Identification of a Composite Latent Dimension of Reward and Impulsivity Across Clinical, Behavioral, and Neurobiological Domains Among Youth

BACKGROUND

Individual differences in reward processing are central to heightened risk-taking behaviors during adolescence, but there is inconsistent evidence for the relationship between risk-taking phenotypes and the neural substrates of these behaviors.

METHODS

Here, we identify latent features of reward in an attempt to provide a unifying framework linking together aspects of the brain and behavior during early adolescence using a multivariate pattern learning approach. Data (N = 8295; n male = 4190; n female = 4105) were acquired as part of the Adolescent Brain Cognitive Development (ABCD) Study and included neuroimaging (regional neural activity responses during reward anticipation) and behavioral (e.g., impulsivity measures, delay discounting) variables.

RESULTS

We revealed a single latent dimension of reward driven by shared covariation between striatal, thalamic, and anterior cingulate responses during reward anticipation, negative urgency, and delay discounting behaviors. Expression of these latent features differed among adolescents with attention-deficit/hyperactivity disorder and disruptive behavior disorder, compared with those without, and higher expression of these latent features was negatively associated with multiple dimensions of executive function and cognition.

CONCLUSIONS

These results suggest that cross-domain patterns of anticipatory reward processing linked to negative features of impulsivity exist in both the brain and in behavior during early adolescence and that these are representative of 2 commonly diagnosed reward-related psychiatric disorders, attention-deficit/hyperactivity disorder and disruptive behavior disorder. Furthermore, they provide an explicit baseline from which multivariate developmental trajectories of reward processes may be tracked in later waves of the ABCD Study and other developmental cohorts.

Neural correlates of altered emotional responsivity to infant stimuli in mothers who use substances

Mothers who use substances during pregnancy and postpartum may have altered maternal behavior towards their infants, which can have negative consequences on infant social-emotional development. Since maternal substance use has been associated with difficulties in recognizing and responding to infant emotional expressions, investigating mothers' subjective responses to emotional infant stimuli may provide insight into the neural and psychological processes underlying these differences in maternal behavior. In this study, 39 mothers who used substances during the perinatal period and 42 mothers who did not underwent functional magnetic resonance imaging while viewing infant faces and hearing infant cries. Afterwards, they rated the emotional intensity they thought each infant felt ('think'-rating), and how intensely they felt in response to each infant stimulus ('feel'-rating). Mothers who used substances had lower 'feel'-ratings of infant stimuli compared to mothers who did not. Brain regions implicated in affective processing (e.g., insula, inferior frontal gyrus) were less active in response to infant stimuli, and activity in these brain regions statistically predicted maternal substance-use status. Interestingly, 'think'-ratings and activation in brain regions related to cognitive processing (e.g., medial prefrontal cortex) were comparable between the two groups of mothers. Taken together, these results suggest specific neural and psychological processes related to emotional responsivity to infant stimuli may reflect differences in maternal affective processing and may contribute to differences in maternal behavior in mothers who use substances compared to mothers who do not. The findings suggest potential neural targets for increasing maternal emotional responsivity and improving child outcomes.

Investigating brain dynamics and their association with cognitive control in opioid use disorder using naturalistic and drug cue paradigms

Objectives

Opioid use disorder (OUD) impacts millions of people worldwide. The prevalence and debilitating effects of OUD present a pressing need to understand its neural mechanisms to provide more targeted interventions. Prior studies have linked altered functioning in large-scale brain networks with clinical symptoms and outcomes in OUD. However, these investigations often do not consider how brain responses change over time. Time-varying brain network engagement can convey clinically relevant information not captured by static brain measures.

Methods

We investigated brain dynamic alterations in individuals with OUD by applying a new multivariate computational framework to movie-watching (i.e., naturalistic; N=76) and task-based (N=70) fMRI. We further probed the associations between cognitive control and brain dynamics during a separate drug cue paradigm in individuals with OUD.

Results

Compared to healthy controls (N=97), individuals with OUD showed decreased variability in the engagement of recurring brain states during movie-watching. We also found that worse cognitive control was linked to decreased variability during the rest period when no opioid-related stimuli were present.

Conclusions

These findings suggest that individuals with OUD may experience greater difficulty in effectively engaging brain networks in response to evolving internal or external demands. Such inflexibility may contribute to aberrant response inhibition and biased attention toward opioid-related stimuli, two hallmark characteristics of OUD. By incorporating temporal information, the current study introduces novel information about how brain dynamics are altered in individuals with OUD and their behavioral implications.

Connectome-based prediction of craving in gambling disorder and cocaine use disorder

INTRODUCTION

Craving, involving intense and urgent desires to engage in specific behaviours, is a feature of addictions. Multiple studies implicate regions of salience/limbic networks and basal ganglia, fronto-parietal, medial frontal regions in craving in addictions. However, prior studies have not identified common neural networks that reliably predict craving across substance and behavioural addictions.

METHODS

Functional magnetic resonance imaging during an audiovisual cue-reactivity task and connectome-based predictive modelling (CPM), a data-driven method for generating brain-behavioural models, were used to study individuals with cocaine-use disorder and gambling disorder. Functions of nodes and networks relevant to craving were identified and interpreted based on meta-analytic data.

RESULTS

Craving was predicted by neural connectivity across disorders. The highest degree nodes were mostly located in the prefrontal cortex. Overall, the prediction model included complex networks including motor/sensory, fronto-parietal, and default-mode networks. The decoding revealed high functional associations with components of memory, valence ratings, physiological responses, and finger movement/motor imagery.

CONCLUSIONS

Craving could be predicted across substance and behavioural addictions. The model may reflect general neural mechanisms of craving despite specificities of individual disorders. Prefrontal regions associated with working memory and autobiographical memory seem important in predicting craving. For further validation, the model should be tested in diverse samples and contexts.

Brain Networks and Adolescent Alcohol Use

Importance

Alcohol misuse in adolescence is a leading cause of disability and mortality in youth and is associated with higher risk for alcohol use disorder. Brain mechanisms underlying risk of alcohol misuse may inform prevention and intervention efforts.

Objective

To identify neuromarkers of alcohol misuse using a data-driven approach, with specific consideration of neurodevelopmental sex differences.

Design, Setting, and Participants

Longitudinal multisite functional magnetic resonance imaging (fMRI) data collected at ages 14 and 19 years were used to assess whole-brain patterns of functional organization associated with current and future alcohol use risk as measured by the Alcohol Use Disorder Identification Test (AUDIT). Primary data were collected by the IMAGEN consortium, a European multisite study of adolescent neurodevelopment. Model generalizability was further tested using data acquired in a single-site study of college alcohol consumption conducted in the US. The primary sample was a developmental cohort of 1359 adolescents with neuroimaging, phenotyping, and alcohol use data. Model generalizability was further assessed in a separate cohort of 114 individuals.

Main Outcomes and Measures

Brain-behavior model accuracy, as defined by the correspondence between model-predicted and actual AUDIT scores in held-out testing data, Bonferroni corrected across the number of models run at each time point, 2-tailed α < .008, as determined via permutation testing.

Results

Among 1359 individuals in the study, the mean (SD) age was 14.42 (0.40) years, and 729 individuals (54%) were female. The data-driven, whole-brain connectivity approach identified networks associated with vulnerability for future and current AUDIT-defined alcohol use risk (primary outcome, as specified above, future: ρ, 0.22; P < .001 and present: ρ, 0.27; P < .001). Results further indicated sex divergence in the accuracies of brain-behavior models, such that female-only models consistently outperformed male-only models. Specifically, female-only models identified networks conferring vulnerability for future and current severity using data acquired during both reward and inhibitory fMRI tasks. In contrast, male-only models were successful in accurately identifying networks using data acquired during the inhibitory control-but not reward-task, indicating domain specificity of alcohol use risk networks in male adolescents only.

Conclusions and Relevance

These data suggest that interventions focusing on inhibitory control processes may be effective in combating alcohol use risk in male adolescents but that both inhibitory and reward-related processes are likely of relevance to alcohol use behaviors in female adolescents. They further identify novel networks of alcohol use risk in youth, which may be used to identify adolescents who are at risk and inform intervention efforts.

