Mapping cerebellar granule cell function with novel genetic and optical tools

项目摘要/摘要 来自多个实验室在人类和动物模型中的最新证据支持颗粒细胞(GRC)的作用 小脑代表各种感觉、运动和内部信息的通路。古典主义理论 小脑功能认为，少量GRC(1%)中的活动编码特定的感觉运动背景。 然而，最近的群体水平的钙成像研究表明，GRC的群体编码 感觉和运动事件，以及奖励和运动准备等复杂属性。然而，这些研究缺乏 时间分辨率，以确定这些事件和GRC触发之间的特定关系。这两项研究的设计也 排除了直接确定是什么输入途径驱动了观察到的GRC活动模式。一个全面的 理解GRC执行的输入-输出转换将需要在解剖学上精确扰动的能力 具体的下降输入，同时以高时空精度密集记录活动的结果模式。 为了弥补这一方法论上的差距，我建议(1)从整体上发展一种用于遗传分析的穗计数方法。 通过调整电流传感器属性和创建钙的体内生物物理模型来编码指示器(GECI) 传感器GCaMP，(2)光遗传扰动新大脑皮层，将其功能输入映射到GRC，同时光学访问 整个小脑表面，以及(3)使用啮齿动物的行为任务来消除感觉、运动和内部状态的歧义 对颗粒细胞活动模式的贡献。完成这些目标将允许直接测试GRC是否真的 对他们的输入信号进行稀疏表示。我的目标也是提供迄今为止最全面的关于 推动GRC活动的输入的组成。

Project Summary/Abstract Recent evidence from multiple laboratories in both human and animal models supports a role for the granule cell (GrC) pathway of the cerebellum in representing a wide range of sensory, motor, and internal information. Classical theories of cerebellar function proposed that activity in a small number of GrCs (<1%) encodes a particular sensorimotor context. However, recent population level calcium imaging studies of GrC somata indicate that populations of GrCs encode sensory and motor events, and complex properties such as reward and motor preparation. However, these studies lacked the temporal resolution to identify specific relationships between those events and GrC firing. Both study designs also precluded direct determination of what input pathways drove the observed patterns of GrC activity. A comprehensive understanding of the input-output transform performed by GrCs will require the ability to precisely perturb anatomically specific descending inputs while densely recording the resultant patterns of activity with high spatiotemporal precision. To approach this set of methodological gaps, I propose to (1) holistically develop a spike-counting method for genetically encoded indicators (GECIs) by adjusting current sensor properties and creating a biophysical in vivo model of the calcium sensor GCaMP, (2) optogenetically perturb neocortex to map its functional inputs to GrCs while optically accessing the entire cerebellar surface, and (3) use a rodent behavioral task to disambiguate sensory, motor and internal-state contributions to granule cell activity patterns. Completion of these aims will allow a direct test of whether GrCs indeed make a sparse representation of their input signals. I also aim to provide the most comprehensive analysis to date on the makeup of the inputs that drive GrC activity.