Testing whether the relations between sex and psychopathology are accounted for by structural morphometry in ABCD

Sex differences in psychopathology are well-established, with females demonstrating higher rates of internalizing (INT) psychopathology and males demonstrating higher rates of externalizing (EXT) psychopathology. Using two waves of data from the Adolescent Brain Cognitive Development Study (N = 6,778 at each wave), the current study tested whether the relations between sex and psychopathology might be accounted for by structural brain differences. In general, we found robust, relatively consistent relations between sex and structural morphometry across waves. Relatively few morphometric brain variables were significantly related to INT or EXT across waves, however, with very small effect sizes when present. Next, we tested the extent to which each morphometric brain variable could account for the associations of sex with INT and EXT psychopathology. We found a total of 26 brain regions that accounted for significant portions of the associations between sex and psychopathology across both waves (almost all related to EXT), although the effects present were very small. The current evidence suggests that in children aged 9-12, multiple whole-brain and regional brain variables appear to statistically account for small portions of the sex-psychopathology links, especially for externalizing. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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.

Neuroanatomical profile of BMI implicates impulsive delay discounting and general cognitive ability

OBJECTIVE

Obesity is a disorder of excessive adiposity, typically assessed via the anthropometric density measure of BMI. Numerous studies have implicated BMI with differences in brain structure, but with highly inconsistent findings.

METHODS

Machine learning elastic net regression models with cross-validation were conducted to characterize a neuroanatomical morphometry profile associated with BMI in 1100 participants (22% BMI > 30, n = 242) from the Human Connectome Project Young Adult project.

RESULTS

Using five-fold cross-validation, the multiregion neuroanatomical profile substantively predicted BMI (R2  = 10.05%), and this was robust in a held-out test set (R2  = 8.87%). In terms of specific regions, the neuroanatomical profile was enriched for nodes in the default mode, executive control, and salience networks. The relationship between the morphometry profile and BMI itself was partially mediated by impulsive delay discounting and general cognitive ability.

CONCLUSIONS

Taken together, these findings reveal a robust machine learning-derived neuroanatomical profile of BMI, one that comprises nodes in motivational brain networks and suggests the functional links to obesity are via self-regulatory capacity and cognitive function.

Test-retest reliability of the neuroanatomical correlates of impulsive personality traits in the adolescent brain cognitive development study

While the neuroanatomical correlates of impulsivity in youths have been examined, there is little research on whether those correlates are consistent across childhood/adolescence. The current study uses data from the age 11/12 (N = 7,083) visit of the Adolescent Brain Cognitive Development Study to investigate the replicability of previous work (Owens et al., 2020) the neuroanatomical correlates of impulsive personality traits identified at age 9/10. Neuroanatomy was measured using structural and diffusion magnetic resonance imaging, and impulsive personality was measured using the UPPS-P Impulsive Behavior Scale. Replicability was quantified using three Open Science Collaboration replication criteria, intraclass correlations, and elastic net regression modeling to make predictions across timepoints. Replicability was highly variable among traits: The neuroanatomical correlates of positive urgency showed substantial similarity between ages 9/10 and 11/12, negative urgency and sensation seeking showed moderate similarity across ages, and (lack of) premeditation and perseverance showed substantial dissimilarity across ages. In all cases, effect sizes between impulsive traits and brain variables were small. These findings suggest that, even for studies with large sample sizes and the same participant pool, the replicability of brain-behavior correlations across a 2-year period cannot be assumed. This may be due to developmental changes across the two timepoints or false-positive/false-negative results at one or both timepoints. These results also highlight an array of neuroanatomical structures that may be important to impulsive personality traits across development from childhood into adolescence. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Molecular brain differences and cannabis involvement: A systematic review of positron emission tomography studies

BACKGROUND

An increasing number of studies have used positron emission tomography (PET) to investigate molecular neurobiological differences in individuals who use cannabis. This study aimed to systematically review PET imaging research in individuals who use cannabis or have cannabis use disorder (CUD).

METHODS

Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria, a comprehensive systematic review was undertaken using the PubMed, Scopus, PsycINFO and Web of Science databases.

RESULTS

In total, 20 studies were identified and grouped into three themes: (1) studies of the dopamine system primarily found that cannabis use was associated with abnormal striatal dopamine synthesis capacity, which was in turn correlated with clinical symptoms; (2) studies of the endocannabinoid system found that cannabis use and CUD are associated with lower cannabinoid receptor type 1 availability and global reductions in fatty acid amide hydrolase binding; (3) studies of brain metabolism found that individuals who use cannabis exhibit lower normalized glucose metabolism in both cortical and subcortical brain regions, and reduced cerebral blood flow in the lateral prefrontal cortex during experimental tasks. Heterogeneity across studies prevented meta-analysis.

CONCLUSION

Existing PET imaging research reveals substantive molecular differences in cannabis users in the dopamine and endocannabinoid systems, and in global brain metabolism, although the heterogeneity of designs and approaches is very high, and whether these differences are causal versus consequential is largely unclear.

A machine learning-derived neuroanatomical pattern predicts delayed reward discounting in the Human Connectome Project Young Adult sample

Delayed reward discounting (DRD) is defined as the extent to which person favors smaller rewards that are immediately available over larger rewards available in the future. Higher levels of DRD have been identified in individuals with a wide range of clinical disorders. Although there have been studies adopting larger samples and using only gray matter volume to characterize the neuroanatomical correlates of DRD, it is still unclear whether previously identified relationships are generalizable (out-of-sample) and how cortical thickness and cortical surface area contribute to DRD. In this study, using the Human Connectome Project Young Adult dataset (N = 1038), a machine learning cross-validated elastic net regression approach was used to characterize the neuroanatomical pattern of structural magnetic resonance imaging variables associated with DRD. The results revealed a multi-region neuroanatomical pattern predicted DRD and this was robust in a held-out test set (morphometry-only R² = 3.34%, morphometry + demographics R²  = 6.96%). The neuroanatomical pattern included regions implicated in the default mode network, executive control network, and salience network. The relationship of these regions with DRD was further supported by univariate linear mixed effects modeling results, in which many of the regions identified as part of this pattern showed significant univariate associations with DRD. Taken together, these findings provide evidence that a machine learning-derived neuroanatomical pattern encompassing various theoretically relevant brain networks produces robustly predicts DRD in a large sample of healthy young adults.

