Structural degree predicts functional network connectivity: A multimodal resting-state fMRI and MEG study

NeuroImage

Volumn 97, Issue , 2014, Pages 296-307

  Tewarie, P ^a   Hillebrand, A ^a   van Dellen, E ^a,b,c   Schoonheim, M M ^a   Barkhof, F ^a   Polman, C H ^a   Beaulieu, C ^d   Gong, G ^e   van Dijk, B W ^a   Stam, C J ^a  

^a VU UNIVERSITY MEDICAL CENTER   (Netherlands)

^b VU UNIVERSITY MEDICAL CENTER   (Netherlands)

^c UNIVERSITY MEDICAL CENTER UTRECHT   (Netherlands)

^d UNIVERSITY OF ALBERTA   (Canada)

^e BEIJING NORMAL UNIVERSITY   (China)

Author keywords

Degree product; Euclidean distance; FMRI; Functional connectivity; Functional networks; MEG; Neural mass; Structural networks

Indexed keywords

ADULT; ARTICLE; BRAIN REGION; DATA PROCESSING; EUCLIDEAN DISTANCE; FUNCTIONAL MAGNETIC RESONANCE IMAGING; FUNCTIONAL NETWORK CONNECTIVITY; HUMAN; HUMAN EXPERIMENT; INFORMATION PROCESSING; MAGNETOENCEPHALOGRAPHY; MATHEMATICAL PARAMETERS; NERVOUS SYSTEM PARAMETERS; NEUROIMAGING; NORMAL HUMAN; NUCLEAR MAGNETIC RESONANCE SCANNER; PREDICTION; PRIORITY JOURNAL; RESTING STATE NETWORK; ALGORITHM; ANATOMY AND HISTOLOGY; FEMALE; IMAGE PROCESSING; MALE; NERVE CELL NETWORK; NERVE TRACT; NUCLEAR MAGNETIC RESONANCE IMAGING; PHYSIOLOGY; PROCEDURES;

ADULT; ALGORITHMS; FEMALE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MAGNETOENCEPHALOGRAPHY; MALE; NERVE NET; NEURAL PATHWAYS;

EID: 84901398994     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2014.04.038     Document Type: Article

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