Structural indices of brain aging in methamphetamine use disorder.

BACKGROUND: Methamphetamine use is surging globally. It has been linked to premature stroke, Parkinsonism, and dementia, suggesting that it may accelerate brain aging. METHODS: We performed a retrospective study to determine if structural indices of brain aging were more prevalent prior to old age (26 - 54 years) in individuals with Methamphetamine Use Disorder (MUD), who were in early abstinence (M ± SD = 22.1 ± 25.6 days) than in healthy control (HC) participants. We compared T1-weighted MRI brain scans in age- and sex-matched groups (n = 89/group) on three structural features of brain aging: the brain volume/cerebrospinal fluid (BV/CSF) index, volume of white matter hypointensities/lesions, and choroid plexus volume. RESULTS: The MUD group had a lower mean BV/CSF index and larger volumes of white matter hypointensities and choroid plexus (p-values < 0.01). Regression analyses showed significant age-by-group effects, indicating different age trajectories of the BV/CSF index and choroid plexus volume, consistent with abnormal global brain atrophy and choroid plexus pathology in the MUD group. Significant age and group main effects reflected a larger volume of white matter hypointensities for older participants across groups and for the MUD group irrespective of age. None of the three measures of brain aging correlated significantly with recent use or duration of recent abstinence from methamphetamine. CONCLUSIONS: Premature brain pathology, which may reflect cerebrovascular damage and dysfunction of the choroid plexus, occurs in people with MUD. Such pathology may affect cognition and thereby efficacy of behavioral treatments for MUD.

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

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

Value-based decision-making predicts alcohol use and related problems in young men.

BACKGROUND: Alcohol consumption is a leading cause of morbidity and mortality worldwide, disproportionately affecting young men. Heavy episodic drinking is particularly prevalent among men, with this behavior peaking between the ages of 20 and 24. AIMS: We sought to identify dimensions of decision-making in men that would predict the development of hazardous alcohol use through emerging adulthood. METHODS: This prospective observational study profiled value-based decision-making in 198 healthy men at age 18 and assessed their alcohol involvement annually until age 24. Latent growth curve modeling estimated individual variability in trajectories of alcohol involvement and regressed this variability on five choice dimensions. RESULTS: Low loss aversion predicted sustained heavy episodic drinking from age 18 to 24. Both high delay discounting and risk-seeking for gains independently predicted a considerably higher cumulative alcohol use during these 6 years, with high delay discounting indicating escalating consumption from age 21. Risk-seeking for gains additionally predicted meeting more criteria for Alcohol Use Disorder in these 6 years. Risk-seeking for losses was not significantly related to alcohol outcomes. Choice preferences were largely independent of each other but were correlated with choice consistency, with low consistency predicting heavy episodic drinking from age 18 to 24 beyond these associations. CONCLUSIONS: The predictive effects collectively suggest that overvaluing immediate and probabilistic incentives, rather than underestimating harm, drives hazardous drinking in young men. The differential relations of choice preferences and consistency to alcohol involvement through emerging adulthood provide distinct cognitive-behavioral patterns that warrant consideration in the development of harm reduction interventions.

Mindfulness and clinical correlates in methamphetamine use disorder.

BACKGROUND: Mindfulness-based interventions are increasingly used for the treatment of substance use disorders, including methamphetamine use disorder (MUD). Literature indicates that trait mindfulness may play a key role in the effectiveness of these treatments on therapeutic outcome, yet no prior studies have tested for differences in trait mindfulness between individuals with MUD and healthy control participants. Such differences are important for treatment implementation. OBJECTIVES: The goals of this study were to evaluate trait mindfulness and to determine its clinical correlates in individuals with MUD. METHODS: A group of participants with MUD at varying lengths of abstinence from methamphetamine (< 1h to 90 days; mean 5.4 ± 12.5 days; N=95, 53 female, 42 male) and a healthy control group (N=65, 30 female, 35 male) completed the Mindfulness Attention Awareness Scale (MAAS). Group differences and relationships between trait mindfulness and several measures of drug use and psychiatric symptoms were evaluated. RESULTS: In participants with MUD, trait mindfulness was 10% lower than in healthy controls (p < 0.001), but it was not significantly correlated with measures of drug use or craving. Across both groups, trait mindfulness was negatively correlated with state anxiety, depression, emotional dysregulation, impulsivity, and a history of childhood trauma, while it was positively correlated with self-compassion (ps < 0.001). CONCLUSION: The deficit in trait mindfulness in MUD presents a capacity that can be targeted for improved treatment outcome with mindfulness-based therapies. Trait mindfulness is inversely related to mood dysregulation.