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.

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).

Neuroeconomic predictors of smoking cessation outcomes: A preliminary study of delay discounting in treatment-seeking adult smokers

Large proportions of smokers are unsuccessful in evidence-based smoking cessation treatment and identifying prognostic predictors may inform improvements in treatment. Steep discounting of delayed rewards (delay discounting) is a robust predictor of poor smoking cessation outcome, but the underlying neural predictors have not been investigated. Forty-one treatment-seeking adult smokers completed a functional magnetic resonance imaging (fMRI) delay discounting paradigm prior to initiating a 9-week smoking cessation treatment protocol. Behavioral performance significantly predicted treatment outcomes (verified 7-day abstinence, n = 18; relapse, n = 23). Participants in the relapse group exhibited smaller area under the curve (d = 1.10) and smaller AUC was correlated with fewer days to smoking relapse (r = 0.56, p < 0.001) Neural correlates of discounting included medial and dorsolateral prefrontal cortex, posterior cingulate, precuneus and anterior insula, and interactions between choice type and relapse status were present for the dorsolateral prefrontal cortex, precuneus and the striatum. This initial investigation implicates differential neural activity in regions associated with frontal executive and default mode activity, as well as motivational circuits. Larger samples are needed to improve the resolution in identifying the neural underpinnings linking steep delay discounting to smoking cessation.

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.

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.

A methodological checklist for fMRI drug cue reactivity studies: development and expert consensus

Cue reactivity is one of the most frequently used paradigms in functional magnetic resonance imaging (fMRI) studies of substance use disorders (SUDs). Although there have been promising results elucidating the neurocognitive mechanisms of SUDs and SUD treatments, the interpretability and reproducibility of these studies is limited by incomplete reporting of participants' characteristics, task design, craving assessment, scanning preparation and analysis decisions in fMRI drug cue reactivity (FDCR) experiments. This hampers clinical translation, not least because systematic review and meta-analysis of published work are difficult. This consensus paper and Delphi study aims to outline the important methodological aspects of FDCR research, present structured recommendations for more comprehensive methods reporting and review the FDCR literature to assess the reporting of items that are deemed important. Forty-five FDCR scientists from around the world participated in this study. First, an initial checklist of items deemed important in FDCR studies was developed by several members of the Enhanced NeuroImaging Genetics through Meta-Analyses (ENIGMA) Addiction working group on the basis of a systematic review. Using a modified Delphi consensus method, all experts were asked to comment on, revise or add items to the initial checklist, and then to rate the importance of each item in subsequent rounds. The reporting status of the items in the final checklist was investigated in 108 recently published FDCR studies identified through a systematic review. By the final round, 38 items reached the consensus threshold and were classified under seven major categories: 'Participants' Characteristics', 'General fMRI Information', 'General Task Information', 'Cue Information', 'Craving Assessment Inside Scanner', 'Craving Assessment Outside Scanner' and 'Pre- and Post-Scanning Considerations'. The review of the 108 FDCR papers revealed significant gaps in the reporting of the items considered important by the experts. For instance, whereas items in the 'General fMRI Information' category were reported in 90.5% of the reviewed papers, items in the 'Pre- and Post-Scanning Considerations' category were reported by only 44.7% of reviewed FDCR studies. Considering the notable and sometimes unexpected gaps in the reporting of items deemed to be important by experts in any FDCR study, the protocols could benefit from the adoption of reporting standards. This checklist, a living document to be updated as the field and its methods advance, can help improve experimental design, reporting and the widespread understanding of the FDCR protocols. This checklist can also provide a sample for developing consensus statements for protocols in other areas of task-based fMRI.

Structural brain differences do not mediate the relations between sex and personality or psychopathology

INTRODUCTION

Males and females tend to exhibit small but reliable differences in personality traits and indices of psychopathology that are relatively stable over time and across cultures. Previous work suggests that sex differences in brain structure account for differences in domains of cognition.

METHODS

We used data from the Human Connectome Project (N = 1098) to test whether sex differences in brain morphometry account for observed differences in the personality traits neuroticism and agreeableness, as well as symptoms of internalizing and externalizing psychopathology. We operationalized brain morphometry in three ways: omnibus measures (e.g., total gray matter volume), Glasser regions defined through a multi-modal parcellation approach, and Desikan regions defined by structural features of the brain.

RESULTS

Most expected sex differences in personality, psychopathology, and brain morphometry were observed, but the statistical mediation analyses were null: sex differences in brain morphometry did not account for sex differences in personality or psychopathology.

CONCLUSIONS

Men and women tend to exhibit meaningful differences in personality and psychopathology, as well as in omnibus morphometry and regional morphometric differences as defined by the Glasser and Desikan atlases, but these morphometric differences appear unrelated to the psychological differences.

Searching high and low for meaningful and replicable morphometric correlates of personality

Recent personality neuroscience research in large samples suggests that personality traits tend to bear null-to-small relations to morphometric (i.e., brain structure) regions of interest (ROIs). In this preregistered, two-part study using Human Connectome Project data (N = 1,105), we address the possibility that these null-to-small relations are due, in part, to the "level" (i.e., hierarchical placement) of personality and/or morphometry examined. We used a Five-Factor Model framework and operationalized personality in terms of meta-traits, domains, facets, and items; we operationalized morphometry in terms of omnibus measures (e.g., total brain volume), and cortical thickness and area in the ROIs of the Desikan and Destrieux atlases. First, we compared the patterns of effect sizes observed between these levels using mixed effects modeling. Second, we used a machine learning framework for estimating out-of-sample predictability. Results highlight that personality-morphometry relations are generally null-to-small no matter how they are operationalized. Relatively, the largest mean effect sizes were observed at the domain level of personality, but the largest individual effect sizes were observed at the facet and item level, particularly for the Ideas facet of Openness and its constituent items. The largest effect sizes observed were at the omnibus level of morphometry, and predictive models containing only omnibus variables were comparably predictive to models including both omnibus variable and ROIs. We conclude by encouraging researchers to search across levels of analysis when investigating relations between personality and morphometry and consider prioritizing omnibus measures, which appear to yield the largest and most consistent effects. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Recalibrating expectations about effect size: A multi-method survey of effect sizes in the ABCD study

