Background: The arbitration between decision-making strategies is shaped by the degree of controllability over environmental events. Under low control, individuals might rely more heavily on Pavlovian bias (PB), which facilitates and inhibits actions when facing appetitive and aversive cues, respectively. More recently, extreme PB was implicated in learned helplessness (LH), which is typically induced by uncontrollable punishment. On the neural level, the medial prefrontal cortex (mPFC) was pinpointed as a region underlying both cognitive control over PB, and the pathogenesis of LH.Objective/Hypothesis: To test if high-definition transcranial direct current stimulation (HD-tDCS) targeting the mPFC counteracts with the deleterious behavioral effects of low controllability over rewards/losses (“yoking”) during reinforcement learning.Methods: In a pre-registered, between-group, double-blind study (N = 103, healthy adults), we tested the interaction of low controllability and HD-tDCS on performance in a Go/NoGo task. Yoking was implemented by presenting random outcomes following responses, while matching reward/loss frequencies between control and yoked groups. HD-tDCS was delivered for 15 minutes at 2 mA using a 4x1 montage centered at position Fz.Results: HD-tDCS improved response accuracy by the end of the task only when applied simultaneously with yoking. The beneficial consequences of active stimulation in yoked participants were more pronounced in reward-predictive trials. Finally, computational modeling revealed that parameter estimates of learning rate and choice randomness were modulated by yoking and HD-tDCS in an interactive manner.Conclusions: These results highlight the potential of our HD-tDCS protocol for interfering with choice arbitration in volatile environments, resulting in more adaptive behavior.