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Computational modeling of autonomic nerve stimulation: Vagus et al.
被引:1
|作者:
Grill, Warren M.
[1
]
Pelot, Nicole A.
[1
]
机构:
[1] Duke Univ, Dept Biomed Engn, Durham, NC 27708 USA
基金:
美国国家卫生研究院;
关键词:
Computational modeling;
Vagus nerve stimulation;
Peripheral nerve;
stimulation;
Autonomic nerve stimulation;
Neural engineering;
CURRENT FLOW;
EXCITATION;
D O I:
10.1016/j.cobme.2024.100557
中图分类号:
R318 [生物医学工程];
学科分类号:
0831 ;
摘要:
Computational models of electrical stimulation, block and recording of autonomic nerves enable analysis of mechanisms of action underlying neural responses and design of optimized stimulation parameters. We reviewed advances in computational modeling of autonomic nerve stimulation, block, and recording over the past five years, with a focus on vagus nerve stimulation, including both implanted and less invasive approaches. Few models achieved quantitative validation, but integrated computational pipelines increase the reproducibility, reusability, and accessibility of computational modeling. Modelbased optimization enabled design of electrode geometries and stimulation parameters for selective activation (across fiber locations or types). Growing efforts link models of neural activity to downstream physiological responses to represent more directly the therapeutic effects and side effects of stimulation. Thus, computational modeling is an increasingly important tool for analysis and design of bioelectronic therapies.
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