Effect sizes are commonly interpreted using heuristics established by Cohen (e.g., small: r = .1, medium r = .3, large r = .5), despite mounting evidence that these guidelines are mis-calibrated to the effects typically found in psychological research. This study's aims were to 1) describe the distribution of effect sizes across multiple instruments, 2) consider factors qualifying the effect size distribution, and 3) identify examples as benchmarks for various effect sizes. For aim one, effect size distributions were illustrated from a large, diverse sample of 9/10-year-old children. This was done by conducting Pearson's correlations among 161 variables representing constructs from all questionnaires and tasks from the Adolescent Brain and Cognitive Development Study® baseline data. To achieve aim two, factors qualifying this distribution were tested by comparing the distributions of effect size among various modifications of the aim one analyses. These modified analytic strategies included comparisons of effect size distributions for different types of variables, for analyses using statistical thresholds, and for analyses using several covariate strategies. In aim one analyses, the median in-sample effect size was .03, and values at the first and third quartiles were .01 and .07. In aim two analyses, effects were smaller for associations across instruments, content domains, and reporters, as well as when covarying for sociodemographic factors. Effect sizes were larger when thresholding for statistical significance. In analyses intended to mimic conditions used in "real-world" analysis of ABCD data, the median in-sample effect size was .05, and values at the first and third quartiles were .03 and .09. To achieve aim three, examples for varying effect sizes are reported from the ABCD dataset as benchmarks for future work in the dataset. In summary, this report finds that empirically determined effect sizes from a notably large dataset are smaller than would be expected based on existing heuristics.

Baseline brain function in the preadolescents of the ABCD Study

The Adolescent Brain Cognitive Development (ABCD) Study® is a 10-year longitudinal study of children recruited at ages 9 and 10. A battery of neuroimaging tasks are administered biennially to track neurodevelopment and identify individual differences in brain function. This study reports activation patterns from functional MRI (fMRI) tasks completed at baseline, which were designed to measure cognitive impulse control with a stop signal task (SST; N = 5,547), reward anticipation and receipt with a monetary incentive delay (MID) task (N = 6,657) and working memory and emotion reactivity with an emotional N-back (EN-back) task (N = 6,009). Further, we report the spatial reproducibility of activation patterns by assessing between-group vertex/voxelwise correlations of blood oxygen level-dependent (BOLD) activation. Analyses reveal robust brain activations that are consistent with the published literature, vary across fMRI tasks/contrasts and slightly correlate with individual behavioral performance on the tasks. These results establish the preadolescent brain function baseline, guide interpretation of cross-sectional analyses and will enable the investigation of longitudinal changes during adolescent development.

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.

Investigating the neural substrates of Antagonistic Externalizing and social-cognitive Theory of Mind: an fMRI examination of functional activity and synchrony

Recently developed quantitative models of psychopathology (i.e., Hierarchical Taxonomy of Psychopathology) identify an Antagonistic Externalizing spectrum that captures the psychological disposition toward criminal and antisocial behavior. The purpose of the present study was to examine relations between Antagonistic psychopathology (and associated Five-Factor model Antagonism/Agreeableness) and neural functioning related to social-cognitive Theory of Mind using a large sample (N = 973) collected as part of the Human Connectome Project (Van Essen et al., 2013a). No meaningful relations between Antagonism/Antagonistic Externalizing and Theory of Mind-related neural activity or synchrony were observed (p < .005). We conclude by outlining methodological considerations (e.g., validity of social cognition task and low test-retest reliability of functional biomarkers) that may account for these null results, and present recommendations for future research.

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.

Recent cannabis use is associated with smaller hippocampus volume: High-resolution segmentation of structural subfields in a large non-clinical sample

There is mixed evidence that individuals who use cannabis have reduced hippocampal and amygdalar gray matter volume, potentially because of small sample sizes and imprecise morphological characterization. New automated segmentation procedures have improved the measurement of these structures and allow better examination of their subfields, which have been linked to distinct aspects of memory and emotion. The current study applies this new segmentation procedure to the Human Connectome Project Young Adult dataset (N = 1080) to investigate associations of cannabis use with gray matter volume in the hippocampus and amygdala. Results revealed significant bilateral inverse associations of hippocampal volume with recent cannabis use (THC+ urine drug screen; P < .005). Hippocampal subfield analyses indicated these associations were primarily driven by the head of the hippocampus, the first section of the cornu amonis (CA1), the subicular complex, and the molecular layer of the hippocampus. No associations were detected for age of cannabis initiation, the frequency of cannabis use across the lifespan, or the lifetime presence of cannabis use disorder. In one of the largest studies to date, these results support the hypothesis that recent cannabis use is linked to reduced hippocampal volume, but that this effect may dissipate following prolonged abstinence. Furthermore, these results clarify the specific subfields which may be most associated with recent cannabis use.

Cannabis use, cognitive performance, and symptoms of attention deficit/hyperactivity disorder in community adults

There is some evidence that cannabis use is associated with lower cognitive performance and symptoms of attention-deficit/hyperactivity disorder (ADHD), but the existing literature is relatively inconsistent, potentially due to small samples in previous studies. Using a dimensional design, the current study examined cannabis use severity and age of first cannabis use in relation to neurocognitive performance and ADHD symptoms in a large sample of community adults (N = 1,008, M_age = 38.49, 56.0% female). Participants were assessed for cannabis involvement, neurocognitive performance, and ADHD symptoms. Dimensional relationships were investigated using multiple hierarchical regressions. Using a covariate model of age, income, sex, alcohol use, and tobacco use, severity of cannabis involvement was significantly associated with greater endorsement of both hyperactive-impulsive and inattentive ADHD symptoms but not with any other cognitive measures in the full sample. Exploratory analyses found greater cannabis use severity was associated with digit span forward and hyperactive ADHD symptoms in young adults (n = 371) and was associated with greater delay discounting, hyperactive, and impulsive ADHD symptoms in high-risk cannabis users (n = 161). Age of first cannabis use was not significantly associated with any neurocognitive variables or ADHD symptomatology in all analyses. The current findings provide evidence of a link between current cannabis misuse and both hyperactive and inattentive ADHD symptoms in general, and possible links to attention and impulsive delay discounting in subgroups of cannabis users, but no associations in other cognitive domains or implication of earlier initiation of cannabis use in relation to cognitive performance or ADHD. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

