Integrating reinforcement-learning, accumulator models, and motor-primitives to study action selection and reaching in monkeys

This paper presents a model of brain systems underlying reaching in monkeys based on the idea that complex behaviors are built on the basis of a repertoire of motor primitives organized around specific goals (in this case, arm's postures). The architecture of the system is based on an actor-critic reinforcement-learning model, enhanced with an accumulator model for action selection, capable of selecting sensorimotor primitives so as to accomplish a discrimination reaching task that has been used in physiological studies of monkeys' premotor cortex. The results show that the proposed architecture is a first important step towards the construction of a biologically plausible integrated motor-primitive based model of the hierarchical organization of mammals' sensorimotor systems.