Anatomically informed Bayesian model selection for fMRI group data analysis

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5762 LNCS, Issue PART 2, 2009, Pages 450-457

  Keller, Merlin ^a,b,c   Lavielle, Marc ^b,e   Perrot, Matthieu ^a,d   Roche, Alexis ^a  

^a DIF   (France)

^b UNIVERSITÉ PARIS SACLAY   (France)

^c INRIA SACLAY   (France)

^d INSERM   (France)

^e UNIVERSITÉ PARIS DESCARTES   (France)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN; BAYESIAN MODEL SELECTION; COGNITIVE TASK; DATA ANALYSIS; FALSE NEGATIVES; FALSE POSITIVE; FUNCTIONAL NETWORK; MENTAL CALCULATIONS; NEW APPROACHES; POSTERIOR PROBABILITY; STATISTICAL PARAMETRIC MAPPING; TESTING METHOD;

BAYESIAN NETWORKS; CHEMICAL ACTIVATION; MEDICAL COMPUTING;

DATA HANDLING;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; BAYES THEOREM; BIOLOGICAL MODEL; BRAIN; BRAIN MAPPING; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; EVOKED RESPONSE; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; PHYSIOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; BAYES THEOREM; BRAIN; BRAIN MAPPING; COMPUTER SIMULATION; EVOKED POTENTIALS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MODELS, NEUROLOGICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

EID: 84860346729     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04271-3_55     Document Type: Conference Paper

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