An online global survey and follow-up expert groups on the scope and needs related to training, research, and mentorship among early-career addiction medicine professionals.

Addiction medicine is a rapidly growing field with many young professionals seeking careers in this field. However, early-career professionals (ECPs) face challenges such as a lack of competency-based training due to a shortage of trainers, limited resources, limited mentorship opportunities, and establishment of suitable research areas. The International Society of Addiction Medicine (ISAM) New Professionals Exploration, Training & Education (NExT) committee, a global platform for early-career addiction medicine professionals (ECAMPs), conducted a two-phase online survey using a modified Delphi-based approach among ECAMPs across 56 countries to assess the need for standardized training, research opportunities, and mentorship. A total of 110 respondents participated in Phase I (online key informant survey), and 28 respondents participated in Phase II (online expert group discussions on three themes identified in Phase I). The survey found that there is a lack of standardized training, structured mentorship programs, research funding, and research opportunities in addiction medicine for ECAMPs. There is a need for standardized training programs, improving research opportunities, and effective mentorship programs to promote the next generation of addiction medicine professionals and further development in the entire field. The efforts of ISAM NExT are well-received and give a template of how this gap can be addressed.

A voxel-based morphometry study on gray matter correlates of need for cognition and exploratory information seeking.

BACKGROUND: Need for cognition (NFC) represents interindividual differences in tendencies to engage and enjoy cognitive endeavors. Exploratory information seeking (EIS) refers to individual tendencies to attain cognitive stimulation through acquiring information related to consumer products or services out of curiosity. METHODS: The current study aims to provide an in-depth investigation of the relationship between NFC and EIS and extend this relation to determine neuroanatomical correlates of NFC and EIS. This study proposed two central hypotheses: (1) NFC and EIS scores are positively correlated and (2) the gray matter volume (GMV) of brain regions implicated in motivation, valuation, and reward systems are positively associated with both NFC and EIS. Self-report and structural MRI data of 91 Singaporean Chinese participants were utilized for the study. RESULTS: No statistically significant correlation was revealed between NFC and EIS scores. Neuroanatomical associations of the GMV of brain regions implicated in visuospatial, attentional, and reward processing with individual constructs of interest were explored. When examining NFC and EIS scores, larger GMV in the right pallidum and left fusiform gyrus was found in participants that reported higher levels of NFC (vs. lower NFC levels), larger GMV in the left precuneus in those with greater tendencies to engage in EIS (vs. lower EIS levels), and larger GMV of the left fusiform gyrus associated with greater endorsement of both NFC and EIS. When investigating the exploratory factor analysis-generated factors of NFC and EIS, similar patterns of associations were found between self-reported levels of agreement against factors and GMV of brain regions implicated. CONCLUSIONS: Correlational analysis and exploratory factor analysis indicated the absence of a relationship between NFC and EIS. Additionally, voxel-based morphometry whole-brain analysis revealed neuroanatomical correlates of the GMV of brain regions implicated in visuospatial, attentional, and reward processing with NFC and EIS.

Neuroanatomical correlates of system-justifying ideologies: a pre-registered voxel-based morphometry study on right-wing authoritarianism and social dominance orientation.

System-justifying ideologies are a cluster of ideals that perpetuate a hierarchical social system despite being fraught with inequalities. Right-wing authoritarianism (RWA) and social dominance orientation (SDO) are two ideologies that have received much attention in the literature separately and together. Given that these ideologies are considered to be stable individual differences that are likely to have an evolutionary basis, there has yet to be any examination for volumetric brain structures associated with these variables. Here, we proposed an investigation of overlapping and non-overlapping brain regions associated with RWA and SDO in a sample recruited in Singapore. Indeed, it will be interesting to determine how RWA and SDO correlate in a country that proactively promotes institutionalized multi-culturalism such as Singapore. RWA and SDO scores were collected via self-report measures from healthy individuals (39 males and 43 females; age 25.89 ± 5.68 years). Consequently, voxel-based morphometry (VBM) whole brain and region of interest (ROI) analyses were employed to identify neuroanatomical correlates of these system-justifying ideologies. RWA and SDO scores were strongly correlated despite the low ideological contrast in Singapore's sociopolitical context. The whole brain analysis did not reveal any significant clusters associated with either RWA or SDO. The ROI analyses revealed clusters in the bilateral amygdala and ventromedial prefrontal cortex (vmPFC) that were associated with both RWA and SDO scores, whereas two clusters in the left anterior insula were negatively associated with only SDO scores. The study corroborates the claim of RWA and SDO as stable individual differences with identifiable neuroanatomical correlates, but our exploratory analysis suggests evidence that precludes any definitive conclusion based on the present evidence.

