Development and validation of the Autonomy Scale Amsterdam.

This paper describes the development and validation of the Autonomy Scale Amsterdam (ASA). We propose that a new measure of autonomy is needed and, as such, we developed and validated an autonomy scale relevant for psychiatry. Based on literature, an expert meeting and three samples of the general population (N = 298, N = 207, N = 309) we provide evidence (a) that supports a 6-factor structure model as a better fit than alternative models with a high reliability to capture the concept of autonomy consisting of: Self-integration, Engagement with life, Goal-directedness, Self-control, External constraints and Social support, (b) for the scale's convergent and discriminant validity with constructs in autonomy's nomological network and (c) for the scale's criterion validity with well-established well-being outcomes, and (d) that the measure is not redundant with a prior measure of autonomy, the autonomy-connectedness scale, and demonstrates incremental validity in the prediction of mental health over and above an existing measure of autonomy. Taken together, the results suggest that the ASA is a useful scale that shows positive evidence of psychometric quality to measure autonomy in a sample of the general population (total N = 856), accounting for a unique predictive value over and above an existing measure of autonomy concerning several mental health outcomes. The ASA can further help our understanding of the role of autonomy in mental disorders.

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.

Learning and metacognition under volatility in GD: Lower learning rates and distorted coupling between action and confidence.

Background and aims: Decisions and learning processes are under metacognitive control, where confidence in one's actions guides future behaviour. Indeed, studies have shown that being more confident results in less action updating and learning, and vice versa. This coupling between action and confidence can be disrupted, as has been found in individuals with high compulsivity symptoms. Patients with Gambling Disorder (GD) have been shown to exhibit both higher confidence and deficits in learning. Methods: In this study, we tested the hypotheses that patients with GD display increased confidence, reduced action updating and lower learning rates. Additionally, we investigated whether the action-confidence coupling was distorted in patients with GD. To address this, 27 patients with GD and 30 control participants performed a predictive inference task designed to assess action and confidence dynamics during learning under volatility. Action-updating, confidence and their coupling were assessed and computational modeling estimated parameters for learning rates, error sensitivity, and sensitivity to environmental changes. Results: Contrary to our expectations, results revealed no significant group differences in action updating or confidence levels. Nevertheless, GD patients exhibited a weakened coupling between confidence and action, as well as lower learning rates. Discussion and conclusions: This suggests that patients with GD may underutilize confidence when steering future behavioral choices. Ultimately, these findings point to a disruption of metacognitive control in GD, without a general overconfidence bias in neutral, non-incentivized volatile learning contexts.

The landscape of open science in behavioral addiction research: Current practices and future directions.

Open science refers to a set of practices that aim to make scientific research more transparent, accessible, and reproducible, including pre-registration of study protocols, sharing of data and materials, the use of transparent research methods, and open access publishing. In this commentary, we describe and evaluate the current state of open science practices in behavioral addiction research. We highlight the specific value of open science practices for the field; discuss recent field-specific meta-scientific reviews that show the adoption of such practices remains in its infancy; address the challenges to engaging with open science; and make recommendations for how researchers, journals, and scientific institutions can work to overcome these challenges and promote high-quality, transparently reported behavioral addiction research. By collaboratively promoting open science practices, the field can create a more sustainable and productive research environment that benefits both the scientific community and society as a whole.

Confidence and risky decision-making in gambling disorder.

Background and aims: People with Gambling Disorder (GD) often make risky decisions and experience cognitive distortions about gambling. Moreover, people with GD have been shown to be overly confident in their decisions, especially when money can be won. Here we investigated if and how the act of making a risky choice with varying monetary stakes impacts confidence differently in patients with GD (n = 27) relative to healthy controls (HCs) (n = 30). Methods: We used data from our previous mixed-gamble study, in which participants were given the choice of a certain option or a 50/50 gamble with potential gains or losses, after which they rated their confidence. Results: While HCs were more confident when making certain than risky choices, GD patients were specifically more confident when making risky choices than certain choices. Notably, relative to HCs, confidence of patients with GD decreased more strongly with higher gain values when making a certain choice, suggesting a stronger fear of missing out or "anticipated regret" of missing out on potential gains when rejecting the risky choice. Discussion: The current findings highlight the potential relevance of confidence and "regret" as cognitive mechanisms feeding into excessive risk-taking as seen in GD. Moreover, this study adds to the limited previous work investigating how confidence is affected in value-based risky contexts.