Distinct neural networks predict cocaine versus cannabis treatment outcomes

Treatment outcomes for individuals with substance use disorders (SUDs) are variable and more individualized approaches may be needed. Cross-validated, machine-learning methods are well-suited for probing neural mechanisms of treatment outcomes. Our prior work applied one such approach, connectome-based predictive modeling (CPM), to identify dissociable and substance-specific neural networks of cocaine and opioid abstinence. In Study 1, we aimed to replicate and extend prior work by testing the predictive ability of the cocaine network in an independent sample of 43 participants from a trial of cognitive-behavioral therapy for SUD, and evaluating its ability to predict cannabis abstinence. In Study 2, CPM was applied to identify an independent cannabis abstinence network. Additional participants were identified for a combined sample of 33 with cannabis-use disorder. Participants underwent fMRI scanning before and after treatment. Additional samples of 53 individuals with co-occurring cocaine and opioid-use disorders and 38 comparison subjects were used to assess substance specificity and network strength relative to participants without SUDs. Results demonstrated a second external replication of the cocaine network predicting future cocaine abstinence, however it did not generalize to cannabis abstinence. An independent CPM identified a novel cannabis abstinence network, which was (i) anatomically distinct from the cocaine network, (ii) specific for predicting cannabis abstinence, and for which (iii) network strength was significantly stronger in treatment responders relative to control particpants. Results provide further evidence for substance specificity of neural predictors of abstinence and provide insight into neural mechanisms of successful cannabis treatment, thereby identifying novel treatment targets. Clinical trials registation: "Computer-based training in cognitive-behavioral therapy web-based (Man VS Machine)", registration number: NCT01442597 . "Maximizing the Efficacy of Cognitive Behavior Therapy and Contingency Management", registration number: NCT00350649 . "Computer-Based Training in Cognitive Behavior Therapy (CBT4CBT)", registration number: NCT01406899 .

From Computation to Clinic

Theory-driven and data-driven computational approaches to psychiatry have enormous potential for elucidating mechanism of disease and providing translational linkages between basic science findings and the clinic. These approaches have already demonstrated utility in providing clinically relevant understanding, primarily via back translation from clinic to computation, revealing how specific disorders or symptoms map onto specific computational processes. Nonetheless, forward translation, from computation to clinic, remains rare. In addition, consensus regarding specific barriers to forward translation-and on the best strategies to overcome these barriers-is limited. This perspective review brings together expert basic and computationally trained researchers and clinicians to 1) identify challenges specific to preclinical model systems and clinical translation of computational models of cognition and affect, and 2) discuss practical approaches to overcoming these challenges. In doing so, we highlight recent evidence for the ability of computational approaches to predict treatment responses in psychiatric disorders and discuss considerations for maximizing the clinical relevance of such models (e.g., via longitudinal testing) and the likelihood of stakeholder adoption (e.g., via cost-effectiveness analyses).

Task-based co-activation patterns reliably predict resting state canonical network engagement during development

Neurodevelopmental research has traditionally focused on development of individual structures, yet multiple lines of evidence indicate parallel development of large-scale systems, including canonical neural networks (i.e., default mode, frontoparietal). However, the relationship between region- vs. network-level development remains poorly understood. The current study tests the ability of a recently developed multi-task coactivation matrix approach to predict canonical resting state network engagement at baseline and at two-year follow-up in a large and cohort of young adolescents. Pre-processed tabulated neuroimaging data were obtained from the Adolescent Brain and Cognitive Development (ABCD) study, assessing youth at baseline (N = 6073, age = 10.0 ± 0.6 years, 3056 female) and at two-year follow-up (N = 3539, age = 11.9 ± 0.6 years, 1726 female). Individual multi-task co-activation matrices were constructed from the beta weights of task contrasts from the stop signal task, the monetary incentive delay task, and emotional N-back task. Activation-based predictive modeling, a cross-validated machine learning approach, was adopted to predict resting-state canonical network engagement from multi-task co-activation matrices at baseline. Note that the tabulated data used different parcellations of the task fMRI data ("ASEG" and Desikan) and the resting-state fMRI data (Gordon). Despite this, the model successfully predicted connectivity within the default mode network (DMN, rho = 0.179 ± 0.002, p < 0.001) across participants and identified a subset of co-activations within parietal and occipital macroscale brain regions as key contributors to model performance, suggesting an underlying common brain functional architecture across cognitive domains. Notably, predictive features for resting-state connectivity within the DMN identified at baseline also predicted DMN connectivity at two-year follow-up (rho = 0.258). These results indicate that multi-task co-activation matrices are functionally meaningful and can be used to predict resting-state connectivity. Interestingly, given that predictive features within the co-activation matrices identified at baseline can be extended to predictions at a future time point, our results suggest that task-based neural features and models are valid predictors of resting state network level connectivity across the course of development. Future work is encouraged to verify these findings with more consistent parcellations between task-based and resting-state fMRI, and with longer developmental trajectories.

A multidimensional approach to understanding the emergence of sex differences in internalizing symptoms in adolescence

Women are more vulnerable to internalizing disorders (e.g., depression and anxiety). This study took an integrative developmental approach to investigate multidimensional factors associated with the emergence of sex differences in internalizing symptoms, using data from the Adolescent Brain Cognitive Development (ABCD) study. Indices of sex hormone levels (dehydroepiandrosterone, testosterone, and estradiol), physical pubertal development, task-based functional brain activity, family conflict, and internalizing symptoms were drawn from the ABCD study's baseline sample (9- to 10-year-old; N = 11,844). Principal component analysis served as a data-driven dimensionality reduction technique on the internalizing subscales to yield a single robust measure of internalizing symptoms. Moderated mediation analyses assessed whether associations between known risk factors and internalizing symptoms vary by sex. Results revealed direct and indirect effects of physical pubertal development on internalizing symptoms through family conflict across sexes. No effects were found of sex hormone levels or amygdala response to fearful faces on internalizing symptoms. Females did not report overall greater internalizing symptoms relative to males, suggesting that internalizing symptoms have not yet begun to increase in females at this age. Findings provide an essential baseline for future longitudinal research on the endocrine, neurocognitive, and psychosocial factors associated with sex differences in internalizing symptoms.

Bayesian network mediation analysis with application to the brain functional connectome

The brain functional connectome, the collection of interconnected neural circuits along functional networks, facilitates a cutting-edge understanding of brain functioning, and has a potential to play a mediating role within the effect pathway between an exposure and an outcome. While existing mediation analytic approaches are capable of providing insight into complex processes, they mainly focus on a univariate mediator or mediator vector, without considering network-variate mediators. To fill the methodological gap and accomplish this exciting and urgent application, in the article, we propose an integrative mediation analysis under a Bayesian paradigm with networks entailing the mediation effect. To parameterize the network measurements, we introduce individually specified stochastic block models with unknown block allocation, and naturally bridge effect elements through the latent network mediators induced by the connectivity weights across network modules. To enable the identification of truly active mediating components, we simultaneously impose a feature selection across network mediators. We show the superiority of our model in estimating different effect components and selecting active mediating network structures. As a practical illustration of this approach's application to network neuroscience, we characterize the relationship between a therapeutic intervention and opioid abstinence as mediated by brain functional sub-networks.

Effects of Smoking Status and State on Intrinsic Connectivity

BACKGROUND

Smoking behavior during the first 24 hours of a quit attempt is a significant predictor of longer-term abstinence, yet little is known about the neurobiology of early tobacco abstinence. Specifically, the effects of acute tobacco deprivation and reinstatement on brain function-particularly at the level of large-scale network dynamics and assessed across the entire brain-remain incompletely understood. To address this gap, this study used a mixed within- and between-subjects design to assess the effects of smoking status (yes/no smoker) and state (deprived vs. satiated) on whole-brain patterns of intrinsic connectivity.

METHODS

Participants included 42 tobacco smokers who underwent resting-state functional magnetic resonance imaging following overnight abstinence (deprived state) and following smoking reinstatement (satiated state, randomized order across participants). Sixty healthy control nonsmokers underwent a single resting-state scan using the same acquisition parameters. Functional connectivity data were analyzed using both a canonical network-of-interest approach and a whole-brain, data-driven approach, i.e., intrinsic connectivity distribution.

RESULTS

Network-of-interest-based analyses indicated decreased functional connectivity within frontoparietal and salience networks among smokers relative to nonsmokers as well as effects of smoking state on default mode connectivity. In addition, intrinsic connectivity distribution analyses identified novel between-group differences in subcortical-cerebellar and corticocerebellar networks that were largely smoking state dependent.

