CRCNS: Dissecting Directed Interactions Amongst Multiple Neuronal Populations

CRCNS：剖析多个神经元群之间的定向相互作用

• 批准号: 10830525
• 负责人: ADAM KOHN
• 金额: $ 34.05万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10830525
• 关键词: Address; Anatomy; Area; Brain; Calcium; Collaborations; Communication; Data; Dimensions; Disease; Electrodes; Feedback; Floods; Functional Magnetic Resonance Imaging; Goals; Image; Macaca; Mental disorders; Methods; Neurons; Pathway interactions; Pattern; Population; Poverty; Process; Property; Role; Sampling; Schizophrenia; Signal Transduction; Statistical Methods; System; Techniques; Technology; Time; Utah; Visual Cortex; Visual System; Work; analytical tool; area V1; area striata; autism spectrum disorder; insight; neural; nonhuman primate; response; retinotopic; tool; transmission process

Nearly all brain functions involve activity that is distributed across multiple areas. To understand these functions, it is critical to understand the flow of signals across this distributed network. To date approaches to understanding inter-areal signaling have been limited in several critical ways. First, they often focus on single neurons or a few voxels to summarize an area’s activity—an impoverished sample of the intricate neuronal population activity patterns that are known to represent and transmit information. Second, prior approaches often consider only pairwise inter-areal interactions, though the relevant network of areas is often much larger. Third, they rarely consider the concurrent flow of signals both from and to any given node in the network. In this project, we aim to overcome all three of these limitations. In Aim 1, we will develop and validate statistical methods that allow us to assess the directed, multi-dimensional flow of neuronal population signals among multiple (more than two) brain areas. We will identify directed interactions based on if the activation of a population activity pattern in one brain area tends to reliably precede the activation of a population activity pattern in another brain area with a consistent time delay. In Aim 2, we will refine and deploy the methods we develop to assess signal flow across multiple stages of the macaque visual system, an ideal testbed given a great deal of prior work on the anatomical and functional properties of the sampled areas. Specifically, we will record hundreds of neurons distributed across different layers of primary visual cortex (V1), V2, and V3. We will determine how columnar interactions within each area interact with feedforward and feedback processes, at a laminar level. Our project aims to provide insights that will strongly advance understanding of fundamental aspects of cortical function—how neuronal populations communicate with each other and how that communication relates to cortical processing. We expect the understanding we gain, and the analytic and conceptual tools we develop, will be broadly applicable across different brain systems. Our ambitious goals will be accomplished by pooling complementary expertise of three PIs, building on a successful collaboration that has extended over many years.

几乎所有的大脑功能都涉及分布在多个领域的活动 功能，了解迄今为止的信号流是至关重要的 要了解严重性的限制，他们通常专注于严重性的信号。 单个神经元或几个体素来总结区域的活动 已知代表信息的神经元人口活动模式 方法经常考虑在各个方面的交互作用，尽管相关的区域网络是istes 第三，他们很少考虑与任何给定的信号的同时流动 网络中的节点。 开发和验证统计方法，使我们能够评估 多个大脑区域中的神经元人口信号。 基于一个大脑区域中种群活动模式的激活往往会倾向于容忍的相互作用 在另一个大脑中具有一致的时间延迟的大脑中的人口活动模式 AIM 2，我们将完善并部署我们开发的方法，以评估跨多个阶段的信号流 猕猴的视觉系统是一个理想的测试床，鉴于解剖学和 采样区域的功能特性。 在不同的视觉皮层（V1）和V3的不同层中。 与区域的相互作用与层状级别相互作用和反馈过程 项目旨在提供洞察力，这些见解将对皮质的基本方面有深刻的理解 功能 - 神经元种群如何相互交流，以及对tanication的影响如何 皮质处理。 开发，将广泛适用于不同的大脑系统。 通过汇总三个PI的补充专业知识来完成 多年来已经延长了。