A computationally efficient, exploratory approach to brain connectivity incorporating false discovery rate control, a priori knowledge, and group inference

Computational and Mathematical Methods in Medicine

Volumn 2012, Issue , 2012, Pages

  Liu, Aiping ^a   Li, Junning ^b   Wang, Z Jane ^a   McKeown, Martin J ^a  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL EFFICIENCY;

BIOLOGICAL INTERPRETATION; BRAIN CONNECTIVITY; COMPUTATIONALLY EFFICIENT; FALSE DISCOVERY RATE; FUNCTIONAL NEUROIMAGING DATA; MULTIVARIATE TIME SERIES; PARKINSON'S DISEASE; PRIORI INFORMATION;

FUNCTIONAL NEUROIMAGING;

LEVODOPA;

ALGORITHM; ARTICLE; BRAIN FUNCTION; CLINICAL ARTICLE; CONTROLLED STUDY; FALSE DISCOVERY RATE; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; NERVE CELL NETWORK; NEUROIMAGING; PARKINSON DISEASE; PETER SPIRTES AND CLARK GLYMOUR ALGORITHM; SIMULATION; TIME SERIES ANALYSIS; BAYES THEOREM; BIOLOGICAL MODEL; BRAIN; BRAIN MAPPING; COMPUTER GRAPHICS; COMPUTER SIMULATION; LABORATORY DIAGNOSIS; METABOLISM; METHODOLOGY; MULTIVARIATE ANALYSIS; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; PHYSIOLOGY; PROBABILITY; STATISTICAL MODEL; THEORETICAL MODEL;

ALGORITHMS; BAYES THEOREM; BRAIN; BRAIN MAPPING; COMPUTER GRAPHICS; COMPUTER SIMULATION; FALSE POSITIVE REACTIONS; HUMANS; LEVODOPA; MAGNETIC RESONANCE IMAGING; MODELS, BIOLOGICAL; MODELS, STATISTICAL; MODELS, THEORETICAL; MULTIVARIATE ANALYSIS; PARKINSON DISEASE; PROBABILITY;

EID: 84870205364     PISSN: 1748670X     EISSN: 17486718     Source Type: Journal    
DOI: 10.1155/2012/967380     Document Type: Article

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