Brain volumes in alcohol use disorder: Do females and males differ? A whole-brain magnetic resonance imaging mega-analysis.

Emerging evidence suggests distinct neurobiological correlates of alcohol use disorder (AUD) between sexes, which however remain largely unexplored. This work from ENIGMA Addiction Working Group aimed to characterize the sex differences in gray matter (GM) and white matter (WM) correlates of AUD using a whole-brain, voxel-based, multi-tissue mega-analytic approach, thereby extending our recent surface-based region of interest findings on a nearly matching sample using a complementary methodological approach. T1-weighted magnetic resonance imaging (MRI) data from 653 people with AUD and 326 controls was analyzed using voxel-based morphometry. The effects of group, sex, group-by-sex, and substance use severity in AUD on brain volumes were assessed using General Linear Models. Individuals with AUD relative to controls had lower GM volume in striatal, thalamic, cerebellar, and widespread cortical clusters. Group-by-sex effects were found in cerebellar GM and WM volumes, which were more affected by AUD in females than males. Smaller group-by-sex effects were also found in frontotemporal WM tracts, which were more affected in AUD females, and in temporo-occipital and midcingulate GM volumes, which were more affected in AUD males. AUD females but not males showed a negative association between monthly drinks and precentral GM volume. Our results suggest that AUD is associated with both shared and distinct widespread effects on GM and WM volumes in females and males. This evidence advances our previous region of interest knowledge, supporting the usefulness of adopting an exploratory perspective and the need to include sex as a relevant moderator variable in AUD.

Striatal ups or downs? Neural correlates of monetary reward anticipation, cue reactivity and their interaction in alcohol use disorder and gambling disorder.

Background and aims: Dysfunction of the striatum, a brain region part of the mesolimbic reward system, is a key characteristic of addictive disorders, but neuroimaging studies have reported conflicting findings. An integrative model of addiction points to the presence or absence of addiction-related cues as an explanation for hyper- or hypoactivation, respectively, of the striatum. Methods: To test this model directly, we investigated striatal activation during monetary reward anticipation in the presence versus absence of addiction-related cues using functional MRI. Across two studies, we compared 46 alcohol use disorder (AUD) patients with 30 matched healthy controls; and 24 gambling disorder (GD) patients with 22 matched healthy controls. Results: During monetary reward anticipation, hypoactivation of the reward system was seen in AUD individuals compared to HCs. Additionally, a behavioral interaction was seen where gambling cues made participants, across groups, respond faster for bigger, but slower for smaller rewards. However, no striatal differences were seen in response to addiction-related cues between AUD or GD patients and their matched controls. Finally, despite substantial individual differences in neural activity to cue-reactivity and reward anticipation, these measures did not correlate, suggesting that they contribute independently to addiction aetiology. Discussion and Conclusions: Our findings replicate previous findings of blunted striatal activity during monetary reward anticipation in alcohol use disorder but do not support the idea that addiction-related cues explain striatal dysfunction as suggested by the model.

Goal-directed and habitual decision making under stress in gambling disorder: An fMRI study.

The development of addictive behaviors has been suggested to be related to a transition from goal-directed to habitual decision making. Stress is a factor known to prompt habitual behavior and to increase the risk for addiction and relapse. In the current study, we therefore used functional MRI to investigate the balance between goal-directed 'model-based' and habitual 'model-free' control systems and whether acute stress would differentially shift this balance in gambling disorder (GD) patients compared to healthy controls (HCs). Using a within-subject design, 22 patients with GD and 20 HCs underwent stress induction or a control condition before performing a multistep decision-making task during fMRI. Salivary cortisol levels showed that the stress induction was successful. Contrary to our hypothesis, GD patients did not show impaired goal-directed 'model-based' decision making, which remained similar to HCs after stress induction. Bayes factors provided three times more evidence against a difference between the groups or a group-by-stress interaction on the balance between model-based and model-free decision making. Similarly, no differences were found between groups and conditions on the neural estimates of model-based or model-free decision making. These results challenge the notion that GD is related to an increased reliance on habitual (or decreased goal-directed) control, even during stress.

