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Spatiotemporal dynamic analysis of phase synchronized sources based on factor analysis

Li Ling Jin Zhen-Lan Li Bin

Spatiotemporal dynamic analysis of phase synchronized sources based on factor analysis

Li Ling, Jin Zhen-Lan, Li Bin
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  • Correlations in time courses of scalp electroencephalogram(EEG) may be represented by the phase synchronization in cerebral cortex sources to a certain some degree. Therefore, it is very important to localize the sources of phase synchronization and find corresponding time courses in the brain imaging study. Based on coupled Rössler oscillators with different coupling strengths, we propose a new method of simulating phase synchronized dipole sources and use a concentric 4-sphere head model to obtain simulation forward scalp EEG data. In addition, we propose the spatiotemporal dynamic analysis of phase synchronized sources based on the maximum likelihood factor analysis, verify the simulated and real scalp EEG data, and further compare the results with those of principal component analysis. Simulation results demonstrate that time courses estimated by maximum likelihood factor analysis have higher correlation with simulated sources, and less locational error between estimated sources and simulated sources. Factor analysis shows a better robust to the spatial resolution and the noise than principal component analysis. Furthermore, real data from spatial attention experiments show that factor analysis is capable of obtaining time courses and spatial distribution under the physiological base.
    • Funds:
    [1]

    Gevins A 1998 Electroenceph. Clin. Neurophysiol. 106 165

    [2]

    Michel C M, Murray M M, Lantz G, Gonzalez S, Spinelli L, Rolando Grave de Peralta 2004 Clin. Neurophysiol. 115 2195

    [3]

    Nunez P L, Silibertein R B, Cdush P J, Wijesinghe R S, Westdrop A F, Srinivasan R 1994 Electroenceph. Clin. Neurophysiol. 90 40

    [4]

    Yao D 2002 Clin. Neurophysol. 113 956

    [5]

    Pascual-Marqui R D, Michel C M, Lehmann D 1994 Int. J. Psychophysiol. 18 49

    [6]

    Yao D, He B 2001 Ann. Biomed. Eng. 29 1019

    [7]

    Yao D 2001 Phys. Med. Biol. 46 3177

    [8]

    Mosher J C, Leahy R M 1998 IEEE Trans. Biomed. Eng. 45 1342

    [9]

    Stam C J, van Dijk B W 2002 Phys. D 163 236

    [10]

    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]

    [11]

    Meng Q F, Zhou W D, Chen Y H, Peng Y H 2010 Acta. Phys. Sin. 59 123 (in Chinese) [孟庆芳、周卫东、陈月辉、彭玉华 2010 物理学报 59 123] 〖12] Xie Y, Xu J X, Yang H J, Hu S J 2002 Acta. Phys. Sin. 51 205 [谢 勇、徐健学、杨红军、胡三觉 2002 物理学报 51 205]

    [12]

    Benjamin L, Jurgen S, Andreas S 2006 J. Physiol. 99 66

    [13]

    Van Boxtel G J M 1998 Behav. Res. Methods. Instrum. Comput. 30 87

    [14]

    Kayser J, Tenke C E 2003 Clin. Neurophysiol. 114 2307

    [15]

    Wood C C, McCarthy G 1984 Electroencephalogr. Clin. Neurophysiol. 59 249

    [16]

    Rosenblum M G, Pikovsky A S, Kurths J 1996 Phys. Rev. Lett. 76 1804

    [17]

    Cuffin B N, Cohen D 1997 IEEE Trans. Biomed. Eng. 24 372

    [18]

    Yao D 2003 Phys. Med. Biol. 48 1997

    [19]

    Li L, Yao D, Yin G 2009 Brain Res. 1282 84

    [20]

    Jöreskog K G 1967 Psychometrika. 32 443

    [21]

    Rubin D B, Thayer D T 1982 Psychometrika. 47 69

    [22]

    Clark V, Hillyard S A 1996 J. Cogn. Neurosci. 8 387

  • [1]