Smoking, tobacco dependence, and neurometabolites in the dorsal anterior cingulate cortex.

Cigarette smoking has a major impact on global health and morbidity, and positron emission tomographic research has provided evidence for reduced inflammation in the human brain associated with cigarette smoking. Given the consequences of inflammatory dysfunction for health, the question of whether cigarette smoking affects neuroinflammation warrants further investigation. The goal of this project therefore was to validate and extend evidence of hypoinflammation related to smoking, and to examine the potential contribution of inflammation to clinical features of smoking. Using magnetic resonance spectroscopy, we measured levels of neurometabolites that are putative neuroinflammatory markers. N-acetyl compounds (N-acetylaspartate + N-acetylaspartylglutamate), glutamate, creatine, choline-compounds (phosphocholine + glycerophosphocholine), and myo-inositol, have all been linked to neuroinflammation, but they have not been examined as such with respect to smoking. We tested whether people who smoke cigarettes have brain levels of these metabolites consistent with decreased neuroinflammation, and whether clinical features of smoking are associated with levels of these metabolites. The dorsal anterior cingulate cortex was chosen as the region-of-interest because of previous evidence linking it to smoking and related states. Fifty-four adults who smoked daily maintained overnight smoking abstinence before testing and were compared with 37 nonsmoking participants. Among the smoking participants, we tested for associations of metabolite levels with tobacco dependence, smoking history, craving, and withdrawal. Levels of N-acetyl compounds and glutamate were higher, whereas levels of creatine and choline compounds were lower in the smoking group as compared with the nonsmoking group. In the smoking group, glutamate and creatine levels correlated negatively with tobacco dependence, and creatine correlated negatively with lifetime smoking, but none of the metabolite levels correlated with craving or withdrawal. The findings indicate a link between smoking and a hypoinflammatory state in the brain, specifically in the dorsal anterior cingulate cortex. Smoking may thereby increase vulnerability to infection and brain injury.

Negative affect and craving during abstinence from smoking are both linked to default mode network connectivity.

BACKGROUND: Negative affect and craving during abstinence from cigarettes predict resumption of smoking. Therefore, understanding their neural substrates may guide development of new interventions. Negative affect and craving have traditionally been linked to functions of the brain's threat and reward networks, respectively. However, given the role of default mode network (DMN), particularly the posterior cingulate cortex (PCC), in self-related thought, we examined whether DMN activity underlies both craving and negative affective states in adults who smoke. METHODS: 46 adults who smoke abstained from smoking overnight and underwent resting-state fMRI, after self-reporting their psychological symptoms (negative affect) and craving on the Shiffman-Jarvik Withdrawal Scale and state anxiety (negative affect) on the Spielberger State-Trait Anxiety Inventory. Within-DMN functional connectivity using 3 different anterior PCC seeds was tested for correlations with self-report measures. Additionally, independent component analysis with dual regression was performed to measure associations of self-report with whole-brain connectivity of the DMN component. RESULTS: Craving correlated positively with connectivity of all three anterior PCC seeds with posterior PCC clusters (pcorr<0.04). The measures of negative affective states correlated positively with connectivity of the DMN component to various brain regions, including posterior PCC (pcorr=0.02) and striatum (pcorr<0.008). Craving and state anxiety were correlated with connectivity of an overlapping region of PCC (pcorr=0.003). Unlike the state measures, nicotine dependence and trait anxiety were not associated with PCC connectivity within DMN. CONCLUSIONS: Although negative affect and craving are distinct subjective states, they appear to share a common neural pathway within the DMN, particularly involving the PCC.

