Modeling V1 circuit dynamics

摘要神经科学的一个基本问题是了解大脑皮层回路的运作。 尽管不同物种和地区有许多不同，但所有大脑皮层回路的基本相似之处，请理解- 任何特定大脑皮层环路的修复都将是朝着这一目标迈出的重要一步。在这里，我们建议为您带来一个极端的 强大的理论家团队一起以无与伦比的深度对小鼠初级视觉皮质(V1)的回路进行建模， 在与实验者的紧密互动中，他们将产生变革性的数据来告知和测试我们的模型。 我们首先将重点放在理解语境调制及其通过跑步和唤醒 第2/3层处理，结合了研究最深入的三种抑制神经元亚型，小白蛋白-(PV)， 生长抑素(SOM)或血管活性肠肽表达(VIP)中间神经元，以及可能的亚型 SOM神经元。我们还将开发易于处理的树突状细胞抑制的单室模型，这将是一个 关键进展允许网络模型解决不同类型的中间神经元针对不同类型的功能 神经元隔间，同时保持足够简单，以产生洞察力。我们将研究对网络的影响 树突的SOM抑制行为与PV对胞体的抑制以及突触的短期可塑性 在系统中。然后，我们将继续并入更多的子类型，以解决更广泛的动态 响应属性，并对第4层和第2层到第4层的整个系统进行建模，构建在广泛的 本提案中的实验项目收集的数据。最后，与项目1合作，我们将开发一个统一的fiED 平均刺激反应和相关fl反应的模型，并解决V1对自然刺激的反应。 为了理解皮质特化的功能，如细胞亚型和层，我们不仅必须 系统地纳入数据中揭示的结构，但使用旨在获得洞察力的建模方法， 例如，了解产生特定fic活动的机制，或可能导致的电路调制形式 以特定组合中的特定细胞类型为目标。为了实现这一目标，我们将逐步、一步步地增加 我们的模型变得复杂，在每一步都理解引入了哪些新行为，哪些更大的结构 或者在先前已知的机制中发生变化，以及哪些新的机制变得可见。 这项建议最具创新性的方面是，我们将使用旨在让步的理论方法- 洞察机制，以解决复杂的特定fic细节的鼠标V1。现有的方法通常 要么研究更抽象的模型(例如，普通的兴奋性和抑制性细胞)，要么把所有已知的细节 必然有许多未知的东西)输入计算机，并相信这将复制大脑 活动，一种不太可能产生功能反应或可测试预测的方法。我们的方法承诺 极大地加深了我们对皮层，特别是小鼠V1的处理机制的洞察。

Summary A fundamental problem of neuroscience is understanding the operation of cerebral cortical circuits. Given the basic similarity of all cortical circuitry despite many differences across species and areas, understand- ing of any particular cortical circuit will be a major step toward that goal. Here we propose to bring an extremely strong team of theorists together to model the circuitry of mouse primary visual cortex (V1) in unparalleled depth, in tight interaction with experimentalists who will produce transformative data to inform and test our models. We will initially focus on understanding contextual modulation and its modulation by running and arousal in layer 2/3 processing, incorporating the three best-studied subtypes of inhibitory neurons, parvalbumin- (PV), somatostatin- (SOM), or vasoactive-intestinal-peptide-expressing (VIP) interneurons, and possible subtypes of SOM neurons. We will also develop tractable single-compartment models of dendritic inhibition, which will be a critical advance allowing network models to address the function of different interneuron types targeting different neuronal compartments while remaining simple enough to yield insight. We will study the impacts on network behavior of SOM inhibition at dendrites vs. PV inhibition on soma and of the short-term plasticity of synapses in the system. We will then advance to incorporating further subtypes, addressing a wider range of dynamic response properties, and modeling layer 4 and the full system of layers 2 through 4, building on the extensive data gathered by experimental projects in this proposal. Finally, working with Project 1, we will develop a unified model of mean stimulus responses and correlated fluctuations, and address V1 responses to natural stimuli. To understand the functions of cortical specializations such as cell subtypes and layers, we must not only systematically incorporate structure revealed in the data, but use modeling approaches aimed at gaining insight, e.g. understanding mechanisms that produce specific activities, or the forms of circuit modulation that can result from targeting particular cell types in particular combinations. To achieve this, we will gradually, step-by-step, add complexity to our models, understanding at each step what new behaviors are introduced, what greater structure or alterations occur in previously understood mechanisms, and what new mechanisms become visible. The most innovative aspect of this proposal is that we will use theoretical approaches designed to give in- sight into mechanisms to grapple with the complex specific details of mouse V1. Existing approaches typically either study more abstract models (e.g., generic excitatory and inhibitory cells) or put all known details (along with, necessarily, a great many unknown ones) into the computer with the belief that this will reproduce brain activity, an approach unlikely to generate functional responses or testable predictions. Our approach promises to dramatically deepen our insight into the mechanisms of processing in cortex and in mouse V1 in particular.