An fMRI investigation of the relations between Extraversion, internalizing psychopathology, and neural activation following reward receipt in the Human Connectome Project sample

Quantitative models of psychopathology (i.e., HiTOP) propose that personality and psychopathology are intertwined, such that the various processes that characterize personality traits may be useful in describing and predicting manifestations of psychopathology. In the current study, we used data from the Human Connectome Project (N = 1050) to investigate neural activation following receipt of a reward during an fMRI task as one shared mechanism that may be related to the personality trait Extraversion (specifically its sub-component Agentic Extraversion) and internalizing psychopathology. We also conducted exploratory analyses on the links between neural activation following reward receipt and the other Five-Factor Model personality traits, as well as separate analyses by gender. No significant relations (p < .005) were observed between any personality trait or index of psychopathology and neural activation following reward receipt, and most effect sizes were null to very small in nature (i.e., r < |.05|). We conclude by discussing the appropriate interpretation of these null findings, and provide suggestions for future research that spans psychological and neurobiological levels of analysis.

Neuroanatomical correlates of impulsive traits in children aged 9 to 10

Impulsivity refers to a set of traits that are generally negatively related to critical domains of adaptive functioning and are core features of numerous psychiatric disorders. The current study examined the gray and white matter correlates of five impulsive traits measured using an abbreviated version of the UPPS-P (Urgency, (lack of) Premeditation, (lack of) Perseverance, Sensation-Seeking, Positive Urgency) impulsivity scale in children aged 9 to 10 (N = 11,052) from the Adolescent Brain and Cognitive Development (ABCD) study. Linear mixed effect models and elastic net regression were used to examine features of regional gray matter and white matter tractography most associated with each UPPS-P scale; intraclass correlations were computed to examine the similarity of the neuroanatomical correlates among the scales. Positive Urgency showed the most robust association with neuroanatomy, with similar but less robust associations found for Negative Urgency. Perseverance showed little association with neuroanatomy. Premeditation and Sensation Seeking showed intermediate associations with neuroanatomy. Critical regions across measures include the dorsolateral prefrontal cortex, lateral temporal cortex, and orbitofrontal cortex; critical tracts included the superior longitudinal fasciculus and inferior fronto-occipital fasciculus. Negative Urgency and Positive Urgency showed the greatest neuroanatomical similarity. Some UPPS-P traits share neuroanatomical correlates, while others have distinct correlates or essentially no relation to neuroanatomy. Neuroanatomy tended to account for relatively little variance in UPPS-P traits (i.e., Model R2 < 1%) and effects were spread throughout the brain, highlighting the importance of well powered samples. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

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.

Functional and structural neuroimaging studies of delayed reward discounting in addiction: A systematic review

Given the robust behavioral association between delayed reward discounting (DRD) and addictive behavior, there is an expanding literature investigating the neural correlates of this relationship. The objective of this systematic review was to characterize and critically appraise the existing literature examining the neural correlates of DRD in individuals exhibiting addictive behavior using functional and structural MRI (fMRI/MRI) and to do so through the lens of the neural networks implicated in addiction. Using a systematic search strategy, 20 studies were identified, with 12 focusing on task fMRI, 4 focusing on functional connectivity fMRI, and 4 focusing on structural MRI. Behaviorally, significantly steeper DRD was present in individuals with addictive disorders across studies, reproducing earlier findings. Among individuals with addictive disorders, there was substantial evidence of greater neural activity in the executive control network during choices for larger-delayed rewards (delayed gratification) relative to choices for smaller-immediate rewards (immediate gratification), particularly in dorsolateral prefrontal cortex, as well as moderate evidence of greater recruitment of the default mode, salience, and reward valuation networks during larger-delayed choices. In functional connectivity fMRI studies, there was moderate evidence for greater connectivity between the executive control, salience, and default mode networks in individuals exhibiting addictive behavior. Structural MRI studies reported highly heterogeneous findings and no consistent conclusions could be drawn. As a whole, this review suggests consistent differences in neural activation and connectivity relating to DRD in individuals with addictive disorders. It also reveals heterogeneity of methods and findings in this line of inquiry. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Adverse Childhood Experiences and Amygdalar Reduction: High-Resolution Segmentation Reveals Associations With Subnuclei and Psychiatric Outcomes

The aim of the present study was 2-fold: (1) to utilize improved amygdala segmentation and exploratory factor analysis to characterize the latent volumetric structure among amygdala nuclei and (2) to assess the effect of adverse childhood experiences (ACEs) on amygdalar morphometry and current psychiatric symptoms. To investigate these aims, structural (T1) MRI and self-report data were obtained from 119 emerging adults. Regression analysis showed that higher ACE scores were related to reduced volume of the right, but not the left, amygdalar segments. Further, exploratory factor analysis yielded a two-factor structure, basolateral and central-medial nuclei of the right amygdala. Stractual equation modeling analyses revealed that higher ACE scores were significantly related to a reduced volume of the right basolateral and central-medial segments. Furthermore, reduction in the right basolateral amygdala was associated with increased anxiety, depressive symptoms, and alcohol use. This association supports an indirect effect between early adversity and psychiatric problems via reduced right basolateral amygdalar volume. The high-resolution segmentation results reveal a latent structure among amygdalar nuclei, which is consistent with prior work conducted in nonhuman mammals. These findings extend previous reports linking early adversity, right amygdala volume, and psychopathology.

Cannabis involvement and neuropsychological performance: findings from the Human Connectome Project

BACKGROUND

There is evidence that heavy cannabis use is associated with decrements in cognitive performance, but findings are mixed and studies are often limited by small sample sizes and narrow adjustment for potential confounding variables. In a comparatively large sample, the current study examined associations between multiple indicators of cannabis use in relation to performance on a variety of neuropsychological tasks.

METHODS

Participants were 1121 adults (54% female) enrolled in the Human Connectome Project. Cannabis involvement comprised recent cannabis use (positive tetrahydrocannabinol screen), total number of lifetime uses, cannabis use disorder and age at first use. The neuropsychological battery comprised performance in episodic memory, fluid intelligence, attention, working memory, executive function, impulsive decision-making, processing speed and psychomotor dexterity. Covariates were age, sex, income, family structure and alcohol and tobacco use.

