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Reward-based decision-learning refers to the process of learning to select those actions that lead to rewards while avoiding actions that lead to punishments. This process, known to rely on dopaminergic activity in striatal brain regions, is compromised in Parkinson’s disease (PD). We hypothesized that such decision-learning deficits are alleviated by induced positive affect, which is thought to incur transient boosts in midbrain and striatal dopaminergic activity. Computational measures of probabilistic reward-based decision-learning were determined for 51 patients diagnosed with PD. Previous work has shown these measures to rely on the nucleus caudatus (outcome evaluation during the early phases of learning) and the putamen (reward prediction during later phases of learning). We observed that induced positive affect facilitated learning, through its effects on reward prediction rather than outcome evaluation. Viewing a few minutes of comedy clips served to remedy dopamine-related problems associated with frontostriatal circuitry and, consequently, learning to predict which actions will yield reward

A Tribute to Charlie Chaplin: Induced Positive Affect Improves Reward-Based Decision-Learning in Parkinson’s Disease