CRCNS: Targeted Stimulations in Brain Network of Networks

本项目的目标是研究心理状态的特征，使用状态之间的转换的诱导作为实验策略。这项工作是由一种新的网络理论驱动的-网络的网络（NoN）-强调弱链接的重要性。该项目将确定一个新的网络范式，同时确定网络标记和计算，为不同处理模块之间的信息传输和门控提供特异性和鲁棒性。前瞻性干预的目的是提供强大的经验约束的大脑网络结构的理论超出了具体的NoN假设测试，包括替代网络模型，例如“无标度”和“丰富的俱乐部”，以获得可证伪的预测的前瞻性干预。 这些结果也可以很容易地应用到其他系统，从代谢，蛋白质和遗传网络，社交网络和Internet.The本研究将测试具体的预测网络理论的相关结构的功能性磁共振（fMRI）和局部场电位（LFP）记录。研究人员将通过分析基于啮齿动物Connectome数据的结构连接性结合功能连接性来确定网络结构和大脑网络拓扑中关键节点的位置。拟议的NoN框架将揭示这些关键节点的位置-“超级传播者”和“超级抑制者”-并对级联神经活动，大脑网络的鲁棒性和脆弱性进行预测。

The goal of this project is to investigate the signature of mental states, using the induction of transitions among states as an experimental strategy. The work is driven by a novel network theory -- Network of Networks (NoN) -- that emphasizes the importance of weak links. The project will identify a new network paradigm with the concomitant identification of network markers and computations that confer specificity and robustness to information transmission and gating between different processing modules. The prospective interventions are designed to provide strong empirical constraints on theories of brain network structure beyond the specific NoN hypothesis tested here, including alternate network models, e.g "scale-free" and "rich-club," in order to obtain falsifiable predictions for the prospective interventions. The results can also be readily applied to other systems ranging from metabolic, protein and genetic networks to social networks and the Internet.The present study will test specific predictions of network theory with regards to the correlation structure of in-vivo functional magnetic resonance (fMRI) and local field potential (LFP) recordings. The investigators will determine network structure and location of key nodes in the brain network topology by analyzing the structural connectivity based on Connectome data from rodents combined with functional connectivity. The proposed NoN framework will reveal the location of such key nodes -- "superspreaders" and "superinhibitors" -- and make predictions on cascading neural activity, robustness and vulnerability of the brain network.