We present a cortico-basal ganglia model to study the neural mechanisms behind reaching movements in normal and in Parkinson’s disease conditions. The model consists of the following components: a two-joint arm model (AM), a layer of motor neurons in the spinal cord (MN), the proprioceptive cortex (PC), the motor cortex (MC), the prefrontal cortex (PFC), and the basal ganglia (BG). The model thus has an outer sensory-motor cortical loop and an inner cortico-basal ganglia loop to drive learning of reaching behavior. Sensory and motor maps are formed by the PC and MC which represent the space of arm configurations. The BG sends control signals to the MC following a stochastic gradient ascent policy applied to the value function defined over the arm configuration space. The trainable connections from PFC to MC can directly activate the motor cortex, thereby producing rapid movement avoiding the slow search conducted by the BG. The model captures the two main stages of motor learning, i.e., slow movements dominated by the BG during early stages and cortically driven fast movements with smoother trajectories at later stages. The model explains PD performance in stationary and pursuit reaching tasks. The model also shows that PD symptoms like tremor and rigidity could be attributed to synchronized oscillations in STN–GPe. The model is in line with closed-loop control and with neural representations for all the nuclei which explains Parkinsonian reaching. By virtue of its ability to capture the role of cortico-basal ganglia systems in controlling a wide range of features of reaching, the proposed model can potentially serve as a benchmark to test various motor pathologies of the BG. © Springer Nature Singapore Pte Ltd. 2018.