Multi-level predictors of depression symptoms in the Adolescent Brain Cognitive Development (ABCD) study.

BACKGROUND: While identifying risk factors for adolescent depression is critical for early prevention and intervention, most studies have sought to understand the role of isolated factors rather than across a broad set of factors. Here, we sought to examine multi-level factors that maximize the prediction of depression symptoms in US children participating in the Adolescent Brain and Cognitive Development (ABCD) study. METHODS: A total of 7,995 participants from ABCD (version 3.0 release) provided complete data at baseline and 1-year follow-up data. Depression symptoms were measured with the Child Behavior Checklist. Predictive features included child demographic, environmental, and structural and resting-state fMRI variables, parental depression history and demographic characteristics. We used linear (elastic net regression, EN) and non-linear (gradient-boosted trees, GBT) predictive models to identify which set of features maximized prediction of depression symptoms at baseline and, separately, at 1-year follow-up. RESULTS: Both linear and non-linear models achieved comparable results for predicting baseline (EN: MAE = 3.757; R2 = 0.156; GBT: MAE = 3.761; R2 = 0.147) and 1-year follow-up (EN: MAE = 4.255; R2 = 0.103; GBT: MAE = 4.262; R2 = 0.089) depression. Parental history of depression, greater family conflict, and shorter child sleep duration were among the top predictors of concurrent and future child depression symptoms across both models. Although resting-state fMRI features were relatively weaker predictors, functional connectivity of the caudate was consistently the strongest neural feature associated with depression symptoms at both timepoints. CONCLUSIONS: Consistent with prior research, parental mental health, family environment, and child sleep quality are important risk factors for youth depression. Functional connectivity of the caudate is a relatively weaker predictor of depression symptoms but may represent a biomarker for depression risk.

Amphetamine use disorder is associated with striatum hypoactivation during anticipation of loss and reward.

BACKGROUND: Dysregulated ventral striatum function has been proposed as one important process occurring in individuals with substance use disorder. This study investigates the role of altered reward and loss anticipation, which is an important component of impaired decision-making, impulsivity, and vulnerability to relapse in individuals with amphetamine use disorder (AMP). AIMS: To determine whether AMP is associated with blunted striatum, prefrontal cortex, and insula signals during win and loss anticipation. METHODS: Participants with and without AMP (AMP+ n = 46, AMP- n = 90) from the Tulsa 1000 study completed a monetary incentive delay (MID) task during functional magnetic resonance imaging. RESULTS: Group main effects indicated that: (1) AMP+ exhibited lower bilateral caudate/putamen and left nucleus accumbens signal than AMP- across anticipation of wins and losses; and (2) AMP+ showed slower reaction times than AMP- during loss anticipation. Group*condition interactions demonstrated that AMP+ exhibited greater right amygdala signal than AMP- while anticipating large wins, a pattern that reversed when anticipating small losses. Left caudate/putamen attenuations in AMP+ during small loss anticipation were also evident. Groups did not differ in prefrontal or insula signals. CONCLUSIONS: AMP+ individuals have altered neural processing and response patterns during reward and loss anticipation, potentially reflecting impairments in dopamine function, which may influence their decision-making and reactions to different win/loss scenarios. These findings help to explain why AMP+ have difficulty with decision-making and exhibit a heightened focus on immediate rewards or punishments.

Regional cortical brain volumes at treatment entry relates to post treatment WHO risk drinking levels in those with alcohol use disorder.

