DEFINING FUNCTIONAL AREAS IN THE HUMAN BRAIN USING RESTING FUNCTIONAL CONNECTIVIT

描述(申请人提供)：大脑皮层在许多物理尺度上进行解剖组织。这种组织从神经元及其连接的层面延伸，将神经元的集合扩展到列，将列的集合扩展到功能区或地图，将区域的集合扩展到系统或网络。目前人类的功能性磁共振成像(FMRI)技术主要集中在细胞和柱状物的水平上，最常见的是功能区和系统的规模。除非在极少数情况下，例如地形图组织的感觉区，否则很难使用功能磁共振来确定人脑的区域边界。非侵入性地在更大范围的皮质中描绘功能区的能力将允许在受试者内定义皮质的不同区域，并允许对不同受试者的区域进行更适当的比较，从而提高许多类型的功能和结构研究的精确度，包括调查婴儿/儿童和患者等特殊人群的研究。静息相关活动的初步测量，即所谓的静息状态功能连接性(FcMRI)，显示出大脑皮质各部分之间相关强度的强烈局部性差异。这一观察提供了希望，以类似于非人类灵长类动物的连接解剖学的方式，fcMRI测量可以帮助定义人脑中的功能区边界。目的1：建立利用静息状态fcMRI确定功能区边界的方法。我们将利用相对较新的静息状态fcMRI度量，基于fcMRI数据中相邻点的相关曲线的突然变化来定义假定的功能区之间的边界。各种图像处理策略(例如，边缘检测和图像分割算法)将被用来产生fcMRI导出的边界的地图，这些地图限定了大脑皮质中假定的功能区。目的2：使用多个收敛检验来验证方法。在构建了假设的fcMRI边界图后，将使用几种融合的方法来测试其可靠性和有效性：1)重复受试者内部检查以测试fcMRI派生边界的可靠性；2)比较按地形图组织的视觉皮质区域中功能定义的(FMRI)边界与fcMRI定义的边界；3)比较可靠的功能激活(例如眼动和错误相关活动)与fcMRI定义的区域，以确定功能激活是否遵守fcMRI派生的边界；4)多个受试者检查以测试这些图的普适性。公共卫生相关性这项拨款提出了一系列方法开发和验证，以使用一种特定的成像测量方法，即静息状态功能连接磁共振成像，将大脑皮层划分为个别受试者的单独功能区域。成功的开发将使研究人员超越目前的宏观结构、立体定向和组合方法，提供更准确的功能区位置。这将在总体上推进神经成像研究，特别是在个人或群体变异性很高的情况下，例如发育研究，以及包括精神分裂症、抑郁症、运动障碍和中风在内的神经精神和神经疾病的研究。

DESCRIPTION (provided by applicant): The cerebral cortex is anatomically organized at many physical scales. This organization extends from the level of a neuron and its connections, collections of neurons into columns, collections of columns into functional areas or maps, and collections of areas into systems or networks. Current functional magnetic resonance imaging (fMRI) techniques in humans focuses above the level of cells and columns, most often at the scale of functional areas and systems. Except in rare circumstances, e.g. topographically-organized sensory regions, it is difficult to determine areal boundaries in the human brain using fMRI. The ability to non- invasively delineate functional areas in greater extents of cortex would allow both within-subject definition of separate areas of cortex, and allow for more appropriate comparison of areas across subjects, enhancing the precision of many types of both functional and structural studies, including those investigating special populations such as infants/children and patients. Preliminary measures of resting correlated activity, so-called resting state functional connectivity (fcMRI), show strong localized differences in correlation strength across expanses of cortex. This observation provides hope that, in similar fashion to connectional anatomy in non-human primates, fcMRI measures could aid in the definition of functional area boundaries in the human brain. Aim 1: To develop methods to define functional area boundaries using resting state fcMRI. We will utilize the relatively new metric of resting state fcMRI to define boundaries between putative functional areas based on abrupt changes in the correlation profiles of adjacent points in fcMRI data. Various image processing strategies (e.g., edge detection and image segmentation algorithms) will be used to produce maps of fcMRI-derived boundaries that circumscribe putative functional areas in the cortex. Aim 2: To validate methods using multiple converging tests. After putative fcMRI boundary maps are constructed, their reliability and validity will be tested using several converging approaches: 1) repeated within-subject examinations to test the reliability of fcMRI-derived boundaries; 2) comparison of functionally-defined (fMRI) boundaries in topographically organized visual cortical regions with fcMRI-defined borders; 3) Comparison of reliable functional activations (e.g. eye- movement and error-related activity) with fcMRI-defined regions to determine whether functional activations respect fcMRI-derived boundaries; 4) examination of multiple subjects to test the generalizability of these maps. PUBLIC HEALTH RELEVANCE This grant proposes a series of methods development and validations for using a specific imaging measure, resting-state functional connectivity magnetic resonance imaging, to parcellate the cortex of the brain into individual functional regions in individual subjects. Successful developments would allow researchers to move beyond current macrostructural, stereotactic and combined methods to provide more accurate locations of functional areas. This would advance neuroimaging studies generally, but particularly in situations where individual or group variability would be high, such as development studies, and studies of neuropsychiatric and neurological disease including schizophrenia, depression, movement disorders, and stroke.