Examining the unique relationships between problematic use of the internet and impulsive and compulsive tendencies: network approach.

BACKGROUND: Both impulsivity and compulsivity have been identified as risk factors for problematic use of the internet (PUI). Yet little is known about the relationship between impulsivity, compulsivity and individual PUI symptoms, limiting a more precise understanding of mechanisms underlying PUI. AIMS: The current study is the first to use network analysis to (a) examine the unique association among impulsivity, compulsivity and PUI symptoms, and (b) identify the most influential drivers in relation to the PUI symptom community. METHOD: We estimated a Gaussian graphical model consisting of five facets of impulsivity, compulsivity and individual PUI symptoms among 370 Australian adults (51.1% female, mean age = 29.8, s.d. = 11.1). Network structure and bridge expected influence were examined to elucidate differential associations among impulsivity, compulsivity and PUI symptoms, as well as identify influential nodes bridging impulsivity, compulsivity and PUI symptoms. RESULTS: Results revealed that four facets of impulsivity (i.e. negative urgency, positive urgency, lack of premeditation and lack of perseverance) and compulsivity were related to different PUI symptoms. Further, compulsivity and negative urgency were the most influential nodes in relation to the PUI symptom community due to their highest bridge expected influence. CONCLUSIONS: The current findings delineate distinct relationships across impulsivity, compulsivity and PUI, which offer insights into potential mechanistic pathways and targets for future interventions in this space. To realise this potential, future studies are needed to replicate the identified network structure in different populations and determine the directionality of the relationships among impulsivity, compulsivity and PUI symptoms.

Attentional Biases and Their Association with Substance-Use-Related Problems and Addictive Behaviors: The Utility of a Gamified Value-Modulated Attentional Capture Task.

Background: Attentional biases towards reward stimuli have been implicated in substance use-related problems. The value-modulated attentional capture (VMAC) task assesses such reward-related biases. The VMAC task widely used in lab studies tends to be monotonous and susceptible to low effort. We therefore tested a gamified online version of the VMAC that aimed to increase participant engagement. Our goal was to examine how VMAC is associated with substance use-related problems and addictive behaviors, and whether this association is moderated by cognitive control. Methods: We recruited 285 participants from an online community, including heavy alcohol users. All participants completed a novel gamified version of the VMAC task, measures of substance use and addictive behaviors (addictive-like eating behavior, problematic smartphone use), the WebExec measure of problems with executive functions, and the Stroop Adaptive Deadline Task (SDL) as a measure of cognitive control. Results: The gamified VMAC task successfully identified value-modulated attentional capture effects towards high-reward stimuli. We found no significant associations between VMAC scores, problematic alcohol or cannabis use, addictive behaviors, or any moderation by a behavioral measure of cognitive control. Exploratory analyses revealed that self-reported cognitive problems were associated with more alcohol-, and cannabis-related problems, and addictive behaviors. Greater attentional capture (VMAC) was associated with more cannabis use-related problems among individuals with higher levels of self-reported cognitive problems. Conclusions: Our study is one of the first to demonstrate the utility of the gamified version of the VMAC task in capturing attentional reward biases. Self-reported problems with cognitive functions represent a key dimension associated with substance use-related problems and addictive behaviors.

The neurocognitive correlates of non-substance addictive behaviors.

Neurocognitive deficits have been implicated as transdiagnostic risk markers of substance use disorders. However, these have yet to be comprehensively evaluated in other, non-substance addictions. In a large, general community sample (N = 475) the present study evaluated the neurocognitive correlates of problem alcohol use and three non-substance-related addictive behaviors: addictive eating (AE), problematic pornography use (PPU), and problematic use of the internet (PUI), to identify potential shared and distinct neurocognitive correlates. A sample of Australian residents (54.4 % female M[SD] age = 32.4[11.9] years) completed a comprehensive online assessment of neurocognitive tasks tapping into eight distinct expert-endorsed domains purportedly associated with addiction. Multiple linear regressions with bootstrapping were used to examine associations among each addictive behavior of interest and neurocognition, trait impulsivity, and compulsivity, as well as key covariates. Neurocognition was differentially associated with each addictive behavior. None of the neurocognitive domains were significantly associated with problematic alcohol use or AE (p >.05), poorer performance monitoring was significantly associated with higher levels of PPU and PUI (ß = -0.10, p =.049; ß = -0.09, p =.028), and a preference for delayed gratification was associated with more severe PUI (ß = -0.10, p =.025). Our findings have theoretical implications for how we understand non-substance addiction and suggest the need for a more nuanced approach to studying addictive behaviors that take into account the underlying neurocognitive mechanisms associated with each type of addiction.

