Circuit basis of social behavior decision-making in a subcortical network

项目摘要/摘要 这一建议响应了FOA(RFA-NS-18-030)呼吁1)使用新的方法来理解神经 与明确定义的社会行为相关的电路；2)有助于协调的分布式电路 激励状态和奖励行为；“3)”经验和分析方法，以了解如何 行为状态是神经元、电路和网络相互作用的紧急属性。的研究。 控制保守的自然主义行为的皮质下回路对于理解大脑功能至关重要。我们 目的了解下丘脑不同回路节点之间的动态相互作用是如何扩展的 杏仁核决定(“头”)网络控制先天的社会行为决定，例如，在攻击性和 生殖行为。我们提出了一种结合显微内窥镜检查的综合方法。 基于自动机器学习的遗传识别神经元亚群成像(MEI) 自由活动小鼠的社会行为分类以及神经元活动的功能扰动 在活体内。我们广泛而长期的目标是了解如何在相互关联的 头部网络中的结构控制着以目标为导向的竞争对手之间的即时决策 对动物和人类的生存至关重要的行为。这项提议的中心目标是 了解在社交互动期间信息如何通过此网络流动，并被解码以控制 决定从事生殖与攻击性的社会行为。要了解“上游”的活动如何 节点控制下游节点中的神经表示，我们将实现一种新的方法来结合 前者的可逆性化学发生抑制与神经元群体活动的同步成像 后者。这种方法的基本原理是，对系统的理解需要描述影响的特征 在行为和电路水平的表型上的功能操纵。为了实现我们的目标，我们将 首先刻画了神经编码的行为和同种性别认同在多个节点上的扩展 杏仁核，使用单部位显微内窥镜成像和计算分析方法(目标1)； 确定这类节点活动的扰动如何影响下丘脑节点的表征 (目标2)；调查核内和核间相互作用在确定活动平衡方面的作用 在攻击性和促进生殖的下丘脑节点之间(目标3)；确定这种平衡是如何 由下游的中脑结构进行解码，以确定要表达的社会行为类型(目标4)。这 贡献是重大的，因为它代表了一种系统级的方法来理解皮质下 网络控制着行为决策。这一贡献具有创新性，因为它集成了对 神经元群体活动，自然社会行为和功能的定量测量 特定神经元亚群的活动扰动，以深入了解神经回路如何分布 控制生存行为，在与导致人类精神障碍的适应不良相关的背景下。

Project Summary/Abstract This proposal responds to an FOA (RFA-NS-18-030) calling for 1) “novel approaches to understand neural circuitry associated with well-defined social behaviors;” 2) Distributed circuits that contribute to the coordination of motivational states and reward behavior;” 3) “Empirical and analytical approaches to understand how behavioral states are emergent properties of the interaction of neurons, circuits and networks.” The study of subcortical circuits that control conserved, naturalistic behaviors is crucial to understanding brain function. We aim to understand how dynamic interactions between different circuit nodes in the Hypothalamic-Extended Amygdala Decision (“HEAD”) network control innate social behavior decisions, e.g., between aggressive and reproductive behaviors. We propose an integrated approach to this problem that combines microendoscopic imaging (MEI) of genetically identified neuronal subpopulations with automated, machine learning-based classification of social behavior in freely moving mice, together with functional perturbations of neuronal activity in vivo. Our broad, long-term objective is to understand how distributed activity among interconnected structures in the HEAD network controls moment-to-moment decisions between competing goal-directed behaviors that are crucial for the survival of animals and humans. The central objective of this proposal is to understand how information flows through this network during social interactions, and is decoded to control the decision to engage in reproductive vs. aggressive social behaviors. To understand how activity in “upstream” nodes controls neural representations in “downstream” nodes, we will implement a novel approach combining reversible chemogenetic inhibition of the former with concurrent imaging of neuronal population activity in the latter. The rationale for this approach is that an understanding of the system requires characterizing the effects of functional manipulations on both behavioral and circuit-level phenotypes. To achieve our objective, we will first characterize the neural coding of behavior and conspecific sex identity in multiple nodes of the extended amygdala, using single-site microendoscopic imaging and computational analytic approaches (Aim 1); determine how perturbations in the activity of such nodes influence representations in hypothalamic nodes (Aim 2); investigate the roles of intra- and inter-nuclear interactions in determining the balance of activity between aggression and reproduction-promoting hypothalamic nodes (Aim 3); determine how this balance is decoded by downstream mid-brain structures to determine the type of social behavior to express (Aim 4). This contribution is significant because it represents a systems-level approach to understanding how a subcortical network controls behavioral decision-making. The contribution is innovative because it integrates analysis of neuronal population activity, quantitative measurement of naturalistic social behavior and functional perturbations of activity in specific neuronal subpopulations to gain insight into how distributed neural circuits control survival behaviors, in a context that is relevant to maladaptations causing human psychiatric disorders.