Blunted Expected Reward Value Signals in Binge Alcohol Drinkers.

Alcohol-related morbidities and mortality are highly prevalent, increasing the burden to societies and health systems with 3 million deaths globally each year in young adults directly attributable to alcohol. Cue-induced alcohol craving has been formulated as a type of aberrant associative learning, modeled using temporal difference theory with an expected reward value (ERV) linked to craving. Clinically, although harmful use of alcohol is associated with increased time spent obtaining and using alcohol, it is also associated with self-neglect. The latter implies that the motivational aspects of nonalcohol stimuli are blunted. Using an instrumental learning task with non-alcohol-related stimuli, here, we tested hypotheses that the encoding of cue signals (ERV) predicting reward delivery would be blunted in binge alcohol drinkers in both sexes. We also predicted that for the binge drinking group alone, ratings of problematic alcohol use would correlate with abnormal ERV signals consistent with between groups (i.e., binge drinkers vs controls) abnormalities. Our results support our hypotheses with the ERV (nonalcohol cue) signal blunted in binge drinkers and with the magnitude of the abnormality correlating with ratings of problematic alcohol use. This implies that consistent with hypotheses, the motivational aspects of non-alcohol-related stimuli are blunted in binge drinkers. A better understanding of the mechanisms of harmful alcohol use will, in time, facilitate the development of more effective interventions, which should aim to decrease the motivational value of alcohol and increase the motivational value of non-alcohol-related stimuli.SIGNIFICANCE STATEMENT Allostasis theory predicts specific abnormalities in brain function and subjective experiences that occur when people develop drug problems including addiction. Cue-induced alcohol craving has been formulated as a type of aberrant associative learning, modeled using temporal difference theory with ERV linked to craving. Here, we used an instrumental learning task with non-alcohol-associated stimuli to test hypotheses that the encoding of nonalcohol cue signals (ERV) and reward prediction error signals showed blunting in binge alcohol drinkers. We conclude that fMRI can be used to noninvasively test allostasis and associative learning theory predictions in binge drinkers.

Transdiagnostic clustering of self-schema from self-referential judgements identifies subtypes of healthy personality and depression.

Introduction: The heterogeneity of depressive and anxiety disorders complicates clinical management as it may account for differences in trajectory and treatment response. Self-schemas, which can be determined by Self-Referential Judgements (SRJs), are heterogeneous yet stable. SRJs have been used to characterize personality in the general population and shown to be prognostic in depressive and anxiety disorders. Methods: In this study, we used SRJs from a Self-Referential Encoding Task (SRET) to identify clusters from a clinical sample of 119 patients recruited from the Institute of Mental Health presenting with depressive or anxiety symptoms and a non-clinical sample of 115 healthy adults. The generated clusters were examined in terms of most endorsed words, cross-sample correspondence, association with depressive symptoms and the Depressive Experiences Questionnaire and diagnostic category. Results: We identify a 5-cluster solution in each sample and a 7-cluster solution in the combined sample. When perturbed, metrics such as optimum cluster number, criterion value, likelihood, DBI and CHI remained stable and cluster centers appeared stable when using BIC or ICL as criteria. Top endorsed words in clusters were meaningful across theoretical frameworks from personality, psychodynamic concepts of relatedness and self-definition, and valence in self-referential processing. The clinical clusters were labeled "Neurotic" (C1), "Extraverted" (C2), "Anxious to please" (C3), "Self-critical" (C4), "Conscientious" (C5). The non-clinical clusters were labeled "Self-confident" (N1), "Low endorsement" (N2), "Non-neurotic" (N3), "Neurotic" (N4), "High endorsement" (N5). The combined clusters were labeled "Self-confident" (NC1), "Externalising" (NC2), "Neurotic" (NC3), "Secure" (NC4), "Low endorsement" (NC5), "High endorsement" (NC6), "Self-critical" (NC7). Cluster differences were observed in endorsement of positive and negative words, latency biases, recall biases, depressive symptoms, frequency of depressive disorders and self-criticism. Discussion: Overall, clusters endorsing more negative words tended to endorse fewer positive words, showed more negative biases in reaction time and negative recall bias, reported more severe depressive symptoms and a higher frequency of depressive disorders and more self-criticism in the clinical population. SRJ-based clustering represents a novel transdiagnostic framework for subgrouping patients with depressive and anxiety symptoms that may support the future translation of the science of self-referential processing, personality and psychodynamic concepts of self-definition to clinical applications.

