Group-PCA for very large fMRI datasets

NeuroImage

Volumn 101, Issue , 2014, Pages 738-749

  Smith, Stephen M ^a   Hyvärinen, Aapo ^b   Varoquaux, Gaël ^c   Miller, Karla L ^a   Beckmann, Christian F ^a,d  

^a UNIVERSITY OF OXFORD   (United Kingdom)

^b UNIVERSITY OF HELSINKI   (Finland)

^c INRIA SACLAY   (France)

^d RADBOUD UNIVERSITY   (Netherlands)

Author keywords

Big data; FMRI; ICA; PCA

Indexed keywords

ACCURACY; ARTICLE; CONNECTOME; DATA BASE; DATA PROCESSING; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; INTERMETHOD COMPARISON; MATHEMATICAL PARAMETERS; PRINCIPAL COMPONENT ANALYSIS; RESTING STATE NETWORK; SIMULATION; TEMPORAL CONCATENATION; VALIDATION STUDY; WHITE NOISE; ARTIFACT; COMPUTER SIMULATION; NUCLEAR MAGNETIC RESONANCE IMAGING; PROCEDURES; STATISTICAL ANALYSIS;

ARTIFACTS; COMPUTER SIMULATION; CONNECTOME; DATA INTERPRETATION, STATISTICAL; HUMANS; MAGNETIC RESONANCE IMAGING; PRINCIPAL COMPONENT ANALYSIS;

EID: 84907056848     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2014.07.051     Document Type: Article

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