Stephan Nebe

Pavlovian-to-instrumental transfer effects in the nucleus accumbens relate to relapse in alcohol dependence

In detoxified alcohol‐dependent patients, alcohol‐related stimuli can promote relapse. However, to date, the mechanisms by which contextual stimuli promote relapse have not been elucidated in detail. One hypothesis is that such contextual stimuli directly stimulate the motivation to drink via associated brain regions like the ventral striatum and thus promote alcohol seeking, intake and relapse. Pavlovian‐to‐Instrumental‐Transfer (PIT) may be one of those behavioral phenomena contributing to relapse, capturing how Pavlovian conditioned (contextual) cues determine instrumental behavior (e.g. alcohol seeking and intake). We used a PIT paradigm during functional magnetic resonance imaging to examine the effects of classically conditioned Pavlovian stimuli on instrumental choices in n = 31 detoxified patients diagnosed with alcohol dependence and n = 24 healthy controls matched for age and gender. Patients were followed up over a period of 3 months. We observed that (1) there was a significant behavioral PIT effect for all participants, which was significantly more pronounced in alcohol‐dependent patients; (2) PIT was significantly associated with blood oxygen level‐dependent (BOLD) signals in the nucleus accumbens (NAcc) in subsequent relapsers only; and (3) PIT‐related NAcc activation was associated with, and predictive of, critical outcomes (amount of alcohol intake and relapse during a 3 months follow‐up period) in alcohol‐dependent patients. These observations show for the first time that PIT‐related BOLD signals, as a measure of the influence of Pavlovian cues on instrumental behavior, predict alcohol intake and relapse in alcohol dependence.

When habits are dangerous - Alcohol expectancies and habitual decision-making predict relapse in alcohol dependence

BACKGROUND Addiction is supposedly characterized by a shift from goal-directed to habitual decision making, thus facilitating automatic drug intake. The two-step task allows distinguishing between these mechanisms by computationally modeling goal-directed and habitual behavior as model-based and model-free control. In addicted patients, decision making may also strongly depend upon drug-associated expectations. Therefore, we investigated model-based versus model-free decision making and its neural correlates as well as alcohol expectancies in alcohol-dependent patients and healthy controls and assessed treatment outcome in patients. METHODS Ninety detoxified, medication-free, alcohol-dependent patients and 96 age- and gender-matched control subjects underwent functional magnetic resonance imaging during the two-step task. Alcohol expectancies were measured with the Alcohol Expectancy Questionnaire. Over a follow-up period of 48 weeks, 37 patients remained abstinent and 53 patients relapsed as indicated by the Alcohol Timeline Followback method. RESULTS Patients who relapsed displayed reduced medial prefrontal cortex activation during model-based decision making. Furthermore, high alcohol expectancies were associated with low model-based control in relapsers, while the opposite was observed in abstainers and healthy control subjects. However, reduced model-based control per se was not associated with subsequent relapse. CONCLUSIONS These findings suggest that poor treatment outcome in alcohol dependence does not simply result from a shift from model-based to model-free control but is instead dependent on the interaction between high drug expectancies and low model-based decision making. Reduced model-based medial prefrontal cortex signatures in those who relapse point to a neural correlate of relapse risk. These observations suggest that therapeutic interventions should target subjective alcohol expectancies.

No association of goal-directed and habitual control with alcohol consumption in young adults

Alcohol dependence is a mental disorder that has been associated with an imbalance in behavioral control favoring model‐free habitual over model‐based goal‐directed strategies. It is as yet unknown, however, whether such an imbalance reflects a predisposing vulnerability or results as a consequence of repeated and/or excessive alcohol exposure. We, therefore, examined the association of alcohol consumption with model‐based goal‐directed and model‐free habitual control in 188 18‐year‐old social drinkers in a two‐step sequential decision‐making task while undergoing functional magnetic resonance imaging before prolonged alcohol misuse could have led to severe neurobiological adaptations. Behaviorally, participants showed a mixture of model‐free and model‐based decision‐making as observed previously. Measures of impulsivity were positively related to alcohol consumption. In contrast, neither model‐free nor model‐based decision weights nor the trade‐off between them were associated with alcohol consumption. There were also no significant associations between alcohol consumption and neural correlates of model‐free or model‐based decision quantities in either ventral striatum or ventromedial prefrontal cortex. Exploratory whole‐brain functional magnetic resonance imaging analyses with a lenient threshold revealed early onset of drinking to be associated with an enhanced representation of model‐free reward prediction errors in the posterior putamen. These results suggest that an imbalance between model‐based goal‐directed and model‐free habitual control might rather not be a trait marker of alcohol intake per se.

How Accumulated Real Life Stress Experience and Cognitive Speed Interact on Decision-Making Processes

Rationale: Advances in neurocomputational modeling suggest that valuation systems for goal-directed (deliberative) on one side, and habitual (automatic) decision-making on the other side may rely on distinct computational strategies for reinforcement learning, namely model-free vs. model-based learning. As a key theoretical difference, the model-based system strongly demands cognitive functions to plan actions prospectively based on an internal cognitive model of the environment, whereas valuation in the model-free system relies on rather simple learning rules from operant conditioning to retrospectively associate actions with their outcomes and is thus cognitively less demanding. Acute stress reactivity is known to impair model-based but not model-free choice behavior, with higher working memory capacity protecting the model-based system from acute stress. However, it is not clear which impact accumulated real life stress has on model-free and model-based decision systems and how this influence interacts with cognitive abilities. Methods: We used a sequential decision-making task distinguishing relative contributions of both learning strategies to choice behavior, the Social Readjustment Rating Scale questionnaire to assess accumulated real life stress, and the Digit Symbol Substitution Test to test cognitive speed in 95 healthy subjects. Results: Individuals reporting high stress exposure who had low cognitive speed showed reduced model-based but increased model-free behavioral control. In contrast, subjects exposed to accumulated real life stress with high cognitive speed displayed increased model-based performance but reduced model-free control. Conclusion: These findings suggest that accumulated real life stress exposure can enhance reliance on cognitive speed for model-based computations, which may ultimately protect the model-based system from the detrimental influences of accumulated real life stress. The combination of accumulated real life stress exposure and slower information processing capacities, however, might favor model-free strategies. Thus, the valence and preference of either system strongly depends on stressful experiences and individual cognitive capacities.

