Mean-field Oscillator Games with Application to Thalamocortical Network Dynamics

平均场振荡器游戏在丘脑皮质网络动力学中的应用

• 批准号: 1334987
• 负责人: Prashant Mehta
• 金额: $ 34万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-15 至 2017-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1334987&HistoricalAwards=false
• 关键词: Mean; field; Oscillator; Games; Application

The research objective of this award is to explore phase transition and self-organization in large population dynamic systems. The thrust of the methodological work is at the intersection of the dynamical systems theory and game theory. The application focus is on investigating plasticity in the thalamocortical neuronal network in brain. The research will develop methods that are general enough to apply for mean-field games and that can be exploited in diverse applications. The research approach progresses from development of theoretical tools to their specialized application to thalamocortical network modeling. Deliverables include methods and computational tools to investigate phase transitions and stability in coupled oscillator models; algorithms for adaptation in such models; and applications of these tools to reduced order modeling of thalamocortical networks; and to development of specialized network adaptation schemes for plasticity therein.If successful, the results of this research can lead to fundamental advances in our understanding of the emergence of complex behavior in a large population of dynamically interacting agents. For biological systems, this methodology offers new organizing principles to address longstanding questions concerning collective emergent behavior in terms of generalizations of game theoretic concepts. A specific research outcome concerns mechanisms for plasticity (learning) in neuronal networks. This project has put together several educational initiatives to help disseminate the methods, outcomes, and the interdisciplinary synergies. This project seeks to develop and maintain strong undergraduate involvement in research, interdisciplinary outreach activities, exposure of the engineering undergraduates to the central role of dynamics and control in applications, and foster symbiotic relationship between neuroscience and engineering.

该奖项的研究目标是探索大群体动态系统中的相变和自组织。 该方法论工作的主旨是动力系统理论和博弈论的交叉点。 应用重点是研究大脑丘脑皮质神经元网络的可塑性。 该研究将开发足够通用的方法，适用于平均场博弈，并且可以在不同的应用中利用。 研究方法从理论工具的开发发展到丘脑皮质网络建模的专门应用。可交付成果包括研究耦合振荡器模型中相变和稳定性的方法和计算工具；此类模型的适应算法；以及这些工具在丘脑皮质网络降阶建模中的应用；如果成功的话，这项研究的结果可以使我们对大量动态交互代理中复杂行为的出现的理解产生根本性的进展。 对于生物系统来说，这种方法提供了新的组织原则，以博弈论概念的概括来解决有关集体紧急行为的长期存在的问题。 一项具体的研究成果涉及神经元网络中的可塑性（学习）机制。 该项目汇集了多项教育举措，以帮助传播方法、成果和跨学科协同作用。该项目旨在培养和保持本科生对研究、跨学科推广活动的强烈参与，让工程本科生接触动力学和控制在应用中的核心作用，并促进神经科学和工程学之间的共生关系。