RESULTS

Positive urinary tetrahydrocannabinol status was associated with worse performance in episodic memory and processing speed, and positive cannabis use disorder status was associated with lower fluid intelligence (all p < 0.005). No other significant associations were present.

LIMITATIONS

The sample was limited to young adults aged 22–36 years. The measures of cannabis involvement were relatively coarse.

CONCLUSION

Beyond an array of potential confounders, recent cannabis use was associated with deficits in memory and psychomotor performance, and cannabis use disorder was associated with lower overall cognitive functioning in a large normative sample of adults. The findings pertaining to recent use have particular relevance for occupational settings.

Deficits in executive function and suppression of default mode network in obesity

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Using a case-control design, obese individuals exhibited worse performance across a number of neurocognitive tests compared to healthy BMI controls, particularly in tasks measuring executive function.

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In a functional MRI N-Back task measuring working memory performance, obese individuals exhibited greater BOLD activity in task-negative brain regions, suggesting deficits in suppression of the default mode network (DMN).

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Obese individuals exhibited differences in cortical morphometry in frontal, temporal, and parietal regions linked to executive function.

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Integrative analyses implicated aspects of behavioral performance, inefficient DMN suppression, and cortical morphometry.

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Results suggest that obesity is associated with a diverse range of functional, structural and behavioural deficits in executive functioning; longitudinal studies are needed to clarify causal versus consequential influences.

Background

Although nutritional and metabolic factors are well established in obesity, neurocognitive determinants are less understood. Using data from the Human Connectome Project, this study concurrently investigated neurocognitive performance, neural activation during a working memory task, and cortical brain morphometry in relation to obesity in a group of young adults, 22–35 years old.

Methods

Using a case-control design, obese individuals (n = 243, body mass index [BMI] ≥ 30 kg/m²) were compared to a control group of lean BMI individuals (n = 469, BMI = 18–24.9 kg/m²). Performance tests comprised a battery of behavioral neurocognitive assessments. Neural activity was measured as blood-oxygenation-level-dependent (BOLD) activity during an N-Back task using functional magnetic resonance imaging (fMRI). Cortical morphometry included indices of volume, thickness, and surface area.

Results

Relative to the control group, the obese group exhibited significantly worse performance in terms of the National Institutes of Health Toolkit (NIH) 9-Hole Peg Board, Penn Working Memory Test, Delay Discounting, Penn Progressive Matrices, NIH Picture Vocabulary Test, Dimensional Change Card Sort Test and the in-scanner N-Back working memory test (FDR-corrected ps<0.05; ds = 0.231–0.405). The obese group also exhibited significantly greater BOLD activation in N-Back task-negative regions, including the ventromedial prefrontal cortex, posterior cingulate, and right precentral gyrus (FDR-corrected ps<0.05). Supplemental functional connectivity analyses provided evidence that the implicated regions were part of the default mode network. Significant differences in morphometry were present in the medial orbitofrontal cortex, rostral anterior cingulate cortex, inferior and superior parietal gyri, and temporal pole (FDR-corrected p<0.001). A data-driven integrative model classified 73.8% of participants correctly.

Conclusions and Relevance

This multimodal investigation suggests diverse aspects of neurocognition are associated with obesity, particularly implicating deficits in executive function and ineffective suppression of the default mode network.

The quandary of covarying: A brief review and empirical examination of covariate use in structural neuroimaging studies on psychological variables

Although covarying for potential confounds or nuisance variables is common in psychological research, relatively little is known about how the inclusion of covariates may influence the relations between psychological variables and indices of brain structure. In Part 1 of the current study, we conducted a descriptive review of relevant articles from the past two years of NeuroImage in order to identify the most commonly used covariates in work of this nature. Age, sex, and intracranial volume were found to be the most commonly used covariates, although the number of covariates used ranged from 0 to 14, with 37 different covariate sets across the 68 models tested. In Part 2, we used data from the Human Connectome Project to investigate the degree to which the addition of common covariates altered the relations between individual difference variables (i.e., personality traits, psychopathology, cognitive tasks) and regional gray matter volume (GMV), as well as the statistical significance of values associated with these effect sizes. Using traditional and random sampling approaches, our results varied widely, such that some covariate sets influenced the relations between the individual difference variables and GMV very little, while the addition of other covariate sets resulted in a substantially different pattern of results compared to models with no covariates. In sum, these results suggest that the use of covariates should be critically examined and discussed as part of the conversation on replicability in structural neuroimaging. We conclude by recommending that researchers pre-register their analytic strategy and present information on how relations differ based on the inclusion of covariates.

Associations Between Drinking and Cortical Thickness in Younger Adult Drinkers: Findings From the Human Connectome Project

BACKGROUND

Previous neuroimaging studies examining relations between alcohol misuse and cortical thickness have revealed that increased drinking quantity and alcohol-related problems are associated with thinner cortex. Although conflicting regional effects are often observed, associations are generally localized to frontal regions (e.g., dorsolateral prefrontal cortex [DLPFC], inferior frontal gyrus [IFG], and anterior cingulate cortex). Inconsistent findings may be attributed to methodological differences, modest sample sizes, and limited consideration of sex differences.

METHODS

This study examined neuroanatomical correlates of drinking quantity and heavy episodic drinking in a large sample of younger adults (N = 706; Mage  = 28.8; 51% female) using magnetic resonance imaging data from the Human Connectome Project. Exploratory analyses examined neuroanatomical correlates of executive function (flanker task) and working memory (list sorting).

RESULTS

Hierarchical linear regression models (controlling for age, sex, education, income, smoking, drug use, twin status, and intracranial volume) revealed significant inverse associations between drinks in past week and frequency of heavy drinking and cortical thickness in a majority of regions examined. The largest effect sizes were found for frontal regions (DLPFC, IFG, and the precentral gyrus). Follow-up regression models revealed that the left DLPFC was uniquely associated with both drinking variables. Sex differences were also observed, with significant effects largely specific to men.

CONCLUSIONS

This study adds to the understanding of brain correlates of alcohol use in a large, gender-balanced sample of younger adults. Although the cross-sectional methodology precludes causal inferences, these findings provide a foundation for rigorous hypothesis testing in future longitudinal investigations.

