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

Association between DRD2/ANKK1 TaqIA Allele Status and Striatal Dopamine D2/3 Receptor Availability in Alcohol Use Disorder

Background: The association between blunted dopaminergic neurotransmission and alcohol use disorder (AUD) is well-known. In particular, the impairment of postsynaptic dopamine 2 and 3 receptors (DRD2/3) in the ventral and dorsal striatum during the development and maintenance of alcohol addiction has been investigated in several positron emission tomography (PET) studies. However, it is unclear whether these changes are the result of adaptation or genetic predisposition. Methods: Here we investigated the association between DRD2/ankyrin repeat and kinase domain-containing 1 (ANKK1) TaqIA allele (rs1800497) status and striatal DRD2/3 availability measured by 18F-fallypride PET in 12 AUD patients and 17 sex-matched healthy controls. Age and smoking status were included as covariates. Results: Contrary to our expectations, TaqIA allele status was not associated with striatal DRD2/3 availability in either group and there was no significant difference between groups, possibly due to the relatively small sample size (N = 29). Conclusions: Nonetheless, this is the first in vivo study investigating the relationship between dopamine receptor availability and genetic factors in AUD. The pitfalls of assessing such relationships in a relatively small sample are discussed. Clinical Trial Registration: The published analysis is an additional, post hoc analysis to the preregistered trial with clinical trial number NCT01679145 available on https://clinical - trials.gov/ct2/show/NCT01679145

Fronto-striatal structures related with model-based control as an endophenotype for obsessive–compulsive disorder

Recent theories suggest a shift from model-based goal-directed to model-free habitual decision-making in obsessive-compulsive disorder (OCD). However, it is yet unclear, whether this shift in the decision process is heritable. We investigated 32 patients with OCD, 27 unaffected siblings (SIBs) and 31 healthy controls (HCs) using the two-step task. We computed behavioral and reaction time analyses and fitted a computational model to assess the balance between model-based and model-free control. 80 subjects also underwent structural imaging. We observed a significant ordered effect for the shift towards model-free control in the direction OCD>SIB>HC in our computational parameter of interest. However less directed analyses revealed no shift towards model-free control in OCDs. Nonetheless, we found evidence for reduced model-based control in OCDs compared to HCs and SIBs via 2nd stage reaction time analyses. In this measure SIBs also showed higher levels of model-based control than HCs. Across all subjects these effects were associated with the surface area of the left medial/right dorsolateral prefrontal cortex. Moreover, correlations between bilateral putamen/right caudate volumes and these effects varied as a function of group: they were negative in SIBs and OCDs, but positive in HCs. Associations between fronto-striatal regions and model-based reaction time effects point to a potential endophenotype for OCD

Dopamine D2/3 receptor availability in alcohol use disorder and individuals at high risk: Towards a dimensional approach

Alcohol use disorder (AUD) is the most common substance use disorder worldwide. Although dopamine-related findings were often observed in AUD, associated neurobiological mechanisms are still poorly understood. Therefore, in the present study, we investigate D2/3 receptor availability in healthy participants, participants at high risk (HR) to develop addiction (not diagnosed with AUD), and AUD patients in a detoxified stage, applying F-18-fallypride positron emission tomography (F-18-PET). Specifically, D2/3 receptor availability was investigated in (1) 19 low-risk (LR) controls, (2) 19 HR participants, and (3) 20 AUD patients after alcohol detoxification. Quality and severity of addiction were assessed with clinical questionnaires and (neuro)psychological tests. PET data were corrected for age of participants and smoking status. In the dorsal striatum, we observed significant reductions of D2/3 receptor availability in AUD patients compared with LR participants. Further, receptor availability in HR participants was observed to be intermediate between LR and AUD groups (linearly decreasing). Still, in direct comparison, no group difference was observed between LR and HR groups or between HR and AUD groups. Further, the score of the Alcohol Dependence Scale (ADS) was inversely correlated with D2/3 receptor availability in the combined sample. Thus, in line with a dimensional approach, striatal D2/3 receptor availability showed a linear decrease from LR participants to HR participants to AUD patients, which was paralleled by clinical measures. Our study shows that a core neurobiological feature in AUD seems to be detectable in an early, subclinical state, allowing more individualized alcohol prevention programs in the future