Identifying psychiatric manifestations in schizophrenia and depression from audio-visual behavioural indicators through a machine-learning approach.

Schizophrenia (SCZ) and depression (MDD) are two chronic mental disorders that seriously affect the quality of life of millions of people worldwide. We aim to develop machine-learning methods with objective linguistic, speech, facial, and motor behavioral cues to reliably predict the severity of psychopathology or cognitive function, and distinguish diagnosis groups. We collected and analyzed the speech, facial expressions, and body movement recordings of 228 participants (103 SCZ, 50 MDD, and 75 healthy controls) from two separate studies. We created an ensemble machine-learning pipeline and achieved a balanced accuracy of 75.3% for classifying the total score of negative symptoms, 75.6% for the composite score of cognitive deficits, and 73.6% for the total score of general psychiatric symptoms in the mixed sample containing all three diagnostic groups. The proposed system is also able to differentiate between MDD and SCZ with a balanced accuracy of 84.7% and differentiate patients with SCZ or MDD from healthy controls with a balanced accuracy of 82.3%. These results suggest that machine-learning models leveraging audio-visual characteristics can help diagnose, assess, and monitor patients with schizophrenia and depression.

Spatial and chronic differences in neural activity in medicated and unmedicated schizophrenia patients.

A major caveat with investigations on schizophrenic patients is the difficulty to control for medication usage across samples as disease-related neural differences may be confounded by medication usage. Following a thorough literature search (632 records identified), we included 37 studies with a total of 740 medicated schizophrenia patients and 367 unmedicated schizophrenia patients. Here, we perform several meta-analyses to assess the neurofunctional differences between medicated and unmedicated schizophrenic patients across fMRI studies to determine systematic regions associated with medication usage. Several clusters identified by the meta-analysis on the medicated group include three right lateralized frontal clusters and a left lateralized parietal cluster, whereas the unmedicated group yielded concordant activity among right lateralized frontal-parietal regions. We further explored the prevalence of activity within these regions across illness duration and task type. These findings suggest a neural compensatory mechanism across these regions both spatially and chronically, offering new insight into the spatial and temporal dynamic neural differences among medicated and unmedicated schizophrenia patients.

Prognostic Neurotransmitter Receptors Genes Are Associated with Immune Response, Inflammation and Cancer Hallmarks in Brain Tumors.

Glioblastoma multiforme (GBM) is one of the most aggressive forms of cancer. Neurotransmitters (NTs) have recently been linked with the uncontrolled proliferation of cancer cells, but the role of NTs in the progression of human gliomas is still largely unexplored. Here, we investigate the genes encoding for neurotransmitter receptors (NTRs) by analyzing public transcriptomic data from GBM and LGG (low-grade glioma) samples. Our results showed that 50 out of the 98 tested NTR genes were dysregulated in brain cancer tissue. Next, we identified and validated NTR-associated prognostic gene signatures for both LGG and GBM. A subset of 10 NTR genes (DRD1, HTR1E, HTR3B, GABRA1, GABRA4, GABRB2, GABRG2, GRIN1, GRM7, and ADRA1B) predicted a positive prognosis in LGG and a negative prognosis in GBM. These genes were progressively downregulated across glioma grades and exhibited a strong negative correlation with genes associated with immune response, inflammasomes, and established cancer hallmarks genes in lower grade gliomas, suggesting a putative role in inhibiting cancer progression. This study might have implications for the development of novel therapeutics and preventive strategies that target regulatory networks associated with the link between the autonomic nervous system, cancer cells, and the tumor microenvironment.

Protracted abstinence in males with an opioid use disorder: partial recovery of nucleus accumbens function.

