Reproducible brain-wide association studies require thousands of individuals.

Magnetic resonance imaging (MRI) has transformed our understanding of the human brain through well-replicated mapping of abilities to specific structures (for example, lesion studies) and functions1-3 (for example, task functional MRI (fMRI)). Mental health research and care have yet to realize similar advances from MRI. A primary challenge has been replicating associations between inter-individual differences in brain structure or function and complex cognitive or mental health phenotypes (brain-wide association studies (BWAS)). Such BWAS have typically relied on sample sizes appropriate for classical brain mapping4 (the median neuroimaging study sample size is about 25), but potentially too small for capturing reproducible brain-behavioural phenotype associations5,6. Here we used three of the largest neuroimaging datasets currently available-with a total sample size of around 50,000 individuals-to quantify BWAS effect sizes and reproducibility as a function of sample size. BWAS associations were smaller than previously thought, resulting in statistically underpowered studies, inflated effect sizes and replication failures at typical sample sizes. As sample sizes grew into the thousands, replication rates began to improve and effect size inflation decreased. More robust BWAS effects were detected for functional MRI (versus structural), cognitive tests (versus mental health questionnaires) and multivariate methods (versus univariate). Smaller than expected brain-phenotype associations and variability across population subsamples can explain widespread BWAS replication failures. In contrast to non-BWAS approaches with larger effects (for example, lesions, interventions and within-person), BWAS reproducibility requires samples with thousands of individuals.

An integrative model of the maturation of cognitive control.

Brains systems undergo unique and specific dynamic changes at the cellular, circuit, and systems level that underlie the transition to adult-level cognitive control. We integrate literature from these different levels of analyses to propose a novel model of the brain basis of the development of cognitive control. The ability to consistently exert cognitive control improves into adulthood as the flexible integration of component processes, including inhibitory control, performance monitoring, and working memory, increases. Unique maturational changes in brain structure, supported by interactions between dopaminergic and GABAergic systems, contribute to enhanced network synchronization and an improved signal-to-noise ratio. In turn, these factors facilitate the specialization and strengthening of connectivity in networks supporting the transition to adult levels of cognitive control. This model provides a novel understanding of the adolescent period as an adaptive period of heightened experience-seeking necessary for the specialization of brain systems supporting cognitive control.

Future Directions in the Mental Health of Transgender Youth: Towards a Social-Affective Developmental Model of Health Disparity.

Mental health disparities in transgender and gender diverse (TGD) youth are well-documented. These disparities are often studied in the context of minority stress theory, and most of this research focuses on experiences of trauma and discrimination TGD youth experience after coming out. However, TGD youth may be targets of violence and victimization due to perceived gender nonconformity before coming out. In this Future Directions, we integrate research on attachment, developmental trauma, and effects of racism and homophobia on mental health to propose a social-affective developmental framework for TGD youth. We provide a clinical vignette to highlight limitations in current approaches to mental health assessment in TGD youth and to illustrate how using a social-affective developmental framework can improve clinical assessment and treatment approaches and deepen our understanding of mental health disparities in TGD people.

Developmental influences on symptom expression in antipsychotic-naïve first-episode psychosis.