A Novel, Expert-Endorsed, Neurocognitive Digital Assessment Tool for Addictive Disorders: Development and Validation Study.

BACKGROUND: Many people with harmful addictive behaviors may not meet formal diagnostic thresholds for a disorder. A dimensional approach, by contrast, including clinical and community samples, is potentially key to early detection, prevention, and intervention. Importantly, while neurocognitive dysfunction underpins addictive behaviors, established assessment tools for neurocognitive assessment are lengthy and unengaging, difficult to administer at scale, and not suited to clinical or community needs. The BrainPark Assessment of Cognition (BrainPAC) Project sought to develop and validate an engaging and user-friendly digital assessment tool purpose-built to comprehensively assess the main consensus-driven constructs underpinning addictive behaviors. OBJECTIVE: The purpose of this study was to psychometrically validate a gamified battery of consensus-based neurocognitive tasks against standard laboratory paradigms, ascertain test-retest reliability, and determine their sensitivity to addictive behaviors (eg, alcohol use) and other risk factors (eg, trait impulsivity). METHODS: Gold standard laboratory paradigms were selected to measure key neurocognitive constructs (Balloon Analogue Risk Task [BART], Stop Signal Task [SST], Delay Discounting Task [DDT], Value-Modulated Attentional Capture [VMAC] Task, and Sequential Decision-Making Task [SDT]), as endorsed by an international panel of addiction experts; namely, response selection and inhibition, reward valuation, action selection, reward learning, expectancy and reward prediction error, habit, and compulsivity. Working with game developers, BrainPAC tasks were developed and validated in 3 successive cohorts (total N=600) and a separate test-retest cohort (N=50) via Mechanical Turk using a cross-sectional design. RESULTS: BrainPAC tasks were significantly correlated with the original laboratory paradigms on most metrics (r=0.18-0.63, P<.05). With the exception of the DDT k function and VMAC total points, all other task metrics across the 5 tasks did not differ between the gamified and nongamified versions (P>.05). Out of 5 tasks, 4 demonstrated adequate to excellent test-retest reliability (intraclass correlation coefficient 0.72-0.91, P<.001; except SDT). Gamified metrics were significantly associated with addictive behaviors on behavioral inventories, though largely independent of trait-based scales known to predict addiction risk. CONCLUSIONS: A purpose-built battery of digitally gamified tasks is sufficiently valid for the scalable assessment of key neurocognitive processes underpinning addictive behaviors. This validation provides evidence that a novel approach, purported to enhance task engagement, in the assessment of addiction-related neurocognition is feasible and empirically defensible. These findings have significant implications for risk detection and the successful deployment of next-generation assessment tools for substance use or misuse and other mental disorders characterized by neurocognitive anomalies related to motivation and self-regulation. Future development and validation of the BrainPAC tool should consider further enhancing convergence with established measures as well as collecting population-representative data to use clinically as normative comparisons.

Neurocognitive predictors of addiction-related outcomes: A systematic review of longitudinal studies.