BACKGROUND: Abstinence following treatment for alcohol use disorder (AUD) is associated with significant improvements in psychiatric and physical health, however, recent studies suggest resumption of low risk levels of alcohol use can also be beneficial. The present study assessed whether post-treatment levels of alcohol use were associated with cortical brain volumedifferences at treatment entry. METHODS: Individuals seeking treatment for AUD (n=75) and light/non-drinking controls (LN, n=51) underwent 1.5T magnetic resonance imaging. The volumes of 34 bilateral cortical regions of interest (ROIs) were quantitated via FreeSurfer. Individuals with AUD were classified according to post-treatment alcohol consumption using the WHO risk drinking levels (abstainers: AB; low risk: RL; or higher risk: RH). Regional volumes for AB, RL and RH, at treatment entry, were compared to LN. RESULTS: Relative to LN, AB demonstrated smaller volumes in 18/68 (26%), RL in 24/68 (35%) and RH in 34/68 (50%) ROIs with the largest magnitude volume differences observed between RH and LN. RH and RL reported a higher frequency of depressive disorders than AB. Among RH and RL, level of depressive and anxiety symptomatology were associated with daily number of drinks consumed after treatment. CONCLUSIONS: Volumetric differences, at treatment entry, in brain regions implicated in executive function and salience networks corresponded with post-treatment alcohol consumption levels suggesting that pre-existing differences in neural integrity may contribute to treatment outcomes. Depressive and anxiety symptomatology was also associated with brain morphometrics and alcohol use patterns, highlighting the importance of effectively targeting these conditions during AUD treatment.

C-reactive protein concentrations diverge as a function of substance use disorder: A pre-registered replication in a clinical sample.

BACKGROUND: Inflammatory biomarkers may differentiate clinical disorders, which could lead to more targeted interventions. Analyses within a clinical sample (May et al., 2021) revealed that females with substance use disorders (SUD) exhibited lower C-reactive protein (CRP) and higher interleukin (IL)-8 and -10 concentrations than females without SUD who met criteria for mood/anxiety disorders. We aimed to replicate these findings in a new sample. METHODS: Hypotheses and analyses were preregistered. Treatment-seeking individuals with mood/anxiety disorders and/or SUD (N = 184) completed a blood draw, clinical interview, and questionnaires. Participants were categorized as SUD+ (45F, 43M) and SUD- (78F, 18M). Principal component analysis (PCA) of questionnaire data resulted in two factors reflecting appetitive and aversive emotional states. SUD group and nuisance covariates (PCA factors, age, body mass index [BMI], medication, nicotine [and hormones in females]) predicted biomarker concentrations (CRP, IL-8, and IL-10) in regressions. RESULTS: In females, the omnibus CRP model [F(8, 114) = 8.02, p <.001, R²-adjusted =.32] indicated that SUD+ exhibited lower CRP concentrations than SUD- (ß = -.33, t = -3.09, p =.002, 95% CI [-.54, -.12]) and greater BMI was associated with higher CRP levels (ß =.58, t = 7.17, p <.001, 95% CI [.42,.74]). SUD+ exhibited higher IL-8 levels than SUD- in simple but not omnibus regression models. CONCLUSION: Findings across two samples bolster confidence that females with SUD show attenuated CRP-indexed inflammation. As SUD+ comorbidity was high, replication is warranted with respect to specific SUD classes (i.e., stimulants versus cannabis).

Mindfulness-Based Interventions for the Treatment of Aberrant Interoceptive Processing in Substance Use Disorders.

Altered interoception, or the processing of bodily signals, has been argued to play a role in the development and maintenance of substance use disorders (SUD). Therefore, interoceptive interventions focusing on bodily awareness, such as mindfulness meditation, may improve treatment outcomes for individuals with SUD. Here we review: (1) subjective, behavioral and brain evidence for altered interoceptive processing in SUD, focusing on insular and anterior cingulate cortices (INS, ACC), key regions for interoceptive processing; (2) research highlighting links between mindfulness and brain function; and (3) extant brain research investigating mindfulness-based interventions in SUD. SUD tend to be characterized by heightened INS and ACC responses to drug cues but blunted interoceptive awareness and attenuated INS and ACC responses during tasks involving bodily attention and/or perturbations. In contrast, mindfulness interventions in healthy individuals are linked to enhanced INS and ACC responses and heightened interoceptive awareness. It is crucial for future research to identify: (1) whether mindfulness-based treatments are efficacious across substance classes; (2) what particular approaches and dosages show the largest effect sizes in enhancing INS and ACC function to non-drug stimuli and reducing responsivity to substance cues, thereby improving SUD treatment outcomes (reducing drug craving and relapse).