Neurocompensatory Effects of the Default Network in Older Adults

The hemispheric asymmetry reduction in older adults (HAROLD) is a neurocompensatory process that has been observed across several cognitive functions but has not yet been examined in relation to task-induced relative deactivations of the default mode network. The present study investigated the presence of HAROLD effects specific to neural activations and deactivations using a functional magnetic resonance imaging (fMRI) n-back paradigm. It was hypothesized that HAROLD effects would be identified in relative activations and deactivations during the paradigm, and that they would be associated with better 2-back performance. Forty-five older adults (M age = 63.8; range = 53-83) were administered a verbal n-back paradigm during fMRI. For each participant, the volume of brain response was summarized by left and right frontal regions of interest, and laterality indices (LI; i.e., left/right) were calculated to assess HAROLD effects. Group level results indicated that age was significantly and negatively correlated with LI (i.e., reduced left lateralization) for deactivations, but positively correlated with LI (i.e., increased left lateralization) for activations. The relationship between age and LI for deactivation was significantly moderated by performance level, revealing a stronger relationship between age and LI at higher levels of 2-back performance. Findings suggest that older adults may employ neurocompensatory processes specific to deactivations, and task-independent processes may be particularly sensitive to age-related neurocompensation.

Cortical morphometry of the five-factor model of personality: findings from the Human Connectome Project full sample

This study is a replication of an existing large study (N = 507) on the surface-based morphometric correlates of five-factor model (FFM) personality traits. The same methods were used as the original study in another large sample drawn from the same population (N = 597) with results then being aggregated from both samples (N = 1104), providing the largest investigation into the neuroanatomical correlates of FFM personality traits to date. Clusters of association between brain morphometry and each FFM trait are reported. For neuroticism, agreeableness, openness and conscientiousness clusters of association were found in the dorsolateral prefrontal cortex for at least one morphometric index. Morphometry in various other regions was also associated with each personality trait. While some regions found in the original study were confirmed in the replication and full samples, others were not, highlighting the importance of replicating even high-quality, well-powered studies. Effect sizes were very similar in the replication and whole samples as those found in the original study. As a whole, the current results provide the strongest evidence to date on the neuroanatomical correlates of personality and highlights challenges in using this approach to understanding the neural correlates of personality.

Urinary tetrahydrocannabinol is associated with poorer working memory performance and alterations in associated brain activity

Worldwide, cannabis is one of the most widely used psychoactive substances and cannabis use has been implicated in poorer performance in several cognitive domains, including working memory (WM). However, the neural mechanisms underlying these WM decrements are not well understood and the current study investigated the association of cannabis involvement with WM performance and associated neural activation in the Human Connectome Project (N = 1038). Multiple indicators of cannabis involvement were examined in relation to behavioral performance and brain activity in a visual N-back task using functional magnetic resonance imaging. A positive urine drug screen for tetrahydocannabinol (THC+ status), the principal psychoactive constituent in cannabis, was associated with worse WM performance and differential brain response in areas previously linked to WM performance. Furthermore, decreases in blood-activation-level-dependent (BOLD) signal in WM task-positive brain regions and increases in task-negative regions mediated the relationship between THC+ status and WM performance. In contrast, WM performance and BOLD response during the N-back task were not associated with total lifetime cannabis use, age of first use, or other indicators of involvement, suggesting that the effects of cannabis on WM were short-term residual effects, rather than long-term persistent effects. These findings elucidate differential influences of cannabis involvement on neurocognition and have significant potential implications for occupational performance in diverse settings.

No evidence for morphometric associations of the amygdala and hippocampus with the five-factor model personality traits in relatively healthy young adults

Despite the important functional role of the amygdala and hippocampus in socioemotional functioning, there have been limited adequately powered studies testing how the structure of these regions relates to putatively relevant personality traits such as neuroticism. Additionally, recent advances in MRI analysis methods provide unprecedented accuracy in measuring these structures and enable segmentation into their substructures. Using the new FreeSurfer amygdala and hippocampus segmentation pipelines with the full Human Connectome Project sample (N = 1105), the current study investigated whether the morphometry of these structures is associated with the five-factor model (FFM) personality traits in a sample of relatively healthy young adults. Drawing from prior findings, the following hypotheses were tested: 1) amygdala and hippocampus gray matter volume would be associated with neuroticism, 2) CA2/3 and dentate gyrus would account for the relationship of the hippocampus with neuroticism, and 3) amygdala gray matter volume would be inversely associated with extraversion. Exploratory analyses were conducted investigating potential associations between all of the FFM traits and the structure of the hippocampus and amygdala and their subregions. Despite some previous positive findings of whole amygdala and hippocampus with personality traits and related psychopathology (e.g., depression), the current results indicated no relationships between the any of the brain regions and the FFM personality traits. Given the large sample and utilization of sophisticated analytic methodology, the current study suggests no association of amygdala and hippocampus morphometry with major domains of personality.

Neural correlates of tobacco cue reactivity predict duration to lapse and continuous abstinence in smoking cessation treatment

It has been hypothesized that neural reactivity to drug cues in certain limbic/paralimbic regions of the brain is an indicator of addiction severity and a marker for likelihood of success in treatment. To address this question, in the current study, 32 participants (44 percent female) completed a functional magnetic resonance imaging cigarette cue exposure paradigm 2 hours after smoking, and then enrolled in a 9-week smoking cessation treatment program. Neural activation to smoking cues was measured in five a priori defined limbic/paralimbic regions previously implicated with cue reactivity across substances. These included regions of the ventral striatum, anterior cingulate cortex and amygdala. Cox proportional hazard modeling was conducted to predict the number of days to first smoking lapse by using neural activation in these regions. Greater neural activation during pre-treatment exposure to smoking cues in the right ventral striatum, the left amygdala, and the anterior cingulate was associated with longer periods of abstinence following cessation. A similar pattern was present for continuous abstinence for the full duration of treatment. While baseline levels of nicotine dependence were strongly associated with treatment outcome, activation in the right ventral striatum predicted duration of abstinence beyond level of nicotine dependence. These results suggest that pre-treatment reactivity to smoking cues in areas associated with cue reactivity may be associated with successfully maintaining abstinence during treatment. This is consistent with models that propose that as addiction becomes more severe, motivational processing shifts from regions that subserve reward salience and learning to regions responsible motor behavior and habit learning.

