Cortical profiles of numerous psychiatric disorders and normal development share a common pattern.

The neurobiological bases of the association between development and psychopathology remain poorly understood. Here, we identify a shared spatial pattern of cortical thickness (CT) in normative development and several psychiatric and neurological disorders. Principal component analysis (PCA) was applied to CT of 68 regions in the Desikan-Killiany atlas derived from three large-scale datasets comprising a total of 41,075 neurotypical participants. PCA produced a spatially broad first principal component (PC1) that was reproducible across datasets. Then PC1 derived from healthy adult participants was compared to the pattern of CT differences associated with psychiatric and neurological disorders comprising a total of 14,886 cases and 20,962 controls from seven ENIGMA disease-related working groups, normative maturation and aging comprising a total of 17,697 scans from the ABCD Study® and the IMAGEN developmental study, and 17,075 participants from the ENIGMA Lifespan working group, as well as gene expression maps from the Allen Human Brain Atlas. Results revealed substantial spatial correspondences between PC1 and widespread lower CT observed in numerous psychiatric disorders. Moreover, the PC1 pattern was also correlated with the spatial pattern of normative maturation and aging. The transcriptional analysis identified a set of genes including KCNA2, KCNS1 and KCNS2 with expression patterns closely related to the spatial pattern of PC1. The gene category enrichment analysis indicated that the transcriptional correlations of PC1 were enriched to multiple gene ontology categories and were specifically over-represented starting at late childhood, coinciding with the onset of significant cortical maturation and emergence of psychopathology during the prepubertal-to-pubertal transition. Collectively, the present study reports a reproducible latent pattern of CT that captures interregional profiles of cortical changes in both normative brain maturation and a spectrum of psychiatric disorders. The pubertal timing of the expression of PC1-related genes implicates disrupted neurodevelopment in the pathogenesis of the spectrum of psychiatric diseases emerging during adolescence.

Machine learning approaches linking brain function to behavior in the ABCD STOP task.

The stop-signal task (SST) is one of the most common fMRI tasks of response inhibition, and its performance measure, the stop-signal reaction-time (SSRT), is broadly used as a measure of cognitive control processes. The neurobiology underlying individual or clinical differences in response inhibition remain unclear, consistent with the general pattern of quite modest brain-behavior associations that have been recently reported in well-powered large-sample studies. Here, we investigated the potential of multivariate, machine learning (ML) methods to improve the estimation of individual differences in SSRT with multimodal structural and functional region of interest-level neuroimaging data from 9- to 11-year-olds children in the ABCD Study. Six ML algorithms were assessed across modalities and fMRI tasks. We verified that SST activation performed best in predicting SSRT among multiple modalities including morphological MRI (cortical surface area/thickness), diffusion tensor imaging, and fMRI task activations, and then showed that SST activation explained 12% of the variance in SSRT using cross-validation and out-of-sample lockbox data sets (n = 7298). Brain regions that were more active during the task and that showed more interindividual variation in activation were better at capturing individual differences in performance on the task, but this was only true for activations when successfully inhibiting. Cortical regions outperformed subcortical areas in explaining individual differences but the two hemispheres performed equally well. These results demonstrate that the detection of reproducible links between brain function and performance can be improved with multivariate approaches and give insight into a number of brain systems contributing to individual differences in this fundamental cognitive control process.

Cognitive and brain development is independently influenced by socioeconomic status and polygenic scores for educational attainment.

