Parkinson’s disease is the second most common neurodegenerative disorder with a signiVcant social cost. The disease that develops over years results in signiVcant movement related problems for the aUected. The pathogenesis however is partially understood. Computational approaches are signiVcant in the analysis of events that are multi-factorial. Parkinson’s Disease results from a system failure that leads to severe degeneration in the substantia nigra , a locus in the mid-brain. Traditional approaches tend to focus on isolated sub-components of the pathogenic pathways. However, such an approach may be inadequate to describe the pathogenesis. Substantia nigra neurons function on an expensive energy budget, due to a high level of arborisation and pacemaking activity. Spontaneous oscillations of these neurons are an important feature of motor control. Pacemaking involves the L-type calcium channel, and could impose long-term accumulation of calcium within its organelles. Modelling of this activity is an important part of developing an understanding of the pathogenic process. We develop a mathematical paradigm to describe this activity with a single compartment approach. To develop the mathematical framework we initially identify the components that contribute to the process and investigate an appropriate mathematical representation for the respective components. In the next part, we bring together such representation to develop a model that can reproduce measured data. Global optimisation strategies are adopted to tune important parameters. The model explicitly describes the dynamics of the transmembrane potential with changes in the levels of important cations. The model is veriVed for two major observations in literature regarding its response in the presence of channel blockers. The model is analysed for parameter bifurcation and stability of oscillations. Finally a framework is proposed to extend the model to include aspects of calcium homeostasis.