Opioid use disorder (OUD) affects more than 27 million people globally accounting for more than 300,000 deaths annually. Protracted abstinence among individuals with OUD is rare due to a high relapse rate among those not receiving medications for OUD. Extensive preclinical studies form the basis of the allostasis theory, which proposes long-lasting functional brain abnormalities that persist after opioid withdrawal and contribute to relapse. Few studies have tested the allostasis theory in humans using neuroimaging. Here, we used fMRI and an instrumental learning task to test allostasis theory predictions (ATP) of functional abnormalities in both positive valence (PVS) and negative valence (NVS) accumbens systems in OUD patients with protracted abstinence (n = 15), comparing them with OUD patients receiving methadone treatment (MT) (n = 33), and with healthy controls (n = 23). As hypothesized, protracted abstinence OUD patients showed incomplete recovery of nucleus accumbens function, as evidenced by the blunted response to aversive events (NVS) during negative reinforcement, as observed in MT patients. In contrast, their accumbens response to rewarding events (PVS) during positive reinforcement was similar to that of controls and different from that in MT patients whose response was blunted. Protracted abstinence OUD patients also showed improvements in depression symptoms compared to MT patients. Residual depressive symptoms and pre-MT intravenous drug measures were associated with worse accumbens function in protracted abstinence. These results support the ATP of long-lasting dysfunction of NVS after withdrawal and show preliminary evidence of recovery of PVS function with protracted withdrawal. Therapeutic strategies that target NVS may facilitate recovery.

Brain network dysfunctions in addiction: a meta-analysis of resting-state functional connectivity.

Resting-state functional connectivity (rsFC) provides novel insights into variabilities in neural networks associated with the use of addictive drugs or with addictive behavioral repertoire. However, given the broad mix of inconsistent findings across studies, identifying specific consistent patterns of network abnormalities is warranted. Here we aimed at integrating rsFC abnormalities and systematically searching for large-scale functional brain networks in substance use disorder (SUD) and behavioral addictions (BA), through a coordinate-based meta-analysis of seed-based rsFC studies. A total of fifty-two studies are eligible in the meta-analysis, including 1911 SUD and BA patients and 1580 healthy controls. In addition, we performed multilevel kernel density analysis (MKDA) for the brain regions reliably involved in hyperconnectivity and hypoconnectivity in SUD and BA. Data from fifty-two studies showed that SUD was associated with putamen, caudate and middle frontal gyrus hyperconnectivity relative to healthy controls. Eight BA studies showed hyperconnectivity clusters within the putamen and medio-temporal lobe relative to healthy controls. Altered connectivity in salience or emotion-processing areas may be related to dysregulated affective and cognitive control-related networks, such as deficits in regulating elevated sensitivity to drug-related stimuli. These findings confirm that SUD and BA might be characterized by dysfunctions in specific brain networks, particularly those implicated in the core cognitive and affective functions. These findings might provide insight into the development of neural mechanistic biomarkers for SUD and BA.

tDCS effect on prosocial behavior: a meta-analytic review.

Previous studies have shown that transcranial direct current stimulation (tDCS) could potentially promote prosocial behaviors. However, results from randomized controlled trials are inconsistent. The current meta-analysis aimed to assess the effects of anodal and cathodal tDCS using single-session protocols on prosocial behaviors in healthy young adults and explore potential moderators of these effects. The results showed that compared with sham stimulation, anodal (excitatory) stimulation significantly increased (g = 0.27, 95% CI [0.11, 0.43], Z = 3.30, P = 0.001) and cathodal (inhibitory) stimulation significantly decreased prosocial behaviors (g = -0.19, 95% CI [-0.39, -0.01], Z = -1.95, P = 0.051) using a multilevel meta-analytic model. These effects were not significantly modulated by stimulation parameters (e.g. duration, intensity and site) and types of prosocial behavior. The risk of publication bias for the included effects was minimal, and no selective reporting (e.g. P-hacking) was found in the P-curve analysis. This meta-analysis showed that both anodal and cathodal tDCS have small but significant effects on prosocial behaviors. The current study provides evidence that prosocial behaviors are linked to the activity of the 'social brain'. Future studies are encouraged to further explore whether tDCS could effectively treat social dysfunctions in psychiatry disorders.

Blunted reward prediction error signals in internet gaming disorder.

BACKGROUND: Internet gaming disorder (IGD) is a type of behavioural addictions. One of the key features of addiction is the excessive exposure to addictive objectives (e.g. drugs) reduces the sensitivity of the brain reward system to daily rewards (e.g. money). This is thought to be mediated via the signals expressed as dopaminergic reward prediction error (RPE). Emerging evidence highlights blunted RPE signals in drug addictions. However, no study has examined whether IGD also involves alterations in RPE signals that are observed in other types of addictions. METHODS: To fill this gap, we used functional magnetic resonance imaging data from 45 IGD and 42 healthy controls (HCs) during a reward-related prediction-error task and utilised a psychophysiological interaction (PPI) analysis to characterise the underlying neural correlates of RPE and related functional connectivity. RESULTS: Relative to HCs, IGD individuals showed impaired reinforcement learning, blunted RPE signals in multiple regions of the brain reward system, including the right caudate, left orbitofrontal cortex (OFC), and right dorsolateral prefrontal cortex (DLPFC). Moreover, the PPI analysis revealed a pattern of hyperconnectivity between the right caudate, right putamen, bilateral DLPFC, and right dorsal anterior cingulate cortex (dACC) in the IGD group. Finally, linear regression suggested that the connection between the right DLPFC and right dACC could significantly predict the variation of RPE signals in the left OFC. CONCLUSIONS: These results highlight disrupted RPE signalling and hyperconnectivity between regions of the brain reward system in IGD. Reinforcement learning deficits may be crucial underlying characteristics of IGD pathophysiology.