Genetic factors and socioeconomic status (SES) inequalities play a large role in educational attainment, and both have been associated with variations in brain structure and cognition. However, genetics and SES are correlated, and no prior study has assessed their neural associations independently. Here we used a polygenic score for educational attainment (EduYears-PGS), as well as SES, in a longitudinal study of 551 adolescents to tease apart genetic and environmental associations with brain development and cognition. Subjects received a structural MRI scan at ages 14 and 19. At both time points, they performed three working memory (WM) tasks. SES and EduYears-PGS were correlated (r = 0.27) and had both common and independent associations with brain structure and cognition. Specifically, lower SES was related to less total cortical surface area and lower WM. EduYears-PGS was also related to total cortical surface area, but in addition had a regional association with surface area in the right parietal lobe, a region related to nonverbal cognitive functions, including mathematics, spatial cognition, and WM. SES, but not EduYears-PGS, was related to a change in total cortical surface area from age 14 to 19. This study demonstrates a regional association of EduYears-PGS and the independent prediction of SES with cognitive function and brain development. It suggests that the SES inequalities, in particular parental education, are related to global aspects of cortical development, and exert a persistent influence on brain development during adolescence.

Individual Differences in Cognitive Performance Are Better Predicted by Global Rather Than Localized BOLD Activity Patterns Across the Cortex.

Despite its central role in revealing the neurobiological mechanisms of behavior, neuroimaging research faces the challenge of producing reliable biomarkers for cognitive processes and clinical outcomes. Statistically significant brain regions, identified by mass univariate statistical models commonly used in neuroimaging studies, explain minimal phenotypic variation, limiting the translational utility of neuroimaging phenotypes. This is potentially due to the observation that behavioral traits are influenced by variations in neuroimaging phenotypes that are globally distributed across the cortex and are therefore not captured by thresholded, statistical parametric maps commonly reported in neuroimaging studies. Here, we developed a novel multivariate prediction method, the Bayesian polyvertex score, that turns a unthresholded statistical parametric map into a summary score that aggregates the many but small effects across the cortex for behavioral prediction. By explicitly assuming a globally distributed effect size pattern and operating on the mass univariate summary statistics, it was able to achieve higher out-of-sample variance explained than mass univariate and popular multivariate methods while still preserving the interpretability of a generative model. Our findings suggest that similar to the polygenicity observed in the field of genetics, the neural basis of complex behaviors may rest in the global patterning of effect size variation of neuroimaging phenotypes, rather than in localized, candidate brain regions and networks.

Functional Connectivity Predicts Individual Development of Inhibitory Control during Adolescence.

Derailment of inhibitory control (IC) underlies numerous psychiatric and behavioral disorders, many of which emerge during adolescence. Identifying reliable predictive biomarkers that place the adolescents at elevated risk for future IC deficits can help guide early interventions, yet the scarcity of longitudinal research has hindered the progress. Here, using a large-scale longitudinal dataset in which the same subjects performed a stop signal task during functional magnetic resonance imaging at ages 14 and 19, we tracked their IC development individually and tried to find the brain features predicting their development by constructing prediction models using 14-year-olds' functional connections within a network or between a pair of networks. The participants had distinct between-subject trajectories in their IC development. Of the candidate connections used for prediction, ventral attention-subcortical network interconnections could predict the individual development of IC and formed a prediction model that generalized to previously unseen individuals. Furthermore, we found that connectivity between these two networks was related to substance abuse problems, an IC-deficit related problematic behavior, within 5 years. Our study reveals individual differences in IC development from mid- to late-adolescence and highlights the importance of ventral attention-subcortical network interconnections in predicting future IC development and substance abuse in adolescents.

Peer victimization and its impact on adolescent brain development and psychopathology.

Chronic peer victimization has long-term impacts on mental health; however, the biological mediators of this adverse relationship are unknown. We sought to determine whether adolescent brain development is involved in mediating the effect of peer victimization on psychopathology. We included participants (n = 682) from the longitudinal IMAGEN study with both peer victimization and neuroimaging data. Latent profile analysis identified groups of adolescents with different experiential patterns of victimization. We then associated the victimization trajectories and brain volume changes with depression, generalized anxiety, and hyperactivity symptoms at age 19. Repeated measures ANOVA revealed time-by-victimization interactions on left putamen volume (F = 4.38, p = 0.037). Changes in left putamen volume were negatively associated with generalized anxiety (t = -2.32, p = 0.020). Notably, peer victimization was indirectly associated with generalized anxiety via decreases in putamen volume (95% CI = 0.004-0.109). This was also true for the left caudate (95% CI = 0.002-0.099). These data suggest that the experience of chronic peer victimization during adolescence might induce psychopathology-relevant deviations from normative brain development. Early peer victimization interventions could prevent such pathological changes.

