Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:4482-4486. doi: 10.1109/EMBC46164.2021.9630642.
Partial vision restoration on degenerated retina can be achieved by electrically stimulating the surviving retinal ganglion cells via implanted electrodes to elicit a signal corresponding to the natural response of the cells. Realistic computational models of electrical stimulation of the retina can prove useful to test different stimulation strategies and improve the performance of retinal implants. Simulation of healthy retinal networks and their dynamical response to natural light stimulation may also help us understand how retinal processing takes place via a series of electrical signals flowing through different stages of retinal processing, ultimately giving rise to visual percepts. Such models may provide further insights on retinal network processing and thus guide the design of retinal prostheses and their stimulation protocols to generate more natural percepts. This work aims to characterize the photocurrent generated by healthy cone photoreceptors in response to a light flash stimulation and the resulting membrane potential for the photoreceptors and its postsynaptic cone bipolar cells. A simple network of ten cone photoreceptors synapsing with a cone bipolar cell is simulated using the NEURON environment and validated against patch-clamp recordings of cone photoreceptors and ON-type bipolar cells (ON-BC). The results presented will be valuable in modeling light-evoked or electrically stimulated retinal networks that comprise cone pathways. The computational models and methods developed in this work will serve as an integral building block in the development of large and realistic retinal networks.Clinical Relevance- Accurate computational model of a retinal neural network can help in predicting cell responses to electrical stimulation in vision restoration therapies using prostheses. It can be leveraged to optimize the stimulation parameters to match the natural light response of the network as closely as possible.
退化视网膜的部分视力可以通过植入电极刺激存活的视网膜神经节细胞来实现，从而产生与细胞自然反应相对应的信号。视网膜电刺激的现实计算模型可以证明有助于测试不同的刺激策略并提高视网膜植入物的性能。对健康视网膜网络及其对自然光刺激的动态响应的模拟也可以帮助我们了解视网膜处理是如何通过一系列流经视网膜处理不同阶段的电信号来进行的，最终产生视觉感知。此类模型可以进一步深入了解视网膜网络处理，从而指导视网膜假体的设计及其刺激方案，以产生更自然的感知。本工作旨在表征健康视锥光感受器在光闪光刺激下产生的光电流以及光感受器及其光感受器型双极细胞的膜电位。使用 NEURON 环境模拟了十个视锥光感受器与视锥双极细胞（ON-BC）突触的简单网络，并针对视锥光感受器和 ON 型双极细胞（ON-BC）的膜片钳记录进行了验证。所呈现的结果对于建模包含视锥途径的光诱发或电刺激视网膜网络将是有价值的。本工作中开发的计算模型和方法将作为开发大型和现实视网膜网络的一个基本构建块。临床相关性-视网膜神经网络的精确计算模型可以帮助预测使用假体进行视力恢复治疗中细胞对电刺激的反应。可以利用它来优化刺激参数，使其尽可能接近网络的自然光响应。
