Effective connectivity analysis of default mode network based on the bayesian network learning approach

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volumn 7262, Issue , 2009, Pages

  Li, Rui ^a   Chen, Kewei ^b   Zhang, Nan ^a   Fleisher, Adam S ^b   Yao, Li ^a   Wu, Xia ^a  

^a BEIJING NORMAL UNIVERSITY   (China)

^b BANNER ALZHEIMER S INSTITUTE   (United States)

Author keywords

Bayesian network (BN); Default mode network (DMN); Effective connectivity; Hippocampus (HC); Network refining; Posterior cingulate cortex (PCC); Statistical significance testing

Indexed keywords

DEFAULT MODE NETWORK (DMN); EFFECTIVE CONNECTIVITY; HIPPOCAMPUS (HC); NETWORK REFINING; POSTERIOR CINGULATE CORTEX (PCC); STATISTICAL SIGNIFICANCE TESTING;

BRAIN; DISTRIBUTED PARAMETER NETWORKS; EDUCATION; INDEPENDENT COMPONENT ANALYSIS; INFERENCE ENGINES; INTELLIGENT NETWORKS; MAGNETIC RESONANCE IMAGING; MEDICAL IMAGING; REFINING; REGRESSION ANALYSIS; SPEECH ANALYSIS; STATISTICAL TESTS;

BAYESIAN NETWORKS;

EID: 67249145323     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.810893     Document Type: Conference Paper

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