Circuit architecture and dynamics of the insular cortex underlying motivational behaviors

项目总结 岛叶皮质(IC)是一个整合内感和外感信息的多通道中枢 控制与认知、情绪和动机相关的动物行为的不同方面。其中 其他功能，IC接收有关动物新陈代谢状态和驱动的信息 动机和价态特定行为。然而，我们对神经元底物的理解 而IC功能背后的电路原理仍处于初级阶段。向前迈出的重要一步是 确定单个神经元在离散IC电路中的活动前后的活动 动物的行为。要实现这一目标，前提是要勾勒出个别IC中的事件 在动机行为中产生不同功能的神经元类型。然而，有两个主要的 挑战是存在的。首先，神经元回路是围绕亚区和神经元类型组织的。它是 越来越清楚的是，传统的IC亚区和细胞类型分类不足以 解释IC的功能多样性。对亚区、神经元类型和 需要特定于神经元的连接。其次，动物的内部状态在一定程度上由 神经调节剂，如多巴胺，动态调节单个IC的功能 电路。尽管最近在测量细胞外多巴胺和其他神经调节剂方面取得了进展， 它们以特定细胞类型的方式触发细胞内信号事件。在此，我们建议 通过整合来自 三个PI。首先，我们将使用基于机器学习的算法来全面识别函数 IC中的细分、神经元类型和细胞特异性连接。第二，我们将把活动联系起来 应用双光子钙成像技术研究单个IC细胞类型和亚区对动物活力的影响 通过梯度折射率(GRIN)透镜。第三，我们将同时描绘出 CAMP/蛋白激酶A(PKA)，介导神经调节的关键细胞内信号通路。vbl.使用 这些方法，我们的目标是获得一个无与伦比的了解活动和 作为活力和价态处理基础的离散IC电路的神经调节，两个基本和 动机行为的不同方面，在细胞分辨率上。我们将检验不同的假设 IC锥体神经元类型形成不同的局部和长程回路，这还不同 合作推动激励行为的活力和效价，取决于 神经调节。

PROJECT SUMMARY The insular cortex (IC) is a multimodal hub that integrates interoceptive and exteroceptive information to control diverse aspects of animal behaviors related to cognition, emotion, and motivation. Among other functions, the IC receives information regarding an animal’s metabolic states and drives motivation and valence-specific behaviors. However, our understanding of the neuronal substrates and circuit principles underlying IC function is still in its infancy. An important step forward is to determine the activities of individual neurons within discrete IC circuits before, during, and after an animal behavior. To achieve this goal, a prerequisite is to delineate the events in individual IC neuronal types that give rise to the diverse functions in motivated behaviors. However, two major challenges exist. First, neuronal circuits are organized around subregions and neuronal types. It is increasingly clear that traditional classifications of IC subregions and cell types are insufficient to explain the functional diversity of the IC. Precise classification of subregions, neuronal types, and neuron-specific connectivity is needed. Second, an animal’s internal state is in part encoded by neuromodulators, such as dopamine, which dynamically modulate the functions of individual IC circuits. Despite recent progress in measuring extracellular dopamine and other neuromodulators, they trigger intracellular signaling events in a cell type-specific manner. Herein, we propose to overcome these barriers by integrating the latest complementary technological advances from the three PIs. First, we will use machine learning-based algorithms to comprehensively identify functional subdivisions, neuronal types, and cell-specific connectivity in the IC. Second, we will link the activities of individual IC cell types and subregions to animal vigor or valence using two-photon calcium imaging through a gradient-index (GRIN) lens. Third, we will simultaneously image the dynamics of cAMP/protein kinase A (PKA), a key intracellular signaling pathway mediating neuromodulation. Using these approaches, we aim to gain an unparalleled understanding of the activities and neuromodulations of discrete IC circuits that underlie vigor and valence processing, two essential and distinct aspects of motivated behaviors, at cellular resolution. We will test the hypothesis that different IC pyramidal neuronal types form distinct local and long-range circuits, which differentially yet cooperatively drive vigor and valence for motivated behaviors in a manner depending on neuromodulation.