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视网膜神经节细胞的细胞外刺激建模:理论与实践方面。

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

机构信息

Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States of America.

BioInterfaces Institute, University of Michigan, Ann Arbor, MI, United States of America.

出版信息

J Neural Eng. 2023 Mar 13;20(2):026011. doi: 10.1088/1741-2552/acbf79.

Abstract

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.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.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.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.

摘要

视网膜假体利用电流激活内视网膜神经元,为盲人提供人工视觉。视网膜上的刺激主要针对视网膜神经节细胞(RGC),这些细胞可以用电缆方程来建模。计算模型为研究视网膜激活机制和改进刺激方案提供了一种工具。然而,RGC 模型结构和参数的文档记录有限,模型的实现会影响模型的预测。我们创建了一个功能指南,用于构建哺乳动物 RGC 多室电缆模型并施加细胞外刺激。接下来,我们研究了神经元的三维形状将如何影响模型的预测。最后,我们测试了几种策略来最大限度地提高计算效率。我们进行了敏感性分析,以检查树突表示、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空间和时间离散化。我们还实现了几种基于激活函数的简化阈值预测理论,但这些理论与电缆方程的预测精度不匹配。通过这项工作,我们为 RGC 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。稳健的计算模型为改善视网膜假体的性能奠定了基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee57/10010067/c7ed8b31fd27/jneacbf79f1_lr.jpg

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