Defining and Describing Functional Brain Networks

描述(由申请人提供)：尽管在网络框架内检查健康和病理的大脑活动的趋势越来越大，但尚未建立对人脑网络的全面、可靠的描述(Bullmore&Sporns，2009)。静息状态功能连接性磁共振成像(rs-fcMRI)有可能在功能区水平上描述脑功能组织，但到目前为止还没有在功能区水平上描述大规模的网络。这项建议旨在为健康的年轻人提供一个严谨、合理和准确的功能区网络描述。第一个目标是使用元分析fMRI技术和最近发展起来的数据驱动的rs-fcMRI技术(fc-map)来定义人类的假定功能区。第二个目标是在rs-fcmri数据中构建全脑网络，使用假设的区域作为网络节点。节点在网络中形成组(称为模块)的趋势将被量化，期望节点将聚集到功能相关区域的模块中。公开的RS-FcMRI网络通常使用体素或预定义的体素解剖部分作为网络中的节点。有理由怀疑这种网络是大脑功能结构的次优表示，最终目的是比较体素、假定区域和地块网络的模块结构，这些网络都来自相同的受试者。模块化结构之间的严重不协调是预期的。将通过检查任务功能磁共振数据(未在目标1中使用)中模块内信号的一致性来测试网络模块的生物可信程度。如果RS-fcMRI信号如人们所认为的那样反映了信息处理的各个方面，那么基于该信号的网络应该反映信息处理系统。功能区域网络应该阐明大脑组织的基本特征，例如功能区域如何组合成功能系统，以及这些系统如何相互联系。对健康年轻人的“典型”功能脑组织的有力描述为病理条件的研究以及发育和衰老的研究提供了一个对照。从理论上讲，这里开发的网络方法比以前的技术对这种变化提供了更高的敏感性，这些方法与FC-map等工具相结合，将成为研究脑功能组织的有力方法。 与公共健康相关：大脑是一个网络，但这个网络的功能组织还没有被很好地理解。该项目旨在更好地定义大脑功能网络，这在健康人和病人身上都可以很容易地测量到。如果这个项目成功，功能性大脑网络的结构和特性将在诊断或理解疾病状态以及了解健康大脑如何工作方面变得更加有用。

DESCRIPTION (provided by applicant): Though there is a growing trend to examine healthy and pathological brain activity in the framework of networks, a comprehensive, robust description of human brain networks has not been established (Bullmore & Sporns, 2009). Resting state functional connectivity MRI (rs-fcMRI) is potentially capable of describing functional brain organization at the level of functional areas, but no large-scale networks at the level of functional areas have been described thus far. This proposal aims to provide a rigorous, reasoned, and accurate description of a network of functional areas in healthy young adults. The first aim is to use meta-analytic fMRI techniques and a recently developed data-driven rs-fcMRI technique (fc-Mapping) to define putative functional areas in humans. The second aim is to construct brain- wide networks in rs-fcMRI data, using putative areas as network nodes. The tendency for nodes to form groups (called modules) within the network will be quantified, with the expectation that nodes will gather into modules of functionally-related areas. Published rs-fcMRI networks typically use voxels or pre-defined anatomical parcellations of voxels as nodes in networks. There are reasons to suspect that such networks are suboptimal representations of the brain's functional architecture, and the final aim is to compare the modular structures of networks of voxels, putative areas, and parcels, all derived from the same subjects. Substantial incongruence between modular structures is expected. The biological plausibility of network modules will be tested by examining the coherence of signals within modules in task fMRI data (that was not used in Aim 1). If the rs-fcMRI signal reflects aspects of information processing, as it is thought to, then networks based on this signal should reflect information processing systems. A network of functional areas should illuminate basic features of brain organization, such as how functional areas group into functional systems, and how such systems relate to one another. A robust description of "typical" functional brain organization in healthy young adults provides a comparator for studies in pathologic conditions, and for studies of development and aging. The network approaches developed herein offer, theoretically, greater sensitivity to such changes than previous techniques, and these approaches, in combination with tools such as fc-Mapping, will be powerful methods for investigating functional brain organization. PUBLIC HEALTH RELEVANCE: The brain is a network, but the functional organization of this network is not well understood. This project aims to better define functional brain networks, which can be measured quite easily in healthy and in sick people. If this project is successful, the structure and properties of functional brain networks will become more useful in diagnosing or understanding disease states, and also for understanding how the healthy brain works.