Early adolescent gender diversity and mental health in the Adolescent Brain Cognitive Development study.

BACKGROUND: There are known associations between mental health symptoms and transgender identity among adults. Whether this relationship extends to early adolescents and to gender domains other than identity is unclear. This study measured dimensions of gender in a large, diverse, sample of youth, and examined associations between diverse gender experiences and mental health. METHODS: The ABCD study is an ongoing, longitudinal, US cohort study. Baseline data (release 2.0) include 11,873 youth age 9/10 (48% female); and the 4,951 1-year follow-up visits (age 10/11; 48% female) completed prior to data release. A novel gender survey at the 1-year visit assessed felt-gender, gender noncontentedness, and gender nonconformity using a 5-point scale. Mental health measures included youth- and parent-reports. RESULTS: Roughly half a percent of 9/10-year-olds (n = 58) responded 'yes' or 'maybe' when asked, 'Are you transgender' at baseline. Recurrent thoughts of death were more prevalent among these youth compared to the rest of the cohort (19.6% vs. 6.4%, χ2  = 16.0, p < .001). At the 1-year visit, when asked about the three dimensions of gender on a 5-point scale, 33.2% (n = 1,605) provided responses that were not exclusively and totally aligned with one gender. Significant relationships were observed between mental health symptoms and gender diversity for all dimensions assessed. CONCLUSIONS: Similar to adult studies, early adolescents identifying as transgender reported increased mental health symptoms. Results also point to considerable diversity in other dimensions of gender (felt-gender, gender noncontentedness, gender nonconformity) among 10/11-year-olds, and find this diversity to be related to critical mental health symptoms. These findings add to our limited understanding of the relationship between dimensions of gender and wellness for youth.

Investigation of Psychiatric and Neuropsychological Correlates of Default Mode Network and Dorsal Attention Network Anticorrelation in Children.

The default mode network (DMN) and dorsal attention network (DAN) demonstrate an intrinsic "anticorrelation" in healthy adults, which is thought to represent the functional segregation between internally and externally directed thought. Reduced segregation of these networks has been proposed as a mechanism for cognitive deficits that occurs in many psychiatric disorders, but this association has rarely been tested in pre-adolescent children. The current analysis used data from the Adolescent Brain Cognitive Development study to examine the relationship between the strength of DMN/DAN anticorrelation and psychiatric symptoms in the largest sample to date of 9- to 10-year-old children (N = 6543). The relationship of DMN/DAN anticorrelation to a battery of neuropsychological tests was also assessed. DMN/DAN anticorrelation was robustly linked to attention problems, as well as age, sex, and socioeconomic factors. Other psychiatric correlates identified in prior reports were not robustly linked to DMN/DAN anticorrelation after controlling for demographic covariates. Among neuropsychological measures, the clearest correlates of DMN/DAN anticorrelation were the Card Sort task of executive function and cognitive flexibility and the NIH Toolbox Total Cognitive Score, although these did not survive correction for socioeconomic factors. These findings indicate a complicated relationship between DMN/DAN anticorrelation and demographics, neuropsychological function, and psychiatric problems.

Grey Matter Volume Differences Associated with Extremely Low Levels of Cannabis Use in Adolescence.