A prospective investigation of youth alcohol experimentation and reward responsivity in the ABCD study.

Rationale: Greater risk-taking behaviors, such as alcohol experimentation, are associated with different patterns of brain functioning in regions implicated in reward (nucleus accumbens, NA) and cognitive control (inferior frontal gyrus, IFG). These neural features have been observed in youth with greater risk-taking tendencies prior to substance use initiation, suggesting NA-IFG disruption may serve as an early marker for subsequent substance use disorders. Prospective studies are needed to determine if NA-IFG neural disruption predicts future substance use in school-age children, including those with minimal use of alcohol (e.g., sipping). The present large-sample prospective study sought to use machine learning to: (1) examine alcohol sipping at ages 9, 10 as a potential behavioral indicator of concurrent underlying altered neural responsivity to reward, and (2) determine if alcohol sipping and NA-IFG activation at ages 9, 10 can be used to predict which youth reported increased alcohol use at ages 11, 12. Additionally, low-level alcohol use and brain functioning at ages 9, 10 were examined as predictors of substance use and brain functioning at ages 11, 12. Design and methods: This project used data from the baseline (Time 1) and two-year follow-up (Time 2) assessments of the Adolescent Brain Cognitive Development (ABCD) Study (Release 3.0). Support Vector Machine (SVM) learning determined if: (1) NA-IFG neural activity could correctly identify youth who reported alcohol sipping at Time 1 (n = 7409, mean age = 119.34 months, SD = 7.53; 50.27% female), and (2) NA-IFG and alcohol sipping frequency at Time 1 could correctly identify youth who reported drinking alcohol at Time 2 (n = 4000, mean age = 143.25 months, SD = 7.63; 47.53% female). Linear regression was also used to examine the relationship between alcohol sipping and NA-IFG activity at Time 1 and substance use and NA-IFG activity at Time 2. Data were also examined to characterize the environmental context in which youth first tried sips of alcohol (e.g., with or without parental permission, as part of a religious experience). Results: Approximately 24% of the sample reported having tried sips of alcohol by ages 9, 10. On average, youth reported trying sips of alcohol 4.87 times (SD = 23.19) with age of first sip occurring at 7.36 years old (SD = 1.91). The first SVM model classified youth according to alcohol sipping status at Time 1 no better than chance with an accuracy of 0.35 (balanced accuracy = 0.52, sensitivity = 0.24, specificity = 0.80). The second SVM model classified youth according to alcohol drinking status at Time 2 with an accuracy of 0.76 (balanced accuracy = 0.56, sensitivity = 0.21, specificity = 0.91). Linear regression demonstrated that frequency of alcohol sipping at Time 1 predicted frequency of alcohol use at Time 2 (p < 0.001, adjusted R 2 = 0.075). Alcohol sipping at Time 1 was not linearly associated with NA or IFG activity at Time 2 (all ps > 0.05), and NA activity at Time 1 and Time 2 were not related (all ps > 0.05). Activity in the three subsections of the IFG at Time 1 predicted activity in those same regions at Time 2 (all ps < 0.02). Conclusions and implications: Early sips of alcohol appear to predict alcohol use in early adolescence. Findings do not provide strong evidence for minimal early alcohol use (sipping) as a behavioral marker of underlying alterations in NA-IFG neural responsivity to reward. Improving our understanding of the neural and behavioral factors that indicate a greater propensity for future substance use is crucial for identifying at-risk youth and potential targets for preventative efforts.

Sex differences in circulating inflammatory mediators as a function of substance use disorder.