CONCLUSIONS

These data demonstrate the importance of considering smoking state and the utility of using both theory- and data-driven analysis approaches. These data provide much-needed insight into the functional neurobiology of early abstinence, which may be used in the development of novel treatments.

Multivariate, Transgenerational Associations of the COVID-19 Pandemic Across Minoritized and Marginalized Communities

IMPORTANCE

The experienced consequences of the COVID-19 pandemic have diverged across individuals, families, and communities, resulting in inequity within a host of factors. There is a gap of quantitative evidence about the transgenerational impacts of these experiences and factors.

OBJECTIVE

To identify baseline predictors of COVID-19 experiences, as defined by child and parent report, using a multivariate pattern-learning framework from the Adolescent Brain and Cognitive Development (ABCD) cohort.

DESIGN, SETTING, AND PARTICIPANTS

ABCD is an ongoing prospective longitudinal study of child and adolescent development in the United States including 11 875 youths, enrolled at age 9 to 10 years. Using nationally collected longitudinal profiling data from 9267 families, a multivariate pattern-learning strategy was developed to identify factor combinations associated with transgenerational costs of the ongoing COVID-19 pandemic. ABCD data (release 3.0) collected from 2016 to 2020 and released between 2019 and 2021 were analyzed in combination with ABCD COVID-19 rapid response data from the first 3 collection points (May-August 2020).

EXPOSURES

Social distancing and other response measures imposed by COVID-19, including school closures and shutdown of many childhood recreational activities.

MAIN OUTCOMES AND MEASURES

Mid-COVID-19 experiences as defined by the ABCD's parent and child COVID-19 assessments.

RESULTS

Deep profiles from 9267 youth (5681 female [47.8%]; mean [SD] age, 119.0 [7.5] months) and their caregivers were quantitatively examined. Enabled by a pattern-learning analysis, social determinants of inequity, including family structure, socioeconomic status, and the experience of racism, were found to be primarily associated with transgenerational impacts of COVID-19, above and beyond other candidate predictors such as preexisting medical or psychiatric conditions. Pooling information across more than 17 000 baseline pre-COVID-19 family indicators and more than 280 measures of day-to-day COVID-19 experiences, non-White (ie, families who reported being Asian, Black, Hispanic, other, or a combination of those choices) and/or Spanish-speaking families were found to have decreased resources (mode 1, canonical vector weight [CVW] = 0.19; rank 5 of 281), escalated likelihoods of financial worry (mode 1, CVW = -0.20; rank 4), and food insecurity (mode 1, CVW = 0.21; rank 2), yet were more likely to have parent-child discussions regarding COVID-19-associated health and prevention issues, such as handwashing (mode 1, CVW = 0.14; rank 9), conserving food or other items (mode 1, CVW = 0.21; rank 1), protecting elderly individuals (mode 1, CVW = 0.11; rank 21), and isolating from others (mode 1, CVW = 0.11; rank 23). In contrast, White families (mode 1, CVW = -0.07; rank 3), those with higher pre-COVID-19 income (mode 1, CVW = -0.07; rank 5), and presence of a parent with a postgraduate degree (mode 1, CVW = -0.06; rank 14) experienced reduced COVID-19-associated impact. In turn, children from families experiencing reduced COVID-19 impacts reported longer nighttime sleep durations (mode 1, CVW = 0.13; rank 14), less difficulties with remote learning (mode 2, CVW = 0.14; rank 7), and decreased worry about the impact of COVID-19 on their family's financial stability (mode 1, CVW = 0.134; rank 13).

CONCLUSIONS AND RELEVANCE

The findings of this study indicate that community-level, transgenerational intervention strategies may be needed to combat the disproportionate burden of pandemics on minoritized and marginalized racial and ethnic populations.

Systematic review of structural and functional neuroimaging studies of cannabis use in adolescence and emerging adulthood: evidence from 90 studies and 9441 participants

Cannabis use peaks in adolescence, and adolescents may be more vulnerable to the neural effects of cannabis and cannabis-related harms due to ongoing brain development during this period. In light of ongoing cannabis policy changes, increased availability, reduced perceptions of harm, heightened interest in medicinal applications of cannabis, and drastic increases in cannabis potency, it is essential to establish an understanding of cannabis effects on the developing adolescent brain. This systematic review aims to: (1) synthesize extant literature on functional and structural neural alterations associated with cannabis use during adolescence and emerging adulthood; (2) identify gaps in the literature that critically impede our ability to accurately assess the effect of cannabis on adolescent brain function and development; and (3) provide recommendations for future research to bridge these gaps and elucidate the mechanisms underlying cannabis-related harms in adolescence and emerging adulthood, with the long-term goal of facilitating the development of improved prevention, early intervention, and treatment approaches targeting adolescent cannabis users (CU). Based on a systematic search of Medline and PsycInfo and other non-systematic sources, we identified 90 studies including 9441 adolescents and emerging adults (n = 3924 CU, n = 5517 non-CU), which provide preliminary evidence for functional and structural alterations in frontoparietal, frontolimbic, frontostriatal, and cerebellar regions among adolescent cannabis users. Larger, more rigorous studies are essential to reconcile divergent results, assess potential moderators of cannabis effects on the developing brain, disentangle risk factors for use from consequences of exposure, and elucidate the extent to which cannabis effects are reversible with abstinence. Guidelines for conducting this work are provided.

Hyperbolic discounting rates and risk for problematic alcohol use in youth enrolled in the Adolescent Brain and Cognitive Development study

Adolescence is the peak period for the emergence of substance use, which can lead to long-term psychosocial, occupational and interpersonal complications. Ongoing large-scale, longitudinal, consortium initiatives, such as the Adolescent Brain and Cognitive Development (ABCD) study, offer unprecedented opportunities to elucidate key risk factors for problematic substance use in a well-powered sample and to examine how changes in risk factors relate to symptoms across time. Delay discounting has been proposed as a putative risk marker for early substance-use initiation and other forms of psychopathology. However, the extent to which other factors (e.g., socio-economic status and cognitive ability) influence discounting behaviour in young adolescents is not well established. The present study leverages data from the ABCD study (n = 11 045) to assess associations between core demographic and familial variables and delay discounting in youth-operationalized using hyperbolic discounting rates (k)-before the onset of significant psychopathology. Model estimates revealed significant effects of individual difference factors (e.g., sex and socio-economic status) and alcohol risk status (based on family history) on delay discounting. No significant differences were observed in the primary sample when comparing the presence of parent drug problems or prenatal drug exposures. These effects will require replication in later waves of ABCD. Nonetheless, these results provide support for delay discounting as a potential risk marker for problematic alcohol use and demonstrate a relationship between key demographic variables and adolescent discounting behaviour. Further, these results provide an empirical baseline from which developmental trajectories of delay discounting and substance use may be tracked throughout future waves of ABCD.

Clinical prediction of extra-medical use of prescription pain relievers from a representative United States sample

Use of prescription opioids 'beyond the bounds' of medical guidance can lead to opioid dependence. Yet recent efforts to predict extra-medical use of prescription pain relievers (EMPPR) have relied on electronic medical or pharmacy records. Because peak incidence of EMPPR occurs during adolescence- a time of relative health- administrative data may be inadequate. In this study, with data from a United States (US) population sample, we develop and internally validate an EMPPR prediction model. We analyzed data from 234,593 individuals aged 12-to-17-years, as sampled by the US National Survey of Drug Use and Health, 2004-2018, an annual cross-sectional survey. We encoded 14 predictors with onset prior to EMPPR initiation, including age, sex, and facets of drug and psychiatric history. We ranked these predictors by clinical utility before sequentially adding each to a regularized logistic regression model. On held-out test data (n = 23,685), the model performs well with 14 predictors, with an area under the precision recall curve (AUPRC) is 0.155. The area under the receiver operator curve (AUC) is 0.819, exceeding a recent benchmark on this dataset. Results are robust to survey redesign that occurred in 2015, and are not moderated by past-year use of medical services. In conclusion, while selection of predictors is limited to those with known timing prior to initiation of EMPPR rather than any cross-sectional variable, this model discriminates well. Good classification occurs even with a small set of clinically available predictors- age, a history of depression and alcohol, cigarette, and cannabis use.