Decomposing risky decision-making in methamphetamine use disorder: Behavioral updating and D2 dopamine receptors.

BACKGROUND: Escalating misuse of amphetamine-type stimulants, mainly methamphetamine, has led to a staggering rise in associated overdose deaths and a pressing need to understand the basis of methamphetamine use disorder (MUD). MUD is characterized by disadvantageous decision-making, and people with MUD perform below controls on the Balloon Analogue Risk Task (BART), a laboratory test of decision-making under uncertainty. The BART presents a series of choices with progressively higher stakes-greater risk of loss and greater potential monetary reward. This research aimed to clarify whether impaired behavioral updating contributes to maladaptive performance on the BART. METHODS: Two groups (28 drug-abstinent participants with MUD and 16 healthy control participants) were compared on BART performance. Using a computational model, we deconstructed behavior into risk-taking and behavioral updating. A subset of participants (22 MUD, 15 healthy control) underwent [18F]fallypride positron emission tomography scans to measure dopamine D2-type receptor availability (BPND) in the striatum (caudate and accumbens nuclei and putamen) and the globus pallidus. RESULTS: Participants with MUD exhibited slower behavioral updating than the healthy controls (p = 0.0004, d=1.77). BPND in all four bilateral volumes of interest were higher in the healthy control group (ps < 0.005, ds < 2.16), and updating rate correlated positively with BPND in the caudate nucleus (p = 0.002), putamen (p = 0.002), and globus pallidus (p = 0.03). CONCLUSIONS: The findings indicate that behavioral updating contributes to maladaptive decision-making in MUD and suggest that dysregulation of D2-type receptor signaling in the striatum and globus pallidus contributes to this behavioral deficit.

Nicotine dependence and insula subregions: functional connectivity and cue-induced activation.

Nicotine dependence is a major predictor of relapse in people with Tobacco Use Disorder (TUD). Accordingly, therapies that reduce nicotine dependence may promote sustained abstinence from smoking. The insular cortex has been identified as a promising target in brain-based therapies for TUD, and has three major sub-regions (ventral anterior, dorsal anterior, and posterior) that serve distinct functional networks. How these subregions and associated networks contribute to nicotine dependence is not well understood, and therefore was the focus of this study. Sixty individuals (28 women; 18-45 years old), who smoked cigarettes daily, rated their level of nicotine dependence (on the Fagerström Test for Nicotine Dependence) and, after abstaining from smoking overnight (~12 h), underwent functional magnetic resonance imaging (fMRI) in a resting state. A subset of these participants (N = 48) also completing a cue-induced craving task during fMRI. Correlations between nicotine dependence and resting-state functional connectivity (RSFC) and cue-induced activation of the major insular sub-regions were evaluated. Nicotine dependence was negatively correlated with connectivity of the left and right dorsal, and left ventral anterior insula with regions within the superior parietal lobule (SPL), including the left precuneus. No relationship between posterior insula connectivity and nicotine dependence was found. Cue-induced activation in the left dorsal anterior insula was positively associated with nicotine dependence and negatively associated with RSFC of the same region with SPL, suggesting that craving-related responsivity in this subregion was greater among participants who were more dependent. These results may inform therapeutic approaches, such as brain stimulation, which may elicit differential clinical outcomes (e.g., dependence, craving) depending on the insular subnetwork that is targeted.

Reduced neural functional connectivity during working memory performance in methamphetamine use disorder.

