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引用次数: 0

摘要

神经元的计算模型是非常有价值的工具,它能让研究人员形成和评估假设,并最大限度地减少高成本的动物实验。我们很快计划使用计算模型来探索不同感觉纤维类型对长时间外部刺激的反应,以尝试选择性阻断痛觉C纤维。在这项工作中,我们修改了现有的特异性 C 纤维轴突模型,增加了浓度依赖性电导变化、纵向电流对局部浓度变化的贡献以及沿轴突的浓度梯度产生的纵向电流。然后,我们研究了这些附加元素对模型动作电位特性、活动相关潜伏期增加以及外部刺激引起的浓度变化的影响。我们发现,这些额外的模型元素并未对动作电位特性或活动依赖行为产生重大影响,但它们确实对模型对外部长时程刺激的反应产生了重大影响。
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The Significance of Concentration-dependent Components in Computational Models of C-Fibers.

Computational models of neurons are valuable tools that allow researchers to form and evaluate hypotheses and minimize high-cost animal work. We soon plan to use computational modeling to explore the response of different sensory fiber types to long duration external stimulation to try to selectively block nociceptive C-fibers. In this work, we modified an existing C-fiber-specific axon model to additionally include concentration-dependent conductance changes, the contribution of longitudinal current flow to changes in local concentrations, and longitudinal currents generated by concentration gradients along the axon. Then, we examined the impact of these additional elements on the modeled action potential properties, activity-dependent latency increases, and concentration changes due to external stimulation. We found that these additional model elements did not significantly affect the action potential properties or activity-dependent behavior, but they did have a significant impact on the modeled response to external long duration stimulation.Clinical Relevance- This presents a computational model that can be used to help investigate and develop electrical stimulation therapies for pathological pain.

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