Altered intrinsic connectivity distribution in internet gaming disorder and its associations with psychotherapy treatment outcomes

Alterations in brain connectivity have been implicated in internet gaming disorder (IGD). However, little is known about alterations in whole-brain connectivity and their associations with long-term treatment outcomes. Here, we used a relatively new analytic approach, intrinsic connectivity distribution (ICD) analysis, to examine brain connectivity in 74 IGD participants and 41 matched healthy controls (HCs) and conducted post hoc seed-based resting-state functional connectivity (rsFC) analyses based on the ICD findings. We also examined how these findings related to outcomes involving a craving behavioral intervention (CBI) for IGD. IGD participants showed less whole-brain connectivity in the left angular gyrus and ventromedial prefrontal cortex (vmPFC) compared with HC participants. Seed-based rsFC analyses revealed that the left angular gyrus in the IGD group showed less connectivity with areas involved in the default-mode network and greater connectivity with areas in the salience and executive control networks. CBI was associated with improved connectivity within regions in the default-mode network and regions across the default-mode and salience networks. ICD-identified connectivity differences in the left angular gyrus and vmPFC were related to changes in craving and severity of addiction 6 months after the intervention. The findings suggest that IGD is associated with alterations in brain connectivity that may be sensitive to interventions. Thus, the findings have implications for understanding mechanisms underlying CBI effects and for further treatment development.

Development and Validation of a Prediction Model of Prescription Tranquilizer Misuse Based on a Nationally Representative United States Sample

BACKGROUND

Prescription tranquilizer misuse is a risky behavior associated with fatal drug poisonings. Although various predictors have been examined, there is no published prediction model for tranquilizer misuse. This study develops and internally validates a tranquilizer misuse prediction model based primarily on drug histories of participants in a national cross-sectional survey. Predictors also include psychiatric, behavioral and demographic variables.

METHODS

We analyzed data from 471,097 individuals aged 14-to-29-years in the United States, as sampled by the National Survey of Drug Use and Health, 2004-2018, an annual cross-sectional survey. We encoded 21 predictors with known or likely onset prior to tranquilizer misuse initiation, (e.g., early onset of cannabis use). With this dataset, we trained a neural network and regularized logistic regression model. While the assessment for tranquilizer misuse changed slightly in 2015, by pooling all years of survey data, predictions are robust to this source of variation.

RESULTS

1.44% of the pooled sample, 2004-2018, recently initiated tranquilizer misuse (unweighted estimate). On held-out test data (n = 43,714), logistic regression and the neural network performed equally well, with an area under the receiver operating characteristic curve (AUC) of ∼0.83 on the primary model, containing 12 variables known to occur before tranquilizer misuse.

CONCLUSION

Built for case prediction rather than case detection, this model restricted predictors to those with known timing prior to initiation of tranquilizer misuse. Yet its performance supersedes commonly accepted criteria for clinical prediction models (AUC > 0.80). Future work should incorporate survey analysis weights into the prediction model to minimize possible bias.

Efficacy of single-session transcranial direct current stimulation on addiction-related inhibitory control and craving: a randomized trial in males with Internet gaming disorder

BACKGROUND

Transcranial direct current stimulation (tDCS) of the dorsolateral prefrontal cortex (dlPFC) may reduce substance use and other addictive behaviours. However, the cognitive mechanisms that underpin such effects remain unclear. Impaired inhibitory control linked to hypoactivation of the prefrontal cortex may allow craving-related motivations to lead to compulsive addictive behaviours. However, very few studies have examined whether increasing the activation of the dlPFC via anodal tDCS could enhance inhibitory control over addiction-related distractors. The current study aimed to enrich empirical evidence related to this issue.

METHODS

Thirty-three males with Internet gaming disorder underwent active (1.5 mA for 20 minutes) and sham tDCS 1 week apart, in randomized order. We assessed inhibitory control over gaming-related distractors and craving pre- and post-stimulation.

RESULTS

Relative to sham treatment, active tDCS reduced interference from gaming-related (versus non-gaming) distractors and attenuated background craving, but did not affect cue-induced craving.

LIMITATIONS

This study was limited by its relatively small sample size and the fact that it lacked assessments of tDCS effects on addictive behaviour. Future tDCS studies with multiple sessions in larger samples are warranted to examine the effects on addictive behaviours of alterations in addiction-related inhibitory control.

CONCLUSION

These findings demonstrate that stimulation of the dlPFC influences inhibitory control over addiction-related cues and addiction-related motivation. This is the first empirical study to suggest that enhanced inhibitory control may be a cognitive mechanism underlying the effects of tDCS on addictions like Internet gaming disorder. Our finding of attenuated background craving replicated previous tDCS studies. Intriguingly, our finding of distinct tDCS effects on 2 forms of craving suggests that they may have disparate underlying mechanisms or differential sensitivity to tDCS.

CLINICAL TRIALS #

NCT03352973.

Alexithymia and pain experience among patients using methadone-maintenance therapy

BACKGROUND

Alexithymia, difficulty identifying and describing one's emotions coupled with a tendency to externalize, is a potentially important yet understudied treatment target for patients with opioid use disorder. The aim of this study was to examine the role of alexithymia in pain experience among individuals with opioid use disorder.

METHODS

One-hundred-and-sixty-four patients receiving methadone maintenance treatment completed a battery of self-report measures related to alexithymia, drug use, and pain experiences. Comparisons were performed on the full sample between those with or without clinically significant levels of alexithymia. For a subsample reporting pain (n = 138), intercorrelations were performed to test whether drug use history, pain catastrophizing, pain acceptance, and alexithymia were related to pain severity and pain interference. Regression analyses were performed to test for serial mediation of pain catastrophizing and pain acceptance on the relationship between alexithymia and pain interference in this subsample.

RESULTS

Individuals with alexithymia showed increased pain catastrophizing and interference, and intercorrelations indicated that increased alexithymia was associated with increased pain interference, more pain catastrophizing, and reduced pain acceptance. A serial regression model among a subset of patients with pain indicated that pain catastrophizing and pain acceptance mediated the effect of alexithymia on pain interference.

CONCLUSIONS

These findings suggest that alexithymia, as well as both pain catastrophizing and pain acceptance, contribute to interference associated with pain and are potentially important intervention targets among methadone-treated patients with pain.

Discrete Roles for Impulsivity and Compulsivity in Gambling Disorder

Background and Objective: Complex associations between gambling disorder (GD) and impulsivity have been identified. However, little is known regarding how compulsivity associates with different impulsivity domains in GD. In this study, we examined associations between self-reported and behavioral measures of impulsivity-assessed through the Barratt Impulsiveness Scale (BIS-11) and the Experiential Discounting Task (EDT), respectively- and compulsivity-measured using the Padua Inventory and the Wisconsin Card Sorting Test (WCST), respectively-, in an adult sample with GD (N = 132, 94 men and 38 women, ages ranging from 18 to 69 years). GD severity was assessed using the South Oaks Gambling Screen. Methods: Structural Equation Modeling was used to examine relationships between impulsivity and compulsivity measures, age, and GD severity. Results: BIS-11 non-planning and BIS-11 total scores positively correlated with GD severity. The standardized coefficients for the SEM showed direct positive contributions of BIS-11 non-planning, Padua and EDT scores to GD severity. Only participants' ages directly contributed to WCST perseverative errors, and no direct or indirect effects were found with respect to GD severity. Conclusion: The findings suggest that specific aspects of impulsivity and compulsivity contribute to GD severity. Interventions specifically targeting domains that are most relevant to GD severity may improve treatment outcomes.

Toward Addiction Prediction: An Overview of Cross-Validated Predictive Modeling Findings and Considerations for Future Neuroimaging Research

Substance use is a leading cause of disability and death worldwide. Despite the existence of evidence-based treatments, clinical outcomes are highly variable across individuals, and relapse rates following treatment remain high. Within this context, methods to identify individuals at particular risk for unsuccessful treatment (i.e., limited within-treatment abstinence), or for relapse following treatment, are needed to improve outcomes. Cumulatively, the literature generally supports the hypothesis that individual differences in brain function and structure are linked to differences in treatment outcomes, although anatomical loci and directions of associations have differed across studies. However, this work has almost entirely used methods that may overfit the data, leading to inflated effect size estimates and reduced likelihood of reproducibility in novel clinical samples. In contrast, cross-validated predictive modeling (i.e., machine learning) approaches are designed to overcome limitations of traditional approaches by focusing on individual differences and generalization to novel subjects (i.e., cross-validation), thereby increasing the likelihood of replication and potential translation to novel clinical settings. Here, we review recent studies using these approaches to generate brain-behavior models of treatment outcomes in addictions and provide recommendations for further work using these methods.

