Circuit-based models of neuronal variability in mouse V1

项目摘要 了解神经元群体的协调活动是神经科学的核心目标。在没有电路 我们是否比初级视觉皮层（V1）更接近理解这一点。然而，尽管经过几十年的研究， 对V1的理解通常仅限于对特殊刺激类别的反应，我们缺乏一种理论， 将刺激概括为包括对自然图像和电影的反应。我们的团队提案提出了一个 该计划大大拓宽了我们对V1电路的理解范围，并深入关注 抑制性神经元阵列。这些数据将推动一个协调一致的建模工作，参与一个良性的背部- 以及与实验项目，其中所有项目的共同目标是建立一个新的电路为基础的理论， 视觉处理 皮层内部产生的变异性是其循环回路的反映。然而，大多数过去的国防部- eling的工作集中在贫困的电路，崩溃的所有来源的抑制，以源于一个 抑制性神经元的中央池。这个项目将扩展经典理论的复发皮层网络， 在小鼠V1中发现的抑制性神经元的丰富多样性。这将包括连接配置文件， 真实的空间和基于特征的布线，兴奋性和不同的抑制性神经元之间。我们的新理论 提出捕获内部产生的群体范围的共享可变性如何取决于电路结构， 并且可以通过与自然输入相关联的丰富的空间和动态刺激统计来操纵。在 特别是，我们将讨论可变性的有效维度，这是当代理论所关注的。 一种无法解释的失落高分辨率钙成像数据和光遗传学扰动是研究的重点。 我们的实验项目提供了一个独特的机会来测试和扩展我们的理论，因为他们出现。最后， 我们的建模工作将集中在波动如何塑造神经元的传输特性。这将作为 一个平台，在我们的同伴理论项目中建立射击率模型。总之，我们的项目提出了一个 一个雄心勃勃的计划，以建立一个理论的神经元的变异性-这是一个关键的第一步，在建立一个基于电路的 啮齿动物视觉加工理论V1.

Project Summary Understanding the coordinated activity of populations of neurons is a central goal in neuroscience. In no circuit are we closer to understanding this than in primary visual cortex (V1). However, despite decades of study our understanding of V1 is often restricted to responses to only special classes of stimuli, and we lack a theory that generalizes over stimuli to include the responses to natural images and movies. Our team proposal puts forth a program to dramatically broaden the scope of our understanding of V1 circuitry, with a deep focus on the vast array of inhibitory neurons. These data will drive a concerted modeling effort that engages in a virtuous back- and-forth with experimental projects where all projects share the goal of building a new circuit-based theory of visual processing. Internally generated variability in the cortex is a reflection of its recurrent circuitry. However, most past mod- eling work has focused on impoverished circuits that collapse all sources of inhibition into stemming from one central pool of inhibitory neurons. This project will extend classic theories of recurrent cortical networks to include the rich diversity of inhibitory neurons that are found in mouse V1. This will include connectivity profiles that cap- ture spatial and featured-based wiring, both between excitatory and diverse inhibitory neurons. Our new theory proposes to capture how internally generated population-wide shared variability depends upon circuit structure, and can be manipulated by the rich spatial and dynamic stimulus statistics associated with natural inputs. In particular, we will discuss the effective dimensionality of variability, something that contemporary theories are at a loss to explain. The high resolution calcium imaging data and optogenetic perturbations that are the focus of our experimental projects offer a unique opportunity to test and expand on our theories as they emerge. Finally, our modeling efforts will focus on how fluctuations shape the transfer properties of neurons. This will serve as a platform to ground the firing rate models in our companion theory project. In sum, our project puts forth an ambitious program to build a theory of neuronal variability — this is a critical first step in building a circuit-based theory of visual processing in rodent V1.