BACKGROUND: Substance use disorders (SUD) with comorbid depression and anxiety are linked to poor treatment outcome and relapse. Although some depressed individuals exhibit elevated blood-based inflammation (interleukin-6 [IL-6] and C reactive protein [CRP]), few studies have examined whether the presence of SUD exacerbates inflammation. METHODS: Treatment-seeking individuals with major depressive disorder (MDD), anxiety disorders, and/or SUD (N = 160; 80 % with MDD) recruited into the Tulsa 1000 study provided blood samples, participated in clinical interviews, and completed a questionnaire battery querying symptoms of current psychopathology and emotional processing. Analyses followed a multistep process. First, groups were created on the presence versus absence of 1+ lifetime SUD diagnoses: SUD+ (37 F, 43 M) and SUD- (60 F, 20 M). Second, a principal component analysis (PCA) of questionnaire data resulted in two factors, one indexing negative emotionality/withdrawal motivation and one measuring positive emotionality/approach motivation. Third, SUD groups, extracted PCA factors, and nuisance covariates (age, body mass index [BMI], nicotine use, psychotropic medication [and hormone/contraception use in females]) were entered as simultaneous predictors of blood-based inflammation (IL-6, IL-8, IL-10, tumor necrosis factor-α, and CRP). RESULTS: Within females, SUD + exhibited higher IL-8 and IL-10 but lower CRP levels than SUD-. In contrast, SUD was not associated with biomarker levels in males. Across sexes, higher BMI was linked to higher IL-6 and CRP levels, and within the five biomarkers, IL-6 and CRP shared the most variance. CONCLUSION: These findings point to sex-specific inflammatory profiles as a function of SUD that may provide new targets for intervention.

Dark Times: The Role of Negative Reinforcement in Methamphetamine Addiction.

Methamphetamine use is associated with substantial adverse outcomes including poor mental and physical health, financial difficulties, and societal costs. Despite deleterious long-term consequences associated with methamphetamine, many people use drugs for short-term reduction of unpleasant physical or emotional sensations. By removing these aversive states, drug use behaviors are negatively reinforced. Abstinence from methamphetamine can then result in a return to previous aversive emotional states linked to withdrawal and craving, often contributing to an increased likelihood for relapse. This negative reinforcement cycle is hypothesized to be a motivating and maintaining factor for addiction. Thus, this review highlights the current evidence for negative reinforcement mechanisms in methamphetamine use disorder by integrating studies of subjective experience, behavior, functional magnetic resonance imaging, positron emission tomography, and event-related potentials and examining the efficacy of treatments targeting aspects of negative reinforcement. Overall, the literature demonstrates that individuals who use methamphetamine have diminished cognitive control and process emotions, loss of reward, and interoceptive information differently than non-using individuals. These differences are reflected in behavioral and subjective experiments as well as brain-based experiments which report significant differences in various frontal regions, insula, anterior cingulate cortex, and striatum. Together, the results suggest methamphetamine users have an altered experience of negative outcomes, difficulties employing effective emotion regulation, and difficulty engaging in adaptive or goal-directed decision-making. Suggestions for future research to improve our understanding of how negative reinforcement contributes to methamphetamine addiction and to develop effective interventions are provided.

Do Adolescents Use Substances to Relieve Uncomfortable Sensations? A Preliminary Examination of Negative Reinforcement among Adolescent Cannabis and Alcohol Users.