Effects of 10 add-on HF-rTMS treatment sessions on alcohol use and craving among detoxified inpatients with alcohol use disorder: a randomized sham-controlled clinical trial.

BACKGROUND AND AIMS: Alcohol use disorder (AUD) is a chronic disorder with high relapse rates. There are currently few clinical trials of high frequency repetitive transcranial magnetic stimulation (HF-rTMS) to reduce alcohol use among AUD patients, and results are mixed. The current study tested the effect of 10 add-on sessions of HF-rTMS over the right dorsolateral pre-frontal cortex (DLPFC) on alcohol use and craving. DESIGN: Single-center, single blind sham-controlled parallel-group RCT (n = 80), with 3 and 6 months follow-up. SETTING: Clinical treatment center in Amsterdam, the Netherlands. PARTICIPANTS: Eighty detoxified and abstinent AUD inpatients in clinical treatment (20 females, average age = 44.35 years). INTERVENTION: Ten sessions of active or sham HF-rTMS (60 10 Hz trains of 5 sec at 110% motor threshold) over the right DLPFC on 10 consecutive work-days. MEASUREMENTS: The primary outcome measure is the number of abstinent days over 6-month follow-up (FU). Secondary outcome measures are craving over 6-month FU (alcohol urge questionnaire and obsessive-compulsive drinking scale), time to first relapse over 6-month FU and grams of alcohol consumed over 6-month FU. Additional outcome measures: full abstinence over 6-month FU and treatment success over 12-month FU. FINDINGS: HF-rTMS did not affect the number of abstinent days over 6 months FU [sham = 124 ± 65.9 days, active = 115 ± 69.8 days, difference: 9 days, 95% confidence interval (CI) = Poisson model: 0.578-3.547]. Moreover, HF-rTMS did not affect craving (AUQ/OCDS) (sham = 15.38/5.28, active = 17.48/4.75, differences = 2.1/-0.53, 95% CI mixed-effects model = -9.14 to 2.07/-1.44 to 2.40). CONCLUSIONS: There was no clear evidence that high-frequency repetitive transcranial magnetic stimulation over the right dorsolateral pre-frontal cortex treatment has a long-term positive effect on alcohol use or craving as add-on treatment for alcohol use disorder. High treatment response at 6-month follow-up could have limited the possibility to find an effect.

The role of attention in decision-making under risk in gambling disorder: An eye-tracking study.

Gambling disorder (GD) is a behavioural addiction characterized by impairments in decision-making, favouring risk- and reward-prone choices. One explanatory factor for this behaviour is a deviation in attentional processes, as increasing evidence indicates that GD patients show an attentional bias toward gambling stimuli. However, previous attentional studies have not directly investigated attention during risky decision-making. 26 patients with GD and 29 healthy matched controls (HC) completed a mixed gambles task combined with eye-tracking to investigate attentional biases for potential gains versus losses during decision-making under risk. Results indicate that compared to HC, GD patients gambled more and were less loss averse. GD patients did not show a direct attentional bias towards gains (or relative to losses). Using a recent (neuro)economics model that considers average attention and trial-wise deviations in average attention, we conducted fine-grained exploratory analyses of the attentional data. Results indicate that the average attention for gains in GD patients moderated the effect of gain value on gambling choices, whereas this was not the case for HC. GD patients with high average attention for gains started gambling at less high gain values. A similar trend-level effect was found for losses, where GD patients with high average attention for losses stopped gambling at lower loss values. This study gives more insight into how attentional processes in GD play a role in gambling behaviour, which could have implications for the development of future treatments focusing on attentional training or for the development of interventions that increase the salience of losses.

Cortical profiles of numerous psychiatric disorders and normal development share a common pattern.

