Prefrontal transcranial magnetic stimulation boosts response vigour during reinforcement learning in healthy adults

Abstract

A 10-Hz repetitive transcranial magnetic stimulation to the left dorsal lateral prefrontal cortex has been shown to increase dopaminergic activity in the dorsal striatum, a region strongly implicated in reinforcement learning. However, the behavioural influence of this effect remains largely unknown. We tested the causal effects of 10-Hz stimulation on behavioural and computational characteristics of reinforcement learning. A total of 40 healthy individuals were randomized into active and sham (placebo) stimulation groups. Each participant underwent one stimulation session (1500 pulses) in which stimulation was applied over the left dorsal lateral prefrontal cortex using a robotic arm. Participants then completed a reinforcement learning task sensitive to striatal dopamine functioning. Participants' choices were modelled using a reinforcement learning model (Q-learning) that calculates separate learning rates associated with positive and negative reward prediction errors. Subjects receiving active stimulation exhibited increased reward rate (number of correct responses per second of task activity) compared with those in sham. Computationally, although no group differences were observed, the active group displayed a higher learning rate for correct trials (αG) compared with incorrect trials (αL). Finally, when tested with novel pairs of stimuli, the active group displayed extremely fast reaction times, and a trend towards a higher reward rate. This study provided specific behavioural and computational accounts of altered striatal-mediated behaviour, particularly response vigour, induced by a proposed increase of dopamine activity by 10-Hz stimulation to the left dorsal lateral prefrontal cortex. Together, these findings bolster the use of repetitive transcranial magnetic stimulation to target neurocognitive disturbances attributed to the dysregulation of dopaminergic-striatal circuits.

Keywords: Q-learning; TMS; dopamine; probabilistic selection task; reinforcement learning; reward prediction errors.