Virtual Reality-Based Treatment Approaches in the Field of Substance Use Disorders

Purpose: Substance use disorders (SUD) are burdening chronic conditions characterized by high relapse rates despite severe negative consequences. Substance-related cues that elicit craving by means of automatic physiological and behavioural responses have long been suggested to predict relapse. One major mechanism contributing to relapse behaviour are cue-induced behavioural approach tendencies towards the addictive agent. Recently, there has been an emerging interest in virtual reality (VR)-based approaches to assess and modify craving and its related responses. This review aims at elucidating (1) VR techniques applied in the field of SUD, (2) VR as an induction/assessment tool for biopsychological correlates of craving and (3) VR-based therapeutic approaches. Findings: There is an emerging number of studies focusing on different substances of abuse incorporating VR in craving induction/assessment as well as therapy. Despite some limitations as missing of randomized controlled clinical trials with large samples and missing data on the long-term effects of VR treatment, the VR approach showed consistent results in eliciting and reducing craving across different substances. Summary: This review suggests virtual reality as a promising tool for the assessment and treatment of craving among individuals with substance use disorders. Because of its ecological validity, VR unifies the benefits of a laboratory setting with the advantages of a realistic environment. Further studies with large samples and randomized controlled clinical trials using more homogenous VR techniques as well as assessment of objective biophysiological craving markers are required

Attenuation of Stimulated Accumbal Dopamine Release by NMDA Is Mediated through Metabotropic Glutamate Receptors

Electrically stimulated dopamine release from the nucleus accumbens is attenuated following application of N-methyl-d-aspartate (NMDA), which is likely to be mediated indirectly through intermediary neuronal mechanisms rather than by a direct action on dopamine terminals. On the basis of known modulatory processes in nucleus accumbens, the current experiments sought to test whether the effect of NMDA was mediated through cholinergic, GABA-ergic, or metabotropic glutamatergic intermediate mechanisms. Fast-scan cyclic voltammetry was used to measure electrically stimulated dopamine release in nucleus accumbens of rat brain slices in vitro. Stimulated dopamine release was attenuated by NMDA, confirming previous findings, but this attenuation was unaffected by either cholinergic or GABA-ergic antagonists. However, it was completely abolished by the nonselective group I/II/III metabotropic glutamate receptor antagonist α-methyl-4-carboxyphenylglycine (MCPG) and by the selective group II antagonist LY 341396. Therefore, group II metabotropic glutamate receptors, but not acetylcholine or GABA receptors, mediate the attenuation of stimulated dopamine release caused by NMDA, probably by presynaptic inhibition through receptors located extra-synaptically on dopamine terminals. This provides a plausible mechanism for the documented role of metabotropic glutamate receptor systems in restoring deficits induced by NMDA receptor antagonists, modeling schizophrenia, underlining the potential for drugs affecting these receptors as therapeutic agents in treating schizophrenia

Elevated Amygdala Responses During De Novo Pavlovian Conditioning in Alcohol Use Disorder Are Associated With Pavlovian-to-Instrumental Transfer and Relapse Latency

BACKGROUND: Contemporary learning theories of drug addiction ascribe a key role to Pavlovian learning mechanisms in the development, maintenance, and relapse of addiction. In fact, cue-reactivity research has demonstrated the power of alcohol-associated cues to activate the brain’s reward system, which has been linked to craving and subsequent relapse. However, whether de novo Pavlovian conditioning is altered in alcohol use disorder (AUD) has rarely been investigated. METHODS: To characterize de novo Pavlovian conditioning in AUD, 62 detoxified patients with AUD and 63 matched healthy control participants completed a Pavlovian learning task as part of a Pavlovian-to-instrumental transfer paradigm during a functional magnetic resonance imaging session. Patients were followed up for 12 months to assess drinking behavior and relapse status. RESULTS: While patients and healthy controls did not differ in their ability to explicitly acquire the contingencies between conditioned and unconditioned stimuli, patients with AUD displayed significantly stronger amygdala responses toward Pavlovian cues, an effect primarily driven by stronger blood oxygen level–dependent differentiation during learning from reward compared with punishment. Moreover, in patients compared with controls, differential amygdala responses during conditioning were positively related to the ability of Pavlovian stimuli to influence ongoing instrumental choice behavior measured during a subsequent Pavlovian-to-instrumental transfer test. Finally, patients who relapsed within the 12-month follow-up period showed an inverse association between amygdala activity during conditioning and relapse latency. CONCLUSIONS: We provide evidence of altered neural correlates of de novo Pavlovian conditioning in patients with AUD, especially for appetitive stimuli. Thus, heightened processing of Pavlovian cues might constitute a behaviorally relevant mechanism in alcohol addiction