BACKGROUND: Methamphetamine misuse, a surging cause of morbidity and mortality worldwide, identifies Methamphetamine Use Disorder (MUD) as a critical public health problem. Treatment for MUD typically is sought during early abstinence when patients are experiencing cognitive difficulties that may hamper their engagement in treatment and recovery. Cognitive difficulties, particularly those that involve executive functions, likely reflect disruptions in neural functioning involving multiple brain areas and circuits. METHODS: To extend knowledge in this area, we compared individuals with MUD (MUD group, n = 30) in early abstinence (3-11 days abstinent) with a healthy control group (HC, n = 33) on brain activation and network connectivity and topology, using functional magnetic resonance imaging (fMRI) during performance on an N-back working memory task. The N-back task involves the maintenance and manipulation of information in short-term memory and engages multiple neural processes related to executive functioning. The task was administered at two working-memory difficulty loads (1-back and 2-back). RESULTS: Compared with the HC group, the MUD group had worse task performance but no differences in task-related brain activation. Network-based statistics analyses, however, revealed that the MUD group exhibited less functional network connectivity at both difficulty loads of the N-back task than the HC group. Additional graph theory analyses showed that path lengths were longer, and clustering was lower across these networks, which also exhibited disrupted small-world properties in the MUD group. CONCLUSION: These results suggest a decoupling in network dynamics that may underlie deficits in cognition during early abstinence in MUD patients.

Recalibrating single-study effect sizes using hierarchical Bayesian models.

Introduction: There are growing concerns about commonly inflated effect sizes in small neuroimaging studies, yet no study has addressed recalibrating effect size estimates for small samples. To tackle this issue, we propose a hierarchical Bayesian model to adjust the magnitude of single-study effect sizes while incorporating a tailored estimation of sampling variance. Methods: We estimated the effect sizes of case-control differences on brain structural features between individuals who were dependent on alcohol, nicotine, cocaine, methamphetamine, or cannabis and non-dependent participants for 21 individual studies (Total cases: 903; Total controls: 996). Then, the study-specific effect sizes were modeled using a hierarchical Bayesian approach in which the parameters of the study-specific effect size distributions were sampled from a higher-order overarching distribution. The posterior distribution of the overarching and study-specific parameters was approximated using the Gibbs sampling method. Results: The results showed shrinkage of the posterior distribution of the study-specific estimates toward the overarching estimates given the original effect sizes observed in individual studies. Differences between the original effect sizes (i.e., Cohen's d) and the point estimate of the posterior distribution ranged from 0 to 0.97. The magnitude of adjustment was negatively correlated with the sample size (r = -0.27, p < 0.001) and positively correlated with empirically estimated sampling variance (r = 0.40, p < 0.001), suggesting studies with smaller samples and larger sampling variance tended to have greater adjustments. Discussion: Our findings demonstrate the utility of the hierarchical Bayesian model in recalibrating single-study effect sizes using information from similar studies. This suggests that Bayesian utilization of existing knowledge can be an effective alternative approach to improve the effect size estimation in individual studies, particularly for those with smaller samples.

Denial and Diagnosis of Methamphetamine Dependence Severity.

Introduction: Denial, or lack of awareness of problems related to substance misuse, is a common feature of drug use disorders and can affect engagement in treatment and recovery. This study tested for association of denial with severity of symptoms used in the diagnosis of Methamphetamine Dependence. Methods: This secondary analysis used data from 69 participants (52.2% male) who met criteria for the diagnosis of Methamphetamine Dependence on the Structured Clinical Interview for DSM-IV (SCID). The association between diagnostic severity, determined from a SCID summary score (8 items), and denial, measured by the University of Rhode Island Change Assessment Scale (URICA) Precontemplation score, was tested by Pearson correlation. In post hoc t-tests, participants who differed on individual SCID items were compared on the Precontemplation score. The additional URICA subscales (Contemplation, Maintenance, Action) were also tested on a secondary basis. Results: SCID summary scores were negatively correlated with URICA Precontemplation scores (P = .003). Post-hoc tests revealed that participants who denied continued methamphetamine use despite persistent or recurrent problems (SCID item 6) had significantly higher Precontemplation scores than those who endorsed these problems (t = 3.066, P = .003). In contrast, positive correlations were observed between diagnostic severity and greater openness/willingness to change on the URICA (eg, Maintenance, r = .26; P = .01). Conclusions: The findings highlight the importance of a patient's insight regarding their addiction in clinical diagnosis. Because minimizing the impact of methamphetamine use may preclude or delay treatment, it is advised that self-report be supplemented to improve accuracy of diagnosis.