Alcohol and cannabis use are highly prevalent among adolescents and associated with negative consequences. Understanding motivations behind substance use in youth is important for informing prevention and intervention efforts. The present study aims to examine negative reinforcement principles of substance use among adolescent cannabis and alcohol users by pairing a cue reactivity paradigm with an aversive interoceptive stimulus. Adolescents (ages 15-17), classified as controls (CTL; n = 18), cannabis and/or alcohol experimenters (CAN+ALC-EXP; n = 16), or individuals meeting clinical criteria for cannabis and/or alcohol use disorder (CAN+ALC-SUD; n = 13) underwent functional magnetic resonance imaging during which they experienced an aversive interoceptive probe delivered via breathing load while simultaneously performing a cue reactivity paradigm. Participants also provided self-report ratings of how their substance use is positively or negatively reinforced. While experiencing the breathing load, CAN+ALC-SUD exhibited greater (p < 0.05) deactivation in the right amygdala, the left inferior frontal gyrus, and the left parahippocampal gyrus than CAN+ALC-EXP and CTL, who did not differ. Across all substance users, activation during the breathing load within the left parahippocampal gyrus negatively correlated with cannabis and alcohol lifetime use episodes and the left inferior frontal gyrus activity negatively correlated with lifetime alcohol use episodes. CAN+ALC-SUD reported experiencing more positive and negative reinforcement of using their substance of choice than CAN+ALC-EXP; both user groups reported higher levels of positive than negative reinforcement. Adolescents with a cannabis/alcohol use disorder demonstrate an altered response to interoceptive perturbations. However, adolescent cannabis/alcohol use does not appear to be driven by negative reinforcement, as viewing substance images did not dampen this response. Based on self-report data, the experience of positive reinforcement may be stronger for adolescents. Future studies should examine whether positive reinforcement contributes to adolescent substance use.

Bouncing back: Brain rehabilitation amid opioid and stimulant epidemics.

Recent methamphetamine and opioid use epidemics are a major public health concern. Chronic stimulant and opioid use are characterized by significant psychosocial, physical and mental health costs, repeated relapse, and heightened risk of early death. Neuroimaging research highlights deficits in brain processes and circuitry that are linked to responsivity to drug cues over natural rewards as well as suboptimal goal-directed decision-making. Despite the need for interventions, little is known about (1) how the brain changes with prolonged abstinence or as a function of various treatments; and (2) how symptoms change as a result of neuromodulation. This review focuses on the question: What do we know about changes in brain function during recovery from opioids and stimulants such as methamphetamine and cocaine? We provide a detailed overview and critique of published research employing a wide array of neuroimaging methods - functional and structural magnetic resonance imaging, electroencephalography, event-related potentials, diffusion tensor imaging, and multiple brain stimulation technologies along with neurofeedback - to track or induce changes in drug craving, abstinence, and treatment success in stimulant and opioid users. Despite the surge of methamphetamine and opioid use in recent years, most of the research on neuroimaging techniques for recovery focuses on cocaine use. This review highlights two main findings: (1) interventions can lead to improvements in brain function, particularly in frontal regions implicated in goal-directed behavior and cognitive control, paired with reduced drug urges/craving; and (2) the targeting of striatal mechanisms implicated in drug reward may not be as cost-effective as prefrontal mechanisms, given that deep brain stimulation methods require surgery and months of intervention to produce effects. Overall, more studies are needed to replicate and confirm findings, particularly for individuals with opioid and methamphetamine use disorders.

Forging Neuroimaging Targets for Recovery in Opioid Use Disorder.

