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Characterization of functional diversity of the human brain based on intrinsic connectivity networks

Congying Chu, Lingzhong Fan, Tianzi Jiang
doi: https://doi.org/10.1101/475855
Congying Chu
aBrainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
bNational Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
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Lingzhong Fan
aBrainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
bNational Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
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Tianzi Jiang
aBrainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
bNational Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
cCAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
dQueensland Brain Institute, The University of Queensland, St Lucia, QLD, 4072, Australia
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  • For correspondence: jiangtz@nlpr.ia.ac.cn
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Abstract

Spontaneous fluctuations underlying the brain activity can reflect the intrinsic organization of the system, such as the functional brain networks. In large scale, a network perspective has emerged as a new avenue to explore the functional properties of human brain. Here, we studied functional diversity in healthy subjects based on the network perspective. We hypothesized that the patterns of participation of different functional networks were related with the functional diversity of particular brain regions. Independent component analysis (ICA) was adopted to detect the intrinsic connectivity networks (ICNs) based on the data of resting-state functional MRI. An index of functional diversity (FD index) was proposed to quantitatively describe the degree of anisotropic distribution related with participation of various ICNs. We found that FD index continuously varied across the brain, for example, the primary motor cortex with low FD value and the precuneus with significantly high FD value. The FD values indicated the different functional roles of the corresponding brain regions, which were reflected by the various patterns of participation of ICNs. The FD index can be used as a new approach to quantitatively characterize the functional diversity of human brain, even for the changed functional properties caused by the psychiatric disorders.

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Posted November 24, 2018.
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Characterization of functional diversity of the human brain based on intrinsic connectivity networks
Congying Chu, Lingzhong Fan, Tianzi Jiang
bioRxiv 475855; doi: https://doi.org/10.1101/475855
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Characterization of functional diversity of the human brain based on intrinsic connectivity networks
Congying Chu, Lingzhong Fan, Tianzi Jiang
bioRxiv 475855; doi: https://doi.org/10.1101/475855

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