neighborhood opportunity associated with aspects of cognition. The present study can help to inform public health efforts and policy on improving modifiable built and natural environmental structures that may aid in supporting cognitive development.

Objective:To determine correspondence between self-reported substance use and biochemical verification through hair samples and to estimate U.S. prevalence of adolescent substance use. Methods:Data came from the nationwide Adolescent Brain Cognitive Development Study (n=11,868; age 9-10 at Baseline, age 15-16 at Wave 6). Past-3-month substance use was measured annually from 2016 to 2024. Hair samples objectively detected moderate+ substance use in a subsample of participants (nsamples=11,865; n=6,133 unique participants). Multi-step weighting methods estimated national prevalence trends of cannabis, alcohol, and nicotine use over time, adjusting for discrepancies in sample representation due to recruitment demography, missed visits, and hair samples testing. Results:Correspondence between self-report and toxicological data improved with age (ages 11-12=<1%; ages 15-16=45%). Weighted estimates of biochemically verified substance use indicated 7.1% of 15-16 year olds engaged in moderate-to-heavy cannabis use, 0.3% heavily used alcohol, and 4.7% heavily used nicotine. Conclusions:Youth reported substance use patterns demonstrated improved biochemical verification with age. Biochemical verification reflects substantive cannabis and nicotine use by ages 15-16, supporting combining toxicological and self-report data to improve identification of substance use in youth.

Nicotine use is increasing in prevalence among adolescents and emerging adults in the United States. While young adulthood nicotine use has been linked to alterations in white matter tissue brain structure, little is known about late childhood nicotine initiation and its associations with white matter microstructural development. In this study, nicotine initiators (ages 9-16, n=556) were compared on white matter regions-of-interest (ROIs) to sociodemographically matched peers (n=556) using a subsample of the Adolescent Brain Cognitive Development (ABCD) Study (baseline to year-4 follow-up). Fractional anisotropy and mean diffusivity metrics were examined across 11 diffusion tensor imaging ROIs. Linear mixed-effects models examined nicotine initiation while controlling for prenatal nicotine exposure, parental history of problematic alcohol/drug use, and other substance use initiation. Findings indicated nicotine initiation-by-age effects for widespread cortical and subcortical fractional anisotropy ROIs, which maintained significance after multiple comparison correction and conducting sensitivity analyses covarying for pubertal staging. These ROIs did not correlate with any dose-dependent (e.g., lifetime use days) measurements among the nicotine initiators. Additionally, no significant findings were observed for mean diffusivity, or exploratory interactions with sex. Overall, neurodevelopmental effects of nicotine use on white matter integrity may appear early and are associated with trajectories of white matter development, yet continued investigations of nicotine initiation and escalation across the lifespan and its relationships with structural neuroimaging outcomes are needed.

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 (PH0, PH1, PH2) on reward processing in preadolescents. This study analyzed data from 10,235 participants (ages 9-14) in the Adolescent Brain Cognitive Development StudySM (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 PHA1 had greater nucleus accumbens activation during reward anticipation than those with no history (PHA0), but no significant differences were found between PHA2 and PHA1 or PHA2 and PHA0. 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.

Background Chronic cannabis use (CU) can result in subtle deficits in cognitive performance that may be linked with alterations in underlying neural functioning. However, these network alterations are not well-characterized following monitored abstinence. Here, we evaluate differences in functional brain network activity associated with CU patterns in adolescents/young adults. Methods Functional connectomes were generated using resting-state fMRI data collected from 83 healthy young adults (44 male) following two weeks of monitored cannabis abstinence. Network topology metrics were calculated for each of the 7 Yeo 2011 intrinsic connectivity networks (ICNs) and on the whole-brain level. Multiple linear regressions were used to evaluate whether CU (regular-users, n = 35 vs. non-using controls, n = 40) was associated with network topology metric differences after controlling for past-year alcohol use, age, sex, and cotinine levels; moderation by sex was also investigated. Regressions were run within CU group to test for associations between cannabis use patterns (lifetime CU, age of CU initiation, and past-year CU) and network topology. Finally, a network-based statistic (NBS) approach was used to search for connectome subcomponents associated with CU group, CU*sex, and patterns of CU. Results No significant association between CU groups and ICN topology was observed. Sex moderation was observed; within male cannabis users, higher past-year CU was associated with significantly higher frontoparietal and ventral attention network (VAN) efficiency. Within female cannabis users, higher past-year CU was associated with significantly lower Default Mode Network assortativity. Within individuals who initiated CU before the age of 17, males had lower assortativity in the VAN and Somatomotor network. NBS analyses indicated that connectivity strength within a primarily right-lateralized subnetwork distributed throughout the connectome was significantly and reliably associated with past-year CU). Conclusion The present findings suggest that subtle differences in resting-state network topology associated with CU may persist after an extended period of abstinence in young adults, particularly males, especially those with heavier past-year use and those who initiated CU earlier in life. While further replication is required in larger samples, these findings suggest potential neuroimaging correlates underlying long-term changes in brain network topology associated with CU.

Objective: Cannabis is widely used, including in early adolescence, with prevalence rates varying by measurement method (e.g., toxicology vs. self-report). Critical neurocognitive development occurs throughout adolescence. Given conflicting prior brain-behavior results in cannabis research, improved measurement of cannabis use in younger adolescents is needed. Methods: Data from the Adolescent Brain Cognitive Development (ABCD) Study Year 4 follow-up (participant age: 13-14 years-old) included hair samples assessed by LC-MS/MS and GC-MS/MS, quantifying THCCOOH (THC metabolite), THC, and cannabidiol concentrations, and the NIH Toolbox Cognitive Battery. Youth whose hair was positive for cannabinoids or reported past-year cannabis use were included in a Cannabis Use (CU) group (n = 123) and matched with non-using Controls on sociodemographics (n = 123). Standard and nested ANCOVAs assessed group status predicting cognitive performance, controlling for family relationships. Followup correlations assessed cannabinoid hair concentration, self-reported cannabis use, and neurocognition. Results: CU scored lower on Picture Memory (p = .03) than Controls. Within the CU group, THCCOOH negatively correlated with Picture Vocabulary (r = -0.20, p = .03) and Flanker Inhibitory Control and Attention (r = -0.19, p = .04), and past-year cannabis use was negatively associated with List Sorting Working Memory (r = -0.33, p = .0002) and Picture Sequence Memory (r = -0.19, p = .04) performances. Conclusions: Youth who had used cannabis showed lower scores on an episodic memory task, and more cannabis use was linked to poorer performances on verbal, inhibitory, working memory, and episodic memory tasks. Combining hair toxicology with self-report revealed more brain-behavior relationships than self-report data alone. These youth will be followed to determine long-term substance use and neurocognition trajectories.