BACKGROUND: The neurodevelopmental model of psychosis was established over 30 years ago; however, the developmental influence on psychotic symptom expression - how age affects clinical presentation in first-episode psychosis - has not been thoroughly investigated. METHODS: Using generalized additive modeling, which allows for linear and non-linear functional forms of age-related change, we leveraged symptom data from a large sample of antipsychotic-naïve individuals with first-episode psychosis (N = 340, 12-40 years, 1-12 visits), collected at the University of Pittsburgh from 1990 to 2017. We examined relationships between age and severity of perceptual and non-perceptual positive symptoms and negative symptoms. We tested for age-associated effects on change in positive or negative symptom severity following baseline assessment and explored the time-varying relationship between perceptual and non-perceptual positive symptoms across adolescent development. RESULTS: Perceptual positive symptom severity significantly decreased with increasing age (F = 7.0, p = 0.0007; q = 0.003) while non-perceptual positive symptom severity increased with age (F = 4.1, p = 0.01, q = 0.02). Anhedonia severity increased with increasing age (F = 6.7, p = 0.00035; q = 0.0003), while flat affect decreased in severity with increased age (F = 9.8, p = 0.002; q = 0.006). Findings remained significant when parental SES, IQ, and illness duration were included as covariates. There were no developmental effects on change in positive or negative symptom severity (all p > 0.25). Beginning at age 18, there was a statistically significant association between severity of non-perceptual and perceptual symptoms. This relationship increased in strength throughout adulthood. CONCLUSIONS: These findings suggest that as maturation proceeds, perceptual symptoms attenuate while non-perceptual symptoms are enhanced. Findings underscore how pathological brain-behavior relationships vary as a function of development.

Adolescent development of cortical oscillations: Power, phase, and support of cognitive maturation.

During adolescence, the integration of specialized functional brain networks related to cognitive control continues to increase. Slow frequency oscillations (4-10 Hz) have been shown to support cognitive control processes, especially within prefrontal regions. However, it is unclear how neural oscillations contribute to functional brain network development and improvements in cognitive control during adolescence. To bridge this gap, we employed magnetoencephalography (MEG) to explore changes in oscillatory power and phase coupling across cortical networks in a sample of 68 adolescents and young adults. We found a redistribution of power from lower to higher frequencies throughout adolescence, such that delta band (1-3 Hz) power decreased, whereas beta band power (14-16 and 22-26 Hz) increased. Delta band power decreased with age most strongly in association networks within the frontal lobe and operculum. Conversely, beta band power increased throughout development, most strongly in processing networks and the posterior cingulate cortex, a hub of the default mode (DM) network. In terms of phase, theta band (5-9 Hz) phase-locking robustly decreased with development, following an anterior-to-posterior gradient, with the greatest decoupling occurring between association networks. Additionally, decreased slow frequency phase-locking between frontolimbic regions was related to decreased impulsivity with age. Thus, greater decoupling of slow frequency oscillations may afford functional networks greater flexibility during the resting state to instantiate control when required.

Development of Hippocampal-Prefrontal Cortex Interactions through Adolescence.

Significant improvements in cognitive control occur from childhood through adolescence, supported by the maturation of prefrontal systems. However, less is known about the neural basis of refinements in cognitive control proceeding from adolescence to adulthood. Accumulating evidence indicates that integration between hippocampus (HPC) and prefrontal cortex (PFC) supports flexible cognition and has a protracted neural maturation. Using a longitudinal design (487 scans), we characterized developmental changes from 8 to 32 years of age in HPC-PFC functional connectivity at rest and its associations with cognitive development. Results indicated significant increases in functional connectivity between HPC and ventromedial PFC (vmPFC), but not dorsolateral PFC. Importantly, HPC-vmPFC connectivity exclusively predicted performance on the Stockings of Cambridge task, which probes problem solving and future planning. These data provide evidence that maturation of high-level cognition into adulthood is supported by increased functional integration across the HPC and vmPFC through adolescence.

Meta-analysis and review of functional neuroimaging differences underlying adolescent vulnerability to substance use.

