title: Application of non-linear control theory to a model of deep brain stimulation.
abstract: Deep brain stimulation (DBS) effectively alleviates the pathological neural activity associated with Parkinson's disease. Its exact mode of action is not entirely understood. This paper explores theoretically the optimum stimulation parameters necessary to quench oscillations in a neural-mass type model with second order dynamics. This model applies well established nonlinear control system theory to DBS. The analysis here determines the minimum criteria in terms of amplitude and pulse duration of stimulation, necessary to quench the unwanted oscillations in a closed loop system, and outlines the relationship between this model and the actual physiological system.
authors.affiliation: School of Electrical, Electronic and Mechanical Engineering, University College Dublin, Dublin 4, Ireland. clare.davidson@ucdconnect.ie
authors.forename: Clare M
authors.initials: CM
authors.lastname: Davidson
authors.forename: Madeleine M
authors.initials: MM
authors.lastname: Lowery
authors.forename: Annraoi M
authors.initials: AM
authors.lastname: de Paor
mesh_terms: D000465:Algorithms; D001479:Basal Ganglia / Q000473:pathology; D046690:Deep Brain Stimulation / Q000379:methods*; D005246:Feedback; D005917:Globus Pallidus / Q000473:pathology; D006801:Humans; D016014:Linear Models; D015233:Models, Statistical; D009474:Neurons / Q000473:pathology; D017711:Nonlinear Dynamics; D009991:Oscillometry / Q000379:methods; D010300:Parkinson Disease / Q000503:physiopathology / Q000628:therapy*; D015203:Reproducibility of Results