The Nanoscale Connectome of the Cochlear Nucleus

耳蜗核是中枢神经系统处理听觉信息的门户， 哺乳动物有人建议在CN中建立并行处理通道，这些通道形成 这是在听觉系统的更高位置进行进一步计算的基础。尽管研究了几十年， CN小区类型的列举是不完整的，并且CN电路仅被表面地描述。在 神经科学一般来说，神经元的分类和命名主要依赖于定性， 基于人类观察能力的方法。我们已经实施，在某些情况下， 开发了用于标记、分割和分类的新型高通量和无偏技术 神经元在3D中，从大规模电子显微镜图像体积产生。我们建议提供一个 小鼠CN的纳米级图谱或连接体，包括计数和定位的细胞类型及其 突触连接这种努力是无偏的，因为所有神经元都将被采样。为了实现这一目标， 我们汇集了四种并行的神经元分类组织分析模式：形态，连接， 分子身份和功能。我们建议，连通性分析将定义长期提出的并行 处理电路将使用识别的细胞类型的真实生物物理模型进行功能测试。 值得注意的是，耳蜗核包含无定形和分层的细胞组织，其作为耳蜗的一部分。 其他脑区的模板通过研究这个感觉中枢的基本结构， 将建立神经计算的原理和结构和功能表型的方法， 将适用于其他大脑区域，无论其特定的神经结构如何。

The cochlear nucleus is the gateway for central nervous system processing of auditory information in mammals. It has been proposed that parallel processing channels are set up in the CN, and these form the basis for further computation at higher stations of the auditory system. Despite decades of study, enumeration of CN cell types is incomplete and CN circuitry is described only superficially. In neuroscience generally, classification and naming of neurons has relied primarily upon qualitative approaches based upon human observational capabilities. We have implemented and in some cases developed novel high-throughput and unbiased techniques for labeling, segmenting and classifying neurons in 3D, generated from large-scale electron microscopy image volumes. We propose to deliver a nanoscale map, or connectome, of the mouse CN with enumerated and localized cell types and their synaptic connections. This effort is unbiased because all neurons will be sampled. To achieve this goal, we bring together four parallel modes of tissue analysis for neuron classification: morphology, connectivity, molecular identity and function. We propose that connectivity analysis will define long-proposed parallel processing circuits that will be tested functionally using realistic biophysical models of identified cell types. Notably, the cochlear nucleus contains both amorphous and layered organizations of cells, which serve as templates for all other brain regions. By investigating the fundamental structure of this sensory center, we will establish principles of neural computation and methods for structural and functional phenotyping that will apply to other brain regions regardless of their particular neural architecture.