Adolescence is increasingly viewed as a sensitive period in the development of substance use disorders (SUDs). Neurodevelopmental 'dual-risk' theories suggest adolescent vulnerability to problematic substance use is driven by an overactive reward drive mediated by the striatum, and poor cognitive control mediated by the prefrontal cortex. To this end, there has been a growing number of neuroimaging studies examining cognitive and affective neural systems during adolescence for markers of vulnerability to problematic substance use. Here, we perform a coordinate-based meta-analysis on this emerging literature. Twenty-two task-based voxelwise fMRI studies with activation differences associated with substance use vulnerability, representative of approximately 1092 subjects, were identified through a systematic literature search (PubMed, Scopus) and coordinates of activation differences (N â€‹= â€‹190) were extracted. Adolescents were defined as 'at-risk' for problematic substance use based on a family history of SUD or through prospective prediction of substance use initiation or escalation. Multilevel kernel density analysis was used to identify the most consistent brain regions associated with adolescent substance use vulnerability. Across the included studies, substance use vulnerability was most reliably associated with activation differences in the striatum, where at-risk adolescents had hyper-activation in the dorsal subdivision (putamen). Follow-up analyses suggested striatal differences were driven by tasks sharing a motivational and/or reward component (e.g., monetary incentive) and common across subgroups of substance use risk (family history and prospective prediction studies). Analyses examining the role of psychiatric comorbidity revealed striatal activation differences were significantly more common in samples whose definition of substance use risk included cooccurring externalizing psychopathology. Furthermore, substance use risk meta-analytic results were no longer significant when excluding these studies, although this may reflect limitations in statistical power. No significant activation differences were observed in prefrontal cortex in any analysis. These results suggest striatal dysfunction, rather than prefrontal, may be a more primary neural feature of adolescent vulnerability to problematic substance use, possibly through a dimension of individual variability shared with externalizing psychopathology. However, our systematic literature search confirms this is still an emerging field. More studies, increased data sharing, and further quantitative integration are necessary for a comprehensive understanding of the neuroimaging markers of adolescent substance use risk.

Adolescent cannabis use and brain systems supporting adult working memory encoding, maintenance, and retrieval.

Given prior reports of adverse effects of cannabis use on working memory, an executive function with a protracted developmental course during adolescence, we examined associations between developmental patterns of cannabis use and adult working memory (WM) processes. Seventy-five adults with longitudinal assessments of cannabis use (60 with reported use, 15 with no reported use) and prenatal drug exposure assessment completed a spatial WM task during fMRI at age 28. All subjects passed a multi-drug urine screen on the day of testing and denied recreational drug use in the past week. A fast event-related design with partial trials was used to separate the BOLD response associated with encoding, maintenance, and retrieval periods of the WM task. Behavioral results showed that subjects who began using cannabis earlier in adolescence had longer reaction times (RT) than those with later initiation. Cannabis age of onset was further associated with reduced posterior parietal cortex (PPC) encoding BOLD activation, which significantly mediated age of onset WM RT associations. However, cannabis age of onset brain-behavior associations did not differ between groups with a single reported use and those with repeated use, suggesting age of onset effects may reflect substance use risk characteristics rather than a developmentally-timed cannabis exposure effect. Within repeated cannabis users, greater levels of total cannabis use were associated with performance-related increases in dorsolateral prefrontal cortex (DLPFC) activation during maintenance. This pattern of significant results remained unchanged with inclusion of demographic and prenatal measures as covariates. Surprisingly, however, at the group level, cannabis users generally performed better than participants who reported never using cannabis (faster RT, higher accuracy). We extend previous investigations by identifying that WM associations with cannabis age of onset may be primary to PPC stimulus encoding activity, while the amount of cannabis use is associated with DLPFC maintenance processes. Poorer performance of participants who reported never using cannabis and the consistency of cannabis age of onset associations across single and repeated users limit interpretation of direct developmental effects of cannabis on WM in adulthood.

Psychiatric neuroimaging designs for individualised, cohort, and population studies.