It is well-established that addiction is typically associated with a distinct pattern of neurocognitive functioning with a consensus that it is typified by impaired top-down executive control and aberrant risk-reward processing. Despite a consensus that neurocognition plays an important role in characterizing and maintaining addictive disorders, there is a lack of systematic, bottom-up synthesis of quantitative evidence showing that neurocognition predicts addictive behaviors, and which neurocognitive constructs have the best predictive validity. This systematic review aimed to assess whether cognitive control and risk-reward processes as defined by the Research Domain Criteria (RDoC) predict the development and maintenance of addictive behaviors specifically, consumption, severity, and relapse. The findings from this review expose the substantial lack of evidence for neurocognition predicting addiction outcomes. However, there is evidence that suggests reward-related neurocognitive processes may be important for the detection of early risk for addiction, as well as a potentially viable target for designing novel, more effective interventions.

Lifestyle risk factors for obsessive-compulsive symptoms and related phenomena: What should lifestyle interventions target?

OBJECTIVE: Understanding the impact of lifestyle on mental illness symptoms is important for informing psycho-education and developing interventions which target mental and physical comorbidities. Obsessive-compulsive and related disorders can have a significant impact on health-related quality of life and physical health. However, our understanding of the impact of lifestyle on obsessive-compulsive symptoms and broader compulsive and impulsive problematic repetitive behaviours is limited. AIMS: We investigated whether lifestyle factors predicted change in obsessive-compulsive symptoms and problematic repetitive behaviours in a general population sample over a 3-month period. METHODS: Eight hundred thirty-five participants completed an online questionnaire battery assessing lifestyle and mental health. Of these, 538 participants completed the same battery 3 months later. We conducted negative binomial regressions to analyse the association of lifestyle factors at baseline with future (1) obsessive-compulsive symptoms, (2) compulsive problematic repetitive behaviours and (3) impulsive problematic repetitive behaviours, adjusting for baseline obsessive-compulsive symptoms and problematic repetitive behaviours. RESULTS: Lower vegetable (p = 0.020) and oily fish (p = 0.040) intake and lower moderate intensity physical activity (p = 0.008) predicted higher obsessive-compulsive symptoms at follow-up. Higher intake of high-fat foods (p < 0.001) predicted higher compulsive problematic repetitive behaviours at follow-up. No lifestyle factors significantly predicted impulsive problematic repetitive behaviours at follow-up. CONCLUSION: Our results speak to the potential importance of lifestyle quality screening, education and lifestyle interventions (e.g. an anti-inflammatory diet) for individuals experiencing compulsivity-related behaviours and/or symptoms. Further research into potential mechanisms of action will allow for more targeted approaches to lifestyle interventions for transdiagnostic compulsive behaviours.

Neural underpinnings of food choice and consumption in obesity.

BACKGROUND/OBJECTIVES: Obesity is associated with unhealthy food choices. Food selection is driven by the subjective valuation of available options, and the perceived and actual rewards accompanying consumption. These cognitive operations are mediated by brain regions including the ventromedial prefrontal cortex (vmPFC), dorsal anterior cingulate cortex (dACC), and ventral striatum (vStr). This study investigated the relationship between body mass index (BMI) and functional activations in the vmPFC, dACC, and vStr during food selection and consumption. SUBJECTS/METHODS: After overnight fasting, 26 individuals (BMI: 18-40 kg/m2) performed a food choice task while being scanned with functional magnetic resonance imaging (fMRI). Each trial involved selecting one beverage from a pair of presented options, followed by delivery of a 3 mL aliquot of the selected option using an MR-compatible gustometer. We also tracked subjective preference for each beverage throughout the experiment. RESULTS: During food choice, individuals with greater BMI had less activation in the dorsolateral prefrontal cortex when selecting a high-value option and less vmPFC activation upon its consumption. Independent of BMI, during food choice the dACC and anterior insula elicited higher activation when a less preferred beverage was selected. Activation of the dACC and a broader frontoparietal network was also observed when deciding between options more similar in value. During consumption, receipt of a more preferred beverage was associated with greater vmPFC response, and attenuation of the dACC. CONCLUSIONS: An individual's preference for a food option modulates the brain activity associated with choosing and consuming it. The relationship between food preference and underlying brain activity is altered in obesity, with reduced engagement of cognition-related regions when presented with a highly valued option, but a blunted response in reward-related regions upon consumption.

Endocannabinoid signaling of homeostatic status modulates functional connectivity in reward and salience networks.

