Investigating Computation and Communication in Multi-Scale Brain Networks

项目摘要 该提案旨在阐明多尺度大脑网络中的跨水平耦合（CLC）-即， 表征大脑组织的不同空间和时间水平之间的相互作用， 集中在单个神经元的尖峰和大规模的分布式活动之间的联系， 它们所嵌入的动态功能网络。本项目将阐明多尺度的性质 耦合和调查因果机制，这些相互作用可以控制。的主要动机 多尺度CLC可能为康复治疗提供一种新的途径， 用于创伤性脑损伤或中风后临床干预的新器械。 重要的是，该项目采用实时，慢性，多位点，高密度微电极阵列记录 脑机接口（BMI）研究中使用的技术与新颖的建模和分析相结合 方法.这种方法最近被用来证明，振荡相位耦合之间的多个 大脑区域协调单个神经元以及解剖学上分散的功能细胞的尖峰 组件（Canolty等人，2010，PNAS）。这些结果表明，大规模网络的动态模式 活动可能有助于调节神经元的集合，提供了一个引人注目的例子，功能相互作用， 多尺度大脑网络 该建议建立在这些结果的基础上，目的是进一步表征相互作用的功能作用， 多尺度大脑网络，它们对任务条件的依赖以及各种其他实验操作， 并研究了通过使用电刺激的因果干预对CLC进行外部控制的可能性。 第一个具体目标，CLC的目标特性，研究如何在多尺度脑网络中CLC 在不同的行为任务之间，不同的神经元组之间，在长时间的 学习，并在操作性条件反射的压力下。第二个目标，CLC的目标控制，研究 使用电刺激直接映射网络连接和因果影响的可行性 神经元的活动和行为通过夹带不同模式的振荡网络耦合。所有这些 有两个目标为一个充满活力的新研究议程提供了重点，该议程针对令人兴奋但知之甚少的领域 CLC现象的方式，可以证明立即有用的发展有效的临床 应用.

PROJECT SUMMARY This proposal seeks to elucidate cross-level coupling (CLC) in multi-scale brain networks - that is, characterizing interactions between different spatial and temporal levels of brain organization, with a particular focus on the connection between spiking in single neurons and the distributed activity of the large-scale, dynamic functional networks in which they are embedded. This project will clarify the nature of multi-scale coupling and investigate causal mechanisms by which these interactions can be controlled. A key motivation for this research is that multi-scale CLC may provide a novel route for rehabilitative therapies and the design of new devices for clinical intervention following traumatic brain injury or stroke. Importantly, this project employs the real-time, chronic, multi-site, high-density microelectrode array recording techniques used in brain-machine interface (BMI) research combined with novel modeling and analysis methods. This approach was recently used to demonstrate that oscillatory phase coupling between multiple brain areas coordinates the spiking of single neurons as well as anatomically-dispersed functional cell assemblies (Canolty, et al., 2010, PNAS). These results, showing that dynamic patterns of large-scale network activity may serve to regulate neuronal ensembles, provide a striking example of functional interactions in multi-scale brain networks. This proposal builds on these results with the aim of further characterizing the functional role of interactions in multi-scale brain networks, their dependence on task conditions and various other experimental manipulations, and investigates the potential for external control of CLC via causal intervention using electrical stimulation. The first specific aim, targeting characterization of CLC, investigates how CLC in multi-scale brain networks changes across different behavioral tasks, between distinct neuronal groups, over extended periods of learning, and under pressure from operant conditioning. The second aim, targeting control of CLC, investigates the feasibility of using electrical stimulation to directly map network connectivity and causally influence neuronal activity and behavior by entraining different patterns of oscillatory network coupling. Together, these two aims provide the focus for a vigorous new research agenda targeting the exciting but poorly understood phenomenon of CLC in ways that may prove immediately useful in the development of effective clinical applications.