Title :
Simulation of Cortico-Basal Ganglia Oscillations and Their Suppression by Closed Loop Deep Brain Stimulation
Author :
Grant, P.F. ; Lowery, M.M.
Author_Institution :
Sch. of Electr., Electron. & Commun. Eng., Univ. Coll. Dublin, Dublin, Ireland
Abstract :
A new model of deep brain stimulation (DBS) is presented that integrates volume conduction effects with a neural model of pathological beta-band oscillations in the cortico-basal ganglia network. The model is used to test the clinical hypothesis that closed-loop control of the amplitude of DBS may be possible, based on the average rectified value of beta-band oscillations in the local field potential. Simulation of closed-loop high-frequency DBS was shown to yield energy savings, with the magnitude of the energy saved dependent on the strength of coupling between the subthalamic nucleus and the remainder of the cortico-basal ganglia network. When closed-loop DBS was applied to a strongly coupled cortico-basal ganglia network, the stimulation energy delivered over a 480 s period was reduced by up to 42%. Greater energy reductions were observed for weakly coupled networks, as the stimulation amplitude reduced to zero once the initial desynchronization had occurred. The results provide support for the application of closed-loop high-frequency DBS based on electrophysiological biomarkers.
Keywords :
bioelectric potentials; brain; neuromuscular stimulation; physiological models; DBS amplitude; closed-loop high-frequency DBS; cortico-basal ganglia oscillation; deep brain stimulation; desynchronization; electrophysiological biomarker; energy magnitude; energy reduction; local field potential; neural model; pathological beta-band oscillation; subthalamic nucleus; time 480 s; volume conduction effect; Brain modeling; Computational modeling; Electrodes; Neurons; Oscillators; Satellite broadcasting; Solid modeling; Closed-loop deep brain stimulation; computational model; Algorithms; Artifacts; Axons; Basal Ganglia; Beta Rhythm; Biological Markers; Cerebral Cortex; Computer Simulation; Deep Brain Stimulation; Electroencephalography; Evoked Potentials; Humans; Models, Theoretical; Nerve Net; Neural Networks (Computer); Neurons;
Journal_Title :
Neural Systems and Rehabilitation Engineering, IEEE Transactions on
DOI :
10.1109/TNSRE.2012.2202403