Is monetary reward processing altered in drug-naïve youth with a behavioral addiction? Findings from internet gaming disorder

Current models of addiction biology highlight altered neural responses to non-drug rewards as a central feature of addiction. However, given that drugs of abuse can directly impact reward-related dopamine circuitry, it is difficult to determine the extent to which reward processing alterations are a trait feature of individuals with addictions, or primarily a consequence of exogenous drug exposure. Examining individuals with behavioral addictions is one promising approach for disentangling neural features of addiction from the direct effects of substance exposure. The current fMRI study compared neural responses during monetary reward processing between drug naïve young adults with a behavioral addiction, internet gaming disorder (IGD; n = 22), and healthy controls (n = 27) using a monetary incentive delay task. Relative to controls, individuals with IGD exhibited blunted caudate activity associated with loss magnitude at the outcome stage, but did not differ from controls in neural activity at other stages. These findings suggest that decreased loss sensitivity might be a critical feature of IGD, whereas alterations in gain processing may be less characteristic of individuals with IGD, relative to those with substance use disorders. Therefore, classic theories of altered reward processing in substance use disorders should be translated to behavioral addictions with caution.

Differential responses to infant faces in relation to maternal substance use: An exploratory study

BACKGROUND

Maternal substance use and addiction has been associated with negative consequences for parenting and may increase addiction vulnerability in the developing child. Neuroimaging research suggests that substance use may decrease the reward of caring for infants and heighten stress reactivity to affective infant cues.

METHODS

Thirty-two substance-using mothers and twenty-two non-substance-using mothers were presented with emotional face and cry stimuli generated from their own and a demographically matched unknown infant during fMRI scanning. Between-group differences in neural activity during task performance were assessed using whole-brain, mixed-effects models corrected for multiple comparisons (voxel-level p < 0.001, pFWE<0.05).

RESULTS

Relative to non-substance-using mothers, substance-using mothers exhibited greater activation when viewing their own infant's face as compared to an unknown infant's face across multiple brain regions, including superior medial frontal, inferior parietal, and middle temporal regions. Substance-using mothers also had a decreased response to sad infant faces in the ventral striatum relative to the non-substance-using mothers. Neural responses to own vs. unknown infant cries did not significantly differ between substance-using and non-substance-using mothers.

CONCLUSIONS

Findings suggest overlapping cortical and subcortical brain regions implicated in responding to infant faces, with activation differences related to infant familiarity, emotional expression, and maternal substance use. While prior work has focused on attenuated neural responses to infant cues, greater attention is needed toward understanding the increased reactivity to affective infant cues observed in substance-using mothers.

Clinical validation of reduction in cocaine frequency level as an endpoint in clinical trials for cocaine use disorder

BACKGROUND

Despite calls for non-abstinence endpoints in randomized clinical trials (RCTs) for cocaine use disorder, there is a lack of data validating non-abstinence endpoints. We conducted a clinical validation of reduction in cocaine frequency level as a non-abstinence endpoint in RCTs for cocaine use disorder (CUD).

METHODS

We utilized a pooled dataset (n = 716; 63.6 % male, 51.4 % non-Hispanic white) from seven RCTs for CUD. We specified three cocaine frequency levels at baseline and end of treatment (EOT): abstinence, low frequency (1-4 days/month), and high frequency (5+ days/month). Multiple regression analyses were conducted.

RESULTS

Among the sample, 38.3 % had at least a one-level reduction from baseline to EOT, whereas 61.7 % did not change/increased frequency level. At least a one-level reduction in cocaine frequency level from baseline to EOT versus no change/increase was significantly associated with better functioning up to one year following treatment on measures of cocaine use, as well as psychological, employment, legal, and other drug use problem severity domains of the Addiction Severity Index (ASI). We also conducted analyses only among those at the high frequency level at baseline and found those who reduced to low frequency use at EOT had similar outcomes at follow-up as those who reduced to abstinence.

CONCLUSIONS

At least a one-level reduction in cocaine frequency level from pretreatment to EOT can be a clinically meaningful endpoint given its relation to sustained clinical benefit up to one-year following treatment. These data parallel recent findings regarding reduction in drinking risk level among individuals with alcohol use disorder.

Increased neural activity in the right dorsolateral prefrontal cortex during a risky decision-making task is associated with cocaine use in methadone-maintained patients

BACKGROUND

Methadone maintenance is an effective treatment for opioid use disorder (OUD), yet many methadone-maintained patients (MMPs) struggle with cocaine use during OUD recovery. The current study aimed to identify whether prefrontal cortex (PFC) activity during a risky decision-making task was associated with cocaine use during a 90-day follow-up in MMPs.

METHODS

MMPs (N = 28) attended a single neuroimaging session wherein PFC activity was measured using functional near-infrared spectroscopy (fNIRS) during the Balloon Analogue Risk Task (BART). Trait impulsivity was assessed via the Barratt Impulsiveness Scale version 11 (BIS-11). Following the neuroimaging session, MMPs were tracked via electronic health records for 90 days to determine treatment outcomes including cocaine use verified by urine drug screens.

RESULTS

During the BART, MMPs who used cocaine displayed increased neural activity in the right PFC during active decision-making (F_{1, 22} = 14.75, p = 0.001) and the right dorsolateral PFC during active minus passive decision-making (F_{1, 22} = 5.56, p = 0.028) compared to participants who did not use cocaine. Receiver operating characteristic curves confirmed that neural activity in the right PFC during active decision-making (AUC = 0.841, 95% CI, 0.697-0.985, p = 002), and in the right dorsolateral PFC during active minus passive decision-making (AUC = 0.805, 95% CI, 0.643-0.968, p = 0.006) was associated with continued cocaine use. MMPs who used cocaine versus those who did not reported increased trait impulsivity on the BIS-11 Total Score (t=-2.28, p = 0.031).

CONCLUSIONS

The fNIRS device is portable, relatively easy to use, and potentially feasible for use in methadone outpatient programs to assess propensity for negative treatment outcomes such as continued cocaine use.

Anhedonia as a key clinical feature in the maintenance and treatment of opioid use disorder

There is a critical need for research on clinical features that may influence response to treatment for opioid use disorder (OUD). Given its neurobiology and relevance to opioid use, anhedonia may be one such promising clinical feature. We identified and reviewed 11 studies that measured anhedonia in humans with OUD to characterize the current state of evidence and highlight potential implications for treatment. The majority of studies were cross-sectional, indicating higher anhedonia scores in opioid-dependent samples compared to healthy controls. Rates of participants with clinically significant anhedonia ranged from 21% to 48%. Anhedonia scores were correlated with opioid craving and use, however there are significant knowledge gaps regarding its time course and impact on treatment adherence and outcomes. Repeated assessment of anhedonia early in treatment for OUD is recommended, as it may be a unique predictor of dropout or non-response, and a potential target for behavioral and/or pharmacological intervention.

Gradient theories of brain activation: A novel application to studying the parental brain

PURPOSE OF REVIEW

Parental brain research primarily employs general-linear-model-based (GLM-based) analyses to assess blood-oxygenation-level-dependent responses to infant auditory and visual cues, reporting common responses in shared cortical and subcortical structures. However, this approach does not reveal intermixed neural substrates related to different sensory modalities. We consider this notion in studying the parental brain.

RECENT FINDINGS

Spatial independent component analysis (sICA) has been used to separate mixed source signals from overlapping functional networks. We explore relative differences between GLM-based analysis and sICA as applied to an fMRI dataset acquired from women while they listened to infant cries or viewed infant sad faces.

SUMMARY

There is growing appreciation for the value of moving beyond GLM-based analyses to consider brain functional organization as continuous, distributive, and overlapping gradients of neural substrates related to different sensory modalities. Preliminary findings suggest sICA can be applied to the study of the parental brain.

Alterations in functional networks during cue-reactivity in Internet gaming disorder

BACKGROUND

Cue-induced brain reactivity has been suggested to be a fundamental and important mechanism explaining the development, maintenance, and relapse of addiction, including Internet gaming disorder (IGD). Altered activity in addiction-related brain regions has been found during cue-reactivity in IGD using functional magnetic resonance imaging (fMRI), but less is known regarding the alterations of coordinated whole brain activity patterns in IGD.

