Virtual prototyping for retinal prosthesis patients

视网膜假体患者的虚拟原型制作

• 批准号: 10200240
• 负责人: Michael Beyeler
• 金额: $ 24.73万
• 依托单位: UNIVERSITY OF CALIFORNIA SANTA BARBARA
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-30 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10200240
• 关键词: Affect; Behavioral; Bionics; Cells; Clinical Trials; Cochlear Implants; Collaborations; Complex; Computer Models; Computer Vision Systems; Data; Development; Devices; Effectiveness; Electric Stimulation; Electrodes; Electronics; Electrophysiology (science); Eye; Eye Movements; Family; Financial compensation; Future; Goals; Head; Human; Implant; In Vitro; Individual; Knowledge; Learning; Letters; Machine Learning; Macular degeneration; Manufacturer Name; Medical; Medicare; Methods; Modeling; Motion; Neurons; Ocular Prosthesis; Online Systems; Outcome; Output; Patients; Pattern; Perceptual distortions; Performance; Photoreceptors; Prosthesis; Prosthesis Design; Protocols documentation; Psychophysics; Rehabilitation therapy; Reporting; Retina; Retinal Diseases; Retinal Dystrophy; Retinitis Pigmentosa; Schedule; Severities; Shapes; Specialist; Stimulus; System; Techniques; Technology; Testing; Training; Vision; Visual; Visual Psychophysics; Visual impairment; Visual system structure; Visualization; Work; base; behavior measurement; behavior test; deep neural network; design; experience; experimental study; gaze; implantation; improved; machine learning algorithm; neurophysiology; neuroprosthesis; novel; object recognition; optogenetics; predictive modeling; prototype; regression algorithm; restoration; retinal prosthesis; simulation; spatiotemporal; success; virtual; virtual reality; virtual reality environment

Project Summary/Abstract Retinal dystrophies such as retinitis pigmentosa and macular degeneration induce progressive loss of photoreceptors, resulting in profound visual impairment in more than ten million people worldwide. Visual neuroprostheses (‘bionic eyes’) aim to restore functional vision by electrically stimulating remaining cells in the retina, analogous to cochlear implants. A wide variety of neuroprostheses are either in development (e.g. optogenetics, cortical) or are being implanted in patients (e.g. subretinal or epiretinal electrical). A limiting factor that affects all device types are perceptual distortions and subsequent loss of information, caused by interactions between the implant technology and the underlying neurophysiology. Understanding the causes of these distortions and finding ways to alleviate them is critically important to the success of current and future sight restoration technologies. In this proposal, human visual psychophysics, computational modeling, data-driven approaches, and virtual reality (VR) will be combined to develop and experimentally validate optimized stimulation protocols for epiretinal prostheses. This approach is analogous to virtual prototyping for airplanes and other complex systems: to use a high-quality model of both the implant electronics and the visual system in order to generate a ‘virtual patient’. Retinal electrophysiological and visual behavioral data will be used to develop and validate a computational model of the expected visual experience of patients when electrically stimulated. One way of using this model will be to generate simulations of the expected perceptual outcome of electrical stimulation across a wide variety of electrical stimulation patterns. These will be used as a training set for machine learning algorithms that will invert the input-output function of the model to find the electrical stimulation protocol that best replicates any desired perceptual experience. The model can also be used to simulate the expected perceptual experience of real patients by using sighted subjects in a VR environment – ‘VR virtual patients’. These virtual patients will be used to discover preprocessing methods (e.g., edge enhancement, retargeting, decluttering) that improve behavioral performance in VR. Although current retinal prostheses have been implanted in over 250 patients worldwide, experimentation with improved stimulation protocols remains challenging and expensive. Implementing ‘virtual patients’ in VR offers an affordable and practical alternative for high-throughput experiments to test new stimulation protocols. Stimulation protocols that result in good VR performance will be experimentally validated in real prosthesis patients in collaboration with Second Sight Medical Products Inc. and Pixium Vision, two leading device manufacturers in the field. This work has the potential to significantly improve the effectiveness of visual neuroprostheses as a treatment option for individuals suffering from blinding retinal diseases.

项目摘要/摘要 视网膜疾病（例如视网膜炎色素和黄斑变性）诱导的逐渐丧失 感光体，在全球超过一千万人中导致了深远的视觉障碍。视觉的 神经假体（“仿生眼”）的目的是通过电力刺激剩余细胞来恢复功能视觉 视网膜，类似于耳蜗。各种各样的神经假体正在发育（例如 光遗传学，皮质）或正在植入患者（例如视网膜下或前电气）。一个限制因素 影响所有设备类型的是感知扭曲和随后的信息丢失，这是由互动引起的 在植入技术和潜在的神经生理学之间。了解这些原因 扭曲并找到减轻它们的方法对于当前和未来意义的成功至关重要 恢复技术。在此建议中，人类视觉心理物理学，计算建模，数据驱动 方法和虚拟现实（VR）将合并以开发和实验验证优化 刺激性假体的刺激方案。这种方法类似于飞机的虚拟原型制作 和其他复杂系统：使用植入物电子和视觉系统的高质量模型 为了产生“虚拟患者”。视网膜电生理和视觉行为数据将用于发展 并验证电刺激时患者预期视觉体验的计算模型。 使用此模型的一种方法是生成对电气的预期感知结果的模拟 跨多种电刺激模式的刺激。这些将被用作训练集 机器学习算法将颠倒模型的输入输出功能以找到电动模拟 最能重复任何理想的感知体验的协议。该模型也可用于模拟 通过在VR环境中使用视力对象的真实患者的预期感知经验 - ‘VR Virtual 患者'。这些虚拟患者将用于发现预处理方法（例如，边缘增强， 重新定位，整理），以改善VR的行为表现。尽管目前的视网膜假体有 已植入全球250多名患者，通过改进的刺激方案进行实验 具有挑战性和昂贵。在VR中实施“虚拟患者”提供了负担得起且实用的替代方案 高通量实验测试新刺激方案。刺激协议导致良好的VR 绩效将在实际假体患者中与第二瞄准镜一起实验验证 Medical Products Inc.和Pixium Visium，该领域的两个领先的设备制造商。这项工作有 有可能显着提高视觉神经植物作为个体的治疗选择的有效性 患有盲目残留疾病。