长程连接是信息在大脑中流动分配、被逐级处理的通道。确定信息流动的通道和通道中传递的信息关联性，是了解神经环路结构与功能的关系的基础。神经元功能特性和长程连接模式存在个体差异，已知的长程连接中可能存在多种信息分流规律。我们的前期工作证实了在小鼠的初级视觉皮层的2/3层细胞中，共同存在这“一对一”和“一对多”的投射模式，后者和同时包含了“随机性一对多”和“有序性一对多”的模式。但是，这样的信息分流模式分别对应分流哪中类型的视觉信息却并不清楚。同时一个神经元的输出的信息是由其输入信息决定的，但是关于一个神经元的输入网络和输出网络的关系我们却知之甚少。在本项目中，我们将筛选V1中具有代表性功能特征的单个神经元，进行正向和逆向标记，利用全脑成像平台，重建以单个神经元为核心的输入和输出神经网络结构。通过比较神经元的功能特征与输入输出网络结构的关系，揭示视觉信息的分流模式和在其中流动的信息内容之间的关系

Long-range connection dictates how information flows between brain areas. Correlating the information and the information transfer pathway is essential to understand how the neuronal network structure determines the brain function. As neighboring neurons within the same brain area often exhibit broad heterogeneity in both projection patterns and function properties, information can be distributed in different ways when it flows through an identified circuit structure. We have mapped the basic logic of information transfer in mouse primary visual cortex by high-throughput single-cell anatomy methods. We confirm the existence of dedicated neurons innervating single cortical areas, we find these are the minority, and instead most V1 neurons broadcast information to multiple cortical targets. The projection of broadcasting neurons can be either random or organized. However, the type of information distributed via each projection model was largely unknown. At the meanwhile, the output information of a neuron is determined by its inputs, but we know very little about the relationship of input and output network structure of individual neurons. Here, we will selectively label V1 neurons with specific functional properties, and reconstruct its axonal structure and its input neuronal population in a whole-brain 3D model. This will enable us to uncover how the sophisticate computation is carried out in our brain network.