Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we'll assume that you are happy to receive all cookies and you won't see this message again. Click 'Find out more' for information on how to change your cookie settings.

Deep brain stimulation (DBS) effectively suppresses the pathological neural activity associated with Parkinson's disease, with a parallel improvement in motor symptoms of the disease observed. However, its exact mode of action is not fully understood. This study explores a fourth order computational model of neural synchrony and applied stimulation using established nonlinear control systems theory. A novel method of combining two describing functions is developed, which allows the amplitude of oscillations in the model to be studied as the applied stimulation parameters vary. The theoretical model parameters are fitted to experimental data recorded in a patient with Parkinson's disease for a range of stimulator settings. © 2013 IEEE.

Original publication




Journal article


International IEEE/EMBS Conference on Neural Engineering, NER

Publication Date



174 - 177