Bayesian models for functional magnetic resonance imaging data analysis

Wiley Interdisciplinary Reviews: Computational Statistics

Volumn 7, Issue 1, 2015, Pages 21-41

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

^a Rice University   (United States)

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

Author keywords

Bayesian statistics; Brain connectivity; Classification and prediction; fMRI; Spatiotemporal activation models

Indexed keywords

BAYESIAN NETWORKS; BRAIN; CHEMICAL ACTIVATION; DIFFUSION TENSOR IMAGING; ELECTROPHYSIOLOGY; MAGNETIC RESONANCE IMAGING; TENSORS;

ACTIVATION MODELS; BAYESIAN STATISTICS; BRAIN CONNECTIVITY; FMRI; FULLY BAYESIAN APPROACHES; FUNCTIONAL MAGNETIC RESONANCE IMAGING; SPATIAL AND TEMPORAL CORRELATION; SPATIO-TEMPORAL MODELS;

FUNCTIONAL NEUROIMAGING;

EID: 84919444733     PISSN: 19395108     EISSN: 19390068     Source Type: Journal    
DOI: 10.1002/wics.1339     Document Type: Article

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