Developing Molecular and Computational Tools to Enable Visualization of Synaptic Plasticity In Vivo

项目摘要 开发新的方法和分析工具来解决目前无法克服的实验问题 对神经科学的未来至关重要。虽然双光子显微镜和活动传感器的最新进展 已经彻底改变了我们对行为的细胞和电路基础的理解，仍然存在许多障碍， 排除了在体内充分探索这些过程的分子基础。这是一个重要的问题，因为 调节突触强度被认为是学习和记忆等高级大脑功能的基础，而 突触退化在许多神经病理学中都能观察到。尽管突触的意义很明显 交流，一项关于突触在大脑中的分布和变化的大规模分析 没有进行学习，主要是由于极其复杂的性质引起的技术困难 突触网络。在这里，我们提出了一套突破这些障碍的新方法。我们的 利用基于CRISPR的体内双光子标记内源性突触蛋白的新方法 显微镜在行为动物身上显示荧光标记的突触，以及基于深度学习的自动 突触检测。使用这些微创方法，我们将能够纵向追踪 数百万个个体突触的强度在学习过程中会发生变化。通过开发和实施新战略 为了自动检测和跟踪整个大脑区域的大量突触，这一开创性的方法 有可能为我们提供一个前所未有的关于动物行为中突触的视角，使新的 关于动态调节突触强度如何编码学习和记忆的发现。

Project Summary Developing new methodological and analytical tools to address currently insurmountable experimental questions is crucial to the future of neuroscience. While recent advances in two-photon microscopy and activity sensors have revolutionized our understanding of the cellular and circuit basis of behavior, many barriers still exist that preclude fully exploring the molecular basis of these processes in vivo. This is an important question, as modulating synaptic strength is thought to underlie higher brain functions such as learning and memory, whereas synaptic degradation is observed in many neurological pathologies. Despite the clear significance of synaptic communication, a large-scale analysis of how synapses across the brain are distributed and change during learning has not been performed, mainly due to technical difficulties arising from the immensely complex nature of synaptic networks. Here, we present a suite of novel methodologies that breaks through these barriers. Our novel approach leverages CRISPR-based labeling of endogenous synaptic proteins, in vivo two-photon microscopy to visualize fluorescently tagged synapses in behaving animals, and deep-learning-based automatic synapse detection. Using these minimally invasive methods, we will be able to longitudinally track how the strength of millions of individual synapses change during learning. By developing and enabling new strategies to automatically detect and track vast numbers of synapses across entire brain regions, this pioneering approach has the potential to provide us with an unprecedented view of synapses in behaving animals, enabling new discoveries regarding how dynamic regulation of synaptic strength encodes learning and memory.