Rates of cannabis use among adolescents are high, and are increasing concurrent with changes in the legal status of marijuana and societal attitudes regarding its use. Recreational cannabis use is understudied, especially in the adolescent period when neural maturation may make users particularly vulnerable to the effects of Δ-9-tetrahydrocannabinol (THC) on brain structure. In the current study, we used voxel-based morphometry to compare gray matter volume (GMV) in forty-six 14-year-old human adolescents (males and females) with just one or two instances of cannabis use and carefully matched THC-naive controls. We identified extensive regions in the bilateral medial temporal lobes as well as the bilateral posterior cingulate, lingual gyri, and cerebellum that showed greater GMV in the cannabis users. Analysis of longitudinal data confirmed that GMV differences were unlikely to precede cannabis use. GMV in the temporal regions was associated with contemporaneous performance on the Perceptual Reasoning Index and with future generalized anxiety symptoms in the cannabis users. The distribution of GMV effects mapped onto biomarkers of the endogenous cannabinoid system providing insight into possible mechanisms for these effects.SIGNIFICANCE STATEMENT Almost 35% of American 10th graders have reported using cannabis and existing research suggests that initiation of cannabis use in adolescence is associated with long-term neurocognitive effects. We understand very little about the earliest effects of cannabis use, however, because most research is conducted in adults with a heavy pattern of lifetime use. This study presents evidence suggesting structural brain and cognitive effects of just one or two instances of cannabis use in adolescence. Converging evidence suggests a role for the endocannabinoid system in these effects. This research is particularly timely as the legal status of cannabis is changing in many jurisdictions and the perceived risk by youth associated with smoking cannabis has declined in recent years.

Ventromedial Prefrontal Volume in Adolescence Predicts Hyperactive/Inattentive Symptoms in Adulthood.

Youths with attention-deficit/hyperactivity disorder symptomatology often exhibit residual inattention and/or hyperactivity in adulthood; however, this is not true for all individuals. We recently reported that dimensional, multi-informant ratings of hyperactive/inattentive symptoms are associated with ventromedial prefrontal cortex (vmPFC) structure. Herein, we investigate the degree to which vmPFC structure during adolescence predicts hyperactive/inattentive symptomatology at 5-year follow-up. Structural equation modeling was used to test the extent to which adolescent vmPFC volume predicts hyperactive/inattentive symptomatology 5 years later in early adulthood. 1104 participants (M = 14.52 years, standard deviation = 0.42; 583 females) possessed hyperactive/inattentive symptom data at 5-year follow-up, as well as quality controlled neuroimaging data and complete psychometric data at baseline. Self-reports of hyperactive/inattentive symptomatology were obtained during adolescence and at 5-year follow-up using the Strengths and Difficulties Questionnaire (SDQ). At baseline and 5-year follow-up, a hyperactive/inattentive latent variable was derived from items on the SDQ. Baseline vmPFC volume predicted adult hyperactive/inattentive symptomatology (standardized coefficient = -0.274, P < 0.001) while controlling for baseline hyperactive/inattentive symptomatology. These results are the first to reveal relations between adolescent brain structure and adult hyperactive/inattentive symptomatology, and suggest that early structural development of the vmPFC may be consequential for the subsequent expression of hyperactive/inattentive symptoms.

The initiation of cannabis use in adolescence is predicted by sex-specific psychosocial and neurobiological features.

Cannabis use initiated during adolescence might precipitate negative consequences in adulthood. Thus, predicting adolescent cannabis use prior to any exposure will inform the aetiology of substance abuse by disentangling predictors from consequences of use. In this prediction study, data were drawn from the IMAGEN sample, a longitudinal study of adolescence. All selected participants (n = 1,581) were cannabis-naïve at age 14. Those reporting any cannabis use (out of six ordinal use levels) by age 16 were included in the outcome group (N = 365, males n = 207). Cannabis-naïve participants at age 14 and 16 were included in the comparison group (N = 1,216, males n = 538). Psychosocial, brain and genetic features were measured at age 14 prior to any exposure. Cross-validated regularized logistic regressions for each use level by sex were used to perform feature selection and obtain prediction error statistics on independent observations. Predictors were probed for sex- and drug-specificity using post-hoc logistic regressions. Models reliably predicted use as indicated by satisfactory prediction error statistics, and contained psychosocial features common to both sexes. However, males and females exhibited distinct brain predictors that failed to predict use in the opposite sex or predict binge drinking in independent samples of same-sex participants. Collapsed across sex, genetic variation on catecholamine and opioid receptors marginally predicted use. Using machine learning techniques applied to a large multimodal dataset, we identified a risk profile containing psychosocial and sex-specific brain prognostic markers, which were likely to precede and influence cannabis initiation.

