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一种用于设计宽视野视神经神经假体的计算模型。

A computational model to design wide field-of-view optic nerve neuroprostheses.

作者信息

Romeni Simone, De Luca Daniela, Pierantoni Luca, Toni Laura, Marino Gabriele, Moccia Sara, Micera Silvestro

机构信息

Modular Implantable Neurotechnologies Laboratory, Università Vita-Salute San Raffaele & Scuola Superiore Sant'Anna, Milan, Italy.

Bertarelli Foundation Chair in Translational Neural Engineering, Center for Neuroprosthetics and Institute of Bioengineering, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland.

出版信息

iScience. 2024 Nov 5;27(12):111321. doi: 10.1016/j.isci.2024.111321. eCollection 2024 Dec 20.

DOI:10.1016/j.isci.2024.111321
PMID:39628568
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11612796/
Abstract

Retinal stimulation (RS) allows restoring vision in blind patients, but it covers only a narrow region of the visual field. Optic nerve stimulation (ONS) has the potential to produce visual perceptions spanning the whole visual field, but it produces very irregular phosphenes. We introduced a geometrical model converting retinal and optic nerve firing rates into visual perceptions and vice versa and a method to estimate the best perceptions elicitable through an electrode configuration. We then compared in silico ONS and RS through simulated prosthetic vision of static and dynamic visual scenes. Both simulations and SPV experiments showed that it might be possible to reconstruct natural visual scenes with ONS and RS, and that ONS wide field-of-view allows the perception of more detail in dynamic scenarios than RS. Our findings suggest that ONS could represent an interesting approach for vision restoration and that our model can be used to optimize it.

摘要

视网膜刺激(RS)可使盲人恢复视力,但它仅覆盖视野的狭窄区域。视神经刺激(ONS)有可能产生覆盖整个视野的视觉感知,但会产生非常不规则的光幻视。我们引入了一个几何模型,可将视网膜和视神经的放电频率转换为视觉感知,反之亦然,还引入了一种方法来估计通过电极配置可引发的最佳感知。然后,我们通过模拟静态和动态视觉场景的假体视觉,在计算机模拟中比较了ONS和RS。模拟和假体视觉实验均表明,使用ONS和RS有可能重建自然视觉场景,并且ONS的宽视野在动态场景中比RS能感知到更多细节。我们的研究结果表明,ONS可能是一种有趣的视力恢复方法,并且我们的模型可用于对其进行优化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3ea/11612796/c0f48fde6172/gr8.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3ea/11612796/18354b8cc5ca/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3ea/11612796/44e33ca573bc/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3ea/11612796/7046be3f14b9/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3ea/11612796/d380f3d01efa/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3ea/11612796/1ab20f498e3b/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3ea/11612796/c0f48fde6172/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3ea/11612796/af0f2967eeb9/fx1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3ea/11612796/294823d32334/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3ea/11612796/b1865481dcae/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3ea/11612796/18354b8cc5ca/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3ea/11612796/44e33ca573bc/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3ea/11612796/7046be3f14b9/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3ea/11612796/d380f3d01efa/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3ea/11612796/1ab20f498e3b/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3ea/11612796/c0f48fde6172/gr8.jpg

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本文引用的文献

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An update on visual prosthesis.视觉假体的最新进展。
Int J Retina Vitreous. 2023 Nov 23;9(1):73. doi: 10.1186/s40942-023-00498-1.
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Attitudes of potential recipients toward emerging visual prosthesis technologies.潜在受赠者对新兴视觉假体技术的态度。
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Combining biophysical models and machine learning to optimize implant geometry and stimulation protocol for intraneural electrodes.结合生物物理模型和机器学习以优化神经内电极的植入几何形状和刺激方案。
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PLoS Comput Biol. 2023 May 25;19(5):e1011184. doi: 10.1371/journal.pcbi.1011184. eCollection 2023 May.
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The role of the visual field size in artificial vision.视野大小在人工视觉中的作用。
J Neural Eng. 2023 Apr 6;20(2). doi: 10.1088/1741-2552/acc7cd.
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Artificial neural network-based rapid predictor of biological nerve fiber activation for DBS applications.用于脑深部电刺激应用的基于人工神经网络的生物神经纤维激活快速预测器。
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Clinical Progress and Optimization of Information Processing in Artificial Visual Prostheses.人工视觉假体中的信息处理的临床进展和优化。
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