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BACKGROUND: Pavlovian-to-instrumental transfer (PIT) describes the influence of conditioned stimuli on instrumental behaviors and is discussed as a key process underlying substance abuse. Here, we tested whether neural responses during alcohol-related PIT predict future relapse in alcohol-dependent patients and future drinking behavior in adolescents. METHODS: Recently detoxified alcohol-dependent patients (n = 52) and young adults without dependence (n = 136) underwent functional magnetic resonance imaging during an alcohol-related PIT paradigm, and their drinking behavior was assessed in a 12-month follow-up. To predict future drinking behavior from PIT activation patterns, we used a multivoxel classification scheme based on linear support vector machines. RESULTS: When training and testing the classification scheme in patients, PIT activation patterns predicted future relapse with 71.2% accuracy. Feature selection revealed that classification was exclusively based on activation patterns in medial prefrontal cortex. To probe the generalizability of this functional magnetic resonance imaging-based prediction of future drinking behavior, we applied the support vector machine classifier that had been trained on patients to PIT functional magnetic resonance imaging data from adolescents. An analysis of cross-classification predictions revealed that those young social drinkers who were classified as abstainers showed a greater reduction in alcohol consumption at 12-month follow-up than those classified as relapsers (Delta = -24.4 +/- 6.0 g vs. -5.7 +/- 3.6 g; p = .019). CONCLUSIONS: These results suggest that neural responses during PIT could constitute a generalized prognostic marker for future drinking behavior in established alcohol use disorder and in at-risk states.
Stress plays a key role in modulating addictive behavior and can cause relapse following periods of abstinence. Common effects of stress and alcohol on the dopaminergic system have been suggested, although the precise mechanisms are unclear. Here, we investigated 20 detoxified alcohol-dependent patients and 19 matched healthy controls and assessed striatal D2/D3 availability using [F-18]-fallypride positron emission tomography and stressful life events. We found a strong association between striatal D2/D3 availability and stress in patients, but not in healthy controls. Interestingly, we found increased D2/D3 receptor availability in patients with higher stress levels. This mirrors complex interactions between stress and alcohol intake in animal studies and emphasizes the importance to investigate stress exposure in neurobiological studies of addiction.
Background Aversive stimuli in the environment influence human actions. This includes valence-dependent influences on action selection, e.g., increased avoidance but decreased approach behavior. However, it is yet unclear how aversive stimuli interact with complex learning and decision-making in the reward and avoidance domain. Moreover, the underlying computational mechanisms of these decision-making biases are unknown. Methods To elucidate these mechanisms, 54 healthy young male subjects performed a two-step sequential decision-making task, which allows to computationally model different aspects of learning, e.g., model-free, habitual, and model-based, goal-directed learning. We used a within-subject design, crossing task valence (reward vs. punishment learning) with emotional context (aversive vs. neutral background stimuli). We analyzed choice data, applied a computational model, and performed simulations. Results Whereas model-based learning was not affected, aversive stimuli interacted with model-free learning in a way that depended on task valence. Thus, aversive stimuli increased model-free avoidance learning but decreased model-free reward learning. The computational model confirmed this effect: the parameter lambda that indicates the influence of reward prediction errors on decision values was increased in the punishment condition but decreased in the reward condition when aversive stimuli were present. Further, by using the inferred computational parameters to simulate choice data, our effects were captured. Exploratory analyses revealed that the observed biases were associated with subclinical depressive symptoms. Conclusion Our data show that aversive environmental stimuli affect complex learning and decision-making, which depends on task valence. Further, we provide a model of the underlying computations of this affective modulation. Finally, our finding of increased decision-making biases in subjects reporting subclinical depressive symptoms matches recent reports of amplified Pavlovian influences on action selection in depression and suggests a potential vulnerability factor for mood disorders. We discuss our findings in the light of the involvement of the neuromodulators serotonin and dopamine.
The influence of Pavlovian conditioned stimuli on ongoing behavior may contribute to explaining how alcohol cues stimulate drug seeking and intake. Using a Pavlovian-instrumental transfer task, we investigated the effects of alcohol-related cues on approach behavior (i.e., instrumental response behavior) and its neural correlates, and related both to the relapse after detoxification in alcohol-dependent patients. Thirty-one recently detoxified alcohol-dependent patients and 24 healthy controls underwent instrumental training, where approach or non-approach towards initially neutral stimuli was reinforced by monetary incentives. Approach behavior was tested during extinction with either alcohol-related or neutral stimuli (as Pavlovian cues) presented in the background during functional magnetic resonance imaging (fMRI). Patients were subsequently followed up for 6 months. We observed that alcohol-related background stimuli inhibited the approach behavior in detoxified alcohol-dependent patients (t = -3.86, p < .001), but not in healthy controls (t = -0.92, p = .36). This behavioral inhibition was associated with neural activation in the nucleus accumbens (NAcc) (t((30)) = 2.06, p < .05). Interestingly, both the effects were only present in subsequent abstainers, but not relapsers and in those with mild but not severe dependence. Our data show that alcohol-related cues can acquire inhibitory behavioral features typical of aversive stimuli despite being accompanied by a stronger NAcc activation, suggesting salience attribution. The fact that these findings are restricted to abstinence and milder illness suggests that they may be potential resilience factors.
Background: Pavlovian processes are thought to play an important role in the development, maintenance and relapse of alcohol dependence, possibly by influencing and usurping on- going thought and behavior. The influence of Pavlovian stimuli on on-going 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 Pavlovian-Instrumental transfer.
Methods: 32 recently detoxified alcohol-dependent patients and 32 age and gender matched healthy controls performed a PIT task with instrumental go/no-go approach behaviours. 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.
Background Exercise rehabilitation is highly recommended by current guidelines on prevention of cardiovascular disease, but its implementation is still poor. Many clinicians experience difficulties in prescribing exercise in the presence of different concomitant cardiovascular diseases and risk factors within the same patient. It was aimed to develop a digital training and decision support system for exercise prescription in cardiovascular disease patients in clinical practice: the European Association of Preventive Cardiology Exercise Prescription in Everyday Practice and Rehabilitative Training (EXPERT) tool. Methods EXPERT working group members were requested to define (a) diagnostic criteria for specific cardiovascular diseases, cardiovascular disease risk factors, and other chronic non-cardiovascular conditions, (b) primary goals of exercise intervention, (c) disease-specific prescription of exercise training (intensity, frequency, volume, type, session and programme duration), and (d) exercise training safety advices. The impact of exercise tolerance, common cardiovascular medications and adverse events during exercise testing were further taken into account for optimized exercise prescription. Results Exercise training recommendations and safety advices were formulated for 10 cardiovascular diseases, five cardiovascular disease risk factors (type 1 and 2 diabetes, obesity, hypertension, hypercholesterolaemia), and three common chronic non-cardiovascular conditions (lung and renal failure and sarcopaenia), but also accounted for baseline exercise tolerance, common cardiovascular medications and occurrence of adverse events during exercise testing. An algorithm, supported by an interactive tool, was constructed based on these data. This training and decision support system automatically provides an exercise prescription according to the variables provided. Conclusion This digital training and decision support system may contribute in overcoming barriers in exercise implementation in common cardiovascular diseases.