Identification of heavy drinking in the 10-item AUDIT: Results from a prospective study among 18–21 years old non-dependent German males

BACKGROUND Alcohol consumption is pivotal for the subsequent development of alcohol use disorders (AUD). The Alcohol Use Disorders Identification Test (AUDIT) is a recommended AUD screening tool for prevention and primary care settings. The objectives of this study were to test how many participants with heavy drinking are unidentified by the AUDIT, if proportions of unidentified participants vary over time, and whether this unidentified risk group (URG) was clinically relevant in terms of drinking behavior reports and AUD risk factors, as well as future adverse outcomes, such as craving, dependence symptoms, or depression. METHODS Our prospective cohort study followed 164 German males aged 18-19years without an alcohol dependence diagnosis over 24months. Only men were included due to higher AUD prevalence and gender-specific differences in metabolism, drinking patterns, and progression to AUD. All participants were screened via telephone interview and answered questionnaires both in person and via internet. Heavy drinking was classified using the AUDIT consumption score (AUDIT-C≥4.50). Standardized AUD diagnoses and symptoms, as well as alcohol use-related outcome criteria were assessed via standardized Composite International Diagnostic Interview (CIDI), and self-report questionnaires. RESULTS One in four participants (22-28% across all four follow-ups) reported heavy drinking but was unidentified by AUDIT total score (i.e. score<8), thus qualifying for URG status. The URG status did not fluctuate considerably across follow-ups (repeated-measures ANOVA, p=0.293). URG participants identified at the six-month follow-up did not generally differ from participants without URG status in terms of AUD family history or temperament (multivariate ANOVA, p=0.114), except for anxiety sensitivity (pBonferroni<0.001). After two years, URG participants reported a similar level of adverse outcomes compared to low-risk participants (multivariate ANOVA, p=0.438), but less alcohol-related problems and less loss of control due to craving compared to high-risk participants (pBonferroni≤0.007). CONCLUSIONS Despite the considerable number of heavy-drinking individuals unidentified by AUDIT total scores, an additional classification according to AUDIT-C values did not prove useful. Combining AUDIT and AUDIT-C scores might not be sufficient for identifying AUD risk groups among young adult German males. There is an urgent need for a replication of our findings among female participants.

Drunk decisions: Alcohol shifts choice from habitual towards goal-directed control in adolescent intermediate-risk drinkers

Background: Studies in humans and animals suggest a shift from goal-directed to habitual decision-making in addiction. We therefore tested whether acute alcohol administration reduces goal-directed and promotes habitual decision-making, and whether these effects are moderated by self-reported drinking problems. Methods: Fifty-three socially drinking males completed the two-step task in a randomised crossover design while receiving an intravenous infusion of ethanol (blood alcohol level=80 mg%), or placebo. To minimise potential bias by long-standing heavy drinking and subsequent neuropsychological impairment, we tested 18- to 19-year-old adolescents. Results: Alcohol administration consistently reduced habitual, model-free decisions, while its effects on goal-directed, model-based behaviour varied as a function of drinking problems measured with the Alcohol Use Disorders Identification Test. While adolescents with low risk for drinking problems (scoring <8) exhibited an alcohol-induced numerical reduction in goal-directed choices, intermediate-risk drinkers showed a shift away from habitual towards goal-directed decision-making, such that alcohol possibly even improved their performance. Conclusions: We assume that alcohol disrupted basic cognitive functions underlying habitual and goal-directed decisions in low-risk drinkers, thereby enhancing hasty choices. Further, we speculate that intermediate-risk drinkers benefited from alcohol as a negative reinforcer that reduced unpleasant emotional states, possibly displaying a novel risk factor for drinking in adolescence.

Risk seeking for losses modulates the functional connectivity of the default mode and left frontoparietal networks in young males

Value-based decision making (VBDM) is a principle that states that humans and other species adapt their behavior according to the dynamic subjective values of the chosen or unchosen options. The neural bases of this process have been extensively investigated using task-based fMRI and lesion studies. However, the growing field of resting-state functional connectivity (RSFC) may shed light on the organization and function of brain connections across different decision-making domains. With this aim, we used independent component analysis to study the brain network dynamics in a large cohort of young males (N = 145) and the relationship of these dynamics with VBDM. Participants completed a battery of behavioral tests that evaluated delay aversion, risk seeking for losses, risk aversion for gains, and loss aversion, followed by an RSFC scan session. We identified a set of large-scale brain networks and conducted our analysis only on the default mode network (DMN) and networks comprising cognitive control, appetitive-driven, and reward-processing regions. Higher risk seeking for losses was associated with increased connectivity between medial temporal regions, frontal regions, and the DMN. Higher risk seeking for losses was also associated with increased coupling between the left frontoparietal network and occipital cortices. These associations illustrate the participation of brain regions involved in prospective thinking, affective decision making, and visual processing in participants who are greater risk-seekers, and they demonstrate the sensitivity of RSFC to detect brain connectivity differences associated with distinct VBDM parameters.