Differential associations of adolescent versus young adult cannabis initiation with longitudinal brain change and behavior.

Leveraging ~10 years of prospective longitudinal data on 704 participants, we examined the effects of adolescent versus young adult cannabis initiation on MRI-assessed cortical thickness development and behavior. Data were obtained from the IMAGEN study conducted across eight European sites. We identified IMAGEN participants who reported being cannabis-naïve at baseline and had data available at baseline, 5-year, and 9-year follow-up visits. Cannabis use was assessed with the European School Survey Project on Alcohol and Drugs. T1-weighted MR images were processed through the CIVET pipeline. Cannabis initiation occurring during adolescence (14-19 years) and young adulthood (19-22 years) was associated with differing patterns of longitudinal cortical thickness change. Associations between adolescent cannabis initiation and cortical thickness change were observed primarily in dorso- and ventrolateral portions of the prefrontal cortex. In contrast, cannabis initiation occurring between 19 and 22 years of age was associated with thickness change in temporal and cortical midline areas. Follow-up analysis revealed that longitudinal brain change related to adolescent initiation persisted into young adulthood and partially mediated the association between adolescent cannabis use and past-month cocaine, ecstasy, and cannabis use at age 22. Extent of cannabis initiation during young adulthood (from 19 to 22 years) had an indirect effect on psychotic symptoms at age 22 through thickness change in temporal areas. Results suggest that developmental timing of cannabis exposure may have a marked effect on neuroanatomical correlates of cannabis use as well as associated behavioral sequelae. Critically, this work provides a foundation for neurodevelopmentally informed models of cannabis exposure in humans.

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.

Performance scaling for structural MRI surface parcellations: a machine learning analysis in the ABCD Study.

The use of predefined parcellations on surface-based representations of the brain as a method for data reduction is common across neuroimaging studies. In particular, prediction-based studies typically employ parcellation-driven summaries of brain measures as input to predictive algorithms, but the choice of parcellation and its influence on performance is often ignored. Here we employed preprocessed structural magnetic resonance imaging (sMRI) data from the Adolescent Brain Cognitive Development Study® to examine the relationship between 220 parcellations and out-of-sample predictive performance across 45 phenotypic measures in a large sample of 9- to 10-year-old children (N = 9,432). Choice of machine learning (ML) pipeline and use of alternative multiple parcellation-based strategies were also assessed. Relative parcellation performance was dependent on the spatial resolution of the parcellation, with larger number of parcels (up to ~4,000) outperforming coarser parcellations, according to a power-law scaling of between 1/4 and 1/3. Performance was further influenced by the type of parcellation, ML pipeline, and general strategy, with existing literature-based parcellations, a support vector-based pipeline, and ensembling across multiple parcellations, respectively, as the highest performing. These findings highlight the choice of parcellation as an important influence on downstream predictive performance, showing in some cases that switching to a higher resolution parcellation can yield a relatively large boost to performance.

An open-access accelerated adult equivalent of the ABCD Study neuroimaging dataset (a-ABCD).

As public access to longitudinal developmental datasets like the Adolescent Brain Cognitive Development StudySM (ABCD Study®) increases, so too does the need for resources to benchmark time-dependent effects. Scan-to-scan changes observed with repeated imaging may reflect development but may also reflect practice effects, day-to-day variability in psychological states, and/or measurement noise. Resources that allow disentangling these time-dependent effects will be useful in quantifying actual developmental change. We present an accelerated adult equivalent of the ABCD Study dataset (a-ABCD) using an identical imaging protocol to acquire magnetic resonance imaging (MRI) structural, diffusion-weighted, resting-state and task-based data from eight adults scanned five times over five weeks. We report on the task-based imaging data (n = 7). In-scanner stop-signal (SST), monetary incentive delay (MID), and emotional n-back (EN-back) task behavioral performance did not change across sessions. Post-scan recognition memory for emotional n-back stimuli, however, did improve as participants became more familiar with the stimuli. Functional MRI analyses revealed that patterns of task-based activation reflecting inhibitory control in the SST, reward success in the MID task, and working memory in the EN-back task were more similar within individuals across repeated scan sessions than between individuals. Within-subject, activity was more consistent across sessions during the EN-back task than in the SST and MID task, demonstrating differences in fMRI data reliability as a function of task. The a-ABCD dataset provides a unique testbed for characterizing the reliability of brain function, structure, and behavior across imaging modalities in adulthood and benchmarking neurodevelopmental change observed in the open-access ABCD Study.

