The First Comprehensive Neural Connectivity Map of Mouse

描述(由申请人提供)：本申请涉及广泛的挑战领域(15)：翻译科学和具体的挑战主题，15-MH-103映射小鼠模型的神经连接。大脑的功能是由它的电路决定的，但我们对它的线路结构知之甚少：在研究最多的哺乳动物(老鼠)中，估计只探测到了10%-30%的长距离电路连接。目前的挑战主题证实了越来越多的共识，即现在是时候通过为模型脊椎动物生成全脑连接图来缩小这一差距的时候了。在过去的两年里，我们组织了几次涉及神经解剖学社区的会议，以深入了解此类项目的技术和科学挑战。基于这一经验，我们已经设计并开始建造和测试一条自动化的实验和计算技术管道，以实现这一目标。我们的建议得益于自动化广域玻片扫描显微镜的进步，数据存储成本的降低，以及使用经典示踪剂和工程病毒注射的已建立的轨迹追踪方法。实验计划可以概括如下。根据经典的神经解剖学和区域基因表达数据，小鼠的大脑被划分为大约200个区域。对于每个区域，我们给一只小鼠注射经典示踪剂，给一只小鼠注射病毒示踪剂。示踪剂从注射部位顺行运送到该地区的投射目标，并逆行运送到投射到注射地点的区域。通过这种方式，个别预测被多次揭示。为了获得这一信息，我们将从每只老鼠身上切下整个大脑，并使用自动载玻片扫描显微镜对这些切片进行成像。产生的2D切片图像将在软件中组合，为每次注射产生3D重建的大脑图像。最后，所有单独注射的3D图像将通过空间注册到艾伦参考地图集进行组合，最终生成统一的全脑神经连接图。在小鼠身上生成第一个无偏见的全脑连接图将具有广泛的神经科学意义。最终拥有这一里程碑式的参考图，有意义地约束理论并帮助实验设计和解释结果，神经发育、神经网络建模、进化神经解剖学以及关联和综合大脑功能的研究将极大地受益。通过分析艾伦研究所生成的基因表达图，结合该项目生成的连接性图，可以探索基因表达和连接性之间的关系。本研究中生成的基线神经连接图将作为后续研究突变小鼠品系间电路多态的基础。客观地量化自闭症和精神分裂症等神经精神障碍小鼠模型中连接性的变化将有助于我们理解它们的病因和病理生理学。最后，我们对开源软件开发、成本优化和可复制性的重视将导致一个负担得起的、集成的仪器，其他学术实验室将能够实施，因此这种方法可以迅速应用于各种神经科学问题。 叙述对神经精神障碍的小鼠模型的研究为这些负担沉重的疾病的治疗方法的开发提供了希望，但由于缺乏关于小鼠大脑如何连接的知识，进展缓慢。该项目旨在通过生成第一个大脑范围的鼠标接线图来弥合这一差距，这些技术是已知有效但劳动密集型的自动化技术。如果成功，该项目有可能从根本上改变我们对正常和无序大脑结构的理解。

DESCRIPTION (provided by applicant): This application addresses broad Challenge Area (15): Translational Science and specific Challenge Topic, 15- MH-103 Mapping the Neural Connectivity of a Mouse Model. Brain function is dictated by its circuitry, yet we know little about its wiring architecture: in the most-studied mammal (rat), only an estimated 10-30% of the long range circuit connections have been probed. The present Challenge Topic validates the growing consensus that it is time to close this gap by generating brainwide connectivity maps for model vertebrates. Over the last two years, we have organized several meetings involving the neuroanatomy community to gain in-depth understanding of the technical and scientific challenges of such a project. Based on this experience, we have designed and have begun to build and test an automated pipeline of experimental and computational techniques for achieving this goal. Our proposal is enabled by advances in automated wide-field slide scanning microscopy, decreasing data-storage costs, and established tract-tracing methods using injections of classical tracers and engineered viruses. The experimental plan can be summarized as follows. The mouse brain is divided into ~200 regions based on classical neuroanatomical and regional gene-expression data. For each region we inject one mouse with classical tracers and one mouse with viral tracers. From the injection site, the tracers are transported anterogradely to the area's projection targets and retrogradely to areas which project to the injection site. In this way, individual projections are revealed multiple times. In order to acquire this information, we will section the entire brain from each mouse and image the sections using an automated slide-scanning microscope. The resulting 2D slice-images will be combined in software to produce a 3D reconstructed brain image for each injection. Finally the 3D images from all of the individual injections will be combined by spatially registering them to the Allen Reference Atlas, ultimately generating a unified brainwide neural connectivity map. Generating the first unbiased, brainwide connectivity map in the mouse will have broad neuroscientific implications. The study of neural development, neural network modeling, evolutionary neuroanatomy, and associative and integrative brain function will benefit tremendously from finally having this landmark reference map to meaningfully constrain theories and aid in experimental design and interpretation of results. Relationships between gene expression and connectivity can be probed by analyzing the gene-expression maps generated by the Allen Institute in combination with the connectivity maps generated by this project. The baseline neural connectivity map generated in the present study will serve as a foundation for subsequently studying circuit polymorphisms across mutant mouse lines. The ability to objectively quantify alterations in connectivity in mouse models of neuropsychiatric disorders such as autism and schizophrenia will aid our understanding of their etiology and pathophysiology. Finally, our emphasis on open source software development, cost optimization and duplicability will result in an affordable, integrated instrument which other academic laboratories will be able to implement, so that this approach can be rapidly applied to a wide variety of neuroscientific problems. NARRATIVE The study of mouse models of neuropsychiatric disorders provides hope for the development of therapies for these burdensome illnesses, but progress has been slow due to the lack of knowledge about how the mouse brain is wired. This project aims to close this gap by generating the first brain-wide wiring diagram of mouse, automating techniques that are known to work but are labor-intensive. If successful, the project has the potential to fundamentally transform our understanding of the architecture of the normal and disordered brain.