Blending oxytocin and dopamine with everyday creativity.

Converging evidence suggests that oxytocin (OT) is associated with creative thinking (CT) and that release of OT depends on ADP ribosyl-cyclases (CD38 and CD157). Neural mechanisms of CT and OT show a strong association with dopaminergic (DA) pathways, yet the link between CT and CD38, CD157, dopamine receptor D2 (DRD2) and catechol-O-methyltransferase (COMT) peripheral gene expression remain inconclusive, thus limiting our understanding of the neurobiology of CT. To address this issue, two principal domains of CT, divergent thinking (AUT), were assessed. In men, both AUT is associated with gene expression of CD38, CD157, and their interaction CD38 × CD157. There were no significant associations for DA expression (DRD2, COMT, DRD2 × COMT) on both CT measures. However, analysis of the interactions of OT and DA systems reveal significant interactions for AUT in men. The full model explained a sizable 39% of the variance in females for the total CT score. The current findings suggest that OT and DA gene expression contributed significantly to cognition and CT phenotype. This provides the first empirical foundation of a more refined understanding of the molecular landscape of CT.

Mapping working memory-specific dysfunction using a transdiagnostic approach.

BACKGROUND: Working memory (WM) is an executive ability that allows one to hold and manipulate information for a short period of time. Schizophrenia and mood disorders are severe psychiatric conditions with overlapping genetic and clinical symptoms. Whilst WM has been suggested as meeting the criteria for being an endophenotype for schizophrenia and mood disorders, it still unclear whether they share overlapping neural circuitry. OBJECTIVE: The n-back task has been widely used to measure WM capacity, such as maintenance, flexible updating, and interference control. Here we compiled studies that included psychiatric populations, i.e., schizophrenia, bipolar disorder and major depressive disorder. METHODS: We performed a coordinate-based meta-analysis that combined 34 BOLD-fMRI studies comparing activity associated with n-back working memory between psychiatric patients and healthy controls. We specifically focused our search using the n-back task to diminish study heterogeneity. RESULTS: All patient groups showed blunted activity in the striatum, anterior insula and frontal lobe. The same brain networks related to WM were compromised in schizophrenia, major depressive disorder and bipolar disorder. CONCLUSION: Our findings support the suggestion of commonal functional abnormalities across schizophrenia and mood disorders related to WM.

Adherence to Prescribed Acamprosate in Alcohol Dependence and 1-Year Morbidities and Mortality: Utilizing a Data Linkage Methodology.

OBJECTIVES: We tested the hypothesis that poor adherence is associated with a greater risk of alcohol-caused mortality and morbidities within the first year of discontinuing this medication. MATERIALS AND METHODS: A retrospective cohort study of 3319 individuals who received acamprosate in the East of Scotland in a 10-year period was conducted using a health informatics approach with record linkage of dispensing data, hospital utilization (SMR) and General Register Office of Scotland (GROS) data. The primary outcome was adherence between one to six months after initiating acamprosate medication. The secondary outcome was all-cause morbidities and mortality. RESULTS: Of the total 3319 individuals identified, a good adherence index of >80% was found in 59% of those prescribed acamprosate after three months and 6% after six months. There were significant linear trends of poorer adherence with increased risk of alcohol-caused mortality (Hazard Ratio, HR 1.2), medical morbidities especially neoplasm (HR 4.1) and poisoning (HR 1.4), and psychiatric morbidities especially stress (HR 35.1), psychotic (HR 5.6) and neurotic disorders, and directly alcohol induced conditions (7.4 HR) after adjustment for other factors within a one-year period of initiation of acamprosate treatment. DISCUSSION AND CONCLUSIONS: Further exploratory studies using this digitalized approach should be encouraged in order to capture role of compliance to acamprosate and other types of medication that are known to reduce relapse into alcohol dependence and its direct relationship to mortality and morbidities in this population.