Effects of cocaine and HIV on decision-making abilities.

Our study aimed to understand the impact of cocaine dependence on high-risk decision-making abilities in individuals with the human immunodeficiency virus (HIV) and individuals with cocaine dependence. We recruited 99 participants (27 HIV/Cocaine, 20 HIV Only, 26 Cocaine Only, and 26 Healthy Controls). The Iowa Gambling Task (IGT) was applied to assess decision-making abilities. Independent and interactive effects of HIV status and cocaine dependence were examined using 2 × 2 factorial ANCOVA with premorbid IQ (WRAT-4: WR) as the covariate. We found cocaine dependence had a significant adverse effect on overall IGT performance (p = 0.015). We also found individuals who were HIV-positive tended to have less total money at the end of the game than individuals who were HIV-negative (p = 0.032), suggesting individuals living with HIV had less focus on long-term gains and more focus on short-term gains. Our findings highlight the significant impact of cocaine dependence on decision-making abilities and the difficulty individuals with HIV have in adequately weighing the cost and benefits of their decisions and making appropriate changes for the future.

Inpatient length of stay moderates the relationship between payer source and functional outcomes in pediatric brain injury.

OBJECTIVE: To examine the extent to which race/ethnicity, length of rehabilitation hospital stay (LOS), and payer source contribute to functional status following inpatient rehabilitation in children with acquired brain injury (ABI). DESIGN: Retrospective cohort study from a pediatric rehabilitation hospital including 485 individuals with ABI. METHODS: Functional Independence Measure for Children (WeeFIM) scores were transformed into age-corrected Developmental Functional Quotients (DFQ) to examine the effects of race/ethnicity, LOS, and payer source (public insurance vs. private) on functional outcomes while controlling for year of admission, admission DFQ, time to rehabilitation, age, and brain injury aetiology. RESULTS: Discharge DFQ scores tended to be lower for children with public insurance as well as those with longer LOS. There was no main effect of race/ethnicity, but a significant interaction effect for payer source×LOS (p < .001) was found. Further breakdown of the interaction showed lower discharge DFQ scores for children with public insurance primarily when LOS exceeded 28 days (p = .001). CONCLUSION: Children with ABI who have both public insurance and LOS beyond 4 weeks tend to have poorer functional outcomes after inpatient rehabilitation. Because all children were receiving services at the same facility, payer source may be functioning as a proxy for other sociodemographic factors.

Parameter Space and Potential for Biomarker Development in 25 Years of fMRI Drug Cue Reactivity: A Systematic Review.

