Computations of transcriptomic neuron types in cortex

大脑皮层含有丰富多样的神经元类型，特别是在抑制细胞之间。转录切割方法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。为了了解这些亚型如何构成皮质计算的基础，需要测量体内大脑皮层群体的活动，确定每个细胞的转录亚型。我们已经开发了一种方法来识别通过双光子钙成像在体内测量其活动的群体中所有细胞的转录亚型。我们将与双光子介镜、特定细胞类型的病毒和数学数据分析等工具一起使用，首次揭示大脑皮质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在兴奋性群体中塑造信息编码。我们将测试这一假说，并详细描述每种细胞类型在回路中的作用。通过在自发行为中的记录，我们将询问抑制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，以及这种抑制活动如何与兴奋性神经元中正在进行的行为和感觉编码相关。通过记录小鼠执行行为任务时转录识别的种群，我们将揭示抑制活动和兴奋性编码如何随着认知环境的变化而变化，如刺激预期和遗漏、参与、冲动和奖励。通过结合特定细胞类型的光遗传学和转录鉴定的记录，我们将揭示每个抑制亚类和神经调节剂的因果作用。总之，这些实验将提供组成大脑皮层回路的不同类型的细胞如何处理信息的基础信息。

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.