Task vs. rest-different network configurations between the coactivation and the resting-state brain networks

被引:140
作者
Di, Xin [1 ]
Gohel, Suril [1 ]
Kim, Eun H. [1 ]
Biswal, Bharat B. [1 ]
机构
[1] New Jersey Inst Technol, Dept Biomed Engn, Newark, NJ 07102 USA
关键词
brain network; coactivation; hub shift; meta-analysis; modularity; resting-state; small world; thalamus; HUMAN CEREBRAL-CORTEX; FUNCTIONAL CONNECTIVITY; SMALL-WORLD; STRUCTURAL NETWORKS; VISUAL PATHWAYS; DEFAULT MODE; ARCHITECTURE; THALAMUS; HUBS; COVARIANCE;
D O I
10.3389/fnhum.2013.00493
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
There is a growing interest in studies of human brain networks using resting-state functional magnetic resonance imaging (fMRI). However, it is unclear whether and how brain networks measured during the resting-state exhibit comparable properties to brain networks during task performance. In the present study, we investigated meta-analytic coactivation patterns among brain regions based upon published neuroimaging studies, and compared the coactivation network configurations with those in the resting-state network. The strength of resting-state functional connectivity between two regions were strongly correlated with the coactivation strength. However, the coactivation network showed greater global efficiency, smaller mean clustering coefficient, and lower modularity compared with the resting-state network, which suggest a more efficient global information transmission and between system integrations during task performing. Hub shifts were also observed within the thalamus and the left inferior temporal cortex. The thalamus and the left inferior temporal cortex exhibited higher and lower degrees, respectively in the coactivation network compared with the resting-state network. These results shed light regarding the reconfiguration of the brain networks between task and resting-state conditions, and highlight the role of the thalamus in change of network configurations in task vs. rest.
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收藏
页数:9
相关论文
共 62 条
[21]   Functional and Effective Connectivity: A Review [J].
Friston, Karl J. .
BRAIN CONNECTIVITY, 2011, 1 (01) :13-36
[22]   GRAPH DRAWING BY FORCE-DIRECTED PLACEMENT [J].
FRUCHTERMAN, TMJ ;
REINGOLD, EM .
SOFTWARE-PRACTICE & EXPERIENCE, 1991, 21 (11) :1129-1164
[23]   The Thalamus and Brainstem Act As Key Hubs in Alterations of Human Brain Network Connectivity Induced by Mild Propofol Sedation [J].
Gili, Tommaso ;
Saxena, Neeraj ;
Diukova, Ana ;
Murphy, Kevin ;
Hall, Judith E. ;
Wise, Richard G. .
JOURNAL OF NEUROSCIENCE, 2013, 33 (09) :4024-4031
[24]   Mapping Anatomical Connectivity Patterns of Human Cerebral Cortex Using In Vivo Diffusion Tensor Imaging Tractography [J].
Gong, Gaolang ;
He, Yong ;
Concha, Luis ;
Lebel, Catherine ;
Gross, Donald W. ;
Evans, Alan C. ;
Beaulieu, Christian .
CEREBRAL CORTEX, 2009, 19 (03) :524-536
[25]   Functional connectivity in the resting brain: A network analysis of the default mode hypothesis [J].
Greicius, MD ;
Krasnow, B ;
Reiss, AL ;
Menon, V .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2003, 100 (01) :253-258
[26]  
Guillery RW, 1995, J ANAT, V187, P583
[27]   Mapping Human Whole-Brain Structural Networks with Diffusion MRI [J].
Hagmann, Patric ;
Kurant, Maciej ;
Gigandet, Xavier ;
Thiran, Patrick ;
Wedeen, Van J. ;
Meuli, Reto ;
Thiran, Jean-Philippe .
PLOS ONE, 2007, 2 (07)
[28]   Comparison of characteristics between region-and voxel-based network analyses in resting-state fMRI data [J].
Hayasaka, Satoru ;
Laurienti, Paul J. .
NEUROIMAGE, 2010, 50 (02) :499-508
[29]   Structural insights into aberrant topological patterns of large-scale cortical networks in Alzheimer's Disease [J].
He, Yong ;
Chen, Zhang ;
Evans, Alan .
JOURNAL OF NEUROSCIENCE, 2008, 28 (18) :4756-4766
[30]   INTERCORRELATIONS OF GLUCOSE METABOLIC RATES BETWEEN BRAIN-REGIONS - APPLICATION TO HEALTHY-MALES IN A STATE OF REDUCED SENSORY INPUT [J].
HORWITZ, B ;
DUARA, R ;
RAPOPORT, SI .
JOURNAL OF CEREBRAL BLOOD FLOW AND METABOLISM, 1984, 4 (04) :484-499