Importance: In the last 25 years, functional magnetic resonance imaging drug cue reactivity (FDCR) studies have characterized some core aspects in the neurobiology of drug addiction. However, no FDCR-derived biomarkers have been approved for treatment development or clinical adoption. Traversing this translational gap requires a systematic assessment of the FDCR literature evidence, its heterogeneity, and an evaluation of possible clinical uses of FDCR-derived biomarkers. Objective: To summarize the state of the field of FDCR, assess their potential for biomarker development, and outline a clear process for biomarker qualification to guide future research and validation efforts. Evidence Review: The PubMed and Medline databases were searched for every original FDCR investigation published from database inception until December 2022. Collected data covered study design, participant characteristics, FDCR task design, and whether each study provided evidence that might potentially help develop susceptibility, diagnostic, response, prognostic, predictive, or severity biomarkers for 1 or more addictive disorders. Findings: There were 415 FDCR studies published between 1998 and 2022. Most focused on nicotine (122 [29.6%]), alcohol (120 [29.2%]), or cocaine (46 [11.1%]), and most used visual cues (354 [85.3%]). Together, these studies recruited 19 311 participants, including 13 812 individuals with past or current substance use disorders. Most studies could potentially support biomarker development, including diagnostic (143 [32.7%]), treatment response (141 [32.3%]), severity (84 [19.2%]), prognostic (30 [6.9%]), predictive (25 [5.7%]), monitoring (12 [2.7%]), and susceptibility (2 [0.5%]) biomarkers. A total of 155 interventional studies used FDCR, mostly to investigate pharmacological (67 [43.2%]) or cognitive/behavioral (51 [32.9%]) interventions; 141 studies used FDCR as a response measure, of which 125 (88.7%) reported significant interventional FDCR alterations; and 25 studies used FDCR as an intervention outcome predictor, with 24 (96%) finding significant associations between FDCR markers and treatment outcomes. Conclusions and Relevance: Based on this systematic review and the proposed biomarker development framework, there is a pathway for the development and regulatory qualification of FDCR-based biomarkers of addiction and recovery. Further validation could support the use of FDCR-derived measures, potentially accelerating treatment development and improving diagnostic, prognostic, and predictive clinical judgments.

Impaired verbal memory in individuals living with HIV and cocaine dependence.

INTRODUCTION: Our study aimed to understand the independent and combined effects of cocaine dependence and HIV status across aspects of verbal memory. METHOD: Our sample consisted of a total of 102 individuals: 28 individuals living with HIV and cocaine dependence (HIV+/CD), 28 individuals who are HIV-negative with cocaine dependence (HIV-/CD), 20 individuals living with HIV without cocaine dependence (HIV+/ND), and 26 individuals who are HIV-negative without cocaine dependence (HIV-/ND). We utilized the Hopkins Verbal Learning Test-Revised Version (HVLT-R) to assess components of verbal memory, including encoding, recall, and recognition. A 2 (HIV: Yes/No) × 2 (Cocaine: Yes/No) MANCOVA on Total and Delayed Recall while controlling for premorbid intelligence was conducted. We used a Kruskal-Wallis H test to examine retrieval and recognition. RESULTS: The combination of HIV and cocaine dependence amplified deficits on Total Recall. We found comparably poor performance across Delayed Recall between all three clinical groups. People living with HIV without cocaine dependence demonstrated intact recognition, whereas those with cocaine dependence had poor recognition. CONCLUSIONS: HIV and cocaine both impacted verbal memory. However, there are potential subtle differences in the role cocaine versus HIV has on the memory process. People living with HIV without cocaine dependence recognized significantly more words than they could freely recall. In contrast, cocaine dependence impacted recognition in HIV and non-HIV groups. These performance patterns suggest HIV may be associated with retrieval deficits, whereas cocaine dependence may be associated with encoding deficits. Further research assessing these specific components of the memory process will help clarify these potential differences.

One-year predictions of delayed reward discounting in the adolescent brain cognitive development study.

Delayed reward discounting (DRD) refers to the extent to which an individual devalues a reward based on a temporal delay and is known to be elevated in individuals with substance use disorders and many mental illnesses. DRD has been linked previously with both features of brain structure and function, as well as various behavioral, psychological, and life-history factors. However, there has been little work on the neurobiological and behavioral antecedents of DRD in childhood. This is an important question, as understanding the antecedents of DRD can provide signs of mechanisms in the development of psychopathology. The present study used baseline data from the Adolescent Brain Cognitive Development Study (N = 4,042) to build machine learning models to predict DRD at the first follow-up visit, 1 year later. In separate machine learning models, we tested elastic net regression, random forest regression, light gradient boosting regression, and support vector regression. In five-fold cross-validation on the training set, models using an array of questionnaire/task variables were able to predict DRD, with these findings generalizing to a held-out (i.e., "lockbox") test set of 20% of the sample. Key predictive variables were neuropsychological test performance at baseline, socioeconomic status, screen media activity, psychopathology, parenting, and personality. However, models using magnetic resonance imaging (MRI)-derived brain variables did not reliably predict DRD in either the cross-validation or held-out test set. These results suggest a combination of questionnaire/task variables as antecedents of excessive DRD in late childhood, which may presage the development of problematic substance use in adolescence. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Bayesian causal network modeling suggests adolescent cannabis use accelerates prefrontal cortical thinning.

