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，大脑是持续活跃的，对单个细胞刺激的反应是嘈杂和不可靠的。大脑依靠的不是单个处理器的速度和准确性，而是成千上万个神经元对信息进行并行、同步采样。尽管神经元群嘈杂且缓慢，但它们共同产生了足够准确的对现实的感知表征，从而比当今存在的任何计算机都更有效、更快地执行行为。这种并行处理的关键是大脑皮层中神经网络之间的有效通信。大脑活动的波动与神经元群体在皮层网络之间有效沟通以编码信息的能力之间的相互作用是未知的。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-皮质通讯的机制和规则。这项工作不仅将解决长期存在的关于皮质-皮质通讯的假设，并导致新的计算分析工具的发展，而且还有助于阐明认知障碍，这些认知障碍被认为部分是由于皮质区域之间错误的信息传递。此外，该项目将为来自不同背景的学生提供参与国际前沿跨学科研究的机会。在这个项目中，研究人员研究了在这两种明确定义的网络状态下，视觉反应是如何在初级视觉皮层2-3层的局部网络之间交流的。具体来说，研究人员将使用电生理学、光遗传学、药理学和计算方法来量化体内初级视觉皮层在网络状态下的细胞和网络通信，这些网络状态已被提议理想地允许皮质皮质通信：伽马振荡和非振荡噪声状态，全球称为异步不规则。研究人员能够通过特定的视觉刺激引发和控制这些状态，并将描述这些状态的神经元背景活动以及它们在皮层柱之间有效传递信息中的作用。数据的大容量和新的定性方面将允许研究人员产生新的分析算法和理论方法，以及大规模的计算模型。最终，计算模型将有助于理解在定义良好的网络状态下信息传输的种群动态。该项目由生物科学理事会的神经系统集群和计算机与信息科学与工程理事会的信息和智能系统部门联合资助。法国国家研究机构（ANR）正在资助一个伙伴项目。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。