搜索

x

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于网络连接度指标的脑梗死患者脑电信号相同步分析

侯凤贞 戴加飞 刘新峰 黄晓林

引用本文:
Citation:

基于网络连接度指标的脑梗死患者脑电信号相同步分析

侯凤贞, 戴加飞, 刘新峰, 黄晓林

Phase synchrony in the cerebral infarction electroencephalogram based on the degree of network-links

Hou Feng-Zhen, Dai Jia-Fei, Liu Xin-Feng, Huang Xiao-Lin
PDF
导出引用
  • 基于图论的脑功能网络分析是近年来的一个研究热点,而相同步分析已被证实为揭示多导联脑电信号之间功能连接的有效工具. 针对当脑电采集系统中导联数目较少而不适用于采用图论分析的情况,提出使用基于导联间相同步分析的网络连接度指标研究脑功能网络的关联特性和整体特性. 采用新的频带划分方法,将0.5–30Hz带宽内的脑电信号划分到5个子带上,计算了不同数据长度下各子带分量的网络连接度指标,并对比分析了各子带分量的相对功率. 结果表明: 在对脑梗死患者的脑电图和正常人的脑电图进行分析时,需要合理的数据长度量化不同动力学系统之间的差异;在合理的数据长度下,在网络连接度指标的区分效果方面,19–24Hz分量信号优于其他分量,而且仅在19–24Hz 频带上,脑梗死患者组的所有导联出现了与对照组的所有导联相同趋势的变化. 研究表明19–24Hz频带是脑梗死最佳的脑电图诊断频段,可将该频段下的网络连接度指标作为脑梗死辅助诊断的新指标.
    Recently, there has been increasing interest in applying graph theory to the quantitative analysis of brain functional networks, while phase synchronization (PS) analysis has been demonstrated to be a useful method to infer functional connectivity with multichannel neural signals, e.g., electroencephalogram (EEG). In this paper, we focus on the case that the number of channels in EEG data is not adequate for the use of graph theory analysis. The degree of network-links (DNLs), an index based on the PS analysis of all the EEG wave pairs, is proposed to study the relevant and the overall characteristics of the brain. With the help of a novel division to the frequency range 0.5–30 Hz, we analyze the DNLs in different frequency bands of the EEG signals. As a comparison, a frequency band analysis of the relative power spectrum is conducted. The results demonstrate that when the cerebral infarction (CI) patients and normal control people are analyzed, there is a need for the reasonable length of EEG data to quantify the differences between different dynamical systems; under a reasonable data length, the frequency band (19–24 Hz) yields the best accuracy for diagnosing CI, which lies within the classical beta band (13–30 Hz); furthermore, only in the 19–24 Hz band, as for the values of relative power spectrum, in each EEG channel, there presents a similar relationship between the CI group and control group. The experimental results suggest that 19–24 Hz should be the optimal range for the diagnosis of CI, further the DNLs calculated within this band serve as an assist indicator in the CI diagnosis.
    • 基金项目: 国家自然科学基金(批准号:61271082)、江苏省自然科学基金(批准号:BK2011565)和江苏省“青蓝”工程(批准号:201027)资助的课题.
    • Funds: Project supported by the National Natural Science Foundation of China (Grant No. 61271082), the Natural Science Foundation of Jiangsu Province, China (Grant No. BK2011565), and the "Qing Lan Program" of Jiangsu Province, China (Grant No. 201027).
    [1]

    Mishra M, Banday M, Derakhshani R, Croom J, Camarata P J 2011 J. Clin. Monit. Comput. 25 295

    [2]

    Zhu Y, Chen C 2011 World Clin. Drugs 32 143 (in Chinese) [朱燕, 陈超 2011 世界临床药物 32 143]

    [3]

    He Y, Chen Z, Gong G L, Evans A 2009 Neuroscientist 15 333

    [4]

    Bullmore E, Sporns O 2009 Nat. Rev. Neurosci. 10 186

    [5]

    Rubinov M, Sporns O 2010 Neuroimage 52 1059

    [6]

    Stam C J 2010 Int. J. Psychophysiol. 77 186

    [7]

    van Straaten E C W, Stam C J 2013 Eur. Neuropsychopharmacol. 23 7

    [8]

