Computations of transcriptomic neuron types in cortex

皮层转录组神经元类型的计算

• 批准号: EP/Y028295/1
• 负责人: Kenneth Harris
• 金额: $ 269.67万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FY028295%2F1
• 关键词: Computations; transcriptomic; neuron; types; cortex

The cerebral cortex contains a rich diversity of neuronal types, particularly among inhibitory cells. Transcriptomic methods, which measure the expression of many genes simultaneously, have identified nearly 100 fine subtypes of cortical neuron. Understanding how these subtypes underlie cortical computation requires measuring the activity of large cortical populations in vivo, identifying each cell's transcriptomic subtype.We have developed a method to identify the transcriptomic subtypes of all cells in a population whose activity has been measured in vivo by 2-photon calcium imaging. We will use this together with tools such as 2-photon mesoscopy, cell-type-specific viruses and mathematical data analysis, to reveal for the first time how the cortex's cell types are coordinated during information processing. Our working hypothesis is that an animal's cognitive state controls the joint activity of inhibitory neurons, which in turn sculpt information coding in excitatory populations. We will test this hypothesis and characterize in detail of each cell type's role in the circuit.By recording during spontaneous behavior, we will ask if inhibitory population activity is constrained to a manifold reflecting fixed interactions between inhibitory subtypes, and how this inhibitory activity correlates with ongoing behavior and sensory coding in excitatory neurons. By recording transcriptomically-identified populations while mice perform a behavioral task, we will reveal how inhibitory activity and excitatory coding vary according to cognitive context such as stimulus expectation and omission, engagement, impulsiveness, and reward. By combining cell-type-specific optogenetics with transcriptomically identified recordings, we will reveal the causal role of each inhibitory subclass and of neuromodulators. Together, these experiments will provide foundational information on how information is processed by the diverse cell types that make up cortical circuits.

大脑皮层包含丰富多样的神经元类型，特别是在抑制细胞中。转录组学方法可以同时测量许多基因的表达，已经识别出近100种皮质神经元的精细亚型。了解这些亚型是如何基于皮质计算需要测量在体内的大型皮质人口的活动，确定每个细胞的转录组subtype.We已经开发出一种方法来确定所有细胞的转录组亚型的人口中的活动已被测量在体内的2-光子钙成像。我们将利用这一点，结合双光子介观、细胞类型特异性病毒和数学数据分析等工具，首次揭示大脑皮层的细胞类型在信息处理过程中是如何协调的。我们的工作假设是，动物的认知状态控制着抑制性神经元的联合活动，而抑制性神经元反过来又塑造了兴奋性群体中的信息编码。我们将测试这一假设，并详细描述每种细胞类型在回路中的作用。通过记录自发行为，我们将询问抑制性群体活动是否被限制在反映抑制亚型之间固定相互作用的流形上，以及这种抑制性活动如何与兴奋性神经元中的持续行为和感觉编码相关。通过记录转录组识别的种群，而小鼠执行行为任务，我们将揭示如何抑制活动和兴奋性编码根据认知环境，如刺激的预期和遗漏，参与，冲动和奖励。通过将细胞类型特异性光遗传学与转录组学鉴定的记录相结合，我们将揭示每个抑制性亚类和神经调质的因果作用。总之，这些实验将提供关于构成皮层回路的不同细胞类型如何处理信息的基础信息。