Interactions between supervised and reinforcement learning processes in a neurorobotic model
Several influential works propose that the acquisition of motor behavior involves different learning mechanisms in the brain, in particular supervised and reinforcement learning, that are respectively associated with cerebellar-thalamocortical and basal ganglia-thalamocortical networks. Despite increasing evidence suggesting anatomical and functional interactions between these circuits, the learning processes operating within them are studied in isolation, neglecting their strong interdependence. This article proposes a bio-inspired neurorobotic model implementing a possible cooperation mechanism between supervised and reinforcement learning. The model, validated with empirical data from healthy participants and patients with cerebellar ataxia, shows how the integration of the two learning processes could lead to benefit both learning performance and movement accuracy.