Correlated light and ultrastructural imaging of learning-related synaptic plasticity

学习包括重组大脑中神经元之间复杂的连接方案。 这种重新连接的关键是形成新的突触连接，因此对支配规则的研究 突触的形成仍然是神经科学的中心焦点。在过去的十年里，它变得越来越多 明确突触遵循特定的空间组织原则，这样在功能上相似的突触往往 在树枝上“聚集”。这种空间模式可能提供了计算优势，使神经元能够 有效地构建其输入曲目的表示形式。然而，目前尚不清楚这是否是新的，以及如何新的 在学习过程中形成的突触有助于这种突触的功能性聚集。我们建议使用 结合尖端成像技术研究新的脊柱形成-及其潜力 集群模式-过度学习，将局部突触活动特征的详细描述与 对周围组织的细胞和亚细胞解剖结构的深入研究。我们将在第一时间完成这项工作 对学习运动技能超过2周的小鼠进行体内树突棘的纵向功能成像， 然后是在体内成像的体积的3D电子显微镜，用于高分辨率重建 相关结构，包括那些没有标记用于活体成像的结构。这种方法将揭示出两者如何 神经元树突的结构和功能环境与新突触的形成有关。通过 聚焦于新的突触，这些突触的活动与同一区域内其他邻近突触的活动相一致 树突，我们将详细描述学习过程中的棘突发生如何对功能 突触聚集。此外，通过重建附近的细胞结构，我们将提供到目前为止 无法获得的细节，例如这种功能相关的突触是否共享相同的轴突输入。最后， 通过使用一个具有良好特征的学习模型，这项工作还将允许对新的 脊椎和它们形成的簇与习得行为的特定特征有关。实验性的 所建立的范例将广泛应用于神经回路的研究。 潜藏在其他类型的学习和行为中。影响神经元的神经系统疾病的流行情况 互联互通凸显了这一追求的重要性。

Learning involves the reorganization of the complex connectivity schemes between neurons in the brain. Critical to this re-wiring is the formation of new synaptic connections, and thus the study of the rules governing synapse formation remains a central focus of neuroscience. Over the past decade, it has become increasingly clear that synapses follow specific spatial organizational principles, such that functionally similar synapses tend to “cluster” on dendrites. This spatial patterning likely affords computational advantages that allow neurons to efficiently construct representations of their input repertoire. However, it is unknown whether and how new synapses that form during learning contribute to such functional clustering of synapses. We propose to use a combination of cutting-edge imaging techniques to investigate new spine formation - and their potential clustering patterns - over learning, integrating a detailed description of the local synaptic activity profiles with a deep interrogation of the cellular and subcellular anatomy of the surrounding tissue. We will do this by first applying longitudinal functional imaging of dendritic spines in vivo in mice learning a motor skill over 2 weeks, followed by 3D electron microscopy of the volume imaged in vivo for a high-resolution reconstruction of relevant structures, including those that are not labeled for in vivo imaging. This approach will reveal how both the structural and functional environment of neuronal dendrites relates to the formation of new synapses. By focusing on new synapses whose activity becomes coherent with other nearby synapses on the same dendrite, we will provide a thorough description of how spinogenesis during learning contributes to functional synaptic clustering. Furthermore, by reconstructing the nearby cellular structures, we will provide heretofore inaccessible details, such as whether such functionally related synapses share the same axonal inputs. Finally, by using a well characterized model of learning, this work will also allow a quantitative description of how new spines and the clusters that they form relate to specific features of a learned behavior. The experimental paradigm established in the proposed project will be widely applicable to the studies of neural circuits underlying other types of learning and behavior. The prevalence of neurological diseases affecting neuronal connectivity highlights the importance this pursuit.