Psychiatric neuroimaging faces challenges to rigour and reproducibility that prompt reconsideration of the relative strengths and limitations of study designs. Owing to high resource demands and varying inferential goals, current designs differentially emphasise sample size, measurement breadth, and longitudinal assessments. In this overview and perspective, we provide a guide to the current landscape of psychiatric neuroimaging study designs with respect to this balance of scientific goals and resource constraints. Through a heuristic data cube contrasting key design features, we discuss a resulting trade-off among small sample, precision longitudinal studies (e.g., individualised studies and cohorts) and large sample, minimally longitudinal, population studies. Precision studies support tests of within-person mechanisms, via intervention and tracking of longitudinal course. Population studies support tests of generalisation across multifaceted individual differences. A proposed reciprocal validation model (RVM) aims to recursively leverage these complementary designs in sequence to accumulate evidence, optimise relative strengths, and build towards improved long-term clinical utility.

The Developmental Timing but Not Magnitude of Adolescent Risk-Taking Propensity Is Consistent Across Social, Environmental, and Psychological Factors.

PURPOSE: Risk-taking is thought to peak during adolescence, but most prior studies have relied on small convenience samples lacking participant diversity. This study tested the generalizability of adolescent self-reported risk-taking propensity across a comprehensive set of participant-level social, environmental, and psychological factors. METHODS: Data (N = 1,005,421) from the National Survey on Drug Use and Health were used to test the developmental timing and magnitude of risk-taking propensity and its link to alcohol and cannabis use across 19 subgroups defined via sex, race/ethnicity, socioeconomic status, population density, religious affiliation, and mental health. RESULTS: The developmental timing of a lifespan peak in risk-taking propensity during adolescence (15-18 years old) generalized across nearly all levels of social, environmental, and psychological factors, whereas the magnitude of this peak widely varied. Nearly all adolescents with regular substance use reported higher levels of risk-taking propensity. DISCUSSION: Results support a broad generalizability of adolescence as the peak lifespan period of self-reported risk-taking but emphasize the importance of participant-level factors in determining the specific magnitude of reported risk-taking.

Use of Tobacco Products and Suicide Attempts Among Elementary School-Aged Children.

Importance: The use of tobacco products, including e-cigarettes and vaping, has rapidly increased among children. However, despite consistent associations found between smoking cigarettes and suicidal behaviors among adolescents and adults, there are limited data on associations between emerging tobacco products and suicidal behaviors, especially among preadolescent children. Objective: To examine whether the use of tobacco products is associated with nonsuicidal self-injury (NSSI), suicidal ideation (SI), and suicide attempts (SAs) among preadolescent children. Design, Setting, and Participants: This cohort study, conducted from September 1, 2022, to September 5, 2023, included participants in the Adolescent Brain Cognitive Development study, a population-based cohort of 11 868 US children enrolled at 9 and 10 years of age. The cross-sectional investigation focused on 3-year periods starting from the baseline to year 2 of follow-up. Statistical analysis was performed from October 1, 2022, to June 30, 2023. Main Outcomes and Measures: Children's use of tobacco products was assessed based on youth reports, including lifetime experiences of various nicotine-related products, supplemented with hair toxicologic tests. Main outcomes were children's lifetime experiences of NSSI, SI, and SAs, assessed using the K-SADS-5 (Kiddie Schedule for Affective Disorders and Schizophrenia for the DSM-5). Multivariate logistic regression was conducted to examine the associations of the use of tobacco products with NSSI, SI, and SAs among the study participants. Sociodemographic, familial, and children's behavioral, temperamental, and clinical outcomes were adjusted in the analyses. Results: Of 8988 unrelated study participants (median age, 9.8 years [range, 8.9-11.0 years]; 4301 girls [47.9%]), 101 children (1.1%) and 151 children (1.7%) acknowledged lifetime use of tobacco products at baseline and at 18-month follow-up, respectively. After accounting for various suicide risk factors and potential confounders, children reporting use of tobacco products were at a 3 to 5 times increased risk of SAs (baseline: n = 153 [adjusted odds ratio (OR), 4.67; 95% CI, 2.35-9.28; false discovery rate (FDR)-corrected P < .001]; year 1: n = 227 [adjusted OR, 4.25; 95% CI, 2.33-7.74; FDR-corrected P < .001]; and year 2: n = 321 [adjusted OR, 2.85; 95% CI, 1.58-5.13; FDR-corrected P = .001]). Of all facets of impulsivity measures that were significant correlates of use of tobacco products, negative urgency was the only independent risk factor for SAs (adjusted OR, 1.52 [95% CI, 1.31-1.78]; FDR-corrected P < .001). In contrast, children's alcohol, cannabis, and prescription drug use were not associated with SAs. Conclusions and Relevance: This study of US children suggests that the increased risk of SAs, consistently reported for adolescents and adults who smoke cigarettes, extends to a range of emerging tobacco products and manifests among elementary school-aged children. Further investigations are imperative to clarify the underlying mechanisms and to implement effective preventive policies for children.

