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Static and dynamic functional connectivity analysis based on resting state functional magnetic resonance imaging and its progress
CHEN Yi  YU Chengxin 

Cite this article as: Chen Y, Yu CX. Static and dynamic functional connectivity analysis based on resting state functional magnetic resonance imaging and its progress. Chin J Magn Reson Imaging, 2019, 10(8): 637-640. DOI:10.12015/issn.1674-8034.2019.08.017.


[Abstract] In clinical medical research, based on resting-state functional magnetic resonance imaging, functional connectivity analysis method can be used to study the neurological mechanism of diseases, including static functional connectivity and dynamic functional connectivity. Static functional connectivity mainly includes model-driven analysis for assessing connectivity among regions or seeds, data-driven analysis for estimating spatial functional network maps and functional network connectivity analysis. Dynamic functional connectivity includes sliding time-window and windowless method. Dynamic functional connectivity analysis can respond to time-varying functional connectivity changes. The analysis of functional connectivity is critical, because the analysis method will greatly affect the accuracy of identification and individual classification of neurological disease biomarkers.
[Keywords] functional magnetic resonance；functional connectivity；static functional connectivity；dynamic functional connection

CHEN Yi The First College of Clinical Medical Science, Three Gorges University, Yichang 443000, China

YU Chengxin* The First College of Clinical Medical Science, Three Gorges University, Yichang 443000, China; Department of Radiology, Yichang Central People’s Hospital, Yichang 443000, China

*Corresponding to: Yu CX, E-mail: ycyucx@163.com

Conflicts of interest   None.

Received  2019-02-25
Accepted  2019-05-08
DOI: 10.12015/issn.1674-8034.2019.08.017
Cite this article as: Chen Y, Yu CX. Static and dynamic functional connectivity analysis based on resting state functional magnetic resonance imaging and its progress. Chin J Magn Reson Imaging, 2019, 10(8): 637-640. DOI:10.12015/issn.1674-8034.2019.08.017.

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