The neurobiological bases of the association between development and psychopathology remain poorly understood. Here, we identify a shared spatial pattern of cortical thickness (CT) in normative development and several psychiatric and neurological disorders. Principal component analysis (PCA) was applied to CT of 68 regions in the Desikan-Killiany atlas derived from three large-scale datasets comprising a total of 41,075 neurotypical participants. PCA produced a spatially broad first principal component (PC1) that was reproducible across datasets. Then PC1 derived from healthy adult participants was compared to the pattern of CT differences associated with psychiatric and neurological disorders comprising a total of 14,886 cases and 20,962 controls from seven ENIGMA disease-related working groups, normative maturation and aging comprising a total of 17,697 scans from the ABCD Study® and the IMAGEN developmental study, and 17,075 participants from the ENIGMA Lifespan working group, as well as gene expression maps from the Allen Human Brain Atlas. Results revealed substantial spatial correspondences between PC1 and widespread lower CT observed in numerous psychiatric disorders. Moreover, the PC1 pattern was also correlated with the spatial pattern of normative maturation and aging. The transcriptional analysis identified a set of genes including KCNA2, KCNS1 and KCNS2 with expression patterns closely related to the spatial pattern of PC1. The gene category enrichment analysis indicated that the transcriptional correlations of PC1 were enriched to multiple gene ontology categories and were specifically over-represented starting at late childhood, coinciding with the onset of significant cortical maturation and emergence of psychopathology during the prepubertal-to-pubertal transition. Collectively, the present study reports a reproducible latent pattern of CT that captures interregional profiles of cortical changes in both normative brain maturation and a spectrum of psychiatric disorders. The pubertal timing of the expression of PC1-related genes implicates disrupted neurodevelopment in the pathogenesis of the spectrum of psychiatric diseases emerging during adolescence.

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.

Metacognition and the effect of incentive motivation in two compulsive disorders: Gambling disorder and obsessive-compulsive disorder.

AIMS: Compulsivity is a common phenotype among psychiatric disorders, such as obsessive-compulsive disorder (OCD) and gambling disorder (GD). Deficiencies in metacognition, such as the inability to estimate one's performance via confidence judgments could contribute to pathological decision-making. Earlier research has shown that patients with OCD exhibit underconfidence, while patients with GD exhibit overconfidence. Moreover, it is known that motivational states (e.g. monetary incentives) influence metacognition, with gain (respectively loss) prospects increasing (respectively decreasing) confidence. Here, we reasoned that OCD and GD symptoms might correspond to an exacerbation of this interaction between metacognition and motivation. METHODS: We hypothesized GD's overconfidence to be exaggerated during gain prospects, while OCD's underconfidence to be worsened in loss context, which we expected to see represented in ventromedial prefrontal cortex (VMPFC) blood-oxygen-level-dependent activity. We tested those hypotheses in a task-based functional magnetic resonance imaging (fMRI) design (27 patients with GD, 28 patients with OCD, 55 controls). The trial is registered in the Dutch Trial Register (NL6171). RESULTS: We showed increased confidence for patients with GD versus patients with OCD, which could partly be explained by sex and IQ. Although our primary analyses did not support the hypothesized interaction between incentives and groups, exploratory analyses did show increased confidence in patients with GD specifically in gain context. fMRI analyses confirmed a central role for VMPFC in the processing of confidence and incentives, but no differences between the groups. CONCLUSION: Patients with OCD and those with GD reside at opposite ends of the confidence spectrum, while no interaction with incentives was found, nor group differences in neuronal processing of confidence.

Motivational signals disrupt metacognitive signals in the human ventromedial prefrontal cortex.

A growing body of evidence suggests that, during decision-making, BOLD signal in the ventromedial prefrontal cortex (VMPFC) correlates both with motivational variables - such as incentives and expected values - and metacognitive variables - such as confidence judgments - which reflect the subjective probability of being correct. At the behavioral level, we recently demonstrated that the value of monetary stakes bias confidence judgments, with gain (respectively loss) prospects increasing (respectively decreasing) confidence judgments, even for similar levels of difficulty and performance. If and how this value-confidence interaction is reflected in the VMPFC remains unknown. Here, we used an incentivized perceptual decision-making fMRI task that dissociates key decision-making variables, thereby allowing to test several hypotheses about the role of the VMPFC in the value-confidence interaction. While our initial analyses seemingly indicate that the VMPFC combines incentives and confidence to form an expected value signal, we falsified this conclusion with a meticulous dissection of qualitative activation patterns. Rather, our results show that strong VMPFC confidence signals observed in trials with gain prospects are disrupted in trials with no - or negative (loss) - monetary prospects. Deciphering how decision variables are represented and interact at finer scales seems necessary to better understand biased (meta)cognition.

