To deconstruct the architecture and function of brain circuits, it is necessary to generate maps of neuronal connectivity and activity on a whole-brain scale. New methods now enable large-scale mapping of the mouse brain at cellular and subcellular resolution. We developed a framework to automatically annotate, analyze, visualize and easily share whole-brain data at cellular resolution, based on a scale-invariant, interactive mouse brain atlas. This framework enables connectivity and mapping projects in individual laboratories and across imaging platforms, as well as multiplexed quantitative information on the molecular identity of single neurons. As a proof of concept, we generated a comparative connectivity map of five major neuron types in the corticostriatal circuit, as well as an activity-based map to identify hubs mediating the behavioral effects of cocaine. Thus, this computational framework provides the necessary tools to generate brain maps that integrate data from connectivity, neuron identity and function.

中文翻译：

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细胞分辨率全脑图谱的交互式框架。

为了解构大脑回路的结构和功能，有必要在全脑范围内生成神经元连接和活动的图谱。新方法现在能够以细胞和亚细胞分辨率大规模绘制小鼠大脑图谱。我们开发了一个框架，基于尺度不变的交互式小鼠大脑图谱，以细胞分辨率自动注释、分析、可视化和轻松共享全脑数据。该框架支持各个实验室和跨成像平台的连接和绘图项目，以及有关单个神经元分子身份的多重定量信息。作为概念证明，我们生成了皮质纹状体回路中五种主要神经元类型的比较连接图，以及基于活动的图来识别介导可卡因行为效应的中枢。因此，该计算框架提供了生成脑图所需的工具，该图集成了连接性、神经元身份和功能的数据。