The United States is in the midst of an opioid epidemic and lacks a range of successful interventions to reduce this public health burden. Many individuals with opioid use disorder (OUD) consume drugs to relieve physical and/or emotional pain, a pattern that may increasingly result in death. The field of addiction research lacks a comprehensive understanding of physiological and neural mechanisms instantiating this cycle of Negative Reinforcement in OUD, resulting in limited interventions that successfully promote abstinence and recovery. Given the urgency of the opioid crisis, the present review highlights faulty brain circuitry and processes associated with OUD within the context of the Three-Stage Model of Addiction (1). This model underscores Negative Reinforcement processes as crucial to the maintenance and exacerbation of chronic substance use together with Binge/Intoxication and Preoccupation/Anticipation processes. This review focuses on cross-sectional as well as longitudinal studies of relapse and treatment outcome that employ magnetic resonance imaging (MRI), functional near-infrared spectroscopy (fNIRs), brain stimulation methods, and/or electroencephalography (EEG) explored in frequency and time domains (the latter measured by event-related potentials, or ERPs). We discuss strengths and limitations of this neuroimaging work with respect to study design and individual differences that may influence interpretation of findings (e.g., opioid use chronicity/recency, comorbid symptoms, and biological sex). Lastly, we translate gaps in the OUD literature, particularly with respect to Negative Reinforcement processes, into future research directions involving operant and classical conditioning involving aversion/stress. Overall, opioid-related stimuli may lessen their hold on frontocingulate mechanisms implicated in Preoccupation/Anticipation as a function of prolonged abstinence and that degree of frontocingulate impairment may predict treatment outcome. In addition, longitudinal studies suggest that brain stimulation/drug treatments and prolonged abstinence can change brain responses during Negative Reinforcement and Preoccupation/Anticipation to reduce salience of drug cues, which may attenuate further craving and relapse. Incorporating this neuroscience-derived knowledge with the Three-Stage Model of Addiction may offer a useful plan for delineating specific neurobiological targets for OUD treatment.

Using neuroimaging to predict relapse in stimulant dependence: A comparison of linear and machine learning models.

OBJECTIVE: Relapse rates are consistently high for stimulant user disorders. In order to obtain prognostic information about individuals in treatment, machine learning models have been applied to neuroimaging and clinical data. Yet few efforts have been made to test these models in independent samples or show that they can outperform linear models. In this exploratory study, we examine whether machine learning models relative to linear models provide greater predictive accuracy and less overfitting. METHOD: This longitudinal study included 63 methamphetamine-dependent (training sample) and 29 cocaine-dependent (test sample) individuals who completed an MRI scan during residential treatment. Linear and machine learning models predicting relapse at a one-year follow up that were previously developed in the methamphetamine-dependent sample using neuroimaging and clinical variables were applied to the cocaine-dependent sample. Receiver operating characteristic analysis was used to assess performance using area under the curve (AUC) as the primary outcome. RESULTS: Twelve individuals in the cocaine-dependent sample remained abstinent, and 17 relapsed. The linear models produced more accurate prediction in the training sample than the machine learning models but showed reduced performance in the testing sample, with AUC decreasing by 0.18. The machine learning models produced similar predictive performance in the training and test samples, with AUC changing by 0.03. In the test sample, neither the linear nor the machine learning model predicted relapse at rates above chance. CONCLUSIONS: Although machine learning algorithms may have advantages, in this study neither model's performance was sufficient to be clinically useful. In order to improve predictive models, stronger predictor variables and larger samples are needed.

Blunted Frontostriatal Blood Oxygen Level-Dependent Signals Predict Stimulant and Marijuana Use.

BACKGROUND: Occasional recreational stimulant (amphetamine and cocaine) use is an important public health problem among young adults because 16% of those who experiment develop stimulant use disorder. This study aimed to determine whether behavioral and/or neural processing measures can forecast the transition from occasional to problematic stimulant use. METHODS: Occasional stimulant users completed a Risky Gains Task during functional magnetic resonance imaging and were followed up 3 years later. Categorical analyses tested whether blood oxygen level-dependent (BOLD) responses differentiated occasional stimulant users who became problem stimulant users (n = 35) from those who desisted from stimulant use (n = 75) at follow-up. Dimensional analyses (regardless of problem stimulant user or desisted stimulant use status; n = 144) tested whether BOLD responses predicted baseline and follow-up stimulant and marijuana use. RESULTS: Categorical results indicated that relative to those who desisted from stimulant use, problem stimulant users 1) made riskier decisions after winning feedback; 2) exhibited lower frontal, insular, and striatal BOLD responses to win/loss feedback after making risky decisions; and 3) displayed lower thalamic but greater temporo-occipital BOLD responses to risky losses than to risky wins. In comparison, dimensional results indicated that lower BOLD signals to risky choices than to safe choices in frontal, striatal, and additional regions predicted greater marijuana use at follow-up. CONCLUSIONS: Taken together, blunted frontostriatal signals during risky choices may quantify vulnerability to future marijuana consumption, whereas blunted frontostriatal signals to risky outcomes mark risk for future stimulant use disorder. These behavioral and neural processing measures may prove to be useful for identifying ultra-high risk individuals prior to onset of problem drug use.

