DEFINING FUNCTIONAL AREAS IN THE HUMAN BRAIN USING RESTING FUNCTIONAL CONNECTIVIT

描述（由申请人提供）：大脑皮层在许多物理尺度上解剖组织。这种组织从神经元及其连接的层次，神经元的集合扩展到列，列的集合扩展到功能区域或地图，区域的集合扩展到系统或网络。目前的人类功能磁共振成像（fMRI）技术主要集中在细胞和柱的水平上，通常是在功能区和系统的尺度上。除了在罕见的情况下，例如，地形组织的感觉区域，很难用功能磁共振成像确定人类大脑的区域边界。在更大范围内非侵入性地描绘皮层功能区域的能力将允许在受试者内定义单独的皮层区域，并允许跨受试者更适当的区域比较，提高许多类型的功能和结构研究的准确性，包括那些调查特殊人群，如婴儿/儿童和患者的研究。静息相关活动的初步测量，即所谓的静息状态功能连通性（fcMRI），显示出皮层各区域的相关强度存在强烈的局部差异。这一观察结果提供了希望，与非人类灵长类动物的连接解剖学类似，fcMRI测量可以帮助定义人类大脑的功能区域边界。目的1：开发使用静息状态功能磁共振成像来定义功能区边界的方法。我们将利用相对较新的静息状态fcMRI指标，根据fcMRI数据中相邻点的相关曲线的突变来定义假定功能区之间的边界。各种图像处理策略（例如，边缘检测和图像分割算法）将用于生成fcmri衍生的边界图，这些边界限定了皮层中假定的功能区。目标2：使用多个收敛测试验证方法。在构建假定的fcMRI边界图后，将使用几种收敛方法来测试其信度和效度：1)重复的受试者内检查来测试fcMRI导出的边界的信度；2)比较地形组织视觉皮质区域的功能定义（fMRI）边界与fMRI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符合fcmri衍生的边界；4)对多个科目进行检验，以检验这些地图的普遍性。这项拨款提出了一系列方法的开发和验证，用于使用特定的成像测量，静息状态功能连接磁共振成像，将大脑皮层分割成个体受试者的单个功能区域。成功的发展将使研究人员超越目前的宏观结构、立体定向和组合方法，以提供更准确的功能区位置。这将普遍推进神经影像学研究，特别是在个体或群体差异很大的情况下，如发育研究，以及神经精神病学和神经疾病（包括精神分裂症、抑郁症、运动障碍和中风）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.