Multimodal Neuroimaging Differences in Nicotine Abstinent Smokers Versus Satiated Smokers.

INTRODUCTION: Research on cigarette smokers suggests cognitive and behavioral impairments. However, much remains unclear how the functional neurobiology of smokers is influenced by nicotine state. Therefore, we sought to determine which state, be it acute nicotine abstinence or satiety, would yield the most robust differences compared with nonsmokers when assessing neurobiological markers of nicotine dependence. METHODS: Smokers (N = 15) and sociodemographically matched nonsmokers (N = 15) were scanned twice using a repeated-measures design. Smokers were scanned after a 24-hour nicotine abstinence and immediately after smoking their usual brand cigarette. The neuroimaging battery included a stop-signal task of response inhibition and pseudocontinuous arterial spin labeling to measure cerebral blood flow (CBF). Whole-brain voxel-wise analyses of covariance were carried out on stop success and stop fail Stop-Signal Task contrasts and CBF maps to assess differences among nonsmokers, abstinent smokers, and satiated smokers. Cluster correction was performed using AFNI's 3dClustSim to achieve a significance of p < .05. RESULTS: Smokers exhibited higher brain activation in bilateral inferior frontal gyrus, a brain region known to be involved in inhibitory control, during successful response inhibitions relative to nonsmokers. This effect was significantly higher during nicotine abstinence relative to satiety. Smokers also exhibited lower CBF in the bilateral inferior frontal gyrus than nonsmokers. These hypoperfusions were not different between abstinence and satiety. CONCLUSIONS: These findings converge on alterations in smokers in prefrontal circuits known to be critical for inhibitory control. These effects are present, even when smokers are satiated, but the neural activity required to achieve performance equal to controls is increased when smokers are in acute abstinence. IMPLICATIONS: Our multimodal neuroimaging study gives neurobiological insights into the cognitive demands of maintaining abstinence and suggests targets for assessing the efficacy of therapeutic interventions.

Individual differences in stop-related activity are inflated by the adaptive algorithm in the stop signal task.

Research using the Stop Signal Task employing an adaptive algorithm to accommodate individual differences often report inferior performance on the task in individuals with ADHD, OCD, and substance use disorders compared to non-clinical controls. Furthermore, individuals with deficits in inhibitory control tend to show reduced neural activity in key inhibitory regions during successful stopping. However, the adaptive algorithm systematically introduces performance-related differences in objective task difficulty that may influence the estimation of individual differences in stop-related neural activity. This report examines the effect that these algorithm-related differences have on the measurement of neural activity during the stop signal task. We compared two groups of subjects (n = 210) who differed in inhibitory ability using both a standard fMRI analysis and an analysis that resampled trials to remove the objective task difficulty confound. The results show that objective task difficulty influences the magnitude of between-group differences and that controlling for difficulty attenuates stop-related activity differences between superior and poor inhibitors. Specifically, group differences in the right inferior frontal gyrus, right middle occipital gyrus, and left inferior frontal gyrus are diminished when differences in objective task difficulty are controlled for. Also, when objective task difficulty effects are exaggerated, group differences in stop related activity emerge in other regions of the stopping network. The implications of these effects for how we interpret individual differences in activity levels are discussed.

Relationship between cerebrospinal fluid flow, ventricles morphology, and DTI properties in internal capsules: differences between Alzheimer's disease and normal-pressure hydrocephalus.

