The present research investigates factors contributing to bradykinesia in the control of simple and complex voluntary limb movement in Parkinson's disease (PD) patients. The functional scheme of the basal ganglia (BG)-thalamocortical circuit was described by a mathematical model based on the mean firing rates of BG nuclei. PD was simulated as a reduction in dopamine levels, and a loss of functional segregation between two competing motor modules. In order to compare model simulations with performed movements, flexion and extension at the elbow joint is taken as a test case. Results indicated that loss of segregation contributed to bradykinesia due to interference between competing modules and a reduced ability to suppress unwanted movements. Additionally, excessive neurotransmitter depletion is predicted as a possible mechanism for the increased difficulty in performing complex movements. The simulation results showed that the model is in qualitative agreement with the results from movement experiments on PD patients and healthy subjects. Furthermore, based on changes in the firing rate of BG nuclei, the model demonstrated that the effective mechanism of Deep Brain Stimulation (DBS) in STN may result from stimulation induced inhibition of STN, partial synaptic failure of efferent projections, or excitation of inhibitory afferent axons even though the underlying methods of action may be quite different for the different mechanisms.

Deep Brain Stimulation (DBS) is effective in the Parkinsonian state, while it seems to produce rather non-selective stimulation over an unknown volume of tissue. Despite a huge amount of anatomical and physiological data regarding the structure of the basal ganglia (BG) and their connections, the computational processes performed by the basal ganglia in health and disease still remain unclear. Its hypothesized roles are discussed in this chapter as well as the changes that are observed under pathophysiological conditions. Several hypotheses exist in explaining the mechanism by which DBS provides its beneficial effects. Computational models of the BG span a range of structural levels, from low-level membrane conductance-based models of single neurons to high level system models of the complete BG circuit. A selection of models is presented in this chapter. This chapter aims at explaining how models of neurons and connected brain nuclei contribute to the understanding of DBS.