METHODS

To investigate the activity of temporally coherent, large-scale functional brain networks (FNs) during cue-reactivity in IGD, independent component analysis was applied to fMRI data from 29 male subjects with IGD and 23 matched healthy controls (HC) performing a cue-reactivity task involving Internet gaming stimuli (i.e., game cues) and general Internet surfing-related stimuli (i.e., control cues).

RESULTS

Four FNs were identified that were related to the response to game cues relative to control cues and that showed altered engagement/disengagement in IGD compared with HC. These FNs included temporo-occipital and temporo-insula networks associated with sensory processing, a frontoparietal network involved in memory and executive functioning, and a dorsal-limbic network implicated in reward and motivation processing. Within IGD, game versus control engagement of the temporo-occipital and frontoparietal networks were positively correlated with IGD severity. Similarly, disengagement of temporo-insula network was negatively correlated with higher game-craving.

DISCUSSION

These findings are consistent with altered cue-reactivity brain regions reported in substance-related addictions, providing evidence that IGD may represent a type of addiction. The identification of the networks might shed light on the mechanisms of the cue-induced craving and addictive Internet gaming behaviors.

Current understanding of the neurobiology of opioid use disorder: An overview

PURPOSE OF REVIEW

This review provides an overview of the neurobiological mechanisms underlying opioid use disorder (OUD) drawing from genetic, functional and structural magnetic resonance imaging (MRI) research.

RECENT FINDINGS

Preliminary evidence suggests an association between OUD and specific variants of the DRD2, δ-opioid receptor 1 (OPRD1) and μ-opioid receptor 1 (OPRM1) genes. Additionally, MRI research indicates functional and structural alterations in striatal and corticolimbic brain regions and pathways underlying reward, emotion/stress and cognitive control processes among individuals with OUD.

SUMMARY

Individual differences in genetic and functional and structural brain-based features are correlated with differences in OUD severity and treatment outcomes, and therefore may potentially one day be used to inform OUD treatment selection. However, given the heterogeneous findings reported, further longitudinal research across different stages of opioid addiction is needed to yield a convergent characterization of OUD and improve treatment and prevention.

Connectome-Based Prediction of Cocaine Abstinence

OBJECTIVE

The authors sought to identify a brain-based predictor of cocaine abstinence by using connectome-based predictive modeling (CPM), a recently developed machine learning approach. CPM is a predictive tool and a method of identifying networks that underlie specific behaviors ("neural fingerprints").

METHODS

Fifty-three individuals participated in neuroimaging protocols at the start of treatment for cocaine use disorder, and again at the end of 12 weeks of treatment. CPM with leave-one-out cross-validation was conducted to identify pretreatment networks that predicted abstinence (percent cocaine-negative urine samples during treatment). Networks were applied to posttreatment functional MRI data to assess changes over time and ability to predict abstinence during follow-up. The predictive ability of identified networks was then tested in a separate, heterogeneous sample of individuals who underwent scanning before treatment for cocaine use disorder (N=45).

RESULTS

CPM predicted abstinence during treatment, as indicated by a significant correspondence between predicted and actual abstinence values (r=0.42, df=52). Identified networks included connections within and between canonical networks implicated in cognitive/executive control (frontoparietal, medial frontal) and in reward responsiveness (subcortical, salience, motor/sensory). Connectivity strength did not change with treatment, and strength at posttreatment assessment also significantly predicted abstinence during follow-up (r=0.34, df=39). Network strength in the independent sample predicted treatment response with 64% accuracy by itself and 71% accuracy when combined with baseline cocaine use.

CONCLUSIONS

These data demonstrate that individual differences in large-scale neural networks contribute to variability in treatment outcomes for cocaine use disorder, and they identify specific abstinence networks that may be targeted in novel interventions.

Can neuroimaging help combat the opioid epidemic? A systematic review of clinical and pharmacological challenge fMRI studies with recommendations for future research

The current opioid epidemic is an urgent public health problem, with enormous individual, societal, and healthcare costs. Despite effective, evidence-based treatments, there is significant individual variability in treatment responses and relapse rates are high. In addition, the neurobiology of opioid-use disorder (OUD) and its treatment is not well understood. This review synthesizes published fMRI literature relevant to OUD, with an emphasis on findings related to opioid medications and treatment, and proposes areas for further research. We conducted a systematic literature review of Medline and Psychinfo to identify (i) fMRI studies comparing OUD and control participants; (ii) studies related to medication, treatment, abstinence or withdrawal effects in OUD; and (iii) studies involving manipulation of the opioid system in healthy individuals. Following application of exclusionary criteria (e.g., insufficient sample size), 45 studies were retained comprising data from ~1400 individuals. We found convergent evidence that individuals with OUD display widespread heightened neural activation to heroin cues. This pattern is potentiated by heroin, attenuated by medication-assisted treatments for opioids, predicts treatment response, and is reduced following extended abstinence. Nonetheless, there is a paucity of literature examining neural characteristics of OUD and its treatment. We discuss limitations of extant research and identify critical areas for future neuroimaging studies, including the urgent need for studies examining prescription opioid users, assessing sex differences and utilizing a wider range of clinically relevant task-based fMRI paradigms across different stages of addiction.

Mechanisms and Clinical Features of Co-occurring Opioid and Nicotine Use

Purpose of review

To review the literature addressing shared pathophysiological and clinical features of opioid and nicotine use to inform etiology and treatment, and highlight areas for future research.

Recent findings

Opioid and nicotine use co-occur at an alarmingly high rate, and this may be driven in part by interactions between the opioid and cholinergic systems underlying drug reward and the transition to dependence. Pain, among other shared risk factors, is strongly implicated in both opioid and nicotine use and appears to play an important role in their co-occurrence. Additionally, there are important sex/gender considerations that require further study. Regarding treatment, smoking cessation can improve treatment outcomes in opioid use disorder, and pharmacological approaches that target the opioid and cholinergic systems may be effective for treating both classes of substance use disorders.

Summary

Understanding overlapping etiological and pathophysiological mechanisms of opioid and nicotine use can aid in understanding their co-occurrence and guiding their treatment.

Accounting for the uncounted: Physical and affective distress in individuals dropping out of oral naltrexone treatment for opioid use disorder

BACKGROUND

The theoretical benefits of naltrexone as a treatment for opioid use disorder (e.g., safety, non-addictive, low risk of diversion) stand in sharp contrast to its disappointing record on retention in most samples. The relationship of uncomfortable physical and dysphoric symptoms to retention on naltrexone is a controversial and under-studied issue.

METHODS

Using data from a randomized controlled trial of voucher-based contingency management and support from a significant other to enhance retention on oral naltrexone, we compared self-reported somatic and dysphoric symptoms, measured weekly, for individuals who were retained on naltrexone through the 12-week trial (n = 50) versus those who dropped out (n = 70).

RESULTS

There were no differences between participants who completed treatment and those who dropped out on multiple baseline characteristics, including somatic or affective symptoms prior to treatment. However, whether analyzed cross-sectionally or over time, participants who dropped out consistently reported higher rates of somatic symptoms, particularly difficulty sleeping, as well as affective symptoms, including multiple indicators of depression, anxiety, and anhedonia.

CONCLUSIONS

Although the smaller group of participants who were retained on oral naltrexone for 12 weeks reported decreasing physical and affective discomfort over time, there was substantial evidence that those who dropped out experienced continued and significant levels of distress. Individuals who report physical or affective distress while taking naltrexone may be at higher risk of dropout.

Childhood trauma moderates inhibitory control and anterior cingulate cortex activation during stress

OBJECTIVE

The anterior cingulate cortex (ACC) is critical for both stress and inhibitory control processes and has been implicated in childhood trauma. This prospective study tested the hypothesis that early trauma moderates the association between inhibitory control during late childhood and ACC stress reactivity during adolescence.

METHOD

Sixty-four adolescents were stratified into higher- or lower-childhood-trauma groups. Inhibitory control was indicated by fewer errors on a Stroop Color-Word task. Personalized stress cues during functional magnetic resonance imaging assessed neural correlates of stress in adolescents.

RESULTS

Using a priori-defined anterior (rCZa) and posterior rostral cingulate zones of the ACC, associated with Stroop Color-Word task performance in prior meta-analyses, Stroop errors correlated inversely with activation in the rCZa during stress-cue exposure (r = -.23, p = .04). Childhood trauma moderated the association between Stroop errors and rCZa stress reactivity (interaction = -1.26, p = .02, 95%CI = -2.33,-0.20), where Stroop errors were inversely associated with brain activation among those with higher childhood trauma (simple slopes = -.83, p = .007, 95%CI = -1.40,-0.25). Low stress-related rCZa activation inversely (R² = 0.19, b = -0.43, p = .001, 95%CI = -4.11,-1.06) and Stroop errors directly (R² = 0.09, b = 0.27, p = .048, 95%CI = 0.02, 5.8) associated with baseline subjective anxiety while controlling for childhood trauma.

