CRCNS US-French Research Proposal: Impact of network state on corticocortical communication

CRCNS 美法研究提案：网络状态对皮质通讯的影响

• 批准号: 2207707
• 负责人: Diego Contreras
• 金额: $ 68万
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-11-01 至 2025-10-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2207707&HistoricalAwards=false
• 关键词: CRCNS; US; French; Research; Proposal

In great contrast to a digital computer, the brain is constantly active and responses to stimuli of single cells are noisy and unreliable. Instead of speed and accuracy by a single processor, brains rely on the parallel, simultaneous sampling of information by thousands of neurons. Neuronal populations, albeit noisy and slow, together generate sufficiently accurate perceptual representations of reality to conduct behavior much more efficiently and orders of magnitude faster than any computer in existence today. Key to such parallel processing is efficient communication among neural networks in the cortex of the brain. The interaction of the fluctuating activity of the brain and the ability of populations of neurons to efficiently communicate between cortical networks in order to encode information is unknown. In this project, the investigators explore and test the mechanisms and rules of cortico-cortical communication using state of the art experimental and computational tools. The work will not only address long-standing hypotheses about cortico-cortical communication and result in the development of novel computational analysis tools but also help shed light on cognitive disorders believed to be due in part to faulty information transmission between cortical areas. In addition, the project will provide opportunities for students from diverse backgrounds to participate in cutting-edge international interdisciplinary research.In this project, the investigators examine how visual responses are communicated between local networks in layers 2-3 of primary visual cortex under those two well-defined network states. Specifically, the investigators will use electrophysiological, optogenetic, pharmacological and computational approaches to quantify cellular and network communication in primary visual cortex in vivo under network states that have been proposed to ideally allow corticocortical communication: gamma oscillations and non-oscillatory noisy states globally termed asynchronous irregular. The investigators are able to elicit and control those states with specific visual stimulation and will characterize the states’ neuronal background activity as well as their role in efficient transmission of information between cortical columns. The large volume and new qualitative aspects of the data will allow the investigators to generate novel analysis algorithms and theoretical approaches, as well as large-scale computational models. Ultimately, the computational models will help understand population dynamics for the transmission of information in well-defined network states. This project is funded jointly by the Neural Systems Cluster in the Biological Sciences Directorate and the Division of Information and Intelligent Systems in the Computer and information Science and Engineering Directorate. A companion project is being funded by the French National Research Agency (ANR).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

与数字计算机形成鲜明对比的是，大脑不断活跃，对单个细胞刺激的反应是噪音且不可靠的。大脑不是单个处理器的速度和准确性，而是依赖数千个神经元对信息的平行，简单采样。神经元种群，尽管噪声和缓慢，但共同产生了足够准确的现实感知表示，以比当今现有的任何计算机更有效地进行行为和更快的数量级。这种并行处理的关键是神经元之间在大脑皮层中的有效通信。大脑波动活动的相互作用以及神经元种群在皮质网络之间有效通信以编码信息的能力是未知的。在这个项目中，研究人员使用最先进的实验和计算工具探索和测试皮质皮质通信的机制和规则。这项工作不仅将解决有关皮质形成通信的长期假设，并导致开发新颖的计算分析工具，还有助于阐明被认为是由于皮质区域之间的信息传播而造成的认知障碍。此外，该项目将为来自潜水员背景的学生提供机会，以参与尖端国际跨学科研究。在该项目中，研究人员研究了如何在这两个明确定义的网络状态下的主要视觉皮层的2-3层本地网络之间进行视觉响应。具体而言，研究人员将使用电生理学，光遗传学，药物和计算方法来量化一级视觉皮层的细胞和网络通信在网络状态下的体内体内，这些状态已提议理想地允许皮质皮质通信：γ振荡和非振荡性噪声状态和非振动性噪声状态，全球范围为全球范围内的违规状态。研究人员能够通过特定的视觉刺激来激发和控制这些状态，并将表征状态的神经元背景活动以及它们在皮质柱之间有效传播信息中的作用。数据的大量和新的定性方面将使研究人员能够生成新颖的分析算法和理论方法以及大规模的计算模型。最终，计算模型将有助于了解人口动态，以传输明确定义的网络状态。该项目由生物科学局的神经系统集群以及计算机和信息科学与工程局中信息和智能系统的部门共同资助。合作伙伴项目由法国国家研究机构（ANR）资助。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的评论标准来评估值得支持的。