RATIONALE: Endocannabinoids are well poised to regulate crosstalk between energy sensing of hunger and satiety and reward-driven motivation. OBJECTIVES: Here, we aimed to unravel associations between plasma endocannabinoids and brain connectivity in homeostatic and reward circuits across hunger and satiety states. METHODS: Fifteen participants (7 females) underwent two counter-balanced resting-state functional magnetic resonance imaging scans, one after overnight fasting and one after consumption of a standardized filling meal (satiety). Before each scan, we drew blood to measure plasma endocannabinoid concentrations (anandamide [AEA], anandamide-derived POEA, and 2-arachidonoylglycerol [2-AG]), analyzed with liquid chromatography tandem mass spectrometry. RESULTS: We found that AEA levels were associated with increased connectivity between the lateral hypothalamus and the ventral striatum during satiety. Furthermore, fasting AEA levels correlated with connectivity between the ventral striatum and the anterior cingulate cortex and the insula. CONCLUSIONS: Altogether, results suggest that peripheral AEA concentrations are sensitive to homeostatic changes and linked to neural communication in reward and salience networks. Findings may have significant implications for understanding normal and abnormal interactions between homeostatic input and reward valuation.

The role of psychological distress in the relationship between lifestyle and compulsivity: An analysis of independent, bi-national samples.

BACKGROUND: Poor mental health is a state of psychological distress that is influenced by lifestyle factors such as sleep, diet, and physical activity. Compulsivity is a transdiagnostic phenotype cutting across a range of mental illnesses including obsessive-compulsive disorder, substance-related and addictive disorders, and is also influenced by lifestyle. Yet, how lifestyle relates to compulsivity is presently unknown, but important to understand to gain insights into individual differences in mental health. We assessed (a) the relationships between compulsivity and diet quality, sleep quality, and physical activity, and (b) whether psychological distress statistically contributes to these relationships. METHODS: We collected harmonized data on compulsivity, psychological distress, and lifestyle from two independent samples (Australian n = 880 and US n = 829). We used mediation analyses to investigate bidirectional relationships between compulsivity and lifestyle factors, and the role of psychological distress. RESULTS: Higher compulsivity was significantly related to poorer diet and sleep. Psychological distress statistically mediated the relationship between poorer sleep quality and higher compulsivity, and partially statistically mediated the relationship between poorer diet and higher compulsivity. CONCLUSIONS: Lifestyle interventions in compulsivity may target psychological distress in the first instance, followed by sleep and diet quality. As psychological distress links aspects of lifestyle and compulsivity, focusing on mitigating and managing distress may offer a useful therapeutic approach to improve physical and mental health. Future research may focus on the specific sleep and diet patterns which may alter compulsivity over time to inform lifestyle targets for prevention and treatment of functionally impairing compulsive behaviors.

The Influence of Trait Compulsivity and Impulsivity on Addictive and Compulsive Behaviors During COVID-19.

Background: The COVID-19 pandemic has resulted in high levels of psychological distress worldwide, with experts expressing concern that this could result in corresponding increases in addictive behaviors as individuals seek to cope with their distress. Further, some individuals may be at greater risk than others for developing problematic addictive behaviors during times of high stress, such as individuals with high trait impulsivity and compulsivity. Despite the potential of such knowledge to inform early detection of risk, no study to date has examined the influence of trait impulsivity and compulsivity on addictive behaviors during COVID-19. Toward this aim, the current study examined the association between impulsive and compulsive traits and problematic addictive and compulsive behaviors during the first COVID-19 lockdown in Australia. Methods: Eight hundred seventy-eight adults completed a cross-sectional online survey during the first lockdown, between late May to June 2020. Participants completed scales for addictive and compulsive behaviors for the period prior to and during lockdown for problematic eating, pornography, internet use, gambling, drinking, and obsessive-compulsive behaviors. Negative binomial regressions examined the associations between impulsivity, compulsivity, and their interaction with problematic behaviors during lockdown, controlling for age, gender, sample, psychological distress, exposure to COVID-related stressors, and pre-COVID problems. Results: Greater trait compulsivity was associated with more problematic obsessive-compulsive behaviors (p < 0.001) and less problematic drinking (p = 0.038) during lockdown. Further, trait compulsivity interacted with trait impulsivity in relation to problematic eating behaviors (p = 0.014) such that greater trait compulsivity was associated with more problems among individuals with low impulsivity only (p = 0.030). Finally, psychological distress and/or exposure to COVID-related stressors were associated with greater problems across all addictive and compulsive behaviors, as was severity of pre-COVID problems. Discussion: Trait compulsivity was associated with addictive and compulsive behaviors in different ways. Further, the finding that stress-related variables (psychological distress and COVID-related stressors) were associated with greater problems across all lockdown behaviors supports the idea that stress may facilitate, or otherwise be associated with, problematic behaviors. These findings highlight the need for interventions that enhance resilience to stress, which in turn may reduce risk for addictive and compulsive disorders.