Model-Based and Model-Free Decisions in Alcohol Dependence

This publication is with permission of the rights owner freely accessible due to an alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.Background: Human and animal work suggests a shift from goal-directed to habitual decision-making in addiction. However, the evidence for this in human alcohol dependence is as yet inconclusive. Methods: Twenty-six healthy controls and 26 recently detoxified alcohol-dependent patients underwent behavioral testing with a 2-step task designed to disentangle goal-directed and habitual response patterns. Results: Alcohol-dependent patients showed less evidence of goal-directed choices than healthy controls, particularly after losses. There was no difference in the strength of the habitual component. The group differences did not survive controlling for performance on the Digit Symbol Substitution Task. Conclusion: Chronic alcohol use appears to selectively impair goal-directed function, rather than promoting habitual responding. It appears to do so particularly after nonrewards, and this may be mediated by the effects of alcohol on more general cognitive functions subserved by the prefrontal cortex.Peer Reviewe

Pavlovian-to-Instrumental Transfer in Alcohol Dependence: A Pilot Study

This publication is with permission of the rights owner freely accessible due to an alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.Background: Pavlovian processes are thought to play an important role in the development, maintenance and relapse of alcohol dependence, possibly by influencing and usurping ongoing thought and behavior. The influence of pavlovian stimuli on ongoing behavior is paradigmatically measured by pavlovian-to-instrumental transfer (PIT) tasks. These involve multiple stages and are complex. Whether increased PIT is involved in human alcohol dependence is uncertain. We therefore aimed to establish and validate a modified PIT paradigm that would be robust, consistent and tolerated by healthy controls as well as by patients suffering from alcohol dependence, and to explore whether alcohol dependence is associated with enhanced PIT. Methods: Thirty-two recently detoxified alcohol-dependent patients and 32 age- and gender-matched healthy controls performed a PIT task with instrumental go/no-go approach behaviors. The task involved both pavlovian stimuli associated with monetary rewards and losses, and images of drinks. Results: Both patients and healthy controls showed a robust and temporally stable PIT effect. Strengths of PIT effects to drug-related and monetary conditioned stimuli were highly correlated. Patients more frequently showed a PIT effect, and the effect was stronger in response to aversively conditioned CSs (conditioned suppression), but there was no group difference in response to appetitive CSs. Conclusion: The implementation of PIT has favorably robust properties in chronic alcohol-dependent patients and in healthy controls. It shows internal consistency between monetary and drug-related cues. The findings support an association of alcohol dependence with an increased propensity towards PIT.Peer Reviewe

Association of the OPRM1 A118G polymorphism and Pavlovian-to-instrumental transfer: Clinical relevance for alcohol dependence

Background: Pavlovian-to-instrumental transfer (PIT) quantifies the extent to which a stimulus that has been associated with reward or punishment alters operant behaviour. In alcohol dependence (AD), the PIT effect serves as a paradigmatic model of cue-induced relapse. Preclinical studies have suggested a critical role of the opioid system in modulating Pavlovian–instrumental interactions. The A118G polymorphism of the OPRM1 gene affects opioid receptor availability and function. Furthermore, this polymorphism interacts with cue-induced approach behaviour and is a potential biomarker for pharmacological treatment response in AD. In this study, we tested whether the OPRM1 polymorphism is associated with the PIT effect and relapse in AD. Methods: Using a PIT task, we examined three independent samples: young healthy subjects ( N = 161), detoxified alcohol-dependent patients ( N = 186) and age-matched healthy controls ( N = 105). We used data from a larger study designed to assess the role of learning mechanisms in the development and maintenance of AD. Subjects were genotyped for the A118G (rs1799971) polymorphism of the OPRM1 gene. Relapse was assessed after three months. Results: In all three samples, participants with the minor OPRM1 G-Allele (G+ carriers) showed increased expression of the PIT effect in the absence of learning differences. Relapse was not associated with the OPRM1 polymorphism. Instead, G+ carriers displaying increased PIT effects were particularly prone to relapse. Conclusion: These results support a role for the opioid system in incentive salience motivation. Furthermore, they inform a mechanistic model of aberrant salience processing and are in line with the pharmacological potential of opioid receptor targets in the treatment of AD

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

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