Abnormal prediction error processing in schizophrenia and depression.

To make adaptive decisions under uncertainty, individuals need to actively monitor the discrepancy between expected outcomes and actual outcomes, known as prediction errors. Reward-based learning deficits have been shown in both depression and schizophrenia patients. For this study, we compiled studies that investigated prediction error processing in depression and schizophrenia patients and performed a series of meta-analyses. In both groups, positive t-maps of prediction error tend to yield striatum activity across studies. The analysis of negative t-maps of prediction error revealed two large clusters within the right superior and inferior frontal lobes in schizophrenia and the medial prefrontal cortex and bilateral insula in depression. The concordant posterior cingulate activity was observed in both patient groups, more prominent in the depression group and absent in the healthy control group. These findings suggest a possible role in dopamine-rich areas associated with the encoding of prediction errors in depression and schizophrenia.

Neural representation of prediction error signals in substance users.

Abnormal decision making can result in detrimental outcomes of clinical importance, and decision making is strongly linked to neural prediction error signalling. Activation likelihood estimation (ALE) meta-analyses were used to examine the neural correlates of prediction error signals of individuals taking different types of substances and healthy controls with contrast and conjunction analyses. Twenty-eight studies were included in the meta-analysis, representing 424 substance users' individuals and 834 healthy control individuals. Robust brain activity associated with prediction error signals in substance users was found for the bilateral striatum and insula. Healthy control subjects also activated bilateral striatum, midbrain, right insula and right medial-inferior frontal gyrus. Compared with healthy controls, substance users showed blunted activity in the bilateral putamen, right medial-inferior frontal gyrus and insula. The current meta-analysis of cross-sectional findings investigated neural prediction error signals in substance users. PE abnormalities in substance users might be related to poor decision making. In conclusion, the present study helps identify the pathophysiological underpinnings of maladaptive decision making in substance users.

Chronic heroin use disorder and the brain: Current evidence and future implications.

The incidence of chronic heroin use disorder, including overdose deaths, has reached epidemic proportions. Here we summarise and evaluate our knowledge of the relationship between chronic heroin use disorder and the brain through a narrative review. A broad range of areas was considered including causal mechanisms, cognitive and neurological consequences of chronic heroin use and novel neuroscience-based clinical interventions. Chronic heroin use is associated with limited or very limited evidence of impairments in memory, cognitive impulsivity, non-planning impulsivity, compulsivity and decision-making. Additionally, there is some evidence for certain neurological disorders being caused by chronic heroin use, including toxic leukoencephalopathy and neurodegeneration. However, there is insufficient evidence on whether these impairments and disorders recover after abstinence. Whilst there is a high prevalence of comorbid psychiatric disorders, there is no clear evidence that chronic heroin use per se causes depression, bipolar disorder, PTSD and/or psychosis. Despite the growing burden on society from heroin use, knowledge of the long-term effects of chronic heroin use disorder on the brain remains limited. Nevertheless, there is evidence for progress in neuroscience-based interventions being made in two areas: assessment (cognitive assessment and neuroimaging) and interventions (cognitive training/remediation and neuromodulation). Longitudinal studies are needed to unravel addiction and neurotoxic mechanisms and clarify the role of pre-existing psychiatric symptoms and cognitive impairments.

Alcohol Binge Drinking: Negative and Positive Valence System Abnormalities.

BACKGROUND: Each year, 3 million deaths occur owing to alcohol misuse. Translational studies are crucial to translate preclinical findings to patients. Preclinical studies have highlighted abnormalities in specific brain systems, with these forming the basis of allostasis theory. However, few studies have tested predictions in humans using neuroimaging. METHODS: We used a Research Domain Criteria approach to test allostasis theory predictions of blunted positive valence system (PVS) and abnormally increased negative valence system (NVS) responses in 57 binge alcohol drinking subjects and healthy control subjects who completed an instrumental task during functional magnetic resonance imaging. RESULTS: As hypothesized, binge alcohol drinkers showed abnormally increased activity in NVS-linked regions, such as the hippocampus and dorsal cingulate, and abnormally blunted activity in PVS-linked regions, such as the striatum, compared with control subjects. Higher measures of problematic alcohol use were associated with more abnormal brain activity only for binge drinkers who had been most recently drinking. CONCLUSIONS: These results support allostasis theory predictions of abnormally increased NVS and blunted PVS responses in binge alcohol drinkers. Further similar translational neuroimaging studies are indicated, particularly focusing on the NVS.