Associations between behavioral and self-reported impulsivity, brain structure, and genetic influences in middle childhood.

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

Study design features that improve effect sizes in cross-sectional and longitudinal brain-wide association studies.

Brain-wide association studies (BWAS) are a fundamental tool in discovering brain-behavior associations. Several recent studies showed that thousands of study participants are required to improve the replicability of BWAS because actual effect sizes are much smaller than those reported in smaller studies. Here, we perform analyses and meta-analyses of a robust effect size index (RESI) using 63 longitudinal and cross-sectional magnetic resonance imaging studies from the Lifespan Brain Chart Consortium (77,695 total scans) to demonstrate that optimizing study design is critical for improving standardized effect sizes and replicability in BWAS. A meta-analysis of brain volume associations with age indicates that BWAS with larger covariate variance have larger effect size estimates and that the longitudinal studies we examined have systematically larger standardized effect sizes than cross-sectional studies. We propose a cross-sectional RESI to adjust for the systematic difference in effect sizes between cross-sectional and longitudinal studies that allows investigators to quantify the benefit of conducting their study longitudinally. Analyzing age effects on global and regional brain measures from the United Kingdom Biobank and the Alzheimer's Disease Neuroimaging Initiative, we show that modifying longitudinal study design through sampling schemes to increase between-subject variability and adding a single additional longitudinal measurement per subject can improve effect sizes. However, evaluating these longitudinal sampling schemes on cognitive, psychopathology, and demographic associations with structural and functional brain outcome measures in the Adolescent Brain and Cognitive Development dataset shows that commonly used longitudinal models can, counterintuitively, reduce effect sizes. We demonstrate that the benefit of conducting longitudinal studies depends on the strengths of the between- and within-subject associations of the brain and non-brain measures. Explicitly modeling between- and within-subject effects avoids conflating the effects and allows optimizing effect sizes for them separately. These findings underscore the importance of considering study design features to improve the replicability of BWAS.

Heritability estimation of subcortical volumes in a multi-ethnic multi-site cohort study.

Heritability of regional subcortical brain volumes (rSBVs) describes the role of genetics in middle and inner brain development. rSBVs are highly heritable in adults but are not characterized well in adolescents. The Adolescent Brain Cognitive Development study (ABCD), taken over 22 US sites, provides data to characterize the heritability of subcortical structures in adolescence. In ABCD, site-specific effects co-occur with genetic effects which can bias heritability estimates. Existing methods adjusting for site effects require additional steps to adjust for site effects and can lead to inconsistent estimation. We propose a random-effect model-based method of moments approach that is a single step estimator and is a theoretically consistent estimator even when sites are imbalanced and performs well under simulations. We compare methods on rSBVs from ABCD. The proposed approach yielded heritability estimates similar to previous results derived from single-site studies. The cerebellum cortex and hippocampus were the most heritable regions (> 50%).

Exploring the multiverse: the impact of researchers' analytic decisions on relationships between depression and inflammatory markers.