The Effects of Citalopram and Thalamic Dopamine D2/3 Receptor Availability on Decision-Making and Loss Aversion in Alcohol Dependence.

Selective serotonin reuptake inhibitors (SSRIs) are commonly prescribed for patients who misuse alcohol, especially in the context of comorbid depressive symptoms. Deficits in impulse control and decision-making are linked to routine alcohol consumption and alcohol dependence. The goal of this study was to determine the effects of a single dose of citalopram on measures of impulsivity, decision-making, and/or brain dopamine receptor availability in alcohol-dependent individuals. A double-blind, placebo-controlled, within-subject, outpatient study was conducted with active alcohol-dependent (DSM-IV-TR criteria) participants (n = 12) and matched healthy controls (n = 13). Serial doses of both citalopram (40 mg) and saline were administered intravenously before laboratory tests of decision-making (Balloon Analogue Risk Task, delay discounting task, and Loss Aversion Gambling Task) and positron emission tomography with [18F]-fallypride to measure dopamine D2/3 receptor availability, separated by at least one week. Alcohol-dependent participants demonstrated greater loss aversion than healthy controls, but there were no group differences in risk taking on the Balloon Analogue Risk Task. Citalopram increased delay discounting across groups, with no group difference in the effect. There were no effects of citalopram on risk taking on the Balloon Analogue Risk Task. PET showed a negative correlation between thalamic dopamine D2/3 receptor availability and loss aversion across groups. The effect of citalopram to decrease the valuation of monetary reward as a function of delay raises the possibility that SSRIs can influence risky decision-making in clinical populations. In addition, these results suggest that altered thalamic dopamine signaling may play an important role in disproportionately valuing losses in patients with Alcohol Use Disorder. This trial is registered under ClinicalTrials.gov registration NCT01657760.

Cortical thickness and related depressive symptoms in early abstinence from chronic methamphetamine use.

Methamphetamine use is surging globally as a cause of morbidity and mortality. Treatment is typically sought in early abstinence, when craving and depressive symptoms are intense, contributing to relapse and poor outcomes. To advance an understanding of this problem and identify therapeutic targets, we conducted a retrospective analysis of brain structure in 89 adults with Methamphetamine Use Disorder who were in early abstinence and 89 healthy controls. Unlike most prior research, the participants did not significantly differ in age, sex and recent use of alcohol and tobacco (p-values ≥ 0.400). We analysed thickness across the entire cerebral cortex by fitting a general linear model to identify differences between groups. Follow-up regressions were performed to determine whether cortical thickness in regions showing group differences was related to craving, measured on a visual analogue scale, or to the Beck Depression Inventory score. Participants in early methamphetamine abstinence (M ± SD = 22.1 ± 25.6 days) exhibited thinner cortex in clusters within bilateral frontal, parietal, temporal, insular, and right cingulate cortices relative to controls (p-values < 0.001, corrected for multiple comparisons). Unlike craving (ß = 0.007, p = 0.947), depressive symptoms were positively correlated with cortical thickness across clusters (ß = 0.239, p = 0.030) and with thickness in the anterior cingulate cluster (ß = 0.246, p = 0.027) in the methamphetamine-dependent group. Inasmuch as anterior cingulate pathology predicts response to antidepressants for Major Depressive Disorder, cingulate structure may also identify patients with Methamphetamine Use Disorder who can benefit from antidepressant medication.

Effects of ibudilast on central and peripheral markers of inflammation in alcohol use disorder: A randomized clinical trial.

