Tools and approaches for functional connectomics of dense neuropils

项目总结 神经系统中的许多计算都是在大范围内单个神经突起的水平上进行的 广泛分枝的乔木(即亚细胞加工)。大多数神经突起在密集的环境中运行 神经鞘，其中不同类型的细胞突起紧密堆积，数量丰富 互联互通。为了了解亚细胞过程，我们需要测量神经突起对 生理刺激，并将它们与突触输入的局部模式联系起来。勾勒出 神经毛球的功能结构并揭示其连通性的逻辑，我们需要 在高密度下描述神经突起反应和突触模式。轴突反应可以是 通过双光子成像观察到，突触输入可以在连续切片上重建 电子显微镜(SSEM)。许多技术障碍排除了将 这些技术(即功能连接学)用来研究密集的亚细胞加工 神经枕头。在这里，我们开发新的工具和方法来克服这些障碍。在目标1中，我们 开发用于多光谱双光子钙成像的遗传、病毒和计算工具 以及信号分离，以实现神经毛的密集功能表征。在目标2中，我们 设计了一种将双光子成像和SSEM(即多模式成像)相结合的新策略， 建立了一种用于分析局部突触连接模式的高通量SSEM方法 在更大规模的电路布线(即，多分辨率成像)的背景下。我们用我们的预付款 研究视网膜中间神经元的一种不同类型的无长突细胞。更多的神经纤维 50种AC类型在视网膜内部密集的神经纤维中提取显著的视觉信息。我们会 获取完整的ACS功能连接数据集。这个数据集，它将被 将形成未来R01应用程序的基础，以研究 急性冠脉综合征的亚细胞处理、AC神经纤维的功能结构及其逻辑 连通性。

PROJECT SUMMARY Many computations in the nervous system occur at the level of individual neurites within large extensively branched arbors (i.e., subcellular processing). Most neurites operate in dense neuropils, in which processes of diverse cell types are tightly packed and abundantly interconnected. To understand subcellular processing, we need to measure neurite responses to physiological stimuli and relate them to local patterns of synaptic inputs. To delineate the functional architecture of neuropils and reveal the logic of their connectivity, we need to characterize neurite responses and synapse patterns at high density. Neurite responses can be observed by two-photon imaging, and synaptic inputs can be reconstructed in serial-section electron microscopy (ssEM). A number of technical obstacles have precluded the combination of these techniques (i.e., functional connectomics) to study subcellular processing in dense neuropils. Here, we develop new tools and approaches to overcome these obstacles. In Aim 1, we develop genetic, viral, and computational tools for multispectral two-photon calcium imaging and signal demixing to enable dense functional characterization of neuropils. In Aim 2, we devise a novel strategy for combining two-photon imaging and ssEM (i.e., multimodal imaging), and establish a high-throughput ssEM method for analyzing local synaptic connectivity patterns in the context of larger-scale circuit wiring (i.e., multiresolution imaging). We use our advances to study amacrine cells (ACs), a diverse class of retinal interneurons. The neurites of more than 50 AC types extract salient visual information in a dense neuropil the inner retina. We will acquire a complete functional connectomic dataset of ACs. This dataset, which will be made publicly available, will form the basis of a future R01 application to study the mechanisms of subcellular processing in ACs, the functional architecture of the AC neuropil, and the logic of its connectivity.