CONCLUSIONS

This is the first study to demonstrate a moderating role of childhood trauma on the relationship between inhibitory control and stress-related ACC activation. Childhood trauma may portend neurodevelopmental changes that impede recruitment of control-associated ACC-functioning during distress, which may relate to dysregulation of stress-induced affective responses. Further work is needed to elucidate relationships between childhood trauma and addictive behaviors precipitated by stress.

Application of Research Domain Criteria to childhood and adolescent impulsive and addictive disorders: Implications for treatment

The Research Domain Criteria (RDoC) initiative provides a large-scale, dimensional framework for the integration of research findings across traditional diagnoses, with the long-term aim of improving existing psychiatric treatments. A neurodevelopmental perspective is essential to this endeavor. However, few papers synthesizing research findings across childhood and adolescent disorders exist. Here, we discuss how the RDoC framework may be applied to the study of childhood and adolescent impulsive and addictive disorders in order to improve neurodevelopmental understanding and to enhance treatment development. Given the large scope of RDoC, we focus on a single construct highly relevant to addictive and impulsive disorders - initial responsiveness to reward attainment. Findings from genetic, molecular, neuroimaging and other translational research methodologies are highlighted.

Is Neural Processing of Negative Stimuli Altered in Addiction Independent of Drug Effects? Findings From Drug-Naïve Youth with Internet Gaming Disorder

Difficulties in emotion regulation are commonly reported among individuals with alcohol and drug addictions and contribute to the acquisition and maintenance of addictive behaviors. Alterations in neural processing of negative affective stimuli have further been demonstrated among individuals with addictions. However, it is unclear whether these alterations are a general feature of addictions or are a result of prolonged exposure to drugs of abuse. To test the hypothesis of altered negative affect processing independent of drug effects, this study assessed neural function among drug-naïve youth with a behavioral addiction-Internet gaming disorder (IGD). Fifty-six young adults (28 with IGD, 28 matched controls) participated in fMRI scanning during performance of a well-validated emotion regulation task. Between-group differences in neural activity during task performance were assessed using a whole-brain, mixed-effects ANOVA with correction for multiple comparisons at currently recommended thresholds (voxel-level p<0.001, pFWE<0.05). Compared to controls, youth with IGD exhibited significantly blunted neural responses within distributed subcortical and cortical regions including the striatum, insula, lateral prefrontal cortex and anterior cingulate in response to negative affective cues, as well as during emotion regulation. Independent component analysis (ICA) further identified between-group differences in engagement of a fronto-cingulo-parietal network, involving decreased engagement in IGD youth relative to controls. Study findings are largely consistent with those from prior neuroimaging studies in substance-use disorders, thus raising the possibility that neural processing of negative affect may be blunted across drug and behavioral addictions independent of acute or chronic drug effects.

Relationships Between Perceived Family Gambling and Peer Gambling and Adolescent Problem Gambling and Binge-Drinking

The study systematically examined the relative relationships between perceived family and peer gambling and adolescent at-risk/problem gambling and binge-drinking. It also determined the likelihood of at-risk/problem gambling and binge-drinking as a function of the number of different social groups with perceived gambling. A multi-site high-school survey assessed gambling, alcohol use, presence of perceived excessive peer gambling (peer excess-PE), and family gambling prompting concern (family concern-FC) in 2750 high-school students. Adolescents were separately stratified into: (1) low-risk, at-risk, and problem/pathological gambling groups; and, (2) non-binge-drinking, low-frequency-binge-drinking, and high-frequency-binge-drinking groups. Multinomial logistic regression showed that relative to each other, FC and PE were associated with greater likelihoods of at-risk and problem/pathological gambling. However, only FC was associated with binge-drinking. Logistic regression revealed that adolescents who endorsed either FC or PE alone, compared to no endorsement, were more likely to have at-risk and problem/pathological gambling, relative to low-risk gambling. Adolescents who endorsed both FC and PE, compared to PE alone, were more likely to have problem/pathological gambling relative to low-risk and at-risk gambling. Relative to non-binge-drinking adolescents, those who endorsed both FC and PE were more likely to have low- and high-frequency-binge-drinking compared to FC alone or PE alone, respectively. Family and peer gambling individually contribute to adolescent at-risk/problem gambling and binge-drinking. Strategies that target adolescents as well as their closely affiliated family and peer members may be an important step towards prevention of harm-associated levels of gambling and alcohol use in youths.

Substance-use initiation moderates the effect of stress on white-matter microstructure in adolescents

BACKGROUND

While childhood stress may contribute risk to substance-use initiation and differences in brain white-matter development, understanding of the potential impact of substance-use initiation on the relationship between experienced stress and white-matter microstructure remains limited.

OBJECTIVES

This study examined whether substance-use initiation moderated the effect of perceived stress on white-matter differences using measures of primary white-matter fiber anisotropy.

METHODS

Forty adolescents (age 14.75 ± .87 years) were assessed on the Perceived Stress Scale, and 50% were determined to have presence of substance-use initiation. White-matter microstructure was examined using primary-fiber orientations anisotropy, which may reflect white-matter integrity, modeled separately from other fiber orientations in the same voxels. Analyses were conducted on regions of interest previously associated with childhood stress and substance use.

RESULTS

Lower perceived stress and presence of substance-use initiation were related to greater right cingulum primary-fiber measures. Substance-use-initiation status moderated the association between perceived stress and right cingulum primary-fiber measures, such that higher perceived stress was associated with lower right cingulum primary-fiber anisotropy in adolescents without substance-use initiation, but not in those with substance-use initiation.

CONCLUSIONS AND SCIENTIFIC SIGNIFICANCE

Findings in primary-fiber anisotropy suggest differences in right cingulum white-matter integrity is associated with substance-use initiation in higher-stress adolescents. This reflects a possible pre-existing risk factor, an impact of early substance use, or a combination thereof. Examination of potential markers associated with substance-use initiation in white-matter microstructure among stress-exposed youth warrant additional investigation as such biomarkers may inform efforts relating to tailored interventions. (Am J Addict 2018;27:217-224).

Gray-matter relationships to diagnostic and transdiagnostic features of drug and behavioral addictions

Alterations in neural structure have been reported in both cocaine-use disorder and gambling disorder, separately, suggesting similarities across addiction diagnoses. Individual variation in neural structure has also been associated with impulsivity, a dimensional construct implicated in addictions. This study combines categorical (diagnosis-based) and dimensional (transdiagnostic) approaches to identify neural structural alterations linked to addiction subtypes and trait impulsivity, respectively, across individuals with gambling disorder (n = 35), individuals with cocaine-use disorder (n = 37) and healthy comparison individuals (n = 37). High-resolution T1-weighted data were analyzed using modulated voxel-based morphometry (VBM). Statistical analyses were conducted using whole-brain general-linear models, corrected for family-wise error (pFWE < .05). Categorical analyses indicated a main effect of diagnostic group on prefrontal (dorsal anterior cingulate and ventromedial prefrontal cortex) gray matter volumes (GMVs), involving decreased GMVs among cocaine-use disorder participants only. Dimensional analyses indicated a negative association between trait impulsivity and cortical (insula) and subcortical (amygdala and hippocampus) GMVs across all participants. Conjunction analysis indicated little anatomical overlap between regions identified as differentiating diagnostic groups and regions covarying with impulsivity. These data provide first evidence of neural structural differences between gambling disorder and an illicit substance-use disorder. They further indicate dissociable effects of diagnostic groupings and trait impulsivity on neural structure among individuals with behavioral and drug addictions. Study findings highlight the importance of considering both categorical and dimensional (e.g. Research Domain Criteria; RDoC) analysis approaches within the context of addictions research.