Negative urgency moderates reactivity to laboratory stress inductions

Impulsive personality traits refer to a group of self-reported dispositions about self-regulatory capacity, several of which have been linked to diverse forms of psychopathology. One of these is negative urgency (NUR), the propensity to act out when experiencing negative emotions, which has been linked to substance use disorders and eating disorders. However, few laboratory studies have investigated the extent to which self-reported NUR relates to an individual's in vivo emotional and behavioral responses. Harmonizing two archival data sets on alcohol and high-energy-dense (HED) food motivation, the current study investigated NUR as a moderator of reactivity to stressful situations elicited by two commonly used stress manipulations, the Trier Social Stress Test and a stress imagery induction. A sample of 148 adults was assessed for NUR, severity of alcohol misuse or binge eating, and measures of negative affect and psychophysiological arousal (i.e., heart rate and blood pressure) prior to and following one of the two manipulations. In addition, a behavioral multiple-choice procedure assessing the relative reinforcing value of alcohol or HED foods followed the manipulations. As predicted, NUR positively moderated the effects of stress induction on self-reported negative affect and relative reinforcing value, although not arousal. Individuals exhibiting elevated NUR also exhibited greater alcohol misuse, although not greater binge eating severity. These findings provide in vivo validation of the construct of NUR and its measurement using the UPPS-P Impulsive Behavior Scale. More broadly, these findings inform the understanding of deficits that are characteristic of self-regulatory disorders. (PsycINFO Database Record

The Effects of Experimental Manipulation of Sleep Duration on Neural Response to Food Cues

Despite growing literature on neural food cue responsivity in obesity, little is known about how the brain processes food cues following partial sleep deprivation and whether short sleep leads to changes similar to those observed in obesity. We used functional magnetic resonance imaging (fMRI) to test the hypothesis that short sleep leads to increased reward-related and decreased inhibitory control-related processing of food cues.In a within-subject design, 30 participants (22 female, mean age = 36.7 standard deviation = 10.8 years, body mass index range 20.4-40.7) completed four nights of 6 hours/night time-in-bed (TIB; short sleep) and four nights of 9 hours/night TIB (long sleep) in random counterbalanced order in their home environments. Following each sleep condition, participants completed an fMRI scan while viewing food and nonfood images.A priori region of interest analyses revealed increased activity to food in short versus long sleep in regions of reward processing (eg, nucleus accumbens/putamen) and sensory/motor signaling (ie, right paracentral lobule, an effect that was most pronounced in obese individuals). Contrary to the hypothesis, whole brain analyses indicated greater food cue responsivity during short sleep in an inhibitory control region (right inferior frontal gyrus) and ventral medial prefrontal cortex, which has been implicated in reward coding and decision-making (false discovery rate corrected q = 0.05).These findings suggest that sleep restriction leads to both greater reward and control processing in response to food cues. Future research is needed to understand the dynamic functional connectivity between these regions during short sleep and whether the interplay between these neural processes determines if one succumbs to food temptation.

Distinct functional and structural neural underpinnings of working memory

Working memory (WM), the short-term abstraction and manipulation of information, is an essential neurocognitive process in daily functioning. Few studies have concurrently examined the functional and structural neural correlates of WM and the current study did so to characterize both overlapping and unique associations. Participants were a large sample of adults from the Human Connectome Project (N = 1064; 54% female) who completed an in-scanner visual N-back WM task. The results indicate a clear dissociation between BOLD activation during the WM task and brain structure in relation to performance. In particular, while activation in the middle frontal gyrus was positively associated with WM performance, cortical thickness in this region was inversely associated with performance. Additional unique associations with WM were BOLD activation in superior parietal lobule, cingulate, and fusiform gyrus and gray matter volume in the orbitofrontal cortex and cuneus. Across findings, substantially larger effects were observed for functional associations relative to structural associations. These results provide further evidence implicating frontoparietal subunits of the brain in WM. Moreover, these findings reveal the distinct, and in some cases opposing, roles of brain structure and neural activation in WM, highlighting the lack of homology between structure and function in relation to cognition.

Neuroanatomical foundations of delayed reward discounting decision making

Resolving tradeoffs between smaller immediate rewards and larger delayed rewards is ubiquitous in daily life and steep discounting of future rewards is associated with several psychiatric conditions. This form of decision-making is referred to as delayed reward discounting (DRD) and the features of brain structure associated with DRD are not well understood. The current study characterized the relationship between gray matter volume (GMV) and DRD in a sample of 1038 healthy adults (54.7% female) using cortical parcellation, subcortical segmentation, and voxelwise cortical surface-based group analyses. The results indicate that steeper DRD was significantly associated with lower total cortical GMV, but not subcortical GMV. In parcellation analyses, less GMV in 20 discrete cortical regions was associated with steeper DRD. Of these regions, only GMV in the middle temporal gyrus (MTG) and entorhinal cortex (EC) were uniquely associated with DRD. Voxelwise surface-based analyses corroborated these findings, again revealing significant associations between steeper DRD and less GMV in the MTG and EC. To inform the roles of MTG and EC in DRD, connectivity analysis of resting state data (N = 1003) using seed regions from the structural findings was conducted. This revealed that spontaneous activity in the MTG and EC was correlated with activation in the ventromedial prefrontal cortex, posterior cingulate cortex, and inferior parietal lobule, regions associated with the default mode network, which involves prospection, self-reflective thinking and mental simulation. Furthermore, meta-analytic co-activation analysis using Neurosynth revealed a similar pattern across 11,406 task-fMRI studies. Collectively, these findings provide robust evidence that morphometric characteristics of the temporal lobe are associated with DRD preferences and suggest it may be because of their role in mental activities in common with default mode activity.

Delay discounting differences in brain activation, connectivity, and structure in individuals with addiction: a systematic review protocol

BACKGROUND

Delayed reward discounting (DRD), the degree to which future rewards are discounted relative to immediate rewards, is used as an index of impulsive decision-making and has been associated with a number of problematic health behaviors. Given the robust behavioral association between DRD and addictive behavior, there is an expanding literature investigating the differences in the functional and structural correlates of DRD in the brain between addicted and healthy individuals. However, there has yet to be a systematic review which characterizes differences in regional brain activation, functional connectivity, and structure and places them in the larger context of the DRD literature. The objective of this systematic review is to summarize and critically appraise the existing literature examining differences between addicted and healthy individuals in the neural correlates of DRD using magnetic resonance imaging (MRI) or functional magnetic resonance imaging (fMRI).

