Human brain systems have their own functional expertise. As they interact, these systems allow for efficient goal-directed behavior. Yet, the interaction between systems is poorly understood. The “action” system represents the sequence of actions needed to perform some task; for instance, the sequential actions a drummer performs to hit the drums. The “when” system represents the time at which actions need to be performed, i.e. the time at which drum strokes are executed to follow the rhythm. I propose to build a neurocomputational model about how the brain implements the interaction between these two systems. I present 3 work packages (WP). WP 1 explains the model and the tools needed to build it. WP 2 proposes two experimental studies to
test the model predictions in distinct action sequences contexts. Various model versions will be compared through model comparison techniques. WP 3 further tests the functional role of the subthalamic nucleus (STN), the brain area suggested to subtend the interaction between both systems. To treat their tremor symptoms, implanted electrodes in Parkinson’s disease patients (PDP) stimulate the STN but simultaneously disrupt its functional role. In collaboration with a specialized lab, I will stimulate STN in PDP while they solve my experimental tasks. I will investigate which model version best accounts for PDP data when I simulate STN stimulation. Overall, I aim to elucidate how humans learn to produce time-dependent action sequences.