Watching a vertebrate brain learn and behave in a virtual environment

描述 摘要： 为了研究导航、学习和记忆的神经基础，重要的是 同时记录参与执行的大量神经元的活动 行为。这在清醒的、自由移动的准备和 用于促进记录的麻醉药和麻药经常改变或废除相关的 行为。我建议建立一个虚构的游泳实验，让瘫痪的斑马鱼幼体 在虚拟环境中导航并与其交互。提供给我们的感觉反馈 这些动物将包括通过视频投影屏幕提供的视觉提示和提供的水流 由计算机控制的阀门系统。鱼被允许通过活动来控制这些刺激 在它们的运动神经元中，由一组外部吸合电极记录。这一安排 使被固定的鱼完全可以通过 他们运动神经元的活动。 作为第一步，我们将把这种分析与双光子激光扫描显微镜相结合，并允许 在所有神经元中表达遗传编码的钙指示物的转基因鱼类品系 在监测神经元活动的同时，在虚拟环境中导航。小巧的尺寸和 斑马鱼幼体的完美半透明，原则上不会对这些提供任何障碍或限制 记录，因此我们可以在这些过程中以单细胞分辨率访问整个大脑 行为任务。因此，我们可以独立地监控成百上千个 神经元就像动物一样在他们的虚拟世界中导航。 作为下一步，我们将实施动物必须进行的不同学习测试 在这个虚拟环境中执行。原则上，这将允许我们跟随神经的流动 在特定训练课程之前、期间和之后的单个动物中的信息。 产生的大量数据将使用自动化算法进行分析和提取 这些结果被用来勾勒出动物如何在神经中存储信息的潜在模型 网络，以便产生适应的行为。随后，我们可以应用特定的 使用基因编码的光学工具来激活和沉默目标子集的操作 来测试和发展这些新兴的理论。 该平台将提供前所未有的能力来跟踪和操纵大小规模的 作为先天和后天行为基础的活动模式。

DESCRIPTION Abstract: In order to study the neural basis of navigation, learning, and memory, it is important to simultaneously record the activity of large populations of neurons involved in execution of behavior. This has been difficult or impossible in awake, freely moving preparations and the anesthetics and paralytics used to facilitate recordings often alter or abolish the relevant behaviors. I propose to establish a fictive swimming assay that allows paralyzed larval zebrafish to navigate through- and interact with a virtual environment. The sensory feedback provided to the animals will consist of visual cues through video projection screens and water flow provided by a computer controlled valve system. The fish are allowed to control these stimuli via activity in their motor-neurons recorded by a set of external suction electrodes. This arrangement makes it possible for immobilized fish to navigate a virtual environment entirely through power of activity in their motorneurons. As a first step we will combine this assay with 2-photon laser-scanning microscopy and allow transgenic fish lines that express genetically encoded calcium indicators in all neurons to navigate through virtual environments while neuronal activity is monitored. The small size and perfect translucence of the larval zebrafish provides in principle no barrier or restriction to these recordings and thus we have access to the whole brain at single cell resolution during these behavioral tasks. We can thus independently monitor the activities of hundreds or thousands of neurons as animals navigate their virtual worlds. As a subsequent step we will implement different learning assays that the animals have to execute in this virtual environment. In principle this will allow us to follow the flow of neural information in a single animal, before, during and after specific training sessions. The large volumes of resulting data will be analyzed and distilled with automated algorithms and the results used to sketch out potential models of how animals store information in neural networks in order to generate adapted behaviors. Subsequently, we can apply specific manipulations using genetically encoded optic tools for activating and silencing targeted subsets of neurons to test and develop these emerging theories. This platform will offer an unprecedented ability to track and manipulate the large- and smallscale activity patterns that underlie innate as well as learned behaviors.