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

点击翻译按钮获取中文摘要

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.