A spatio-temporal nonparametric Bayesian variable selection model of fMRI data for clustering correlated time courses

NeuroImage

Volumn 95, Issue , 2014, Pages 162-175

  Zhang, Linlin ^a   Guindani, Michele ^b   Versace, Francesco ^b   Vannucci, Marina ^a  

^a Rice University   (United States)

^b UNIVERSITY OF TEXAS MD ANDERSON CANCER CENTER   (United States)

Author keywords

Bayesian nonparametric; Dirichlet process prior; Discrete wavelet transform; FMRI; Long memory errors; Markov random field prior

Indexed keywords

ACCURACY; ALGORITHM; ARTICLE; BAYES THEOREM; BRAIN REGION; BRAIN SIZE; DATA ANALYSIS; FUNCTIONAL MAGNETIC RESONANCE IMAGING; MATHEMATICAL MODEL; MONTE CARLO METHOD; PRIORITY JOURNAL; PROBABILITY; REGRESSION ANALYSIS; SIGNAL NOISE RATIO; SIMULATION; SPATIOTEMPORAL ANALYSIS; STATISTICAL DISTRIBUTION; STIMULUS RESPONSE; WAVELET ANALYSIS; BIOLOGICAL MODEL; BRAIN MAPPING; CLUSTER ANALYSIS; HUMAN; IMAGE PROCESSING; NUCLEAR MAGNETIC RESONANCE IMAGING; PROCEDURES;

ALGORITHMS; BAYES THEOREM; BRAIN MAPPING; CLUSTER ANALYSIS; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MODELS, NEUROLOGICAL;

EID: 84899692109     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2014.03.024     Document Type: Article

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