Retinal connectome: mobile game and crowdsourcing algorithms for EyeWire II

视网膜连接组：EyeWire II 的手机游戏和众包算法

• 批准号: 9076876
• 负责人: Hyunjune SEBASTIAN SEUNG
• 金额: $ 32.09万
• 依托单位: PRINCETON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-08 至 2018-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9076876
• 关键词: Algorithms; Arts; Attention; BRAIN initiative; Behavior; Biomedical Research; Blindness; Books; Boston; Breathing; Bypass; Caenorhabditis elegans; Cells; Cellular Phone; Code; Collaborations; Color; Communities; Computer software; Country; Crowding; Data; Development; Electrons; Event; Goals; Human; Image; Institutes; Intelligence; Lead; Learning; Love; Maps; Modeling; Natural regeneration; Nature; Nervous system structure; Neurons; Neurosciences; New York; Organism; Performance; Play; Production; Publishing; Retina; Retinal; Scheme; Science; Sensory; Social Interaction; Source; Statistical Models; Students; Technology; Three-Dimensional Image; Time; Training; United States National Institutes of Health; Universities; Volunteer Group; Voting; Weight; Work; base; citizen science; connectome; crowdsourcing; design; ganglion cell; improved; innovation; microscopic imaging; neural circuit; online community; pleasure; programs; prototype; public health relevance; reconstruction; retinal prosthesis; simulation; starburst amacrine cell; success; university student; visual neuroscience; volunteer

 DESCRIPTION (provided by applicant): An online community called EyeWire proved that volunteers can be motivated to reconstruct neural circuits through an activity resembling a 3D coloring book. EyeWire helped discover space-time specificity of the wiring from bipolar cells to starburst amacrine cells, which suggested a surprising new model for direction selectivity in the retina. Motivated by this success, we are preparing to launch EyeWire II, which aims to map the entire retinal connectome, yielding the first complete wiring diagram for any region of the mammalian CNS. This ambitious goal will require innovative advances in virtually every component of EyeWire. The underlying electron microscopic image of the retina will be replaced by a new image with increased size and quality. A new artificial intelligence (AI) will be trained using a new software package for 3D deep learning. While the improved AI is expected to reduce the amount of human effort required to reconstruct a neuron, the number of neurons targeted for reconstruction will also increase dramatically. Overall, the absolute amount of human effort required will increase rather than decrease. Therefore it is critical to improve EyeWire's crowdsourcing to (1) mobilize more human effort and (2) to use human effort more efficiently. This project aims to radically improve both aspects, thereby making the retinal connectome achievable by EyeWire II. In Aim 1, we will create a compelling mobile game with the target of engaging 10x more people than the existing EyeWire community. In Aim 2, we will develop and deploy new crowdsourcing algorithms that extract wisdom from the crowd by weighted voting and optimally assign players to tasks. The Aims will be achieved through collaboration between three organizations. Wired Differently, Inc. (WD) is a new Boston-based nonprofit organization dedicated to "citizen neuroscience" that was recently spun out of MIT. WD currently operates EyeWire in collaboration with the Princeton Neuroscience Institute. The Entertainment Technology Center (ETC) at Carnegie Mellon University will offer a project-based class to its master's students to design and prototype new ideas for the mobile game. Both Aims will produce code and algorithms that will be made publicly available, and could have broad impact on citizen science. As the first crowdsourcing of 3D image analysis, the code produced by Aim 1 could be useful for the many other kinds of 3D images found in biomedical research. The crowdsourcing algorithms of Aim 2 are potentially useful for any citizen science project facing the challenge of obtaining accurate and reliable results from a heterogeneous group of volunteers.

 描述（由申请人提供）：一个名为 EyeWire 的在线社区证明，可以激励志愿者通过类似于 3D 着色书的活动来重建神经回路，帮助发现从双极细胞到星爆无长突细胞的连线的时空特异性。提出了一种令人惊讶的视网膜方向选择性新模型。受这一成功的启发，我们正准备推出 EyeWire II，旨在绘制整个视网膜的地图。连接组，为哺乳动物中枢神经系统的任​​何区域生成第一个完整的接线图，这一雄心勃勃的目标将需要 EyeWire 的几乎每个组件都取得创新进步，视网膜的底层电子显微镜图像将被尺寸更大、质量更高的新图像所取代。将训练新的人工智能（AI）。 使用新的 3D 深度学习软件包虽然改进的人工智能有望减少重建神经元所需的人力，但重建的神经元数量也将大幅增加。因此，改进 EyeWire 的众包至关重要：(1) 动员更多的人力；(2) 更有效地利用人力。该项目旨在从根本上改善这两方面，从而使视网膜连接组得以实现。在目标 1 中，我们将创建一款引人注目的手机游戏，目标是吸引比现有 EyeWire 社区多 10 倍的人数。在目标 2 中，我们将开发和部署新的众包算法，通过加权投票从人群中汲取智慧。 Wired Differently, Inc. (WD) 是一家位于波士顿的新非营利组织，最近成立，致力于“公民神经科学”。 WD 目前与卡内基梅隆大学的普林斯顿神经科学研究所合作运营 EyeWire，将为其硕士生提供基于项目的课程，以设计和制作移动游戏的新想法。 Aims 将生成公开可用的代码和算法，并可能对公民科学产生广泛影响。作为 3D 图像分析的第一个众包，Aim 1 生成的代码可能对许多其他类型有用。生物医学研究中发现的 3D 图像对于任何面临从异构志愿者群体中获取准确可靠结果的挑战的公民科学项目都可能有用。