In recent years, a replication crisis in psychiatry has led to a growing focus on the impact of researchers' analytic decisions on the results from studies. Multiverse analyses involve examining results across a wide array of possible analytic decisions (e.g., log-transforming variables, number of covariates, or treatment of outliers) and identifying if study results are robust to researchers' analytic decisions. Studies have begun to use multiverse analysis for well-studied relationships that have some heterogeneity in results/conclusions across studies.We examine the well-studied relationship between peripheral inflammatory markers (PIMs; e.g., white blood cell count (WBC) and C-reactive protein (CRP)) and depression severity in the large NHANES dataset (n = 25,962). Specification curve analyses tested the impact of 9 common analytic decisions (comprising of 58,000+ possible combinations) on the association of PIMs and depression severity. Relationships of PIMs and total depression severity are robust to analytic decisions (based on tests of inference jointly examining effect sizes and p-values). However, moderate/large differences are noted in effect sizes based on analytic decisions and the majority of analyses do not result in significant findings, with the percentage of analyses with statistically significant results being 46.1% for WBC and 43.8% for CRP. For associations of PIMs with specific symptoms of depression, some associations (e.g., sleep, appetite) in males (but not females) were robust to analytic decisions. We discuss how multiverse analyses can be used to guide research and also the need for authors, reviewers, and editors to incorporate multiverse analyses to enhance replicability of research findings.

A canonical trajectory of executive function maturation from adolescence to adulthood.

Theories of human neurobehavioral development suggest executive functions mature from childhood through adolescence, underlying adolescent risk-taking and the emergence of psychopathology. Investigations with relatively small datasets or narrow subsets of measures have identified general executive function development, but the specific maturational timing and independence of potential executive function subcomponents remain unknown. Integrating four independent datasets (N = 10,766; 8-35 years old) with twenty-three measures from seventeen tasks, we provide a precise charting, multi-assessment investigation, and replication of executive function development from adolescence to adulthood. Across assessments and datasets, executive functions follow a canonical non-linear trajectory, with rapid and statistically significant development in late childhood to mid-adolescence (10-15 years old), before stabilizing to adult-levels in late adolescence (18-20 years old). Age effects are well captured by domain-general processes that generate reproducible developmental templates across assessments and datasets. Results provide a canonical trajectory of executive function maturation that demarcates the boundaries of adolescence and can be integrated into future studies.

The Cannabis Effects Expectancy Questionnaire-Medical (CEEQ-M): Preliminary psychometric properties and longitudinal validation within a clinical trial.

The use of cannabis for medical symptoms is increasing despite limited evidence for its efficacy. Expectancies-prior beliefs about a substance or medicine-can modulate use patterns and effects of medicines on target symptoms. To our knowledge, cannabis expectancies have not been studied for their predictive value for symptom relief. The 21-item Cannabis Effects Expectancy Questionnaire-Medical (CEEQ-M) is the first longitudinally validated measure of expectancies for cannabis used for medical symptoms. The questionnaire was developed for a randomized clinical trial of the effect of state cannabis registration (SCR) card ownership on symptoms of pain, insomnia, anxiety, and depression in adults (N = 269 across six questionnaire administrations). Item-level analyses (n = 188) demonstrated between-person stability of expectancies and no aggregate, within-person expectancy changes 3 months after individuals gained access to SCR cards. Exploratory factor analysis (n = 269) indicated a two-factor structure. Confirmatory factor analysis at a later timepoint (n = 193) demonstrated good fit and scalar invariance of the measurement model. Cross-lagged panel models across 3 and 12 months (n = 187 and 161, respectively) indicated that CEEQ-M-measured expectancies did not predict changes in self-reported cannabis use; symptoms of pain, insomnia, anxiety, and depression; and well-being. However, greater baseline cannabis use predicted more positive expectancy changes. The findings suggest that the CEEQ-M is psychometrically sound. Future work should clarify at what timescales cannabis expectancies have predictive value and how cannabis expectancies for medical symptoms are maintained and diverge from other substance use expectancies. (PsycInfo Database Record (c) 2023 APA, all rights reserved).