    Gevins A 1998 Electroenceph. Clin. Neurophysiol. 106 165

    [2]

    Michel C M, Murray M M, Lantz G, Gonzalez S, Spinelli L, Rolando Grave de Peralta 2004 Clin. Neurophysiol. 115 2195

    [3]

    Nunez P L, Silibertein R B, Cdush P J, Wijesinghe R S, Westdrop A F, Srinivasan R 1994 Electroenceph. Clin. Neurophysiol. 90 40

    [4]

    Yao D 2002 Clin. Neurophysol. 113 956

    [5]

    Pascual-Marqui R D, Michel C M, Lehmann D 1994 Int. J. Psychophysiol. 18 49

    [6]

    Yao D, He B 2001 Ann. Biomed. Eng. 29 1019

    [7]

    Yao D 2001 Phys. Med. Biol. 46 3177

    [8]

    Mosher J C, Leahy R M 1998 IEEE Trans. Biomed. Eng. 45 1342

    [9]

    Stam C J, van Dijk B W 2002 Phys. D 163 236

    [10]

    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]

    [11]

    Meng Q F, Zhou W D, Chen Y H, Peng Y H 2010 Acta. Phys. Sin. 59 123 (in Chinese) [孟庆芳、周卫东、陈月辉、彭玉华 2010 物理学报 59 123] 〖12] Xie Y, Xu J X, Yang H J, Hu S J 2002 Acta. Phys. Sin. 51 205 [谢 勇、徐健学、杨红军、胡三觉 2002 物理学报 51 205]

    [12]

    Benjamin L, Jurgen S, Andreas S 2006 J. Physiol. 99 66

    [13]

    Van Boxtel G J M 1998 Behav. Res. Methods. Instrum. Comput. 30 87

    [14]

    Kayser J, Tenke C E 2003 Clin. Neurophysiol. 114 2307

    [15]

    Wood C C, McCarthy G 1984 Electroencephalogr. Clin. Neurophysiol. 59 249

    [16]

    Rosenblum M G, Pikovsky A S, Kurths J 1996 Phys. Rev. Lett. 76 1804

    [17]

    Cuffin B N, Cohen D 1997 IEEE Trans. Biomed. Eng. 24 372

    [18]

    Yao D 2003 Phys. Med. Biol. 48 1997

    [19]

    Li L, Yao D, Yin G 2009 Brain Res. 1282 84

    [20]

    Jöreskog K G 1967 Psychometrika. 32 443

    [21]

    Rubin D B, Thayer D T 1982 Psychometrika. 47 69

    [22]

    Clark V, Hillyard S A 1996 J. Cogn. Neurosci. 8 387

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  • Received Date:  14 July 2010
  • Accepted Date:  06 August 2010
  • Published Online:  15 April 2011

Spatiotemporal dynamic analysis of phase synchronized sources based on factor analysis

  • 1. (1)Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China; (2)School of Physical Electronics, University of Electronic Science and Technology of China, Chengdu 610054, China

Abstract: Correlations in time courses of scalp electroencephalogram(EEG) may be represented by the phase synchronization in cerebral cortex sources to a certain some degree. Therefore, it is very important to localize the sources of phase synchronization and find corresponding time courses in the brain imaging study. Based on coupled Rössler oscillators with different coupling strengths, we propose a new method of simulating phase synchronized dipole sources and use a concentric 4-sphere head model to obtain simulation forward scalp EEG data. In addition, we propose the spatiotemporal dynamic analysis of phase synchronized sources based on the maximum likelihood factor analysis, verify the simulated and real scalp EEG data, and further compare the results with those of principal component analysis. Simulation results demonstrate that time courses estimated by maximum likelihood factor analysis have higher correlation with simulated sources, and less locational error between estimated sources and simulated sources. Factor analysis shows a better robust to the spatial resolution and the noise than principal component analysis. Furthermore, real data from spatial attention experiments show that factor analysis is capable of obtaining time courses and spatial distribution under the physiological base.

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