Insular and cingulate attenuation during decision making is associated with future transition to stimulant use disorder.

AIMS: To understand processes placing individuals at risk for stimulant (amphetamine and cocaine) use disorder. DESIGN: Longitudinal study. SETTING: University of California, San Diego Department of Psychiatry, CA, USA. PARTICIPANTS: Occasional stimulant users (OSU; n = 184) underwent a baseline clinical interview and a functional magnetic resonance imaging (fMRI) session. On the basis of a follow-up clinical interview completed 3 years later, OSU (n = 147) were then categorized as problem stimulant users (PSU: n = 36; those who developed stimulant use disorders in the interim) or desisted stimulant users (DSU: n = 74; those who stopped using). OSU who did not meet criteria for PSU or DSU (n = 37) were included in dimensional analyses. MEASUREMENTS: fMRI blood oxygen level-dependent (BOLD) contrast percentage signal change from baseline collected during a Paper-Scissors-Rock task was examined during three decision-making conditions, those resulting in: (1) wins, (2) ties and (3) losses. These data were used as dependent variables in categorical analyses comparing PSU and DSU, as well as dimensional analyses including interim drug use as predictors, controlling for baseline drug use. FINDINGS: PSU exhibited lower anterior cingulate, middle insula, superior temporal, inferior parietal, precuneus and cerebellum activation than DSU across all three conditions (significant brain clusters required > 19 neighboring voxels to exceed F(1,108)  = 5.58, P < 0.01 two-tailed; all Cohen's d > 0.83). Higher interim marijuana use was linked to lower pre-central and superior temporal activation during choices resulting in wins (> 19 neighboring voxels to exceed t = 2.61, P < 0.01 two-tailed; R2 change > 0.11). CONCLUSIONS: Individuals who transition from stimulant use to stimulant use disorder appear to show alterations in neural processing of stimulus valuation and outcome monitoring, patterns also evident in chronic stimulant use disorder. Attenuated anterior cingulate and insular processing may constitute a high-risk neural processing profile, which could be used to calculate risk scores for individuals experimenting with stimulants.

Doubling down: increased risk-taking behavior following a loss by individuals with cocaine use disorder is associated with striatal and anterior cingulate dysfunction.

BACKGROUND: Cocaine use disorders (CUDs) have been associated with increased risk-taking behavior. Neuroimaging studies have suggested that altered activity in reward and decision-making circuitry may underlie cocaine user's heightened risk-taking. It remains unclear if this behavior is driven by greater reward salience, lack of appreciation of danger, or another deficit in risk-related processing. METHODS: Twenty-nine CUD participants and forty healthy comparison participants completed the Risky Gains Task during a functional magnetic resonance imaging scan. During the Risky Gains Task, participants choose between a safe option for a small, guaranteed monetary reward and risky options with larger rewards but also the chance to lose money. Frequency of risky choice overall and following a win versus a loss were compared. Neural activity during the decision and outcome phase were examined using linear mixed effects models. RESULTS: Although the groups did not differ in overall risk-taking frequency, the CUD group chose a risky option more often following a loss. Neuroimaging analyses revealed that the comparison group showed increasing activity in the bilateral ventral striatum as they chose higher-value, risky options, but the CUD group failed to show this increase. During the outcome phase, the CUD group showed a greater decrease in bilateral striatal activity relative to the comparison group when losing the large amount, and this response was correlated with risk-taking frequency after a loss. CONCLUSIONS: The brains of CUD individuals are hypersensitive to losses, leading to increased risk-taking behaviors, and this may help explain why these individuals take drugs despite aversive outcomes.

