Intrinsic electrical properties shape feature selectivity in a novel retinal ganglion cell

新型视网膜神经节细胞的固有电特性形状特征选择性

• 批准号: 10011563
• 负责人: Sophia Rose Wienbar
• 金额: $ 4.55万
• 依托单位: NORTHWESTERN UNIVERSITY AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-01 至 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10011563
• 关键词: Action Potentials; Afferent Neurons; Biophysical Process; Biophysics; Brain; Cells; Classification; Closure by clamp; Data; Diagnosis; Fire - disasters; Goals; Immunohistochemistry; Individual; Injections; Inner Plexiform Layer; Ion Channel; Knowledge; Light; Light Cell; Measures; Morphology; Mus; Names; Neurons; Output; Pharmacology; Physiology; Population Heterogeneity; Process; Property; Research; Retina; Retinal Diseases; Retinal Ganglion Cells; Role; Sensory; Shapes; Signal Transduction; Synapses; Techniques; Testing; Typology; Visual Fields; Work; cell type; density; detector; differential expression; electrical property; experimental study; neuromechanism; neuronal excitability; novel; relating to nervous system; response; single-cell RNA sequencing; transcriptomics; visual process; voltage clamp; Action Potentials; Afferent Neurons; Biophysical Process; Biophysics; Brain; Cells; Classification; Closure by clamp; Data; Diagnosis; Fire - disasters; Goals; Immunohistochemistry; Individual; Injections; Inner Plexiform Layer; Ion Channel; Knowledge; Light; Light Cell; Measures; Morphology; Mus; Names; Neurons; Output; Pharmacology; Physiology; Population Heterogeneity; Process; Property; Research; Retina; Retinal Diseases; Retinal Ganglion Cells; Role; Sensory; Shapes; Signal Transduction; Synapses; Techniques; Testing; Typology; Visual Fields; Work; cell type; density; detector; differential expression; electrical property; experimental study; neuromechanism; neuronal excitability; novel; relating to nervous system; response; single-cell RNA sequencing; transcriptomics; visual process; voltage clamp

Project Summary Neurons use their intrinsic properties to integrate and perform computations on their synaptic inputs. When considering possible mechanisms of neural computations, two primary components to consider are the network that the neuron belongs to and the intrinsic properties of the neuron itself. My proposed project uses a newly discovered retinal ganglion cell (RGC) type in mouse retina to create a clean experimental separation between network and intrinsic aspects of a sensory computation. I have identified a novel retinal ganglion cell (RGC) type: the “Bursty Suppressed-by-Contrast” (bSbC). The primary functional classification for RGC types is whether the cells are ON, OFF, ON-OFF, or the more rarely described suppressed-by-contrast (SbC). SbC RGCs suppress their firing rate from baseline to both positive and negative contrast steps. I will determine how synaptic inputs and the intrinsic properties of the bSbC support this contrast response profile. I will compare the bSbC to a well-known RGC type called the OFF sustained alpha (OFFsA) because these two cell types, despite their key functional difference, have similar morphology and similar synaptic inputs. My preliminary data suggest that differences in intrinsic properties between these two RGC types are responsible for their different contrast response functions. I will compare the intrinsic properties of the bSbC and the OFFsA using a combination of current clamp and voltage clamp recordings, single cell RNAseq, immunohistochemistry, and pharmacology. This project demonstrates that two distinct cell types in similar synaptic networks can have markedly different outputs due to intrinsic properties. I will able to dissect the contribution of channel typology and density to a specific neuronal computation. This work will deepen our understanding of retinal circuitry and, more generally, it will provide a template for dissecting the relative contribution of intrinsic properties in all neural computation.

项目摘要 神经元使用其内在特性在其突触输入上集成和执行计算。什么时候 考虑到神经计算的可能机制，要考虑的两个主要组成部分是网络 神经元属于神经元本身的内在特性。我提议的项目使用了一个新的 发现的视网膜神经节细胞（RGC）在小鼠视网膜中类型 感官计算的网络和内在方面。 我已经确定了一种新型的视网膜神经节细胞（RGC）类型：“爆发抑制”（BSBC）。这 RGC类型的主要功能分类是单元格是打开，关闭，开关还是更少 描述了抑制作用（SBC）。 SBC RGC抑制其从基线到正的发射速率和 负造影剂步骤。我将确定BSBC的突触输入和固有特性如何支持这一点 对比响应概况。 我将将BSBC与称为OFF持续Alpha（OFFSA）的众所周知的RGC类型进行比较，因为这两个 细胞类型，其关键功能差异，具有相似的形态和相似的突触输入。我的 初步数据表明，这两种RGC类型之间的内在特性差异是负责的 对于它们的对比反应函数的不同。我将比较BSBC和OFFSA的内在特性 使用当前夹具和电压夹记录的组合，单细胞RNASEQ，免疫组织化学， 和药理学。 该项目表明，相似的突触网络中的两种不同的单元格类型可能明显不同 由于内在特性而引起的输出。我将能够剖析通道类型和密度的贡献 特定的神经元计算。这项工作将加深我们对视网膜电路的理解，更普遍地 它将提供一个模板，用于剖析所有神经计算中固有特性的相对贡献。