    Yin N, Xu G Z, Zhou Q 2013 Acta Phys. Sin. 62 118704 (in Chinese) [尹宁, 徐桂芝, 周茜 2013 物理学报 62 118704]

    [9]

    Fang X L, Jiang Z L 2007 Acta Phys. Sin. 56 7330 (in Chinese) [方小玲, 姜宗来 2007 物理学报 56 7330]

    [10]

    Bathelt J, O'Reilly H, Clayden J D, Cross J H, de Haan M 2013 NeuroImage 82 595

    [11]

    Stam C J, Jones B F, Nolte G, Breakspear M, Scheltens P 2007 Cereb. Cortex 17 92

    [12]

    Tijms B M, Wink A M, de Haan W, van der Flier W M, Stam C J, Scheltens P, Barkhof F 2013 Neurobiol. Aging 34 2023

    [13]

    Sun J F, Hong X F, Tong S B 2012 IEEE Trans. Bio-Med. Eng. 59 2254

    [14]

    Boccaletti S, Latora V, Moreno Y, Chavez M, Hwang D U 2006 Phys. Rep. 424 175

    [15]

    Quiroga R Q, Kraskov A, Kreuz T, Grassberger P 2002 Phys. Rev. E 65 041903

    [16]

    Dauwels J, Vialatte F, Musha T, Cichocki A 2010 Neuroimage 49 668

    [17]

    Li L, Jin Z L, Li B 2011 Acta Phys. Sin. 60 048703 (in Chinese) [李凌, 金贞兰, 李斌 2011 物理学报 60 048703]

  • [1]

    Mishra M, Banday M, Derakhshani R, Croom J, Camarata P J 2011 J. Clin. Monit. Comput. 25 295

    [2]

    Zhu Y, Chen C 2011 World Clin. Drugs 32 143 (in Chinese) [朱燕, 陈超 2011 世界临床药物 32 143]

    [3]

    He Y, Chen Z, Gong G L, Evans A 2009 Neuroscientist 15 333

    [4]

    Bullmore E, Sporns O 2009 Nat. Rev. Neurosci. 10 186

    [5]

    Rubinov M, Sporns O 2010 Neuroimage 52 1059

    [6]

    Stam C J 2010 Int. J. Psychophysiol. 77 186

    [7]

    van Straaten E C W, Stam C J 2013 Eur. Neuropsychopharmacol. 23 7

    [8]

    Yin N, Xu G Z, Zhou Q 2013 Acta Phys. Sin. 62 118704 (in Chinese) [尹宁, 徐桂芝, 周茜 2013 物理学报 62 118704]

    [9]

    Fang X L, Jiang Z L 2007 Acta Phys. Sin. 56 7330 (in Chinese) [方小玲, 姜宗来 2007 物理学报 56 7330]

    [10]

    Bathelt J, O'Reilly H, Clayden J D, Cross J H, de Haan M 2013 NeuroImage 82 595

    [11]

    Stam C J, Jones B F, Nolte G, Breakspear M, Scheltens P 2007 Cereb. Cortex 17 92

    [12]

    Tijms B M, Wink A M, de Haan W, van der Flier W M, Stam C J, Scheltens P, Barkhof F 2013 Neurobiol. Aging 34 2023

    [13]

    Sun J F, Hong X F, Tong S B 2012 IEEE Trans. Bio-Med. Eng. 59 2254

    [14]

    Boccaletti S, Latora V, Moreno Y, Chavez M, Hwang D U 2006 Phys. Rep. 424 175

    [15]

    Quiroga R Q, Kraskov A, Kreuz T, Grassberger P 2002 Phys. Rev. E 65 041903

    [16]

    Dauwels J, Vialatte F, Musha T, Cichocki A 2010 Neuroimage 49 668

    [17]

    Li L, Jin Z L, Li B 2011 Acta Phys. Sin. 60 048703 (in Chinese) [李凌, 金贞兰, 李斌 2011 物理学报 60 048703]