A multimodal neuroimaging classifier for alcohol dependence

With progress in magnetic resonance imaging technology and a broader dissemination of state-of-the-art imaging facilities, the acquisition of multiple neuroimaging modalities is becoming increasingly feasible. One particular hope associated with multimodal neuroimaging is the development of reliable data-driven diagnostic classifiers for psychiatric disorders, yet previous studies have often failed to find a benefit of combining multiple modalities. As a psychiatric disorder with established neurobiological effects at several levels of description, alcohol dependence is particularly well-suited for multimodal classification. To this aim, we developed a multimodal classification scheme and applied it to a rich neuroimaging battery (structural, functional task-based and functional resting-state data) collected in a matched sample of alcohol-dependent patients (N = 119) and controls (N = 97). We found that our classification scheme yielded 79.3% diagnostic accuracy, which outperformed the strongest individual modality - grey-matter density - by 2.7%. We found that this moderate benefit of multimodal classification depended on a number of critical design choices: a procedure to select optimal modality-specific classifiers, a fine-grained ensemble prediction based on cross-modal weight matrices and continuous classifier decision values. We conclude that the combination of multiple neuroimaging modalities is able to moderately improve the accuracy of machine-learning-based diagnostic classification in alcohol dependence

A multimodal neuroimaging classifier for alcohol dependence

With progress in magnetic resonance imaging technology and a broader dissemination of state-of-the-art imaging facilities, the acquisition of multiple neuroimaging modalities is becoming increasingly feasible. One particular hope associated with multimodal neuroimaging is the development of reliable data-driven diagnostic classifiers for psychiatric disorders, yet previous studies have often failed to find a benefit of combining multiple modalities. As a psychiatric disorder with established neurobiological effects at several levels of description, alcohol dependence is particularly well-suited for multimodal classification. To this aim, we developed a multimodal classification scheme and applied it to a rich neuroimaging battery (structural, functional task-based and functional resting-state data) collected in a matched sample of alcohol-dependent patients (N = 119) and controls (N = 97). We found that our classification scheme yielded 79.3% diagnostic accuracy, which outperformed the strongest individual modality - grey-matter density - by 2.7%. We found that this moderate benefit of multimodal classification depended on a number of critical design choices: a procedure to select optimal modality-specific classifiers, a fine-grained ensemble prediction based on cross-modal weight matrices and continuous classifier decision values. We conclude that the combination of multiple neuroimaging modalities is able to moderately improve the accuracy of machine-learning-based diagnostic classification in alcohol dependence

Alcohol Approach Bias Is Associated With Both Behavioral and Neural Pavlovian-to-Instrumental Transfer Effects in Alcohol-Dependent Patients

BACKGROUND: Even after qualified detoxification, alcohol-dependent (AD) patients may relapse to drinking alcohol despite their decision to abstain. Two mechanisms may play important roles. First, the impact of environmental cues on instrumental behavior (i.e., Pavlovian-to-instrumental transfer [PIT] effect), which was found to be stronger in prospectively relapsing AD patients than in abstaining patients. Second, an automatic approach bias toward alcohol stimuli was observed in AD patients, and interventions targeting this bias reduced the relapse risk in some studies. Previous findings suggest a potential behavioral and neurobiological overlap between these two mechanisms. METHODS: In this study, we examined the association between alcohol approach bias and both behavioral and neural non–drug-related PIT effects in AD patients after detoxification. A total of 100 AD patients (17 females) performed a PIT task and an alcohol approach/avoidance task. Patients were followed for 6 months. RESULTS: A stronger alcohol approach bias was associated with both a more pronounced behavioral PIT effect and stronger PIT-related neural activity in the right nucleus accumbens. Moreover, the association between alcohol approach bias and behavioral PIT increased with the severity of alcohol dependence and trait impulsivity and was stronger in patients who relapsed during follow-up in the exploratory analysis. CONCLUSIONS: A stronger alcohol approach bias was associated with both a more pronounced behavioral PIT effect and stronger PIT-related neural activity in the right nucleus accumbens. Moreover, the association between alcohol approach bias and behavioral PIT increased with the severity of alcohol dependence and trait impulsivity and was stronger in patients who relapsed during follow-up in the exploratory analysis

