Approach of Complex Networks for the Determination of Brain Death
SUN Wei-Gang1,2,, CAO Jian-Ting1,3, WANG Ru-Bin1**
1Institute for Cognitive Neurodynamics, School of Science, School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237 2School of Science, Hangzhou Dianzi University, Hangzhou 310018 3Department of Robotics, Saitama Institute of Technology, Saitama 369-0293, Japan
Approach of Complex Networks for the Determination of Brain Death
SUN Wei-Gang1,2,, CAO Jian-Ting1,3, WANG Ru-Bin1**
1Institute for Cognitive Neurodynamics, School of Science, School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237 2School of Science, Hangzhou Dianzi University, Hangzhou 310018 3Department of Robotics, Saitama Institute of Technology, Saitama 369-0293, Japan
摘要In clinical practice, brain death is the irreversible end of all brain activity. Compared to current statistical methods for the determination of brain death, we focus on the approach of complex networks for real-world electroencephalography in its determination. Brain functional networks constructed by correlation analysis are derived, and statistical network quantities used for distinguishing the patients in coma or brain death state, such as average strength, clustering coefficient and average path length, are calculated. Numerical results show that the values of network quantities of patients in coma state are larger than those of patients in brain death state. Our findings might provide valuable insights on the determination of brain death.
Abstract：In clinical practice, brain death is the irreversible end of all brain activity. Compared to current statistical methods for the determination of brain death, we focus on the approach of complex networks for real-world electroencephalography in its determination. Brain functional networks constructed by correlation analysis are derived, and statistical network quantities used for distinguishing the patients in coma or brain death state, such as average strength, clustering coefficient and average path length, are calculated. Numerical results show that the values of network quantities of patients in coma state are larger than those of patients in brain death state. Our findings might provide valuable insights on the determination of brain death.
SUN Wei-Gang;;CAO Jian-Ting;WANG Ru-Bin**
. Approach of Complex Networks for the Determination of Brain Death[J]. 中国物理快报, 2011, 28(6): 68701-068701.
SUN Wei-Gang, , CAO Jian-Ting, WANG Ru-Bin**
. Approach of Complex Networks for the Determination of Brain Death. Chin. Phys. Lett., 2011, 28(6): 68701-068701.
[1] Albert R and Barabási A L 2002 Rev. Mod. Phys. 74 47
[2] Zhou C S, Zemanová L, Zamora-Lopez G et al 2007 New J. Phys. 9 178
[3] Bullmore E and Sporns O 2009 Nature Rev. Neurosci. 10 186
[4] Bales M E and Johnson S B 2006 J. Biomed. Inform. 39 451
[5] Reijneveld J C, Ponten S C, Berendse H W and Stam C J 2007 Clin. Neurophysiol. 118 2317
[6] Watts D J and Strogatz S H 1998 Nature 393 440
[7] Sporns O and Zwi J D 2004 Neuroinformatics 2 145
[8] Barabási A L and Albert R 1999 Science 286 509
[9] Eguíluz V M, Chialvo D R, Cecchi G A et al 2005 Phys. Rev. Lett. 94 018102
[10] Liu Y, Liang M, Zhou Y et al 2008 Brain 131 945
[11] Dubois J M 2010 J. Med. Philos. 35 365
[12] Chen Z, Cao J T, Cao Y et al 2008 Cogn. Neurodyn. 2 257
[13] Cao J T and Chen Z 2007 International Conference on Cognitive Neurodynamics (Shanghai, China 17–21 November 2007) p 699
[14] Yang K, Shi Q W, Cao J T et al 2009 International Conference on Cognitive Neurodynamics (Hangzhou, China 15–19 November 2009) p 729
[15] Fang X L and Jiang Z L 2007 Acta Phys. Sin. 56 7330 (in Chinese)
[16] Barrat A, Barthélemy M, Pastor-Satorras R et al 2004 Proc. Nat. Acad. Sci. 101 3747
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