Parietal cortex networks for sensorimotor processing during navigation

 描述(申请人提供)：空间导航过程中的感觉运动处理需要大量脑区之间的交流。后顶叶皮质(PPC)是安排这种交流的重要接口。领先的模型基于灵长类动物和最近在啮齿类动物中的广泛研究，假设PPC将感觉和认知信号(如那些引导导航的信号)与驱动即将到来的运动动作的决定和计划联系起来。因此，预计PPC将接收感官信号作为输入，并发送与导航决策和计划有关的信号。尽管PPC功能的所有模型都依赖于PPC与多个其他区域之间的相互作用，但目前人们对PPC接收到什么输入信号以及PPC如何将输出信息路由到目标区域知之甚少，这在很大程度上是由于技术限制。在这里，我们将开发和 实施新的方法来直接测量PPC的输入和输出通道中包含的信号。我们的方法将是在鼠标中使用光学成像和解剖跟踪技术，并结合虚拟现实环境中的行为任务。在第一个目标中，我们将研究PPC如何在导航决策任务中发送与感觉和运动事件相关的信息。我们将测试PPC是否有选择地将不同类型的信息路由到不同的目标区域，或者PPC是否一般地传输信息以建立广泛分布的网络。在第二个目标中，我们将测量PPC从听觉皮质接收的输入信号。我们将测试这些信号是否选择性地编码 感知世界，如空间信息，以及如何根据行为相关性和行为状态调制输入到PPC的信号。总之，这项工作将促进我们对多区域网络中用于感觉运动处理的信息传输的理解，这对几乎所有复杂的行为任务都是必不可少的。

 DESCRIPTION (provided by applicant): Sensorimotor processing during spatial navigation requires the communication between a large number of brain areas. The posterior parietal cortex (PPC) is a crucial interface for arranging this communication. Leading models, based on extensive work in primates and more recently in rodents, hypothesize that the PPC links sensory and cognitive signals, such as those that guide navigation, with the decisions and plans that drive upcoming locomotor actions. The PPC is therefore predicted to receive sensory signals as inputs and to transmit signals regarding navigation decisions and plans. Although all models of PPC function rely on the interaction between the PPC and multiple other regions, it is currently poorly understood what input signals the PPC receives and how the PPC routes output information to target regions, in large part due to technical limitations. Here we will develop and implement new approaches to measure directly the signals contained in the PPC's input and output channels. Our approach will be to use optical imaging and anatomical tracing technologies in the mouse in combination with behavioral tasks in virtual reality environments. In a first aim, we will examine how the PPC routes information related to sensory and motor events during navigation decision tasks. We will test if the PPC selectively routes different types of information to different target regions or if the PPC transmits information generally to establish widely distributed network. In a second aim, we will measure the input signals the PPC receives from the auditory cortex. We will test if these signals selectively encode specific features of the sensory world, such as spatial information, and how the input signals to the PPC are modulated depending on behavioral relevance and behavioral state. Together this work will advance our understanding of information transfer in a multi-region network for sensorimotor processing, which is essential for nearly all complex behavioral tasks.