While there is substantial evidence that cannabis use is associated with differences in human brain development, most of this evidence is correlational in nature. Bayesian causal network (BCN) modeling attempts to identify probable causal relationships in correlational data using conditional probabilities to estimate directional associations between a set of interrelated variables. In this study, we employed BCN modeling in 637 adolescents from the IMAGEN study who were cannabis naïve at age 14 to provide evidence that the accelerated prefrontal cortical thinning found previously in adolescent cannabis users by Albaugh et al. [1] is a result of cannabis use causally affecting neurodevelopment. BCNs incorporated data on cannabis use, prefrontal cortical thickness, and other factors related to both brain development and cannabis use, including demographics, psychopathology, childhood adversity, and other substance use. All BCN algorithms strongly suggested a directional relationship from adolescent cannabis use to accelerated cortical thinning. While BCN modeling alone does not prove a causal relationship, these results are consistent with a body of animal and human research suggesting that adolescent cannabis use adversely affects brain development.

Multimethod investigation of the neurobiological basis of ADHD symptomatology in children aged 9-10: baseline data from the ABCD study.

Attention deficit/hyperactivity disorder is associated with numerous neurocognitive deficits, including poor working memory and difficulty inhibiting undesirable behaviors that cause academic and behavioral problems in children. Prior work has attempted to determine how these differences are instantiated in the structure and function of the brain, but much of that work has been done in small samples, focused on older adolescents or adults, and used statistical approaches that were not robust to model overfitting. The current study used cross-validated elastic net regression to predict a continuous measure of ADHD symptomatology using brain morphometry and activation during tasks of working memory, inhibitory control, and reward processing, with separate models for each MRI measure. The best model using activation during the working memory task to predict ADHD symptomatology had an out-of-sample R2 = 2% and was robust to residualizing the effects of age, sex, race, parental income and education, handedness, pubertal status, and internalizing symptoms from ADHD symptomatology. This model used reduced activation in task positive regions and reduced deactivation in task negative regions to predict ADHD symptomatology. The best model with morphometry alone predicted ADHD symptomatology with an R2 = 1% but this effect dissipated when including covariates. The inhibitory control and reward tasks did not yield generalizable models. In summary, these analyses show, with a large and well-characterized sample, that the brain correlates of ADHD symptomatology are modest in effect size and captured best by brain morphometry and activation during a working memory task.

Examination of the association between exposure to childhood maltreatment and brain structure in young adults: a machine learning analysis.

Exposure to maltreatment during childhood is associated with structural changes throughout the brain. However, the structural differences that are most strongly associated with maltreatment remain unclear given the limited number of whole-brain studies. The present study used machine learning to identify if and how brain structure distinguished young adults with and without a history of maltreatment. Young adults (ages 18-21, n = 384) completed an assessment of childhood trauma exposure and a structural MRI as part of the IMAGEN study. Elastic net regularized regression was used to identify the structural features that identified those with a history of maltreatment. A generalizable model that included 7 cortical thicknesses, 15 surface areas, and 5 subcortical volumes was identified (area under the receiver operating characteristic curve = 0.71, p < 0.001). Those with a maltreatment history had reduced surface areas and cortical thicknesses primarily in fronto-temporal regions. This group also had larger cortical thicknesses in occipital regions and surface areas in frontal regions. The results suggest childhood maltreatment is associated with multiple measures of structure throughout the brain. The use of a large sample without exposure to adulthood trauma provides further evidence for the unique contribution of childhood trauma to brain structure. The identified regions overlapped with regions associated with psychopathology in adults with maltreatment histories, which offers insights as to how these disorders manifest.

