Model-based analysis and design of waveforms for efficient neural stimulation

被引：37

作者：

Grill, Warren M. ^{[1
,2
,3
,4
]}

机构：

[1] Duke Univ, Dept Biomed Engn, Durham, NC 27706 USA

[2] Duke Univ, Dept Elect & Comp Engn, Durham, NC 27706 USA

[3] Duke Univ, Dept Neurobiol, Durham, NC 27706 USA

[4] Duke Univ, Dept Surg, Durham, NC 27706 USA

来源：

COMPUTATIONAL NEUROSTIMULATION | 2015年 / 222卷

关键词：

Neural model; Electrical stimulation; Deep brain stimulation; Energy efficiency; Selectivity; Optimization; DEEP BRAIN-STIMULATION; MOTOR CORTEX STIMULATION; MYELINATED NERVE; PARKINSONS-DISEASE; TRANSIENT DEPOLARIZATION; ELECTRICAL-STIMULATION; SELECTIVE ACTIVATION; STIMULUS PARAMETERS; EXCITATION; FIBERS;

D O I：

10.1016/bs.pbr.2015.07.031

中图分类号：

Q189 [神经科学];

学科分类号：

071006 ;

摘要：

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.

引用

页码：147 / 162

页数：16

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