Task-driven ICA feature generation for accurate and interpretable prediction using fMRI

NeuroImage

Volumn 60, Issue 1, 2012, Pages 189-203

  Duff, Eugene P ^a   Trachtenberg, Aaron J ^b   Mackay, Clare E ^a,b   Howard, Matt A ^c   Wilson, Frederick ^d   Smith, Stephen M ^a   Woolrich, Mark W ^a  

^a UNIVERSITY OF OXFORD   (United Kingdom)

^b WARNEFORD HOSPITAL   (United Kingdom)

^c KING'S COLLEGE LONDON   (United Kingdom)

^d PFIZER GLOBAL RESEARCH AND DEVELOPMENT   (United Kingdom)

Author keywords

Feature generation; Feature selection; FMRI; ICA; MPVA; Parcellation; Prediction

Indexed keywords

ACCURACY; ADULT; ARTICLE; BRAIN REGION; CONTROLLED STUDY; DISCRIMINATIVE STIMULUS; FEMALE; FUNCTIONAL MAGNETIC RESONANCE IMAGING; FUNCTIONAL NEUROIMAGING; HUMAN; HUMAN EXPERIMENT; INDEPENDENT COMPONENT ANALYSIS; MALE; MEMBRANE STEADY POTENTIAL; MENTAL TASK; NERVE CELL NETWORK; NEUROANATOMY; NEUROLOGIC EXAMINATION; NORMAL HUMAN; PREDICTION; PRIORITY JOURNAL; REDUNDANCY ANALYSIS; RELIABILITY; SIGNAL NOISE RATIO; STIMULUS RESPONSE; TASK PERFORMANCE; VALIDATION PROCESS; VISUAL DISCRIMINATION; VISUAL STIMULATION;

ADULT; BRAIN; BRAIN MAPPING; FEMALE; HUMANS; MAGNETIC RESONANCE IMAGING; MALE; PREDICTIVE VALUE OF TESTS; PRINCIPAL COMPONENT ANALYSIS; REPRODUCIBILITY OF RESULTS; TASK PERFORMANCE AND ANALYSIS;

EID: 84862797445     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2011.12.053     Document Type: Article

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