Abstract
IntroductionThere is growing evidence from neuro-computational studies that instrumental learning involves the dynamic interaction of a computationally rigid, low-level striatal and a more flexible, high-level prefrontal component. MethodsTo evaluate the role of the prefrontal cortex in instrumental learning, we applied anodal transcranial direct current stimulation (tDCS) optimized for the left dorsolateral prefrontal cortex, by using realistic MR-derived finite element model-based electric field simulations. In a study with a double-blind, sham-controlled, repeated-measures design, sixteen male participants performed a probabilistic learning task while receiving anodal and sham tDCS in a counterbalanced order. ResultsCompared to sham tDCS, anodal tDCS significantly increased the amount of maladaptive shifting behavior after optimal outcomes during learning when reward probabilities were highly dissociable. Derived parameters of the Q-learning computational model further revealed a significantly increased model parameter that was sensitive to random action selection in the anodal compared to the sham tDCS session, whereas the learning rate parameter was not influenced significantly by tDCS. ConclusionThese results congruently indicate that prefrontal tDCS during instrumental learning increased randomness of choice, possibly reflecting the influence of the cognitive prefrontal component.
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