首页> 外文会议>International conference on medical image computing and computer-assisted intervention;MICCAI 2010 >Fiber-Centered Analysis of Brain Connectivities Using DTI and Resting State FMRI Data
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Fiber-Centered Analysis of Brain Connectivities Using DTI and Resting State FMRI Data

机译:使用DTI和静止状态FMRI数据以纤维为中心的大脑连接性分析

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Recently, inference of functional connectivity between brain regions using resting state fMRI (rsfMRI) data has attracted significant interests in the neuroscience community. This paper proposes a novel fiber-centered approach to study the functional connectivity between brain regions using high spatial resolution diffusion tensor imaging (DTI) and rsfMRI data. We measure the functional coherence of a fiber as the time series' correlation of two gray matter voxels that this fiber connects. The functional connectivity strength between two brain regions is defined as the average functional coherence of fibers connecting them. Our results demonstrate that: 1) The functional coherence of fibers is correlated with the brain regions they connect; 2) The functional connectivity between brain regions is correlated with structural connectivity. And these two patterns are consistent across subjects. These results may provide new insights into the brain's structural and functional architecture.
机译:最近,使用静止状态功能磁共振成像(rsfMRI)数据推断大脑区域之间的功能连通性引起了神经科学界的极大兴趣。本文提出了一种新颖的以纤维为中心的方法,以利用高空间分辨率扩散张量成像(DTI)和rsfMRI数据研究大脑区域之间的功能连接性。我们测量光纤的功能相干性,作为该光纤连接的两个灰质体素在时间序列上的相关性。两个大脑区域之间的功能连接强度定义为连接它们的纤维的平均功能相干性。我们的结果表明:1)纤维的功能连贯性与其连接的大脑区域相关; 2)大脑区域之间的功能连通性与结构连通性相关。并且这两种模式在各个主题之间是一致的。这些结果可能为大脑的结构和功能结构提供新的见解。

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