Department of Physiology & Biophysics, and.
Neuroscience Graduate Program, University of Colorado Denver, University of Colorado School of Medicine, Aurora, Colorado 80045.
J Neurosci. 2019 Feb 13;39(7):1169-1181. doi: 10.1523/JNEUROSCI.1448-18.2018. Epub 2018 Dec 26.
Cerebellar granule cells (GrCs) constitute over half of all neurons in the vertebrate brain and are proposed to decorrelate convergent mossy fiber (MF) inputs in service of learning. Interneurons within the GrC layer, Golgi cells (GoCs), are the primary inhibitors of this vast population and therefore play a major role in influencing the computations performed within the layer. Despite this central function for GoCs, few studies have directly examined how GoCs integrate inputs from specific afferents, which vary in density to regulate GrC population activity. We used a variety of methods in mice of either sex to study feedforward inhibition recruited by identified MFs, focusing on features that would influence integration by GrCs. Comprehensive 3D reconstruction and quantification of GoC axonal boutons revealed tightly clustered boutons that focus feedforward inhibition in the neighborhood of GoC somata. Acute whole-cell patch-clamp recordings from GrCs in brain slices showed that, despite high GoC bouton density, fast phasic inhibition was very sparse relative to slow spillover mediated inhibition. Dynamic-clamp simulating inhibition combined with optogenetic MF activation at moderate rates supported a predominant role of slow spillover mediated inhibition in reducing GrC activity. Whole-cell recordings from GoCs revealed a role for the density of active MFs in preferentially driving them. Thus, our data provide empirical confirmation of predicted rules by which MFs activate GoCs to regulate GrC activity levels. A unifying framework in neural circuit analysis is identifying circuit motifs that subserve common computations. Wide-field inhibitory interneurons globally inhibit neighbors and have been studied extensively in the insect olfactory system and proposed to serve pattern separation functions. Cerebellar Golgi cells (GoCs), a type of mammalian wide-field inhibitory interneuron observed in the granule cell layer, are well suited to perform normalization or pattern separation functions, but the relationship between spatial characteristics of input patterns to GoC-mediated inhibition has received limited attention. This study provides unprecedented quantitative structural details of GoCs and identifies a role for population input activity levels in recruiting inhibition using electrophysiology and optogenetics.
小脑颗粒细胞(GrC)构成了脊椎动物大脑中超过一半的神经元,它们被提出用于去相关会聚的苔藓纤维(MF)输入,以服务于学习。小脑颗粒细胞层内的中间神经元,高尔基细胞(GoC),是这个庞大群体的主要抑制物,因此在影响层内进行的计算中起着主要作用。尽管 GoC 具有这种核心功能,但很少有研究直接研究 GoC 如何整合来自特定传入神经的输入,这些传入神经的密度不同,可调节 GrC 群体的活动。我们使用各种方法研究了雄性和雌性小鼠的前馈抑制作用,这些方法是通过鉴定的 MF 招募的,重点是影响 GrC 整合的特征。对 GoC 轴突末梢的全面 3D 重建和定量分析显示,紧密聚集的末梢将前馈抑制集中在 GoC 体的附近。脑切片中 GrC 的急性全细胞膜片钳记录显示,尽管 GoC 末梢密度很高,但与慢溢出介导的抑制相比,快速相位抑制非常稀疏。模拟抑制的动态钳位与适度速率的光遗传 MF 激活相结合,支持慢溢出介导的抑制在降低 GrC 活性方面的主要作用。从 GoC 进行的全细胞膜片钳记录揭示了活跃 MF 的密度在优先驱动它们方面的作用。因此,我们的数据为 MF 激活 GoC 以调节 GrC 活性水平的预测规则提供了经验证据。神经回路分析中的一个统一框架是确定执行常见计算的回路基元。宽场抑制性中间神经元全局抑制邻居,并在昆虫嗅觉系统中得到了广泛研究,并被提出用于分离功能。小脑高尔基细胞(GoC),一种在颗粒细胞层中观察到的哺乳动物宽场抑制性中间神经元,非常适合执行归一化或模式分离功能,但输入模式到 GoC 介导的抑制的空间特征之间的关系受到的关注有限。这项研究提供了前所未有的 GoC 定量结构细节,并使用电生理学和光遗传学确定了群体输入活动水平在募集抑制方面的作用。