Multivariate dynamical systems models for estimating causal interactions in fMRI

NeuroImage

Volumn 54, Issue 2, 2011, Pages 807-823

  Ryali, Srikanth ^a   Supekar, Kaustubh ^a   Chen, Tianwen ^a   Menon, Vinod ^a  

^a STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Bilinear; Causality; Deconvolution; Dynamical systems; Expectation maximization; Kalman smoother; Variational Bayes

Indexed keywords

OXYGEN;

ARTICLE; BAYES THEOREM; BRAIN BLOOD FLOW; BRAIN OXYGEN CONSUMPTION; BRAIN REGION; CAUSAL MODELING; COGNITION; COMPUTER SIMULATION; CONTROLLED STUDY; FUNCTIONAL MAGNETIC RESONANCE IMAGING; INFORMATION PROCESSING; INTERMETHOD COMPARISON; MATHEMATICAL ANALYSIS; MAXIMUM LIKELIHOOD METHOD; NERVE CELL; PRIORITY JOURNAL; PROBABILITY; SIGNAL NOISE RATIO; SIGNAL PROCESSING;

ALGORITHMS; ANIMALS; BAYES THEOREM; BRAIN; HEMODYNAMICS; HUMANS; MAGNETIC RESONANCE IMAGING; MODELS, NEUROLOGICAL;

EID: 78649648075     PISSN: 10538119     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2010.09.052     Document Type: Article

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