Alcohol Hangover Does Not Alter the Application of Model-Based and Model-Free Learning Strategies

Frequent alcohol binges shift behavior from goal-directed to habitual processing modes. This shift in reward-associated learning strategies plays a key role in the development and maintenance of alcohol use disorders and seems to persist during (early stages of) sobriety in at-risk drinkers. Yet still, it has remained unclear whether this phenomenon might be associated with alcohol hangover and thus also be found in social drinkers. In an experimental crossover design, n = 25 healthy young male participants performed a two-step decision-making task once sober and once hungover (i.e., when reaching sobriety after consuming 2.6 g of alcohol per estimated liter of total body water). This task allows the separation of effortful model-based and computationally less demanding model-free learning strategies. The experimental induction of alcohol hangover was successful, but we found no significant hangover effects on model-based and model-free learning scores, the balance between model-free and model-based valuation (ω), or perseveration tendencies (π). Bayesian analyses provided positive evidence for the null hypothesis for all measures except π (anecdotal evidence for the null hypothesis). Taken together, alcohol hangover, which results from a single binge drinking episode, does not impair the application of effortful and computationally costly model-based learning strategies and/or increase model-free learning strategies. This supports the notion that the behavioral deficits observed in at-risk drinkers are most likely not caused by the immediate aftereffects of individual binge drinking events.