BACKGROUND: Normal-pressure hydrocephalus (NPH) and Alzheimer's disease (AD) have some similar clinical features and both involve white matter and cerebrospinal fluid (CSF) disorders. PURPOSE: To compare putative relationships between ventricular morphology, CSF flow, and white matter diffusion in AD and NPH. MATERIAL AND METHODS: Thirty patients (18 with AD and 12 with suspected NPH) were included in the study. All patients underwent a 3-Tesla MRI scan, which included phase-contrast MRI of the aqueduct (to assess the aqueductal CSF stroke volume) and a DTI session (to calculate the fractional anisotropy [FA] and apparent diffusion coefficient [ADC]) in the internal capsules). RESULTS: FA was correlated with ventricular volume in the suspected NPH population (P < 0.001; rs = 0.88), whereas the ADC was highly correlated with the aqueductal CSF stroke volume in AD (P < 0.001; rs = 0.79). CONCLUSION: Although AD and NPH both involve CSF disorders, the two diseases do not have the same impact on the internal capsules. The magnitude of the ADC is related to the aqueductal CSF stroke volume in AD, whereas FA is related to ventricular volume in NPH.

Prospective associations between Sleep, Sensation-Seeking and Mature Screen Usage in Early Adolescents: Findings from the Adolescent Brain Cognitive Development (ABCD) Study.

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 3,687 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 one 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 one 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. CONCLUSION: Early adolescents with sensation-seeking traits and poorer sleep health were more likely to engage in mature screen usage.

Variation in moment-to-moment brain state engagement changes across development and contributes to individual differences in executive function.

Neural variability, or variation in brain signals, facilitates dynamic brain responses to ongoing demands. This flexibility is important during development from childhood to young adulthood, a period characterized by rapid changes in experience. However, little is known about how variability in the engagement of recurring brain states changes during development. Such investigations would require the continuous assessment of multiple brain states concurrently. Here, we leverage a new computational framework to study state engagement variability (SEV) during development. A consistent pattern of SEV changing with age was identified across cross-sectional and longitudinal datasets (N>3000). SEV developmental trajectories stabilize around mid-adolescence, with timing varying by sex and brain state. SEV successfully predicts executive function (EF) in youths from an independent dataset. Worse EF is further linked to alterations in SEV development. These converging findings suggest SEV changes over development, allowing individuals to flexibly recruit various brain states to meet evolving needs.

Measurement of choroid plexus perfusion using dynamic susceptibility MR imaging: capillary permeability and age-related changes.

INTRODUCTION: The cerebrospinal fluid (CSF) plays a major role in the physiology of the central nervous system. The continuous turnover of CSF is mainly attributed to the highly vascularized choroid plexus (CP) located in the cerebral ventricles which represent a complex interface between blood and CSF. We propose a method for evaluating CP functionality in vivo using perfusion MR imaging and establish the age-related changes of associated parameters. METHODS: Fifteen patients with small intracranial tumors were retrospectively studied. MR Imaging was performed on a 3T MR Scanner. Gradient-echo echo planar images were acquired after bolus injection of gadolinium-based contrast agent (CA). The software developed used the combined T1- and T2-effects. The decomposition of the relaxivity signals enables the calculation of the CP capillary permeability (K2). The relative cerebral blood volume (rCBV), mean transit time (MTT), and signal slope decrease (SSD) were also calculated. RESULTS: The mean permeability K2 of the extracted CP was 0.033+/-0.18 s(-1). K2 and SSD significantly decreased with subject's age whereas MTT significantly increased with subject's age. No significant correlation was found for age-related changes in rCBV and rCBF. CONCLUSION: The decrease in CP permeability is in line with the age-related changes in CSF secretion observed in animals. The MTT increase indicates significant structural changes corroborated by microscopy studies in animals or humans. Overall, DSC MR-perfusion enables an in vivo evaluation of the hemodynamic state of CP. Clinical applications such as neurodegenerative diseases could be considered thanks to specific functional studies of CP.

Gender diversity associated with patterns of brain activation seen in populations that experience childhood stress.

