Brain parcellation driven by dynamic functional connectivity better capture intrinsic network dynamics

Until now, dynamic functional connectivity (dFC) based on functional magnetic resonance imaging is typically estimated on a set of predefined regions of interest (ROIs) derived from an anatomical or static functional atlas which follows an implicit assumption of functional homogeneity within ROIs un...

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Bibliographic Details
Published in:	Human brain mapping Vol. 42; no. 5; pp. 1416 - 1433
Main Authors:	Fan, Liangwei, Zhong, Qi, Qin, Jian, Li, Na, Su, Jianpo, Zeng, Ling‐Li, Hu, Dewen, Shen, Hui
Format:	Journal Article
Language:	English
Published:	Hoboken, USA John Wiley & Sons, Inc 01-04-2021
Subjects:	Adult Atlases as Topic Brain Brain mapping brain network Cerebellum - diagnostic imaging Cerebellum - physiology Cerebral Cortex - diagnostic imaging Cerebral Cortex - physiology Cognitive ability Computational neuroscience Connectome - methods Connectome - standards Default Mode Network - diagnostic imaging Default Mode Network - physiology dynamic functional connectivity functional connectivity degree Functional magnetic resonance imaging Functional morphology Homogeneity Humans Image Processing, Computer-Assisted - methods Image Processing, Computer-Assisted - standards Independent component analysis Intelligence Magnetic resonance imaging Magnetic Resonance Imaging - methods Magnetic Resonance Imaging - standards Nerve Net - diagnostic imaging Nerve Net - physiology Nervous system Neural networks Neuroimaging Neurosciences resting‐state fMRI Support Vector Machine Time Factors dynamic functional connectivity independent component analysis resting-state fMRI brain network functional connectivity degree
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