Meta-analysis of regional white matter volume in bipolar disorder with replication in an independent sample using coordinates, T-maps, and individual MRI data

Converging evidence suggests that bipolar disorder (BD) is associated with white matter (WM) abnormalities. Meta-analyses of voxel based morphometry (VBM) data is commonly performed using published coordinates, however this method is limited since it ignores non-significant data. Obtaining statistical maps from studies (T-maps) as well as raw MRI datasets increases accuracy and allows for a comprehensive analysis of clinical variables. We obtained coordinate data (7-studies), T-Maps (12-studies, including unpublished data) and raw MRI datasets (5-studies) and analysed the 24 studies using Seed-based d Mapping (SDM). A VBM analysis was conducted to verify the results in an independent sample. The meta-analysis revealed decreased WM volume in the posterior corpus callosum extending to WM in the posterior cingulate cortex. This region was significantly reduced in volume in BD patients in the independent dataset (p=0.003) but there was no association with clinical variables. We identified a robust WM volume abnormality in BD patients that may represent a trait marker of the disease and used a novel methodology to validate the findings.

Altered functional connectivity to stressful stimuli in prenatally cocaine-exposed adolescents

BACKGROUND

Prenatal cocaine exposure (PCE) is linked to addiction and obesity vulnerability. Neural responses to stressful and appetitive cues in adolescents with PCE versus those without have been differentially linked to substance-use initiation. However, no prior studies have assessed cue-reactivity responses among PCE adolescents using a connectivity-based approach.

METHODS

Twenty-two PCE and 22 non-prenatally drug-exposed (NDE) age-, sex-, IQ- and BMI-matched adolescents participated in individualized guided imagery with appetitive (favorite-food), stressful and neutral-relaxing cue scripts during functional magnetic resonance imaging. Subjective favorite-food craving scores were collected before and after script exposure. A data-driven voxel-wise intrinsic connectivity distribution analysis was used to identify between-group differences and examine relationships with craving scores.

RESULTS

A group-by-cue interaction effect identified a parietal lobe cluster where PCE versus NDE adolescents showed less connectivity during stressful and more connectivity during neutral-relaxing conditions. Follow-up seed-based connectivity analyses revealed that, among PCE adolescents, the parietal seed was positively connected to inferior parietal and sensory areas and negatively connected to corticolimbic during both stress and neutral-relaxing conditions. For NDE, greater parietal connectivity to parietal, cingulate and sensory areas and lesser parietal connectivity to medial prefrontal areas were found during stress compared to neutral-relaxing cueing. Craving scores inversely correlated with corticolimbic connectivity in PCE, but not NDE adolescents, during the favorite-food condition.

CONCLUSIONS

Findings from this first data-driven intrinsic connectivity analysis of PCE influences on adolescent brain function indicate differences relating to PCE status and craving. These findings provide insight into the developmental impact of in utero drug exposure.

Reward-related frontostriatal activity and smoking behavior among adolescents in treatment for smoking cessation

BACKGROUND

Tobacco use is often initiated during adolescence and continued into adulthood despite desires to quit. A better understanding of the neural correlates of abstinence from smoking in adolescents may inform more effective smoking cessation interventions. Neural reward systems are implicated in tobacco use disorder, and adolescent smokers have shown reduced reward-related ventral striatal activation related to increased smoking.

METHODS

The current study evaluated nondrug reward anticipation in adolescent smokers using a monetary incentive delay task in fMRI pre- and post- smoking cessation treatment (n=14). This study tested how changes in neural responses to reward anticipation pre- to post-treatment were related to reduced smoking. An exploratory analysis in a larger sample of adolescents with only pre-treatment fMRI (n=28) evaluated how neural responses to reward anticipation were related to behavioral inhibition and behavioral activation scales.

RESULTS

Adolescent smokers showed pre- to post-treatment increases in reward anticipation-related activity in the bilateral nucleus accumbens and insula, and medial prefrontal cortex, and greater increases in reward anticipation-related activity were correlated with larger percent days of smoking abstinence during treatment.

CONCLUSIONS

These findings suggest that reduced smoking during smoking cessation treatment is associated with a "recovery of function" in frontostriatal responses to nondrug reward anticipation in adolescent smokers, although comparison with a developmental control group of adolescent nonsmokers is warranted.

White-matter crossing-fiber microstructure in adolescents prenatally exposed to cocaine

BACKGROUND

Prenatal cocaine exposure (PCE) is associated with risk-taking behaviors, including increased initiation of substance use in adolescence. The neurobiological underpinnings of these behaviors in adolescents with PCE are not well understood. The goal of this study was to compare diffusion-weighted imaging data between adolescents with and without PCE using crossing-fiber models, which may provide more comprehensive estimates of white-matter microstructure within regions of multiple (e.g., primary and secondary) fiber orientations.

METHODS

Thirty-nine PCE individuals and 17 comparably aged prenatally non-drug-exposed (NDE) youths were recruited from a longitudinal cohort followed since birth. White matter was examined using tensor-derived and crossing-fiber models. Whole-brain investigations were performed, as were analyses on seven white-matter regions, which included the splenium, body and genu of the corpus callosum, bilateral cingulum, and the right and left superior longitudinal fasciculus (SLF).

RESULTS

Whole-brain analyses revealed no group differences. However, ROI analyses for anisotropy estimates derived from the crossing-fiber model revealed significant group differences for secondary fibers, with reduced anisotropy among PCE adolescents compared to prenatally non-exposed youth in the right cingulum and the left SLF, and increased anisotropy in the genu.

CONCLUSIONS

Our findings suggest that white-matter differences in PCE adolescents are subtle and localized primarily within secondary fiber orientations, perhaps arising from altered white-matter development.

Activation of the ventral and dorsal striatum during cue reactivity in Internet gaming disorder

Studies conducted in drug addiction suggest a transition in processing of drug-related cues from the ventral to the dorsal component of the striatum. However, this process has not been studied in a behavioral addiction. Assessment of this process in a non-drug addiction can provide insight into the pathophysiology of both substance and behavioral addictions. Thirty-nine male Internet gaming disorder (IGD) subjects and 23 male matched healthy controls (HCs) participated in functional magnetic resonance imaging during performance of a cue-reactivity task involving alternating presentation of Internet gaming-related stimuli (game cues) and general Internet surfing-related stimuli (control cues). Cue-induced neural activations in the ventral and dorsal striatum (DS) were compared between IGD and HC participants. Associations between cue-reactivity within these regions and cue-induced craving and severity and duration of IGD were also explored. IGD participants exhibited higher cue-induced activations within both the ventral and DS when compared with HCs. Within the IGD group, activity within the left ventral striatum (VS) was correlated negatively with cue-induced craving; positive associations were found between activations within the DS (right putamen, pallidum and left caudate) and duration of IGD. Cue-induced activity within the left putamen was negatively associated with right VS volumes among IGD participants. Consistent with studies in substance addictions, our results suggest that a transition from ventral to dorsal striatal processing may occur among individuals with IGD, a condition without the impact of substance intake.

Intra-individual changes in Stroop-related activations linked to cigarette abstinence in adolescent tobacco smokers: Preliminary findings

BACKGROUND

Adolescence is a crucial time for initiation of tobacco-smoking. Developing more effective treatment interventions for tobacco-smoking in youth is therefore critical to reduce smoking rates in both adolescent and adult populations. Elucidation of the neural mechanisms of successful behavioral change (abstinence) will allow for improvement of therapies based on known brain mechanisms.

METHODS

Twenty-one adolescent tobacco-smokers (14-19 years) participated in functional magnetic resonance imaging (fMRI) during performance of a cognitive control (Stroop) task prior to randomization to smoking cessation treatment (trial of combined nicotine replacement therapy/placebo and contingency management for attendance/abstinence; NCT01145001). Fourteen adolescents also participated in fMRI scanning following completion of the six-week trial. fMRI data were analyzed using random-effects models in SPM12. Paired t-tests were used to identify group-level changes (main effect of treatment exposure) in neural functional responses. Regression models were used to identify individual-level changes associated with treatment-outcomes (percent days abstinent, maximum days of consecutive abstinence).

RESULTS

Main effects of Stroop task performance (contrast of incongruent versus congruent trials) were seen across a priori ROIs at both pre- and post-treatment (pFWE<0.05). At the group-level, no changes in neural responses were found following treatment. However, intra-individual reductions in Stroop-related activity (within the insula and anterior cingulate) were positively associated with measures of smoking abstinence during treatment (pFWE<0.05).

CONCLUSIONS

Abstinence from tobacco during smoking cessation treatment among adolescents is associated with cognitive-control related reductions in neural activity within specific regions (anterior cingulate, insula), suggesting that increases in cognitive efficiency may underlie optimal treatment responses in this population.