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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

DOI

10.1109/NER.2013.6695900

Type

Journal article

Journal

International IEEE/EMBS Conference on Neural Engineering, NER

Publication Date

01/12/2013

Pages

174 - 177