Does immediate dentin sealing influence postoperative sensitivity in teeth restored with indirect restorations? A systematic review and meta-analysis

Objective: This study comprehensively reviewed clinical trials that investigated the effect of immediate dentin sealing (IDS) technique on postoperative sensitivity (POS) and clinical performance of indirect restorations. Materials and methods: The systematic review was conducted according to the preferred reporting items for systematic reviews and meta-analyses statement, and was guided by the PICOS strategy. Clinical trials in which adult patients received at least one indirect restoration cemented with IDS approach and one restoration cemented following the delayed dentin sealing (DDS) were considered. Results: Following title screening and full-text reading, four studies met the inclusion criteria and were included for qualitative synthesis, while two studies were selected for quantitative synthesis. According to Risk of bias-2 tool, two studies were classified as “some concerns” for the outcome POS. No statistically significant differences were found between teeth restored with indirect restorations using the IDS and DDS approach for POS (p > 0.05), neither at the baseline (very low certainty of evidence according to GRADE) nor after 2 years of follow-up (low certainty of evidence according to GRADE). Conclusion: There is low-certainty evidence that IDS does not reduce POS in teeth restored with indirect restorations. Clinical significance: There is no clinical evidence to favor IDS over DDS when restoring teeth with indirect restorations

Model-Based and Model-Free Control Predicts Alcohol Consumption Developmental Trajectory in Young Adults: A 3-Year Prospective Study.

BACKGROUND: A shift from goal-directed toward habitual control has been associated with alcohol dependence. Whether such a shift predisposes to risky drinking is not yet clear. We investigated how goal-directed and habitual control at age 18 predict alcohol use trajectories over the course of 3 years. METHODS: Goal-directed and habitual control, as informed by model-based (MB) and model-free (MF) learning, were assessed with a two-step sequential decision-making task during functional magnetic resonance imaging in 146 healthy 18-year-old men. Three-year alcohol use developmental trajectories were based on either a consumption score from the self-reported Alcohol Use Disorders Identification Test (assessed every 6 months) or an interview-based binge drinking score (grams of alcohol/occasion; assessed every year). We applied a latent growth curve model to examine how MB and MF control predicted the drinking trajectory. RESULTS: Drinking behavior was best characterized by a linear trajectory. MB behavioral control was negatively associated with the development of the binge drinking score; MF reward prediction error blood oxygen level-dependent signals in the ventromedial prefrontal cortex and the ventral striatum predicted a higher starting point and steeper increase of the Alcohol Use Disorders Identification Test consumption score over time, respectively. CONCLUSIONS: We found that MB behavioral control was associated with the binge drinking trajectory, while the MF reward prediction error signal was closely linked to the consumption score development. These findings support the idea that unbalanced MB and MF control might be an important individual vulnerability in predisposing to risky drinking behavior

Stronger prejudices are associated with decreased model-based control

Background: Prejudices against minorities can be understood as habitually negative evaluations that are kept in spite of evidence to the contrary. Therefore, individuals with strong prejudices might be dominated by habitual or "automatic" reactions at the expense of more controlled reactions. Computational theories suggest individual differences in the balance between habitual/model-free and deliberative/model-based decision-making. Methods: 127 subjects performed the two Step task and completed the blatant and subtle prejudice scale. Results: By using analyses of choices and reaction times in combination with computational modeling, subjects with stronger blatant prejudices showed a shift away from model-based control. There was no association between these decision-making processes and subtle prejudices. Conclusion: These results support the idea that blatant prejudices toward minorities are related to a relative dominance of habitual decision-making. This finding has important implications for developing interventions that target to change prejudices across societies