Functional Augmentation of Existing Networks with New Neurons

用新神经元增强现有网络的功能

• 批准号: 1058034
• 负责人: Michal Zochowski
• 金额: $ 30万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-12-15 至 2015-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1058034&HistoricalAwards=false
• 关键词: Functional; Augmentation; Existing; Networks; New

The discovery that new neurons are born in adult brains and integrate into functional networks raised questions about the dynamics of this process. Namely, what are the activity dependent queues guiding the integration of the new cells into existing networks and how do these queues depend on the intrinsic properties of the augmented networks? The focus of this project is to develop an integrated computational and experimental framework, which will allow for investigation of dynamical mechanisms underlying migration and incorporation of newly born neurons into existing networks. We specifically want to understand whether, and how, network augmentation depends on the ongoing activity of the original network, and to discern the collective changes in the network activity patterns specifically due to network augmentation. To do so the PI will develop a computational approach that will allow him to elucidate links between cellular mechanisms of network augmentation and their network-wide outcomes. In addition the PI will use an in vitro experimental system based on dissociated cell cultures to monitor patterns of network augmentation and changes in spatio-temporal activity, after GFP labeled neuroblasts are added. The neural activity using multi-electrode arrays and calcium imaging will be recorded, and then labeling studies to elucidate structural patterns of neural augmentation will be performed. The proposed project will provide a better understanding of the interaction of cellular and network mechanisms underlying function-dependent network augmentation. This is critical for identifying dynamical mechanisms of self-reorganization in these types systems. This project will allow three collaborating laboratories to serve as a training resource for undergraduate and graduate students. The students will have the opportunity to gain experience in truly interdisciplinary research combining theoretical physics, modeling and neurobiology. They will further gain experience in the scientific process through participation in interdisciplinary meetings to present their results. The knowledge gained through this research will be disseminated to members of the scientific community through publications, seminars, and workshops. Additionally, the obtained results will be incorporated in the "Biocomplexity" course that the PI has developed for the advanced undergraduates.

新的神经元在成人大脑中生成，并整合到功能网络中，这一发现引发了人们对这一过程动力学的质疑。也就是说，指导新单元集成到现有网络中的活动依赖队列是什么？这些队列如何依赖于增强网络的内在属性？该项目的重点是开发一个集成的计算和实验框架，这将允许研究迁移和将新生神经元整合到现有网络中的动态机制。我们特别想了解网络增强是否以及如何依赖于原始网络的持续活动，并辨别网络活动模式的集体变化，特别是由于网络增强。为此，PI将开发一种计算方法，使他能够阐明网络增强的细胞机制与其网络范围内的结果之间的联系。此外，在加入GFP标记的神经母细胞后，PI将使用基于分离细胞培养的体外实验系统来监测网络增强的模式和时空活动的变化。使用多电极阵列和钙成像记录神经活动，然后进行标记研究以阐明神经增强的结构模式。拟议的项目将更好地理解细胞和网络机制之间的相互作用，这些机制是功能依赖网络增强的基础。这对于识别这些类型系统中自我重组的动态机制至关重要。该计划将允许三个合作实验室作为本科生和研究生的培训资源。学生将有机会获得结合理论物理、建模和神经生物学的真正跨学科研究的经验。他们将通过参加多学科会议介绍其成果，进一步获得科学进程方面的经验。通过这项研究获得的知识将通过出版物、研讨会和讲习班传播给科学界的成员。此外，获得的结果将被纳入PI为高级本科生开发的“生物复杂性”课程。