METHODS

A systematic search strategy will be implemented that uses Boolean search terms in PubMed/MEDLINE and PsycINFO, as well as manual search methods, to identify the studies comprehensively. This review will include studies using MRI or fMRI in humans to directly compare brain activation, functional connectivity, or structure in relation to DRD between addicted and healthy individuals or continuously assess addiction severity in the context of DRD. Two independent reviewers will determine studies that meet the inclusion criteria for this review, extract data from included studies, and assess the quality of included studies using the Grading of Recommendations Assessment, Development and Evaluation framework. Then, narrative review will be used to explicate the differences in structural and functional correlates of DRD implicated by the literature and assess the strength of evidence for this conclusion.

DISCUSSION

This review will provide a needed critical exegesis of the MRI studies that have been conducted investigating brain differences in addictive behavior in relation to healthy samples in the context of DRD. This will provide clarity on the elements of neural activation, connectivity, and structure that are most implicated in the differences in DRD seen in addicted individuals.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42017056857.

Neural correlates of graphic cigarette warning labels predict smoking cessation relapse

Exposure to graphic warning labels (GWLs) on cigarette packaging has been found to produce heightened activity in brain regions central to emotional processing and higher-order cognitive processes. The current study extends this literature by using functional magnetic resonance imaging (fMRI) to investigate neural activation in response to GWLs and use it to predict relapse in an evidence-based smoking cessation treatment program. Participants were 48 treatment-seeking nicotine-dependent smokers who completed an fMRI paradigm in which they were exposed to GWLs, text-only warning labels (TOLs), and matched control stimuli. Subsequently, they enrolled in smoking cessation treatment and their smoking behavior was monitored. Activation in bilateral amygdala, right dorsolateral prefrontal cortex, right inferior frontal gyrus, left medial temporal gyrus, bilateral occipital lobe, and bilateral fusiform gyrus was greater during GWLs than TOLs. Neural response in the ventromedial prefrontal cortex (vmPFC) during exposure to GWLs (relative to a visual control image) predicted relapse during treatment beyond baseline demographic and dependence severity, but response in the amygdala to GWLs did not. These findings suggest that neurocognitive processes in the vmPFC may be critical to understanding how GWL's induce behavior change and may be useful as a predictor of smoking cessation treatment prognosis.

The substitutability of cigarettes and food: A behavioral economic comparison in normal weight and overweight or obese smokers

Obesity and cigarette smoking contribute to a multitude of preventable deaths in the United States and eating and smoking behavior may influence each other. The field of behavioral economics integrates principles from psychology and economics and permits systematic examination of how commodities interrelate with one another. Using this framework, the current study evaluated the effects of rising food and cigarette prices on consumption to investigate their substitutability and their relationship to BMI and associated variables. Behavioral economics categorizes commodities as substitutable when the consumption of one increases as a function of a price increase in the other. Smokers (N = 86) completed a 2-part hypothetical task in which money was allocated to purchase cigarettes and fast-food-style reinforcers (e.g., hamburgers, ice cream) at various prices. Results indicated that food and cigarettes were not substitutes for one another (cross-price elasticity coefficients < .20). Food purchases were independent of cigarette price, whereas cigarette purchases decreased as food price rose. Cross-price elasticity coefficients were significantly associated with confidence in one's ability to control weight without smoking (rs = -.23 and .29), but not BMI (rs = .04 and .04) or postcessation weight concerns (rs = -.05 and .12). Perceived ability to manage weight without cigarettes may influence who substitutes food for cigarettes when quitting. In addition, given observed decreases in purchases of both commodities as food prices increased, these findings imply that greater taxation of fast-food-style reinforcers could potentially reduce consumption of these foods and also cigarettes among smokers. (PsycINFO Database Record

Lower subcortical gray matter volume in both younger smokers and established smokers relative to non-smokers

Although established adult smokers with long histories of nicotine dependence have lower neural tissue volume than non-smokers, it is not clear if lower regional brain volume is also observed in younger, less established smokers. The primary goal of this study was to investigate neural tissue volume in a large group of smokers and non-smokers, with a secondary goal of measuring the impact of age on these effects. We used voxel-based morphometry to compare regional gray matter volume in 118 individuals (59 smokers, 59 age- and gender-matched non-smokers). Younger smokers had significantly lower gray matter volume in the left thalamus and the left amygdala than their non-smoking peers (family-wise error-corrected clusters, P < 0.05). There was no correlation between smoking use variables and tissue volume among younger smokers. Established smokers had significantly lower gray matter volume than age-matched non-smokers in the insula, parahippocampal gyrus and pallidum. Medial prefrontal cortex gray matter volume was negatively correlated with pack-years of smoking among the established smokers, but not the younger smokers. These data reveal that regional tissue volume differences are not limited exclusively to established smokers. Deficits in young adults indicate that cigarette smoking may either be deleterious to the thalamus and amygdala at an earlier age than previously reported, or that pre-existing differences in these areas may predispose individuals to the development of nicotine dependence.

Initial Development of a Brief Behavioral Economic Assessment of Alcohol Demand

Due to difficulties with definition and measurement, the role of conscious craving in substance use disorders remains contentious. To address this, behavioral economics is increasingly being used to quantify aspects of an individual's acute motivation to use a substance. Doing so typically involves the use of a purchase task, in which participants make choices about consuming alcohol or other substances at various prices and multiple indices of alcohol demand are generated. However, purchase tasks can be limited by the time required to administer and score them. In the current study, a brief 3-item measure, designed to capture three important indices of demand that are derived from demand curve modeling (intensity, O_max, and breakpoint), was investigated in a group of 84 heavy drinkers. Participants underwent a cue-reactivity paradigm that is established to increase both conscious craving and alcohol demand on traditional purchase tasks. All three indices of demand for alcohol measured using the abbreviated measure increased significantly in response to alcohol cues, analogous to what has been observed using a traditional purchase task. Additionally, the correlations between these indices and subjective craving were modest-to-moderate, as has been found in studies comparing craving to the indices derived from purchase tasks. These findings suggest that this abbreviated measure may be a useful and efficient way to capture important and distinct aspects of motivation for alcohol. If these results are confirmed, this measure may be able to help increase the portability of behavioral economic indices of demand into novel research and clinical contexts.