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题名	基于静息态功能磁共振成像的脑功能连接的研究
作者	刘赐融
学位类别	硕士
答辩日期	2012-04
授予单位	中国科学院研究生院
授予地点	北京
导师	马原野
关键词	静息态功能磁共振 功能连接 脑网络 脑区分割 特征降维
其他题名	Study of functional connectivity pattern based on resting-state fMRI
学位专业	神经生物学
中文摘要	功能分化与功能整合是大脑功能的两个基本组织原则。基于静息态功能磁共振功能连接，我们分别在2个不同的问题上对以上原则进行了研究。本文的第一个问题是关于功能整合的，研究了大脑功能网络的特点。第二个问题是关于功能分化的，提出了关于脑区分割的新方法。本文的主要内容如下： Ø 我们研究了实验猴的大脑功能网络的特点，并将其与成人和小孩的大脑功能网络特点进行了对比，从而对大脑进化和大脑发育模式进行探讨。 基于静息态fMRI的功能连接密度图（计算大脑区域功能连接数量的方法）可以用来确定大脑功能网络的核心节点。在本研究中，我们利用功能连接密度图的方法，对成人，小孩和实验猴的大脑功能网络的特点进行了分析。我们对原始的功能连接密度图的方法（只用一个单边阈值来定义功能连接）进行了改进，通过利用多个单边阈值和区间阈值来揭示不同被试组的功能连接密度图的差异。与成人不同，小孩的功能连接密度图随着阈值的不同会产生质的变化。小孩的前额叶，默认网络有关区域的相对连接度比成人的低，而初级运动和感觉皮层的相对连接度在成人和小孩之间没有明显的差异。该结果表明，功能连接密度图能够很好地反映大脑的成熟度。通过对比实验猴的功能连接密度图，我们也发现实验猴和成人的功能网络组织特点有明显的不同。同时我们对实验猴的扣带分区模式和大脑功能网络进行了深入的研究，通过比较前人在人类被试上所做的相似的研究，我们对大脑的进化模式和大脑的发育模式有了进一步的认识。 Ø 我们对基于功能连接的大脑分区问题进行了研究。我们提出了特征降维和特征选择的方法来提高分区效率和准确性，同时我们也提出了一套构建模拟数据的方法来对不同的降维方法进行评测。 研究大脑的结构和功能分区是神经科学的核心问题之一。传统的人类大脑分区方法多是基于细胞构筑或者是沟回结构，这些方法不仅是创伤式的，而且不能很好的反映大脑区域的外部连接特性。静息态fMRI为无创性研究大脑区域外部连接特性提供了新的方法，基于功能连接模式的大脑分区也成为当前热门领域之一。然而，大脑的体素并不是独立功能单元，使得功能连接模式含有冗余信息，减低了分区的效率和准确性。对于该问题，本文提出并检验了2种不同的特征降维方法，分别是基于主成份分析的方法和基于Affinity Propagation (AP) 算法的方法。同时，我们提出了一套构建模拟数据的方法。有了模拟数据的金标准，对不同降维方法的比较将更具可信性。我们的结果表明，在分区之前对功能连接模式进行降维不仅是可行的也是必要的。
英文摘要	Functional segregation and functional integration are two basic organizational principles of brain functions. Based on the functional connectivity resting-state functional magnetic resonance imaging (fMRI), we explored these principles in two different topics. The first topic of the dissertation is about function integration, investigating the properties of brain networks. The second topic is about functional segregation, developing approaches for the brain parcellation. The main contents of the dissertation are as follows: Ø We investigated the functional architecture of the brain network of monkeys and compared it with those of human adults and children to illustrate patterns of brain evolution and brain development. Functional connectivity density (FCD) mapping based on the resting-state fMRI has recently been used to locate cortical hubs of the adult brain. In previous studies, only one threshold was defined for the significant functional connectivity, since FCD maps of adults are relatively robust under different thresholds. In the present study, we examined the functional architecture of the monkey, human child (7-11 years old) and human adult brains, and compared our results with former related studies on infants. We present results showing that FCD maps of children change qualitatively with different thresholds reflecting the level of cerebral maturity. Compared with the adult brain, the lateral prefrontal cortex and areas related to the default mode network of the child brain show more differences in the FCD than the primary sensory and motor areas and insular cortex. When compared with results of monkey, we discovered the difference between monkey and human in FCD maps pattern. In addition, we investigated the connectivity-based segmentation of the cingulate cortex and brain networks of monkeys. By comparing these results with former related studies in humans, we have a better understanding of the patterns of human brain development as well as brain evolution. Ø We proposed approaches for feature reduction and selection for the functional-connectivity-based brain parcellation and developed semi-simulated data to evaluate these feature reduction approaches. Traditionally, a fundamental field for neuroscience has been the segmentation of structurally and functionally distinct subunits of the brain utilizing invasive techniques and post-mortem investigations based on cytoarchitecture and anatomical landmarks. More recently, resting-state functional magnetic resonance imaging (rs-fMRI) has been used to perform the parcellation of brain regions based on the information available in functional connectivity maps. However, brain voxels are not independent units and adjacent voxels are always highly correlated, leaving functional connectivity maps containing redundant information. This redundancy not only impairs the computational efficiency during clustering, but also reduces the accuracy of these results. In the present study, we proposed and investigated two feature reduction approaches that can reduce this redundancy: (1) based on Principal Component Analysis (PCA) and (2) on Affinity Propagation Algorithm (AP). These two approaches were tested for their feature reduction ability during the parcellation of three brain regions of different sizes. In addition, we developed a method of constructing semi-simulated data from real fMRI data to evaluate these two approaches. With the known ground truth of the semi-simulated data, conclusions drawn from comparison between different approaches would be more reliable. These results suggested that a feature reduction on functional connectivity maps is both feasible and necessary.
语种	中文
公开日期	2013-04-22
内容类型	学位论文
源URL	[http://159.226.149.42:8088/handle/152453/7367]
专题	昆明动物研究所_认知障碍病理学
推荐引用方式 GB/T 7714	刘赐融. 基于静息态功能磁共振成像的脑功能连接的研究[D]. 北京. 中国科学院研究生院. 2012.

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