Investigating the causal nature of the relationship of subcortical brain volume with smoking and alcohol use.

BACKGROUND: Structural variation in subcortical brain regions has been linked to substance use, including the most commonly used substances nicotine and alcohol. Pre-existing differences in subcortical brain volume may affect smoking and alcohol use, but there is also evidence that smoking and alcohol use can lead to structural changes. AIMS: We assess the causal nature of the complex relationship of subcortical brain volume with smoking and alcohol use, using bi-directional Mendelian randomisation. METHOD: Mendelian randomisation uses genetic variants predictive of a certain 'exposure' as instrumental variables to test causal effects on an 'outcome'. Because of random assortment at meiosis, genetic variants should not be associated with confounders, allowing less biased causal inference. We used summary-level data of genome-wide association studies of subcortical brain volumes (nucleus accumbens, amygdala, caudate, hippocampus, pallidum, putamen and thalamus; n = 50 290) and smoking and alcohol use (smoking initiation, n = 848 460; cigarettes per day, n = 216 590; smoking cessation, n = 378 249; alcoholic drinks per week, n = 630 154; alcohol dependence, n = 46 568). The main analysis, inverse-variance weighted regression, was verified by a wide range of sensitivity methods. RESULTS: There was strong evidence that liability to alcohol dependence decreased amygdala and hippocampal volume, and smoking more cigarettes per day decreased hippocampal volume. From subcortical brain volumes to substance use, there was no or weak evidence for causal effects. CONCLUSIONS: Our findings suggest that heavy alcohol use and smoking can causally reduce subcortical brain volume. This adds to accumulating evidence that alcohol and smoking affect the brain, and likely mental health, warranting more recognition in public health efforts.

Predicting alcohol dependence from multi-site brain structural measures.

To identify neuroimaging biomarkers of alcohol dependence (AD) from structural magnetic resonance imaging, it may be useful to develop classification models that are explicitly generalizable to unseen sites and populations. This problem was explored in a mega-analysis of previously published datasets from 2,034 AD and comparison participants spanning 27 sites curated by the ENIGMA Addiction Working Group. Data were grouped into a training set used for internal validation including 1,652 participants (692 AD, 24 sites), and a test set used for external validation with 382 participants (146 AD, 3 sites). An exploratory data analysis was first conducted, followed by an evolutionary search based feature selection to site generalizable and high performing subsets of brain measurements. Exploratory data analysis revealed that inclusion of case- and control-only sites led to the inadvertent learning of site-effects. Cross validation methods that do not properly account for site can drastically overestimate results. Evolutionary-based feature selection leveraging leave-one-site-out cross-validation, to combat unintentional learning, identified cortical thickness in the left superior frontal gyrus and right lateral orbitofrontal cortex, cortical surface area in the right transverse temporal gyrus, and left putamen volume as final features. Ridge regression restricted to these features yielded a test-set area under the receiver operating characteristic curve of 0.768. These findings evaluate strategies for handling multi-site data with varied underlying class distributions and identify potential biomarkers for individuals with current AD.

How do substance use disorders compare to other psychiatric conditions on structural brain abnormalities? A cross-disorder meta-analytic comparison using the ENIGMA consortium findings.

