Exploring the economical small-world characteristics of human brain functional networks based on electroencephalogram data

2015 ◽  
pp. 119-123
Author(s):  
Lulu Wang ◽  
Wentao Huang ◽  
Lianhong Yu ◽  
Junfeng Gao ◽  
Chong Zhang
Keyword(s):  
Human Brain ◽  
Small World ◽  
Functional Networks ◽  
Brain Functional Networks

scholarly journals Adaptive reconfiguration of fractal small-world human brain functional networks

2006 ◽  
Vol 103 (51) ◽  
pp. 19518-19523 ◽  
Author(s):  
D. S. Bassett ◽  
A. Meyer-Lindenberg ◽  
S. Achard ◽  
T. Duke ◽  
E. Bullmore
Keyword(s):  
Human Brain ◽  
Small World ◽  
Functional Networks ◽  
Brain Functional Networks

Different Correlation Metrics Reveal Different Topological Patterns in the Human Brain Functional Networks

NeuroImage ◽  
2009 ◽  
Vol 47 ◽  
pp. S170
Author(s):  
X Liang ◽  
JH Wang ◽  
CG Yan ◽  
J Kang ◽  
H Yang ◽  
...  
Keyword(s):  
Human Brain ◽  
Functional Networks ◽  
Brain Functional Networks

scholarly journals Stress-induced changes in modular organizations of human brain functional networks

2020 ◽  
Vol 13 ◽  
pp. 100231 ◽  
Author(s):  
Yuan Zhang ◽  
Zhongxiang Dai ◽  
Jianping Hu ◽  
Shaozheng Qin ◽  
Rongjun Yu ◽  
...  
Keyword(s):  
Human Brain ◽  
Functional Networks ◽  
Brain Functional Networks ◽  
Induced Changes

scholarly journals Frequency-specific task modulation of human brain functional networks: A fast fMRI study

NeuroImage ◽  
2021 ◽  
Vol 224 ◽  
pp. 117375
Author(s):  
Shuntaro Sasai ◽  
Takahiko Koike ◽  
Sho K. Sugawara ◽  
Yuki H. Hamano ◽  
Motofumi Sumiya ◽  
...  
Keyword(s):  
Human Brain ◽  
Functional Networks ◽  
Specific Task ◽  
Brain Functional Networks ◽  
Fmri Study

scholarly journals Robust dynamic community detection with applications to human brain functional networks

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
L.-E. Martinet ◽  
M. A. Kramer ◽  
W. Viles ◽  
L. N. Perkins ◽  
E. Spencer ◽  
...  
Keyword(s):  
Human Brain ◽  
Community Detection ◽  
Functional Networks ◽  
Brain Functional Networks ◽  
Dynamic Community Detection ◽  
Dynamic Community

scholarly journals Sample Entropy Combined with the K-Means Clustering Algorithm Reveals Six Functional Networks of the Brain

Entropy ◽  
2019 ◽  
Vol 21 (12) ◽  
pp. 1156 ◽  
Author(s):  
Yanbing Jia ◽  
Huaguang Gu
Keyword(s):  
Human Brain ◽  
Resting State ◽  
Clustering Algorithm ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Sample Entropy ◽  
Blood Oxygenation ◽  
Fmri Data ◽  
Functional Networks ◽  
Brain Functional Networks

Identifying brain regions contained in brain functional networks and functions of brain functional networks is of great significance in understanding the complexity of the human brain. The 160 regions of interest (ROIs) in the human brain determined by the Dosenbach’s template have been divided into six functional networks with different functions. In the present paper, the complexity of the human brain is characterized by the sample entropy (SampEn) of dynamic functional connectivity (FC) which is obtained by analyzing the resting-state functional magnetic resonance imaging (fMRI) data acquired from healthy participants. The 160 ROIs are clustered into six clusters by applying the K-means clustering algorithm to the SampEn of dynamic FC as well as the static FC which is also obtained by analyzing the resting-state fMRI data. The six clusters obtained from the SampEn of dynamic FC and the static FC show very high overlap and consistency ratios with the six functional networks. Furthermore, for four of six clusters, the overlap ratios corresponding to the SampEn of dynamic FC are larger than that corresponding to the static FC, and for five of six clusters, the consistency ratios corresponding to the SampEn of dynamic FC are larger than that corresponding to the static FC. The results show that the combination of machine learning methods and the FC obtained using the blood oxygenation level-dependent (BOLD) signals can identify the functional networks of the human brain, and nonlinear dynamic characteristics of the FC are more effective than the static characteristics of the FC in identifying brain functional networks and the complexity of the human brain.

scholarly journals Altered small-world brain functional networks in children with attention-deficit/hyperactivity disorder

2008 ◽  
Vol 30 (2) ◽  
pp. 638-649 ◽  
Author(s):  
Liang Wang ◽  
Chaozhe Zhu ◽  
Yong He ◽  
Yufeng Zang ◽  
QingJiu Cao ◽  
...  
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Attention Deficit ◽  
Small World ◽  
Functional Networks ◽  
Hyperactivity Disorder ◽  
Brain Functional Networks ◽  
World Brain

A study on small-world brain functional networks altered by postherpetic neuralgia

2014 ◽  
Vol 32 (4) ◽  
pp. 359-365 ◽  
Author(s):  
Yue Zhang ◽  
Jing Liu ◽  
Longchuan Li ◽  
Minyi Du ◽  
Wenxue Fang ◽  
...  
Keyword(s):  
Postherpetic Neuralgia ◽  
Small World ◽  
Functional Networks ◽  
Brain Functional Networks ◽  
World Brain
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