Single-cell and target-specific resolution of multiple memories across the brain

项目总结/摘要 大量的研究使我们了解了神经元是如何协同工作的 在个体记忆的形成和提取过程中。虽然我们知道记忆是如何储存在 由于大脑区域的数量有限，我们还不知道多个记忆痕迹是如何存储在 全脑神经网络，以及它们的实时生理动力学，遗传景观， 优先布线。现在需要的是技术来弥合我们理解上的差距， 在神经元水平上的微观相互作用和宏观结构， 参与学习和记忆的网络。使用两个活动依赖标记系统的组合， 利用立即早期基因（IEG）Arc和c-fos，该提案的目的是解决以下关键需求： 获得多个记忆的映射，并提供大脑在行为环境中的动态状态， 性能和记忆表达。我们将首先利用行为分析和全脑成像， 提供了关于多个存储器（例如，积极和消极的记忆）被存储 以单细胞分辨率在全脑范围内进行。确定以下方面的异同 积极和消极记忆集合的群体和投射将被量化，并与 行为表现通过使用神经元建模开发的丹尼实验室。标记的细胞也将 被拉下来并测序，以描绘遗传景观区分积极和消极的， 回忆然后，我们将使用体内Ca 2+成像来解析实时动态（例如，Ca ~（2+）活性 它们参与积极和消极记忆的编码和提取。此外，我们将使用 光遗传学调节以在治疗期间以受试者内的方式操纵阳性或阴性系综 行为表现，以确定参与记忆表达的关键节点。最后，我们将使用病毒追踪 策略，以确定这些合奏如何在结构上连接大脑，从而提供一个连接 大脑中多重体验的图表。总之，综合分子生物学， 将利用免疫组织化学、网络建模、Ca 2+成像和光遗传学技术。因为大多数 研究已经将他们的分析缩小到单一的大脑结构，这些研究将扩大这一范围 通过分析介导多重记忆的全脑记忆痕迹，该组合系统 将产生一个个体记忆的全脑图谱，包括积极和消极的记忆， 细胞分辨率

PROJECT SUMMARY / ABSTRACT A tremendous amount of research has provided us with an understanding of how neurons work in concert during the formation and retrieval of individual memories. While we understand how memories are stored in a limited number of brain regions, we do not yet understand how multiple memory traces are stored across whole-brain neural networks, as well as their real-time physiological dynamics, genetic landscape, and preferential wiring. What is needed now is technology to bridge the gap in our understanding between microscopic interactions at the neuronal level and macroscopic structures that perform computations across networks involved in learning and memory. Using a combination of two activity-dependent tagging systems that utilize the immediate early genes (IEG) Arc and c-fos, the aim of this proposal is to address the critical need for obtaining a map of multiple memories and provide the dynamic states of the brain in the context of behavioral performance and memory expression. We will first utilize behavioral assays and whole-brain imaging to provide unprecedented insight on how multiple memories (e.g., positive and negative memories) are stored with single-cell resolution in a brain-wide manner. Identification of similarities and differences between populations and projections of positive and negative memory ensembles will be quantified and correlated with behavioral performance by using neuronal modeling developed in the Denny laboratory. Tagged cells will also be pulled down and sequenced to delineate the genetic landscape differentiating positive and negative memories. We will then use in vivo Ca2+ imaging to resolve the real-time dynamics (e.g., Ca2+ activity) of neural ensembles as they participate in positive and negative memory encoding and retrieval. Moreover, we will use optogenetic modulation to manipulate the positive or negative ensembles in a within-subject manner during behavioral performance to identify key nodes involved in memory expression. Finally, we will use viral tracing strategies to determine how these ensembles are structurally wired across brain, thereby providing a wiring diagram for multiple experiences in the brain. In summary, comprehensive molecular biology, immunohistochemistry, network modeling, Ca2+ imaging, and optogenetic techniques will be utilized. As most studies have narrowed their analyses to a single brain structure, these studies will expand this scope exponentially by analyzing whole-brain memory traces mediating multiple memories. This combinatory system will result in a whole-brain atlas for individual memories, including positive and negative memories, with single- cell resolution.