Multi-regional neural circuit dynamics underlying short-term memory

短期记忆的多区域神经回路动力学

• 批准号: 10241924
• 负责人: Shaul Druckmann
• 金额: $ 61.69万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-15 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10241924
• 关键词: Address; Algorithms; Alzheimer' s Disease; Anatomy; Animals; Anterior; Area; Atlases; BRAIN initiative; Behavior; Behavior monitoring; Behavioral; Behavioral Paradigm; Biophysical Process; Brain; Brain region; Cerebellum; Code; Cognitive; Data; Data Set; Decision Making; Disease; Etiology; Event; Functional disorder; Funding Opportunities; Future; Gene Expression; Goals; Grant; Individual; Knowledge; Link; Maps; Mediating; Memory; Methods; Midbrain structure; Modeling; Movement; Multiregional Analyses; Mus; Nature; Neurons; Outcome; Pathway Analysis; Pattern; Population Dynamics; Psyche structure; Publishing; Reading; Recovery; Rest; Route; Sensory; Short-Term Memory; Signal Transduction; Silicon; Site; Standardization; Structure; System; Techniques; Technology; Thalamic structure; Volition; Work; base; brain size; cognitive function; cognitive process; control trial; density; driving behavior; experience; experimental analysis; experimental study; flexibility; frontal lobe; information model; innovation; loss of function; multimodality; neural circuit; predicting response; relating to nervous system; response; sensory discrimination; spatiotemporal; theories

Abstract The focus of this BRAIN Initiative funding opportunity is to use “innovative approaches to understand how circuit activity gives rise to a specific behavior”. Cognitive behaviors arise from collective interactions of multiple brain systems. Yet, for most cognitive processes, we do not yet know which brain areas are involved and how multi-regional interactions mediate specific cognitive processes. This gap in knowledge arises because separate parts of the brain are studied individually, yet, the brain circuits driving behavior vary from one behavior to another. The goal of this proposal is to establish a working example of how brain-wide activity dynamics collectively generate one cognitive behavior. We address this question by studying how a mouse flexibly generate a volitional movement based on short-term memory. Neurons in multiple parts of the brain, including the frontal cortex, thalamus, midbrain, and cerebellum respond robustly during this short-term memory and causally contribute to the behavior. Taking advantage of this opportunity to establish how activity distributed across multiple brain systems orchestrates one coherent behavior, in this proposal, we will use newly developed experimental frameworks to analyze the underlying neural circuitry at brain-wide scale and establish causal relationships between specific activity patterns and behavior. First, we will use brain-wide loss-of-function screen, high-density silicon probe recording, and anatomical techniques to produce multi- modal maps of core neural substrates of the short-term memory. The outcome datasets will be put into standardized brain coordinates, making it possible to link the functional data to existing connectional and gene expression atlases. Next, we will use simultaneous recordings and spatiotemporally-precise perturbations to probe multi-regional interactions underlying the observed activity patterns and relationships to behavior. Finally, we will build multi-regional models that offer interpretable description of the behaviorally-relevant dynamics and relate them to underlying circuit connectivity. The outcome will disambiguate competing models of how information distributed over multiple brain regions is coordinated during cognitive processes, how information is dynamically routed and gated. The experimental, analysis, and modeling approaches will be broadly useful for analyzing distributed circuits driving behavior, as is the focus of multiple collaborative U19 grants. All the data and code will be published in the well document Neurodata Without Border (NWB) format.

摘要 这个BRAIN计划资助机会的重点是使用"创新方法来了解如何 电路活动引起特定行为"。认知行为产生于 多重大脑系统然而，对于大多数认知过程，我们还不知道哪些大脑区域参与其中 以及多区域互动如何调节特定的认知过程。这种知识上的差距 因为大脑的不同部分是单独研究的，然而，驱动行为的大脑回路不同， 一种行为对另一种行为的影响。这项提案的目的是建立一个工作的例子，说明大脑活动是如何 动力学共同产生一种认知行为。我们通过研究一只老鼠 灵活地产生基于短期记忆的意志运动。大脑多个部位的神经元， 包括额叶皮层、丘脑、中脑和小脑在这一短期内都有强烈的反应。 记忆和因果关系有助于行为。利用这个机会来确定活动如何 分布在多个大脑系统协调一个连贯的行为，在这个建议中，我们将使用 新开发的实验框架，以分析潜在的神经回路在全脑范围内， 建立特定活动模式和行为之间的因果关系。首先，我们将使用全脑 功能丧失屏幕，高密度硅探头记录，和解剖技术，以产生多个， 短期记忆的核心神经基质的模态图。结果数据集将被放入 标准化的大脑坐标，使得将功能数据与现有的连接和基因联系起来成为可能。 表情图谱接下来，我们将使用同步记录和时空精确扰动， 探索所观察到的活动模式和行为关系的多区域相互作用。 最后，我们将建立多区域模型，为行为相关性提供可解释的描述 动力学，并将它们与底层电路连接性联系起来。其结果将消除竞争模式的歧义 在认知过程中，分布在多个大脑区域的信息是如何协调的， 信息被动态地路由和选通。实验，分析和建模方法将是 广泛用于分析分布式电路驱动行为，这是多个协作U19的重点 补助金。所有数据和代码将以无边界神经数据（NWB）格式发布。