Characterizing reward system neural trajectories from adolescence to young adulthood.

Mixed findings exist in studies comparing brain responses to reward in adolescents and adults. Here we examined the trajectories of brain response, functional connectivity and task-modulated network properties during reward processing with a large-sample longitudinal design. Participants from the IMAGEN study performed a Monetary Incentive Delay task during fMRI at timepoint 1 (T1; n = 1304, mean age=14.44 years old) and timepoint 2 (T2; n = 1241, mean age=19.09 years). The Alcohol Use Disorders Identification Test (AUDIT) was administrated at both T1 and T2 to assess a participant's alcohol use during the past year. Voxel-wise linear mixed effect models were used to compare whole brain response as well as functional connectivity of the ventral striatum (VS) during reward anticipation (large reward vs no-reward cue) between T1 and T2. In addition, task-modulated networks were constructed using generalized psychophysiological interaction analysis and summarized with graph theory metrics. To explore alcohol use in relation to development, participants with no/low alcohol use at T1 but increased alcohol use to hazardous use level at T2 (i.e., participants with AUDIT≤2 at T1 and ≥8 at T2) were compared against those with consistently low scores (i.e., participants with AUDIT≤2 at T1 and ≤7 at T2). Across the whole sample, lower brain response during reward anticipation was observed at T2 compared with T1 in bilateral caudate nucleus, VS, thalamus, midbrain, dorsal anterior cingulate as well as left precentral and postcentral gyrus. Conversely, greater response was observed bilaterally in the inferior and middle frontal gyrus and right precentral and postcentral gyrus at T2 (vs. T1). Increased functional connectivity with VS was found in frontal, temporal, parietal and occipital regions at T2. Graph theory metrics of the task-modulated network showed higher inter-regional connectivity and topological efficiency at T2. Interactive effects between time (T1 vs. T2) and alcohol use group (low vs. high) on the functional connectivity were observed between left middle temporal gyrus and right VS and the characteristic shortest path length of the task-modulated networks. Collectively, these results demonstrate the utility of the MID task as a probe of typical brain response and network properties during development and of differences in these features related to adolescent drinking, a reward-related behaviour associated with heightened risk for future negative health outcomes.

Association of Cannabis Use During Adolescence With Neurodevelopment.

