title: Model-based analysis and design of waveforms for efficient neural stimulation.
abstract: The design space for electrical stimulation of the nervous system is extremely large, and because the response to stimulation is highly nonlinear, the selection of stimulation parameters to achieve a desired response is a challenging problem. Computational models of the response of neurons to extracellular stimulation allow analysis of the effects of stimulation parameters on neural excitation and provide an approach to select or design optimal parameters of stimulation. Here, I review the use of computational models to understand the effects of stimulation waveform on the energy efficiency of neural excitation and to design novel stimulation waveforms to increase the efficiency of neural stimulation.
authors.affiliation: Department of Biomedical Engineering, Duke University, Durham, NC, USA; Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA; Department of Neurobiology, Duke University, Durham, NC, USA; Department of Surgery, Duke University, Durham, NC, USA. Electronic address: warren.grill@duke.edu.
authors.forename: Warren M
authors.initials: WM
authors.lastname: Grill
mesh_terms: D000818:Animals; D003198:Computer Simulation; D004558:Electric Stimulation / Q000379:methods*; D006801:Humans; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*
keywords: Deep brain stimulation; Electrical stimulation; Energy efficiency; Neural model; Optimization; Selectivity