Assessment of murine retinal acuity ex vivo by machine learning of multielectrode array recordings

项目摘要：达尔文巴比诺博士，一位训练有素的药理学家/电生理学家， 在过去的十年里，他致力于视觉科学的几个学科。他的建议 标题为“Assessment of murine retinal acuity ex vivo by machine learning of multielectrode array 记录”提出了他的首要目标，以改善视力恢复的方法， 开发测试这些技术潜力的方法，从而加速 制定有效的干预措施。巴比诺博士和他的主要导师罗素货车博士 盖尔德，已经在华盛顿大学SOM组建了一支强大的共同导师团队， 合作者，以指导他通过拟议的培训和研究。他之前的训练 补充目标，以帮助他发展为一个独立的研究者：1）研究 设计和实践学习进行全视网膜（MEA）生物实验; 2） 提出的光遗传学和干细胞修复的基础和先进技术 技术; 3）应用先进的机器学习技术; 4）培养领导力， 建立独立的专业技能小组。评估功能的能力 全视网膜电路将促进我们对不同的优势和弱点的理解， 修复技术（目标1）。这里提出的工作将改善现有的视网膜敏锐度 一种评估工具，它结合了机器学习技术， 多电极阵列记录几种小鼠模型中的神经节细胞反应。本实用 该系统的功能将在三个实验中评估小鼠视网膜的视觉潜力中得到验证 不同的视力恢复方法对体内评估具有挑战性（目标2）。在 与Deepak A博士合作。在加州大学旧金山分校的兰巴，我们将把我们的系统应用于动物， 已经经历了视网膜细胞包括感光细胞的干细胞替代。一个 光遗传学方法也将与加州大学的John Flannery博士合作进行评估 他的研究小组已经开发出在细胞中表达视紫红质和视锥细胞视蛋白的载体。 神经节和双极细胞。最后，天然和恢复vison之间的差异很小， 分子光开关，电压门控钾通道的光激活抑制剂， 赋予处理的细胞光依赖性放电。由此产生的先进 电生理学的应用将有助于阐明有关功能的基本问题， 视网膜，导致视网膜变性的机制和几种治疗方法的潜力， 视网膜疾病的治疗。此外，该职业发展奖将促进博士。 巴比诺的发展成为一个独立的调查员启动R 01赠款申请。

Project Summary: Darwin Babino, PhD, a trained pharmacologist/electrophysiologist, has spent the last ten years working on several disciplines in the vision sciences. His proposal entitled “Assessment of murine retinal acuity ex vivo by machine learning of multielectrode array recordings” presents his overarching goal to improve vision restoration approaches by developing methods to test the potential of these techniques thereby accelerating the development of effective interventions. Dr. Babino and his primary mentor, Dr. Russell Van Gelder, have assembled a strong team of co-mentors at the University of Washington SOM and collaborators to guide him through the proposed training and research. His previous training will be supplemented with goals to help his development as an independent investigator: 1) Study design and practical learning in performing panretinal (MEA) biological experiments; 2) Fundamental and advanced techniques of the proposed optogenetic and stem-cell restoration techniques; 3) Application of advanced machine learning techniques; 4) Develop leadership and professional skills to establish an independent group. The ability to assess the function of panretinal circuitry will foster our understanding of the advantages and weaknesses of different restoration techniques (Aim 1). The work proposed here will improve an existing retinal acuity assessment tool which combines machine learning techniques on novel, high-density multielectrode array recordings of ganglion cell responses in several mouse models. The utility of this system will be demonstrated in assessing visual potential of the mouse retina in three different approaches to vision restoration that are challenging for in vivo assessment (Aim 2). In collaboration with Dr. Deepak A. Lamba at UCSF, we will apply our system to animals which have undergone stem-cell replacement of retinal cells including photoreceptor cells. An optogenetics approach will also be evaluated in collaboration with Dr. John Flannery at UC Berkeley whose group has developed vectors for expressing rhodopsin and cone opsins in ganglion and bipolar cells. Finally, differences between native and restored vison with small molecule photoswitches, light-activated inhibitors of voltage-gated potassium channels, which confer light-dependent firing on treated cells, will be assessed. The resulting advanced electrophysiology application will help elucidate fundamental questions about the functional retina, mechanisms that lead to retinal degeneration and the potential of several therapeutics for the treatment of retinal diseases. Furthermore, this career development award will facilitate Dr. Babino’s development into an independent investigator by priming an R01 grant application.