Modeling extracellular stimulation of retinal ganglion cells: theoretical and practical aspects.

Modeling extracellular stimulation of retinal ganglion cells: theoretical and practical aspects.
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DOI:
10.1088/1741-2552/acbf79
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发表时间:
2023-03-13
影响因子:
4
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中科院分区:
工程技术2区
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目标。视网膜假体利用电流激活视网膜内神经元,为盲人提供人工视觉。视网膜外刺激主要针对视网膜神经节细胞(RGCs),它可以用电缆方程建模。计算模型为研究视网膜激活机制和改进刺激范式提供了工具。然而,关于RGC模型结构和参数的文档是有限的,并且模型的实现会影响模型的预测。的方法。我们创建了一个功能指南,用于建立哺乳动物RGC多室电缆模型和应用细胞外刺激。接下来,我们研究了神经元的三维形状将如何影响模型预测。最后,我们测试了几种最大化计算效率的策略。主要的结果。我们进行了敏感性分析,以研究树突表现、轴突轨迹和轴突直径如何影响膜动力学和相应的激活阈值。我们优化了我们的多室电缆模型的时空离散化。我们还实现了几种基于激活函数的简化阈值预测理论,但这些理论的预测精度与索方程的预测精度不匹配。的意义。通过这项工作,我们为RGCs的细胞外刺激建模提供了实用的指导,以产生可靠和有意义的预测。稳健的计算模型为提高视网膜假体的性能奠定了基础。
Objective. Retinal prostheses use electric current to activate inner retinal neurons, providing artificial vision for blind people. Epiretinal stimulation primarily targets retinal ganglion cells (RGCs), which can be modeled with cable equations. Computational models provide a tool to investigate the mechanisms of retinal activation, and improve stimulation paradigms. However, documentation of RGC model structure and parameters is limited, and model implementation can influence model predictions. Approach. We created a functional guide for building a mammalian RGC multi-compartment cable model and applying extracellular stimuli. Next, we investigated how the neuron’s three-dimensional shape will influence model predictions. Finally, we tested several strategies to maximize computational efficiency. Main results. We conducted sensitivity analyses to examine how dendrite representation, axon trajectory, and axon diameter influence membrane dynamics and corresponding activation thresholds. We optimized the spatial and temporal discretization of our multi-compartment cable model. We also implemented several simplified threshold prediction theories based on activating function, but these did not match the prediction accuracy achieved by the cable equations. Significance. Through this work, we provide practical guidance for modeling the extracellular stimulation of RGCs to produce reliable and meaningful predictions. Robust computational models lay the groundwork for improving the performance of retinal prostheses.
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