Building and Clustering Analysis of Brain Functional Network in Acupuncture

Dong Dong Liang; Hai Yang Wang; Li Jun  Zhong

doi:10.4028/www.scientific.net/AMR.710.633

Paper Titles

Abnormal Image Monitoring for Transmission Line Based on Digital Image Processing
p.613

A Rough-Fuzzy RBF Neural Network Based on PSO Algorithm
p.617

The Research of Infrared Image Generation Method Based on the OGRE
p.623

The Application of Modified BP Neural Network Method to the Evaluation of the Quality of Teaching
p.628

Building and Clustering Analysis of Brain Functional Network in Acupuncture
p.633

An Improved SDIF Radar Pulse Signal Main Sorting Algorithm
p.637

Research on Algorithm of Boolean Function Isomorphism Decision Based on ROBDD
p.642

Parameter Optimization of Street-Phelps Model Based on Particle Swarm Optimization
p.647

Multi-Objective Optimization of Automobile Powertrain Based on Genetic Algorithm
p.651

HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 710Building and Clustering Analysis of Brain...

Building and Clustering Analysis of Brain Functional Network in Acupuncture

Abstract:

Aimed at exploring the mechanism of acupuncture therapy, we develop functional brain networks using electroencephalogram (EEG) data, and use the methods cluster coefficient to analyze the functional networks. We develop the following result: during the acupuncture, the structure of network becomes tighter, the relativity grows stronger and the structure of the networks becomes complex. Our conclusion is that acupuncture is able to affect the firing properties of the central nervous system, and make the information transmission in the brain functional sections stronger.

You might also be interested in these eBooks

Advanced Technologies and Solutions in Industry

View Preview

Info:

Periodical:

Advanced Materials Research (Volume 710)

Pages:

633-636

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.710.633

Citation:

Cite this paper

Online since:

June 2013

Authors:

Dong Dong Liang, Hai Yang Wang, Li Jun Zhong

Keywords:

Acupuncture, Cluster Coefficient, Functional Network

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] M.T. Wu, J.M. Sheen, K.H. Chuang: NeuroImage Vol. 16 (2002), p.1028.

Google Scholar

[2] G. Litscher. European Journal of Anaesthesiology Vol. 21 (2004), p.13.

Google Scholar

[3] A.C. Chen, F.J. Liu, L. Wang, L Arendt-Nielsen: Neuroimage Vol. 29 (2006), p.1080.

Google Scholar

[4] X.L. Fang and Z.L. Jiang: Acta Physica Sinica Vol. 56 (2007), p.7330.

Google Scholar

[5] J.M.J. Murre and D.P.F. Sturdy: Biological cybernetics Vol. 73 (1995), p.529.

Google Scholar

[6] K.J. Friston: Human Brain Mapping Vol. 2 (1994), p.56.

Google Scholar

[7] K.J. Friston: Annual Review of Psychology Vol.56 (2005), p.57.

Google Scholar

[8] K.J. Friston, L. Harrison and W. Penny: NeuroImage Vol. 19 (2003), p.1273.

Google Scholar

[9] K.A. Schindler, S. Bialonski, M.T. Horstmann, C.E. Elger and K. Lehnertz: Chaos Vol. 18 (2008), p.033119.

DOI: 10.1063/1.2966112

Google Scholar

[10] C.J. Stam, B.F. Jones, G. Nolte, M. Breakspear and P.H. Scheltens: Cerebral Cortex Vol. 17 (2007), p.92.

Google Scholar

[11] D.S. Bassett, A. Meyer-Lindenberg, S. Achard, T. Duke and E.T. Bullmore: Proceedings of the National Academu of Sciences of the United States of America Vol. 103 (2006), p.19518.

Google Scholar

[12] S.C. Ponten, F. Bartolomei and C.J. Stam: Clinical neurophysiology Vol. (2007), p.918.

Google Scholar

[13] V.M. Eguiluz, D.R. Chialvo, G.A. Cecchi, M. Baliki, A.V. Apkarian: Physical Review Letters Vol. 94 (2005), p.018102.

Google Scholar