Large-scale probabilistic functional modes from resting state fMRI

NeuroImage

Volumn 109, Issue , 2015, Pages 217-231

  Harrison, Samuel J ^a,b   Woolrich, Mark W ^a   Robinson, Emma C ^a   Glasser, Matthew F ^c   Beckmann, Christian F ^a,d   Jenkinson, Mark ^a   Smith, Stephen M ^a  

^a UNIVERSITY OF OXFORD   (United Kingdom)

^b Life Sciences Interface Doctoral Training Centre   (United Kingdom)

^c WASHINGTON UNIVERSITY   (United States)

^d RADBOUD UNIVERSITY   (Netherlands)

Author keywords

Bayesian modelling; Functional parcellation; ICA; Resting state fMRI; Subject variability

Indexed keywords

ARTICLE; BAYES THEOREM; BRAIN FUNCTION; CONTROLLED STUDY; DATA ANALYSIS; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HEMODYNAMICS; INDEPENDENT COMPONENT ANALYSIS; NEUROIMAGING; RESTING STATE FUNCTIONAL MAGNETIC RESONANCE IMAGING; SPATIOTEMPORAL ANALYSIS; BRAIN; COMPUTER SIMULATION; CONNECTOME; HUMAN; IMAGE PROCESSING; NUCLEAR MAGNETIC RESONANCE IMAGING; PHYSIOLOGY; PROBABILITY; PROCEDURES; SIGNAL PROCESSING;

BRAIN; COMPUTER SIMULATION; CONNECTOME; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; PROBABILITY; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 84921725194     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2015.01.013     Document Type: Article

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