Computational modeling of autonomic nerve stimulation: Vagus et al.

IF 4.7 3区 工程技术 Q2 ENGINEERING, BIOMEDICAL
Warren M. Grill, Nicole A. Pelot
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引用次数: 0

Abstract

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. Model-based 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.

自律神经刺激的计算建模:Vagus et al.
通过自律神经电刺激、阻断和记录的计算模型,可以分析神经反应的作用机制,并设计优化的刺激参数。我们回顾了过去五年中自律神经刺激、阻断和记录计算模型的进展,重点是迷走神经刺激,包括植入式和微创方法。实现定量验证的模型寥寥无几,但集成计算管道提高了计算建模的可重复性、可重用性和可访问性。基于模型的优化设计实现了电极几何形状和刺激参数的选择性激活(跨纤维位置或类型)。越来越多的研究将神经活动模型与下游生理反应联系起来,以更直接地体现刺激的治疗效果和副作用。因此,计算建模是分析和设计生物电子疗法的一个日益重要的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Current Opinion in Biomedical Engineering
Current Opinion in Biomedical Engineering Medicine-Medicine (miscellaneous)
CiteScore
8.60
自引率
2.60%
发文量
59
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