Alcohol use disorder (AUD) and cannabis use disorder (CUD) are associated with brain alterations particularly involving fronto-cerebellar and meso-cortico-limbic circuitry. However, such abnormalities have additionally been reported in other psychiatric conditions, and until recently there has been few large-scale investigations to compare such findings. The current study uses the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium method of standardising structural brain measures to quantify case-control differences and to compare brain-correlates of substance use disorders with those published in relation to other psychiatric disorders. Using the ENIGMA protocols, we report effect sizes derived from a meta-analysis of alcohol (seven studies, N = 798, 54% are cases) and cannabis (seven studies, N = 447, 45% are cases) dependent cases and age- and sex-matched controls. We conduct linear analyses using harmonised methods to process and parcellate brain data identical to those reported in the literature for ENIGMA case-control studies of major depression disorder (MDD), schizophrenia (SCZ) and bipolar disorder so that effect sizes are optimally comparable across disorders. R elationships between substance use disorder diagnosis and subcortical grey matter volumes and cortical thickness were assessed with intracranial volume, age and sex as co-variates . After correcting for multiple comparisons, AUD case-control meta-analysis of subcortical regions indicated significant differences in the thalamus, hippocampus, amygdala and accumbens, with effect sizes (0.23) generally equivalent to, or larger than |0.23| those previously reported for other psychiatric disorders (except for the pallidum and putamen). On measures of cortical thickness, AUD was associated with significant differences bilaterally in the fusiform gyrus, inferior temporal gyrus, temporal pole, superior frontal gyrus, and rostral and caudal anterior cingulate gyri. Meta-analysis of CUD case-control studies indicated reliable reductions in amygdala, accumbens and hippocampus volumes, with the former effect size comparable to, and the latter effect size around half of that reported for alcohol and SCZ. CUD was associated with lower cortical thickness in the frontal regions, particularly the medial orbitofrontal region, but this effect was not significant after correcting for multiple testing. This study allowed for an unbiased cross-disorder comparison of brain correlates of substance use disorders and showed alcohol-related brain anomalies equivalent in effect size to that found in SCZ in several subcortical and cortical regions and significantly greater alterations than those found in MDD in several subcortical and cortical regions. Although modest, CUD results overlapped with findings reported for AUD and other psychiatric conditions, but appear to be most robustly related to reduce thickness of the medial orbitofrontal cortex.

Advancing urban mental health research: from complexity science to actionable targets for intervention.

Urbanisation and common mental disorders (CMDs; ie, depressive, anxiety, and substance use disorders) are increasing worldwide. In this Review, we discuss how urbanicity and risk of CMDs relate to each other and call for a complexity science approach to advance understanding of this interrelationship. We did an ecological analysis using data on urbanicity and CMD burden in 191 countries. We found a positive, non-linear relationship with a higher CMD prevalence in more urbanised countries, particularly for anxiety disorders. We also did a review of meta-analytic studies on the association between urban factors and CMD risk. We identified factors relating to the ambient, physical, and social urban environment and showed differences per diagnosis of CMDs. We argue that factors in the urban environment are likely to operate as a complex system and interact with each other and with individual city inhabitants (including their psychological and neurobiological characteristics) to shape mental health in an urban context. These interactions operate on various timescales and show feedback loop mechanisms, rendering system behaviour characterised by non-linearity that is hard to predict over time. We present a conceptual framework for future urban mental health research that uses a complexity science approach. We conclude by discussing how complexity science methodology (eg, network analyses, system-dynamic modelling, and agent-based modelling) could enable identification of actionable targets for treatment and policy, aimed at decreasing CMD burdens in an urban context.

Gender-related neuroanatomical differences in alcohol dependence: findings from the ENIGMA Addiction Working Group.

Gender-related differences in the susceptibility, progression and clinical outcomes of alcohol dependence are well-known. However, the neurobiological substrates underlying such differences remain unclear. Therefore, this study aimed to investigate gender differences in the neuroanatomy (i.e. regional brain volumes) of alcohol dependence. We examined the volume of a priori regions of interest (i.e., orbitofrontal cortex, hippocampus, amygdala, nucleus accumbens, caudate, putamen, pallidum, thalamus, corpus callosum, cerebellum) and global brain measures (i.e., total grey matter (GM), total white matter (WM) and cerebrospinal fluid). Volumes were compared between 660 people with alcohol dependence (228 women) and 326 controls (99 women) recruited from the ENIGMA Addiction Working Group, accounting for intracranial volume, age and education years. Compared to controls, individuals with alcohol dependence on average had (3-9%) smaller volumes of the hippocampus (bilateral), putamen (left), pallidum (left), thalamus (right), corpus callosum, total GM and WM, and cerebellar GM (bilateral), the latter more prominently in women (right). Alcohol-dependent men showed smaller amygdala volume than control men, but this effect was unclear among women. In people with alcohol dependence, more monthly standard drinks predicted smaller amygdala and larger cerebellum GM volumes. The neuroanatomical differences associated with alcohol dependence emerged as gross and widespread, while those associated with a specific gender may be confined to selected brain regions. These findings warrant future neuroscience research to account for gender differences in alcohol dependence to further understand the neurobiological effects of alcohol dependence.