CRCNS: Acetylcholine and state-dependent neural network reorganization

CRCNS：乙酰胆碱和状态依赖的神经网络重组

• 批准号: 10830050
• 负责人: SARA J ATON
• 金额: $ 31.9万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-13 至 2028-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10830050
• 关键词: Acetylcholine; Affect; Anatomy; Area; Brain; Cells; Cognition; Cognition Disorders; Cognitive; Computer Models; Dementia; Equilibrium; Generations; Goals; Hippocampus; Hour; Impaired cognition; Individual; Information Storage; Interneurons; Intervention; Learning; Maps; Measures; Memory; Mental Depression; Mental disorders; Modeling; Mus; Muscarinic Acetylcholine Receptor; National Institute of Mental Health; Neural Network Simulation; Neurons; Neurosciences; Nicotinic Receptors; Pathway interactions; Pattern; Physiology; Play; Population; Post-Traumatic Stress Disorders; Process; Property; REM Sleep; Research; Role; Schizophrenia; Signal Transduction; Silicon Dioxide; Sleep; Sleep Architecture; Sleep Deprivation; Sleep disturbances; Somatostatin; Strategic Planning; Structure; Synapses; Synaptic plasticity; Testing; Training; Work; analytical method; analytical tool; autism spectrum disorder; biophysical model; cognitive function; computational network modeling; data modeling; density; experience; experimental study; in silico; in vivo; insight; long term memory; memory consolidation; memory encoding; memory process; network models; neural circuit; neural network; neuronal excitability; neuroregulation; neurotransmission; non rapid eye movement; novel; optogenetics; phenomenological models; recruit; response; segregation; sensory input; synaptic function; tool

Disrupted sleep is a major predictor of disordered cognition and affect, yet many questions regarding sleep's role in brain function remain unanswered. For example, why is sleep critical for memory consolidation? Why is there ubiquitous (presumably, evolutionarily conserved) wake-non-rapid eye movement (NREM)-REM sleep state ordering across species, and what are the differential roles of the two sleep states? How do brain circuit-wide dynamics change during these states, and how do those transitions affect the process of memory consolidation? Wake, NREM, and REM states generate distinct patterns of functional connectivity, which may help to reorganize brain networks in the context of memory storage. However, multiple mechanisms could play a role in this process, including state-driven structural (synaptic) changes, neuromodulatory processes, spike timing, or input alterations. This proposal advances the novel hypothesis that sequential in brain networks' acetylcholine (ACh) signaling and input properties, associated with wake->NREM->REM state transitions, are essential for memory storage In this framework, each state plays a distinct role, associated with state-specific network excitatory/inhibitory balance and neurons' input-response properties. Together, this leads to differential circuit activation and dynamic properties during wake, NREM, and REM. Our preliminary network modeling data suggest that the specific properties of NREM and REM allow for recruitment of neuronal populations into individual engrams (NREM), and generation of distinct, segregated engram representations (REM). These features become critical during consolidation of one or multiple memories, respectively. Here, we propose to apply computational modeling, in vivo experimentation and analytical tools to identify NREM (low ACh) and REM (high ACh)-associated dynamical states, and the specific contribution of these states to information storage in neural circuits. Specifically we will: 1) measure state-associated ACh effects on functional network connectivity and dynamics in highly reduced in silico neural network models, 2) test effects of state-targeted manipulations to hippocampal ACh inputs and excitatory-inhibitory balance during consolidation of one, or multiple, sleep-dependent memories, and 3) develop a predictive in silico model of the hippocampal circuit's reorganization during memory encoding and subsequent wake->NREM->REM transitions. These studies will also clarify state-specific mechanisms of memory storage in the brain, and how the wake-NREM-REM sequential ordering of these states (ubiquitous across vertebrate species) contributes to the process of memory consolidation. These studies will address Objective 1.1. of the NIMH Strategic Plan for Research, by identifying brain state-dependent neural circuit mechanisms underlying sleep's role in promoting healthy cognition and memory storage.

睡眠中断是认知和情感障碍的主要预测因素，但关于睡眠在认知和情感障碍中的作用仍存在许多问题。 大脑功能仍然没有答案。例如，为什么睡眠对于记忆巩固至关重要？为什么会有 普遍存在的（大概是进化上保守的）觉醒-非快速眼动（NREM）-快速眼动睡眠状态 跨物种的排序，以及两种睡眠状态的不同作用是什么？全脑回路如何 在这些状态期间动态会发生变化，这些转变如何影响记忆巩固的过程？ 唤醒、NREM 和 REM 状态产生不同的功能连接模式，这可能有助于重组 记忆存储背景下的大脑网络。然而，多种机制可以在这个过程中发挥作用， 包括状态驱动的结构（突触）变化、神经调节过程、尖峰计时或输入改变。 该提议提出了新的假设，即大脑网络的乙酰胆碱 (ACh) 信号传导和 与唤醒->NREM->REM 状态转换相关的输入属性对于内存存储至关重要 在框架中，每个状态都发挥着独特的作用，与特定状态的网络兴奋/抑制平衡和 神经元的输入响应特性。总之，这导致了差分电路激活和动态特性 在清醒、NREM 和 REM 期间。我们的初步网络建模数据表明 NREM 的具体属性 REM 允许将神经元群招募到个体印迹 (NREM) 中，并生成不同的、 分离印迹表征（REM）。这些功能在一个或多个整合过程中变得至关重要 分别是回忆。在这里，我们建议应用计算模型、体内实验和分析 识别 NREM（低乙酰胆碱）和 REM（高乙酰胆碱）相关动态状态的工具，以及 这些状态将信息存储在神经回路中。具体来说，我们将：1）测量与状态相关的乙酰胆碱效应 高度简化的计算机神经网络模型中的功能网络连接性和动态性，2）测试效果 巩固过程中对海马乙酰胆碱输入和兴奋抑制平衡的状态定向操纵 一个或多个睡眠依赖性记忆，3) 开发海马回路的预测计算机模型 内存编码和随后的唤醒->NREM->REM 转换期间的重组。这些研究也将 阐明大脑中记忆存储的特定状态机制，以及唤醒-NREM-REM序列如何 这些状态的排序（在脊椎动物物种中普遍存在）有助于记忆巩固的过程。 这些研究将解决目标 1.1。 NIMH 研究战略计划，通过识别大脑 睡眠促进健康认知和记忆作用的状态依赖性神经回路机制 贮存。