Deep brain stimulation (DBS) is a clinical therapy, involving the surgical implantation of electrodes into disorder specific nuclei, used to treat the symptoms of movement disorders such as Parkinson¹s disease and essential tremor (ET). The mechanisms through which the electrical stimulation leads to the observed clinical improvements remain unclear, to the extent that it is unknown how stimulation changes neuronal excitation. If we better understood these mechanisms, we could optimise the parameters setting process and minimise unwanted side effects. To study the effect of stimulation on the firing activity of axons, single neurons, and networks of neurons, I take a multi-level computational modelling approach. First I create a finite element model to calculate the distribution of electric potential induced by DBS and then applied the potential as an extracellular stimulus to multicompartment axon or neuron models. I have previously shown that such models can reveal detailed spatial effects of stimulation in the vicinity of the electrode. To study network level changes, I model the network proposed to be involved in generating pathological synchronous activity via a Wilson-Cowan approach. The parameter space of such a model can be explored to uncover regions which produced oscillatory thalamic activity in the typical ET frequency range (4-12Hz). Taken together, these models demonstrate a method of quantitatively assessing neuronal changes induced by DBS, to maximise therapeutic benefit and minimise unwanted side effects.