Electrophysiology for addiction medicine: From methodology to conceptualization of reward deficits.

In the past decade, electroencephalographic research on addiction has employed passive viewing, oddball, inhibition, prediction, gambling, and reversal learning tasks to study how substance users neurally prioritize drug-related rewards at the expense of nondrug rewards. On the whole, findings across substances (alcohol, cannabis, cocaine, nicotine, opiates, gambling, and gaming) demonstrate impairments in the differentiation of monetary incentives and the inhibition of prepotent responses. Furthermore, exaggerated resources devoted to drug cues and attenuated processing of other types of pleasant emotional stimuli predict greater probability of future drug use. However, drug use recency, frequency, sensitivity, and insight all appear to be moderators of these effects. We argue that more longitudinal studies are warranted to determine the time course of reward processing as a function of development and chronicity.

The Effects of Age, Mental Health, and Comorbidity on the Perceived Likelihood of Hiring a Healthcare Advocate.

BACKGROUND AND PURPOSE: The projected increase in chronically ill older adults may overburden the healthcare system and compromise the receipt of quality and coordinated health care services. Healthcare advocates (HCAs) may help to alleviate the burden associated with seeking and receiving appropriate health care. We examined whether having dementia or depression, along with hypertension and arthritis, or having no comorbid medical conditions, and being an older adult, affected the perceived likelihood of hiring an HCA to navigate the health care system. METHOD: Participants (N = 1,134), age 18 or older, read a vignette and imagined themselves as an older adult with either a mood or cognitive disorder, and comorbid medical conditions or as otherwise being physically healthy. They were then asked to complete a questionnaire assessing their perceived likelihood of hiring an HCA. RESULTS: Participants who imagined themselves as having dementia reported a greater likelihood of hiring an HCA than participants who imagined themselves as having depression (p < .001). CONCLUSION: It is imperative that health care professionals attend to the growing and ongoing needs of older adults living with chronic conditions, and HCAs could play an important role in meeting those needs.

When the brain does not adequately feel the body: Links between low resilience and interoception.

This study examined neural processes of resilience during aversive interoceptive processing. Forty-six individuals were divided into three groups of resilience Low (LowRes), high (HighRes), and normal (NormRes), based on the Connor-Davidson Resilience Scale (2003). Participants then completed a task involving anticipation and experience of loaded breathing during functional magnetic resonance imaging (fMRI) recording. Compared to HighRes and NormRes groups, LowRes self-reported lower levels of interoceptive awareness and demonstrated higher insular and thalamic activation across anticipation and breathing load conditions. Thus, individuals with lower resilience show reduced attention to bodily signals but greater neural processing to aversive bodily perturbations. In low resilient individuals, this mismatch between attention to and processing of interoceptive afferents may result in poor adaptation in stressful situations.

Do you feel alright? Attenuated neural processing of aversive interoceptive stimuli in current stimulant users.

Inability to appropriately process afferent interoceptive stimuli may contribute to initiation and/or escalation of substance use. An aversive interoceptive stimulus probed neural processing in problem stimulant users (PSU; n = 19), 18 desisted stimulant users (DSU; n = 18), and healthy comparison subjects (CTL; n = 21). Participants completed a continuous performance task while they anticipated and experienced 40 cm H2 O/L/sec inspiratory breathing loads during fMRI. PSU exhibited lower left dorsolateral prefrontal cortex and inferior frontal gyrus (IFG) activation than DSU and CTL across trials. Greater lifetime drug use due to stimulants was also linked to lower activation in these regions. In addition, PSU displayed lower right IFG and insula activation during breathing load than DSU and CTL. Findings suggest that transition to stimulant use disorders is marked by weakened attentional salience of aversive stimuli.