Introduction: Stressful childhood experiences are associated with unique brain activity patterns during emotional processing. Specifically, pediatric stress is linked to activation in the insulae, superior temporal and parahippocampal gyri, and the amygdalae, as well as differential activation in the dorsal anterior cingulate cortex when viewing emotional faces. Gender diversity is broadly associated with higher victimization and mental health disparities in children aged 9/10, but whether it is associated with stress-like alterations in brain function (BOLD signal during task-based fMRI) remains unknown. We investigate the functional brain correlates of this relationship to determine if gender-diverse youth show patterns of functional activity during an emotional task consistent with those of other populations that experience heightened stress. Methods: We used data from the Adolescent Brain Cognitive Development (ABCD)® study. First, we identified a subset of 4,385 participants aged 10/11 years with gender diversity data and quality-controlled fMRI data from the EN-Back (emotional n-back) task. The EN-Back is a working memory task that presents emotion faces as well as pictures of places as control stimuli. We regressed BOLD signal associated with emotion faces (faces minus places contrast) on gender diversity. Next, we tested if parental acceptance or youth perceptions of their school environment moderated the relationship between gender diversity and activation in the insulae or fusiform gyrus. Finally, we used structural equation modeling to investigate gender diversity's association with parental acceptance, perceptions of school environments, internalizing and externalizing problems. Results: Gender diversity was associated with widespread increases in BOLD signal during the faces condition of the EN-Back task. Youth's report of parental acceptance and school environment did not moderate the relationship between gender diversity and BOLD signal in the insula or fusiform gyrus. Gender diversity was related to greater parent and school-related stress, which was associated with elevated mental health problems. Conclusion: Patterns of functional activity were consistent with those reported in prior literature on childhood stress. Gender diversity was associated with increased emotional and behavioral problems, as well as parent and school-related stress. These findings indicate the importance of the home and school environments for supporting the wellbeing of gender diverse youth.

Associations Between Gender Nonconformity, School Environments, Family Conflict, and Emotional and Behavioral Health Among Children Ages 10-11.

PURPOSE: In youth, gender nonconformity (GNC; gender expression that differs from stereotypes based on assigned sex at birth) is associated with a higher likelihood of peer and caregiver victimization and rejection. However, few studies have examined the relationship between GNC, overall family conflict, perceptions of school environment, and emotional and behavioral health problems among children ages 10-11. METHODS: The Adolescent Brain Cognitive Development Study data release 3.0 was used (n = 11,068; 47.9% female). A path analysis was used to examine whether school environment and family conflict, mediated the relationship between GNC and behavioral and emotional health outcomes. RESULTS: We found significant mediation of the relationship between GNC and behavioral and emotional health by school environment a2b2 = .20, 95% CI [0.13, 0.27] and family conflict a1b1 = 0.34, 95% CI [0.25, 0.42]. DISCUSSION: Our results suggest that youth who present as gender nonconforming experience elevated family conflict, poorer perceptions of their school environment and elevated behavioral and emotional health problems. Further, the relationship between GNC and elevated emotional and behavioral health problems was mediated by perceptions of school environment and family conflict. Clinical and policy suggestions to improve environments and outcomes for youth who present as gender nonconforming are discussed.

Association between vmPFC gray matter volume and smoking initiation in adolescents.

Smoking of cigarettes among young adolescents is a pressing public health issue. However, the neural mechanisms underlying smoking initiation and sustenance during adolescence, especially the potential causal interactions between altered brain development and smoking behaviour, remain elusive. Here, using large longitudinal adolescence imaging genetic cohorts, we identify associations between left ventromedial prefrontal cortex (vmPFC) gray matter volume (GMV) and subsequent self-reported smoking initiation, and between right vmPFC GMV and the maintenance of smoking behaviour. Rule-breaking behaviour mediates the association between smaller left vmPFC GMV and smoking behaviour based on longitudinal cross-lagged analysis and Mendelian randomisation. In contrast, smoking behaviour associated longitudinal covariation of right vmPFC GMV and sensation seeking (especially hedonic experience) highlights a potential reward-based mechanism for sustaining addictive behaviour. Taken together, our findings reveal vmPFC GMV as a possible biomarker for the early stages of nicotine addiction, with implications for its prevention and treatment.