脑静息功能连接自发波动的可变性分析

发布时间：2018-01-10 10:19

本文关键词：脑静息功能连接自发波动的可变性分析　出处：《中国生物医学工程学报》2017年01期 　论文类型：期刊论文

【摘要】：静息脑功能连接的动态性被认为能够反映大尺度功能脑网络的基本性质,近年来受到越来越多的关注。过去很少有研究分析静息脑连接自发波动的空间分布特点。采用远程功能连接度结合滑动窗口方法,分析一组大样本(n=396)年轻成年人脑静息功能连接低频自发波动的可变性。首先采用36 s滑动窗,计算全脑动态连接时间序列;然后在每个窗口内,以半径为14 mm的球形邻域计算每个体素的远程连接度;最后引入低频振荡幅值(ALFF)指标,评估各体素连接度波动的大小。研究结果表明:默认网络具有最小的波动性(ALFF=402.3±79.9),暗示该网络在稳定脑自发神经活动中起主要作用。与之对比,感觉运动网络相关连接波动呈现出最大的可变性(ALFF=551.2±74.7),可能与被试在无任务状态下不定期感知外界环境有关。首次揭示静息态认知网络与感觉运动网络在静息功能连接波动性方面存在显著差异(双样本t检验:t=-6.38,P0.000 1),有助于进一步理解无任务状态下脑功能的动态组织方式,并为研究神经心理疾病提供新的方法。
[Abstract]:The dynamic nature of resting brain functional connections is considered to reflect the basic properties of large scale functional brain networks. In recent years, more and more attention has been paid. In the past few studies have been done to analyze the spatial distribution characteristics of spontaneous fluctuations in resting brain connections. Remote functional connectivity combined with sliding window method is used. The variability of low frequency spontaneous fluctuation of brain resting functional connection in a group of young adults was analyzed. First, 36 s sliding window was used to calculate the whole brain dynamic connection time series. Then, in each window, the distance connection degree of each voxel is calculated by using a spherical neighborhood with a radius of 14 mm. At last, the low frequency oscillation amplitude and ALFFF index are introduced to evaluate the fluctuation of voxel connectivity. The results show that the default network has the lowest volatility (402.3 卤79.9). It is suggested that the neural network plays a major role in stabilizing brain spontaneous neural activity. By contrast, the associated connectivity fluctuations of sensorimotor network show the largest variability (ALFFFN 551.2 卤74.7). It was revealed for the first time that there was a significant difference between resting cognitive network and sensorimotor network in relation to the volatility of resting function connection (2). Double sample t test: t = 6.38. P0.000 1 is helpful to further understand the dynamic organization of brain function in task-free state and to provide a new method for the study of neuropsychological diseases.
【作者单位】：河北科技师范学院;国防科学技术大学机电工程与自动化学院;
【基金】：国家自然科学基金(61351111)
【分类号】：R445.2;R338
【正文快照】： 2(国防科学技术大学机电工程与自动化学院,长沙410073)引言采用基于血氧水平依赖(blood oxygenation leveldependent,BOLD)信号的功能磁共振成像(f MRI)技术来研究大尺度脑功能网络,往往遵循被试在整个扫描期间其功能网络保持不变的静态连接假设。然而,近年来有关人脑与猴脑静

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