Ibudilast, a neuroimmune modulator, shows promise as a pharmacotherapy for alcohol use disorder (AUD). In vivo administration of ibudilast reduces the expression of pro-inflammatory cytokines in animal models, but its effects on markers of inflammation in humans are unknown. This preliminary study examined the effect of ibudilast on peripheral and potential central markers of inflammation in individuals with AUD. This study also explored the predictive relationship of neurometabolite markers with subsequent drinking in the trial. Non-treatment-seeking individuals with an AUD (n = 52) were randomized to receive oral ibudilast (n = 24) or placebo (n = 28) for 2 weeks. Plasma levels of peripheral inflammatory markers were measured at baseline and after 1 and 2 weeks of medication. At study mid-point, proton magnetic resonance spectroscopy was performed to measure potential neurometabolite markers of inflammation: choline-compounds (Cho), myo-inositol (MI) and creatine + phosphocreatine (Cr) in frontal and cingulate cortices from 43 participants (ibudilast: n = 20; placebo: n = 23). The treatment groups were compared on peripheral and central markers. Ibudilast-treated participants had lower Cho in superior frontal white matter and nominally lower MI in pregenual anterior cingulate cortex. Ibudilast-treated participants had nominally lower C-reactive protein levels at visit 2 and nominally lower TNF-α/IL-10 ratios, relative to placebo. C-reactive protein and Cho levels were correlated, controlling for medication. Superior frontal white matter Cho predicted drinking in the following week. Micro-longitudinal ibudilast treatment may induce peripheral and putative central anti-inflammatory responses in patients with AUD. The neurometabolite responses may be associated with reduction in drinking, suggesting an anti-inflammatory component to the therapeutic action of ibudilast.

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

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

Targeting maladaptive reactivity to negative affect in emerging adults with cannabis use disorder: A preliminary test and proof of concept.

INTRODUCTION: Cannabis use disorder (CUD) is a growing public health concern, and is highly comorbid with negative affective conditions such as anxiety and depression. Late adolescence and early adulthood represents a time of rapid emotion regulation development, as well as the onset of anxiety, mood, and substance use disorders, especially CUD. Maladaptive cognitive, behavioral, and emotional responding to one's own negative affect (in an effort to eliminate it) is associated with substance use, and represents a novel treatment target to improve outcomes of treatment for substance misuse. METHOD: After development of a manual for a novel intervention, Affect Management Treatment (AMT) for CUD, a pilot randomized clinical trial was conducted in 18-25 year-old participants with CUD to evaluate the impact of this approach on negative affect, constructs (e.g., distress intolerance) representing maladaptive reactivity to negative affect, and cannabis use. Participants (N = 52) received either 12 sessions of standard cognitive behavioral therapy (CBT) for CUD or 12 sessions of AMT and were assessed on measures of negative affect, reactivity to negative affect, cannabis use, and cannabis use problems at baseline, throughout treatment, post-treatment, and 6-mo follow-up. RESULTS: AMT outperformed CBT in reducing negative affect and reactivity to negative affect, and it had a significant impact on cannabis use and cannabis use problems. There were no statistically significant between-group differences on cannabis outcomes. CONCLUSIONS: AMT offers a novel, successful approach to the treatment of CUD.

White matter microstructure differences in individuals with dependence on cocaine, methamphetamine, and nicotine: Findings from the ENIGMA-Addiction working group.

BACKGROUND: Nicotine and illicit stimulants are very addictive substances. Although associations between grey matter and dependence on stimulants have been frequently reported, white matter correlates have received less attention. METHODS: Eleven international sites ascribed to the ENIGMA-Addiction consortium contributed data from individuals with dependence on cocaine (n = 147), methamphetamine (n = 132) and nicotine (n = 189), as well as non-dependent controls (n = 333). We compared the fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) of 20 bilateral tracts. Also, we compared the performance of various machine learning algorithms in deriving brain-based classifications on stimulant dependence. RESULTS: The cocaine and methamphetamine groups had lower regional FA and higher RD in several association, commissural, and projection white matter tracts. The methamphetamine dependent group additionally showed lower regional AD. The nicotine group had lower FA and higher RD limited to the anterior limb of the internal capsule. The best performing machine learning algorithm was the support vector machine (SVM). The SVM successfully classified individuals with dependence on cocaine (AUC = 0.70, p < 0.001) and methamphetamine (AUC = 0.71, p < 0.001) relative to non-dependent controls. Classifications related to nicotine dependence proved modest (AUC = 0.62, p = 0.014). CONCLUSIONS: Stimulant dependence was related to FA disturbances within tracts consistent with a role in addiction. The multivariate pattern of white matter differences proved sufficient to identify individuals with stimulant dependence, particularly for cocaine and methamphetamine.

