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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.
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Keywords:
- electroencephalogram /
- phase synchrony /
- cerebral infarction /
- complex network
[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]
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[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]
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