IMPORTANCE: Animal studies have shown that the adolescent brain is sensitive to disruptions in endocannabinoid signaling, resulting in altered neurodevelopment and lasting behavioral effects. However, few studies have investigated ties between cannabis use and adolescent brain development in humans. OBJECTIVE: To examine the degree to which magnetic resonance (MR) imaging-assessed cerebral cortical thickness development is associated with cannabis use in a longitudinal sample of adolescents. DESIGN, SETTING, AND PARTICIPANTS: Data were obtained from the community-based IMAGEN cohort study, conducted across 8 European sites. Baseline data used in the present study were acquired from March 1, 2008, to December 31, 2011, and follow-up data were acquired from January 1, 2013, to December 31, 2016. A total of 799 IMAGEN participants were identified who reported being cannabis naive at study baseline and had behavioral and neuroimaging data available at baseline and 5-year follow-up. Statistical analysis was performed from October 1, 2019, to August 31, 2020. MAIN OUTCOMES AND MEASURES: Cannabis use was assessed at baseline and 5-year follow-up with the European School Survey Project on Alcohol and Other Drugs. Anatomical MR images were acquired with a 3-dimensional T1-weighted magnetization prepared gradient echo sequence. Quality-controlled native MR images were processed through the CIVET pipeline, version 2.1.0. RESULTS: The study evaluated 1598 MR images from 799 participants (450 female participants [56.3%]; mean [SD] age, 14.4 [0.4] years at baseline and 19.0 [0.7] years at follow-up). At 5-year follow-up, cannabis use (from 0 to >40 uses) was negatively associated with thickness in left prefrontal (peak: t785 = -4.87, cluster size = 1558 vertices; P = 1.10 × 10-6, random field theory cluster corrected) and right prefrontal (peak: t785 = -4.27, cluster size = 1551 vertices; P = 2.81 × 10-5, random field theory cluster corrected) cortices. There were no significant associations between lifetime cannabis use at 5-year follow-up and baseline cortical thickness, suggesting that the observed neuroanatomical differences did not precede initiation of cannabis use. Longitudinal analysis revealed that age-related cortical thinning was qualified by cannabis use in a dose-dependent fashion such that greater use, from baseline to follow-up, was associated with increased thinning in left prefrontal (peak: t815.27 = -4.24, cluster size = 3643 vertices; P = 2.28 × 10-8, random field theory cluster corrected) and right prefrontal (peak: t813.30 = -4.71, cluster size = 2675 vertices; P = 3.72 × 10-8, random field theory cluster corrected) cortices. The spatial pattern of cannabis-related thinning was associated with age-related thinning in this sample (r = 0.540; P < .001), and a positron emission tomography-assessed cannabinoid 1 receptor-binding map derived from a separate sample of participants (r = -0.189; P < .001). Analysis revealed that thinning in right prefrontal cortices, from baseline to follow-up, was associated with attentional impulsiveness at follow-up. CONCLUSIONS AND RELEVANCE: Results suggest that cannabis use during adolescence is associated with altered neurodevelopment, particularly in cortices rich in cannabinoid 1 receptors and undergoing the greatest age-related thickness change in middle to late adolescence.

Feasibility of a school-based mindfulness program for improving inhibitory skills in children with autism spectrum disorder.

BACKGROUND: Executive dysfunction is prevalent in children with autism spectrum disorder (ASD), including prominent difficulties in the two facets of inhibition, as well as with selective attention. School-based mindfulness has been used in typically-developing children to improve executive functioning, though this has not been investigated in children with ASD. Therefore, the purpose of this study was to examine the efficacy of a school-based mindfulness program for improving inhibition (prepotent response inhibition and interference control) and selective attention in children with ASD. METHOD: Using a quasi-experimental, pre-post design, an eight week school-based mindfulness program (Mindful Schools;https://www.mindfulschools.org/), was administered to students with ASD (n = 27) at a private, not-for-profit school for children with special needs. The Walk/Don't Walk test and the Color-Word Interference test were used to evaluate prepotent response inhibition and interference control, respectively. Selective attention was measured using a cancellation test. RESULTS: Significant improvements followed the intervention for prepotent response inhibition and interference control (medium effect sizes), as well as for overall selective attention (large effect size). CONCLUSIONS: The study's findings demonstrate that school-based mindfulness holds promise for increasing specific executive functioning abilities in children with ASD.

Momentary maximizing and optimal foraging theories of performance on concurrent VR schedules.

Optimal foraging theory proposes that animals obtain the highest rate of reinforcers for the least effort and momentary maximizing theory proposes that animals make the response that at that instant is most likely to be reinforced. While each theory may account for matching on concurrent schedules, the data supporting each theory are weak. Two experiments assessed these theories by considering concurrent choice as consisting of two pairs of stay and switch schedules. Symmetrical arrangements, which are equivalent to standard concurrent schedules, maintained behavior described by the generalized matching law. Weighted arrangements, in which the programmed rate of earning reinforcers was always greater at one alternative, maintained behavior that was biased towards the weighted alternative, yet the bias was less than that predicted by optimal foraging theory. Asymmetrical arrangements, in which the stay and switch schedules operating at an alternative are the same, maintained behavior that favored one alternative, even though momentary maximizing predicted indifference. The generalized matching law poorly described each rat's pooled data from all conditions but these data were described by an equation based on the stay and switch reinforcers earned per-visit and included elements of optimal foraging and momentary maximizing theories of choice.