BRAIN CONNECTS: The center for Large-scale Imaging of Neural Circuits (LINC)

项目摘要：该项目将开发和验证一套全面的新技术工具， 成像轴突投影跨尺度，并将部署这一工具集映射一个复杂的系统皮质， 猕猴和人类大脑皮层下的投射。我们将结合联合收割机的互补优势， 三种创新的显微技术第一，偏振敏感光学相干断层扫描（PS-OCT） 将提供无标记的，在微观束尺度上的轴突方向的未失真成像， 我们可以跟踪大脑中的神经束，而不需要轴突分割。第二，整体安装灯- 透明和免疫标记切片的薄片显微镜（LSM）将使我们能够在亚显微镜下成像纤维束。 微米尺度，分辨单个轴突。第三，分层相衬断层扫描（HiP-CT）将使我们 对轴突及其微环境进行成像，范围从几微米到亚微米， 微米。我们将扩大这三种显微镜技术，以成像大脑的一个大的子体积（高达 大脑半球的三分之二），包含运动、前运动和前额叶皮质的皮质下投射。 在猕猴的大脑中，荧光示踪剂注射将允许直接验证我们的新显微镜 技术.结合广泛收集的先前示踪剂注射，猕猴数据还将 提供皮质-皮质下束中纤维的地形组织规则，然后我们将使用这些规则来 在人脑中验证我们的新型显微技术。在猕猴和人类标本中，我们将 还收集广泛的，尖端的，全脑扩散MRI数据，这将提供连接到非侵入性 神经成像我们的项目产生的前所未有的数据集将使研究发现在两个用途 例在第一个用例中，我们将注释运动、前运动和前额叶皮层到 丘脑底核（subthalamic nucleus，简称TH）。我们将使用它们来推进我们对与临床相关的电路的理解。 在四种疾病的改善，在邻近的分区的脑深部电刺激治疗， 肌张力障碍、图雷特综合征、帕金森病和强迫症。在第二 用例，我们将研究从轴突方向和获得的微观结构特征的映射 从显微镜数据到在同一大脑中获得的dMRI信号。除了前所未有的 数据集和上述两个用例，该项目将生成最先进的管道， 处理、共配准、轴突分割、纤维束成像和量化，跨越 获得的数据。我们将开发一个新的平台，用于共享显微镜，示踪剂和MRI数据， 研究社区。这将远远超出静态数据存储库，允许用户与数据进行交互 并提供一个“验证引擎”，用于根据黄金标准测试神经成像软件工具 本项目收集的尸检数据。如果成功，该项目将产生一个可扩展和验证的 连接解剖学成像工具集，与其在人类疾病研究中的应用有直接联系。

Project summary: This project will develop and validate a comprehensive toolset of novel technologies for imaging axonal projections across scales, and will deploy this toolset to map a complex system of cortico- subcortical projections in the macaque and human brain. We will combine the complementary strengths of three innovative microscopy techniques. First, polarization-sensitive optical coherence tomography (PS-OCT) will provide label-free, undistorted imaging of axonal orientations at the scale of microscopic fascicles, allowing us to follow fascicles across the brain without the need for axon segmentation. Second, whole-mount light- sheet microscopy (LSM) of cleared and immunolabeled sections will allow us to image fascicles at the sub- micron scale, resolving individual axons. Third, hierarchical phase-contrast tomography (HiP-CT) will allow us to image both the axons and their micro-environment, at a range of scales from a few microns down to sub- micron. We will scale these three microscopy techniques up to image a large sub-volume of the brain (up to two thirds of a hemisphere) that contains subcortical projections of the motor, premotor, and prefrontal cortex. In the macaque brains, fluorescent tracer injections will allow direct validation of our novel microscopy techniques. In combination with an extensive collection of prior tracer injections, the macaque data will also provide the topographic organizational rules of fibers in cortico-subcortical bundles, which we will then use to validate our novel microscopy techniques in human brains. In both macaque and human specimens, we will also collect extensive, cutting-edge, whole-brain diffusion MRI data, which will provide the link to non-invasive neuroimaging. The unprecedented datasets generated by our project will enable research discovery in two use cases. In the first use case, we will annotate projections of the motor, premotor, and prefrontal cortex to the subthalamic nucleus (STN). We will use them to advance our understanding of circuits associated with clinical improvements in four diseases that are treated with deep-brain stimulation in neighboring subzones of the STN: dystonia, Tourette’s syndrome, Parkinson’s disease, and obsessive-compulsive disorder. In the second use case, we will investigate the mapping from the axonal orientations and microstructural features obtained from the microscopy data to dMRI signals acquired in the same brains. In addition to the unprecedented datasets and the two use cases described above, this project will generate state-of-the-art pipelines for pre- processing, co-registration, axon segmentation, tractography, and quantification, across the scales spanned by the acquired data. We will develop a novel platform for sharing the microscopy, tracer, and MRI data with the research community. This will go well beyond a static data repository, allowing the user to interact with the data remotely and providing a “validation engine” for testing neuroimaging software tools against the gold standard post mortem data collected by this project. If successful, this project will generate a scalable and validated toolset for imaging connectional anatomy, with a direct link it to its applications in the study of human disease.