Executive Function and Contingency Management in Methamphetamine Use Disorder.

OBJECTIVES: Contingency management is a promising intervention for Methamphetamine Use Disorder (MUD).Impaired executive function may decrease adherence to such treatment, but there are few data on whether impairment in executive function predicts treatment outcomes. We therefore evaluated whether baseline performance on tests of executive function predicted treatment response in a trial of contingency management for MUD. METHODS: Thirty participants with MUD and 23 healthy controls performed the Connors Continuous Performance Task (CPT) and the Trail Making Task. MUD participants then entered an 8-week contingency management trial. Participants were categorized as responders (n=17; no methamphetamine-positive urine tests) or non-responders (n=13; >1 positive test). The Kruskal-Wallis test was used to compare scores in participants with MUD and healthy controls, and in responders versus non-responders. RESULTS: Participants withMUD performed worse than controls on the CPT (d-prime) (p=0.012); non-responders performed worse than responders (p = 0.034). Performance of MUD participants did not differ significantly from controls on the Trail Making Task B (time to completion), but variation was high with non-responders performing worse than responders (p=0.013). CONCLUSION: These findings suggest that tests of executive function at baseline may be useful in predicting treatment response in MUD. Future work in larger samples may ultimately allow a more personalized treatment approach to methamphetamine use disorder.

Age Influences Loss Aversion Through Effects on Posterior Cingulate Cortical Thickness.

Decision-making strategies shift during normal aging and can profoundly affect wellbeing. Although overweighing losses compared to gains, termed "loss aversion," plays an important role in choice selection, the age trajectory of this effect and how it may be influenced by associated changes in brain structure remain unclear. We therefore investigated the relationship between age and loss aversion, and tested for its mediation by cortical thinning in brain regions that are susceptible to age-related declines and are implicated in loss aversion - the insular, orbitofrontal, and anterior and posterior cingulate cortices. Healthy participants (n = 106, 17-54 years) performed the Loss Aversion Task. A subgroup (n = 78) provided structural magnetic resonance imaging scans. Loss aversion followed a curvilinear trajectory, declining in young adulthood and increasing in middle-age, and thinning of the posterior cingulate cortex mediated this trajectory. The findings suggest that beyond a threshold in middle adulthood, atrophy of the posterior cingulate cortex influences loss aversion.

Functional connectivity of the anterior insula during withdrawal from cigarette smoking.

Currently available therapies for smoking cessation have limited efficacy, and potential treatments that target specific brain regions are under evaluation, with a focus on the insula. The ventral and dorsal anterior subregions of the insula serve distinct functional networks, yet our understanding of how these subregions contribute to smoking behavior is unclear. Resting-state functional connectivity (RSFC) provides a window into network-level function associated with smoking-related internal states. The goal of this study was to determine potentially distinct relationships of ventral and dorsal anterior insula RSFC with cigarette withdrawal after brief abstinence from smoking. Forty-seven participants (24 women; 18-45 years old), who smoked cigarettes daily and were abstinent from smoking overnight (~12 h), provided self-reports of withdrawal and underwent resting-state fMRI before and after smoking the first cigarette of the day. Correlations between withdrawal and RSFC were computed separately for ventral and dorsal anterior insula seed regions in whole-brain voxel-wise analyses. Withdrawal was positively correlated with RSFC of the right ventral anterior insula and dorsal anterior cingulate cortex (dACC) before but not after smoking. The correlation was mainly due to a composite effect of craving and physical symptoms of withdrawal. These results suggest a role of right ventral anterior insula-dACC connectivity in the internal states that maintain smoking behavior (e.g., withdrawal) and present a specific neural target for brain-based therapies seeking to attenuate withdrawal symptoms in the critical early stages of smoking cessation.