Interrogation of network-wide neuronal dynamics during fear memory in mouse default mode network

项目摘要 认知症状是许多精神疾病的临床重要组成部分， 影响复杂的领域，如长期记忆，由协调的相互作用介导， 在全脑网络中的活动。重要的是，特定的神经元动力学和 集成网络功能的基本机制尚未完全理解，即使在 健康这个建议的目的是了解如何相关的神经元动力学在一个 临床上重要的记忆相关网络，默认模式网络（DMN），有助于 使用老鼠模型进行记忆处理。核心假设是相关性低- 在DMN上的频率活动在短时间内发生， 网络结构之间的记忆相关活动的传播。提案探讨 DMN功能通过将光遗传学与新型光学技术多光纤相结合来实现 光度法（MFP），直接测量神经元动力学同时跨DMN 地区我用MFP的初步研究显示兴奋性神经元的慢相关动力学 小鼠中DMN（但不是对照区）的种群。我现在可以直接探测真实的- 与相关DMN相关的时间网络范围内的神经元活动和相互作用 记忆中的动态目标1将确定θ，3- 10 Hz活动的可靠性 与存储器相关联，通过处于其相关状态的DMN传播。目标2将 检查由记忆（恐惧条件反射）引起的DMN动态，以及它们与回忆的关系 （context recall）。目的3将通过光遗传学方法证明记忆过程中DMN的相互作用。 在存储器处理期间抑制个别区域并测量所得网络 动力学这些目标代表了第一次深入解剖神经元动力学在整个 记忆中的DMN他们利用创新的方法，利用新颖和普遍的 方法在小鼠模型中产生对DMN功能的基本了解， 术语记忆，与人类神经影像学发现和临床症状相关。在 在这个过程中，我将成为精通全光学方法来探测分布式网络， 分析网络范围内的活动，以及综合行为测试。我会和一个专家合作 顾问委员会（Deisseroth博士，Blair博士，Wiltgen博士，Etkin博士，O 'Hara博士） 在这些方法中指导学员的经验。这种尖端系统的训练 神经科学，将批判性地补充我的分子和细胞神经科学背景， 这让我开始了独立调查员的职业生涯， 神经回路整合并调节它们的功能，以在健康和疾病中产生认知。

Project Abstract Cognitive symptoms are a clinically important component of many psychiatric disorders, affecting complex domains, like long-term memory, mediated by coordinated interaction of activity across brain-wide networks. Importantly, the specific neuronal dynamics and mechanisms underlying integrated network function are incompletely understood, even in health. The objective of this proposal is to understand how correlated neuronal dynamics in a clinically important memory-related network, the default mode network (DMN), contribute to memory processing using a mouse model. The central hypothesis is that correlated low- frequency activity across the DMN occurs in short periods of time associated with propagation of memory-related activity between network structures. The proposal probes DMN function by combining optogenetics with a novel optical technique, multifiber photometry (MFP), which directly measures neuronal dynamics simultaneously across DMN areas. My preliminary studies using MFP show slow correlated dynamics in excitatory neuron populations across DMN (but not a control area) in mouse. I can now directly probe the real- time network-wide neuronal activity and interactions associated with correlated DMN dynamics during memory. Aim 1 will determine how reliably theta, 3-10Hz activity classically associated with memory, propagates through the DMN in its correlated state. Aim 2 will examine DMN dynamics induced by memory (fear conditioning), and their relationship to recall (context recall). Aim 3 will demonstrate DMN interactions during memory by optogenetically inhibiting individual areas during memory processing and measuring resulting network dynamics. These aims represent the first in-depth dissection of neuronal dynamics across the DMN during memory. They utilize an innovative approach, leveraging novel and generalizable methods in a mouse model to generate fundamental insight into DMN function during long- term memory, with relevance to human neuroimaging findings and clinical symptoms. In the process, I will become proficient in all-optical approaches to probing distributed networks, analysis of network-wide activity, and integrated behavioral testing. I will work with an expert advisory committee (Dr. Deisseroth, Dr. Blair, Dr. Wiltgen, Dr. Etkin, Dr. O’Hara) with pioneering experience mentoring trainees in these methods. This training in cutting-edge systems neuroscience, will critically supplement my molecular and cellular neuroscience background, allowing me to launch a career as an independent investigator examining how distributed neural circuits integrate and regulate their function to generate cognition in health and disease.