Cannabis Use in Adolescence: A Review of Neuroimaging Findings.

Objective: Shifting policies and widespread acceptance of cannabis for medical and/or recreational purposes have fueled worries of increased cannabis initiation and use in adolescents. In particular, the adolescent period is thought to be associated with an increased susceptibility to the potential harms of repeated cannabis use, due to being a critical period for neuromaturational events in the brain. This review investigates the neuroimaging evidence of brain harms attributable to adolescent cannabis use. Methods: PubMed and Scopus searches were conducted for empirical articles that examined neuroimaging effects in both adolescent cannabis users and adult user studies that explored the effect of age at cannabis use onset on the brain. Results: We found 43 studies that examined brain effect (structural and functional magnetic resonance imaging) in adolescent cannabis users and 20 that examined the link between onset age of cannabis use and brain effects in adult users. Studies on adolescent cannabis users relative to nonusers mainly implicate frontal and parietal regions and associated brain activation in relation to inhibitory control, reward, and memory. However, studies in adults are more mixed, many of which did not observe an effect of onset age of cannabis use on brain imaging metrics. Conclusions: While there is some evidence of compromised frontoparietal structure and function in adolescent cannabis use, it remains unclear whether the observed effects are specifically attributable to adolescent onset of use or general cannabis use-related factors such as depressive symptoms. The relative contribution of adolescent onset of cannabis use and use chronicity will have to be more comprehensively examined in prospective, longitudinal studies with more rigorous measures of cannabis use (dosage, exposure, dependence, constituent compounds such as the relative cannabinoid levels).

The Endocannabinoid System and Cannabidiol's Promise for the Treatment of Substance Use Disorder.

Substance use disorder is characterized by repeated use of a substance, leading to clinically significant distress, making it a serious public health concern. The endocannabinoid system plays an important role in common neurobiological processes underlying substance use disorder, in particular by mediating the rewarding and motivational effects of substances and substance-related cues. In turn, a number of cannabinoid drugs (e.g., rimonabant, nabiximols) have been suggested for potential pharmacological treatment for substance dependence. Recently, cannabidiol (CBD), a non-psychoactive phytocannabinoid found in the cannabis plant, has also been proposed as a potentially effective treatment for the management of substance use disorder. Animal and human studies suggest that these cannabinoids have the potential to reduce craving and relapse in abstinent substance users, by impairing reconsolidation of drug-reward memory, salience of drug cues, and inhibiting the reward-facilitating effect of drugs. Such functions likely arise through the targeting of the endocannabinoid and serotonergic systems, although the exact mechanism is yet to be elucidated. This article seeks to review the role of the endocannabinoid system in substance use disorder and the proposed pharmacological action supporting cannabinoid drugs' therapeutic potential in addictions, with a focus on CBD. Subsequently, this article will evaluate the underlying evidence for CBD as a potential treatment for substance use disorder, across a range of substances including nicotine, alcohol, psychostimulants, opioids, and cannabis. While early research supports CBD's promise, further investigation and validation of CBD's efficacy, across preclinical and clinical trials will be necessary.