  • [1] 王振华, 刘宗华. 复杂网络上的部分同步化: 奇异态、遥同步与集团同步. 物理学报, 2020, 69(8): 088902. doi: 10.7498/aps.69.20191973
    [2] 胡志强, 李文静, 乔俊飞. 变频正弦混沌神经网络及其应用. 物理学报, 2017, 66(9): 090502. doi: 10.7498/aps.66.090502
    [3] 梁义, 王兴元. 结点含时滞的具有零和非零时滞耦合的复杂网络混沌同步. 物理学报, 2013, 62(1): 018901. doi: 10.7498/aps.62.018901
    [4] 刘金良. 具有随机节点结构的复杂网络同步研究. 物理学报, 2013, 62(4): 040503. doi: 10.7498/aps.62.040503
    [5] 李雨珊, 吕翎, 刘烨, 刘硕, 闫兵兵, 常欢, 周佳楠. 复杂网络时空混沌同步的Backstepping设计. 物理学报, 2013, 62(2): 020513. doi: 10.7498/aps.62.020513
    [6] 梁义, 王兴元. 基于低阶矩阵最大特征值的复杂网络牵制混沌同步. 物理学报, 2012, 61(3): 038901. doi: 10.7498/aps.61.038901
    [7] 柳爽, 吕翎, 李钢. 一类不确定复杂网络的滑模追踪同步. 物理学报, 2012, 61(16): 160507. doi: 10.7498/aps.61.160507
    [8] 杨浦, 郑志刚. 基于动力学同步的复杂网络结构识别速度研究. 物理学报, 2012, 61(12): 120508. doi: 10.7498/aps.61.120508
    [9] 王健安. 时变时滞耦合两个不同复杂网络的自适应广义同步. 物理学报, 2012, 61(2): 020509. doi: 10.7498/aps.61.020509
    [10] 吕翎, 柳爽, 张新, 朱佳博, 沈娜, 商锦玉. 节点结构互异的复杂网络的时空混沌反同步. 物理学报, 2012, 61(9): 090504. doi: 10.7498/aps.61.090504
    [11] 李凌, 金贞兰, 李斌. 基于因子分析方法的相位同步脑电源的时-空动力学分析. 物理学报, 2011, 60(4): 048703. doi: 10.7498/aps.60.048703
    [12] 曾长燕, 孙梅, 田立新. 基于自适应-脉冲控制方法实现时变耦合驱动-响应复杂网络的投影同步. 物理学报, 2010, 59(8): 5288-5292. doi: 10.7498/aps.59.5288
    [13] 卢静, 张荣, 徐振源. 振幅耦合动态网络中相邻结点间的相同步. 物理学报, 2010, 59(9): 5949-5953. doi: 10.7498/aps.59.5949
    [14] 吕翎, 张超. 一类节点结构互异的复杂网络的混沌同步. 物理学报, 2009, 58(3): 1462-1466. doi: 10.7498/aps.58.1462
    [15] 孟 娟, 王兴元. 基于非线性观测器的一类混沌系统的相同步. 物理学报, 2007, 56(9): 5142-5148. doi: 10.7498/aps.56.5142
    [16] 吴玉喜, 黄 霞, 高 建, 郑志刚. 双频驱动混沌系统的相同步和广义同步. 物理学报, 2007, 56(7): 3803-3812. doi: 10.7498/aps.56.3803
    [17] 方小玲, 姜宗来. 基于脑电图的大脑功能性网络分析. 物理学报, 2007, 56(12): 7330-7338. doi: 10.7498/aps.56.7330
    [18] 郝建红, 李 伟. 混沌吸引子在两个周期振子耦合下的相同步. 物理学报, 2005, 54(8): 3491-3496. doi: 10.7498/aps.54.3491
    [19] 莫晓华, 唐国宁. 采用振幅耦合方法研究多旋转中心混沌振子的相同步. 物理学报, 2004, 53(7): 2080-2083. doi: 10.7498/aps.53.2080
    [20] 郑志刚, 胡 岗, 周昌松, 胡斑比. 耦合混沌系统的相同步:从高维混沌到低维混沌. 物理学报, 2000, 49(12): 2320-2327. doi: 10.7498/aps.49.2320
计量
  • 文章访问数:  5981
  • PDF下载量:  1244
  • 被引次数: 0
出版历程
  • 收稿日期:  2013-10-20
  • 修回日期:  2013-11-04
  • 刊出日期:  2014-02-05

/

返回文章
返回