Computational inference of neural information flow networks

PLoS Computational Biology

Volumn 2, Issue 11, 2006, Pages 1436-1449

  Smith, V Anne ^a,e   Yu, Jing ^a,b,f   Smulders, Tom V ^c   Hartemink, Alexander J ^d   Jarvis, Erich D ^a  

^a DUKE UNIVERSITY MEDICAL CENTER   (United States)

^b Duke University   (United States)

^c NEWCASTLE UNIVERSITY   (United Kingdom)

^d Duke University   (United States)

^e UNIVERSITY OF ST ANDREWS   (United Kingdom)

^f NOVARTIS INSTITUTES FOR BIOMEDICAL RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORKS; GENE EXPRESSION; INFERENCE ENGINES; MICROELECTRODES;

BAYESIAN NETWORK INFERENCE; BRAIN PATHWAYS; COMPUTATIONAL INFERENCES; DYNAMIC BAYESIAN NETWORKS; INFERENCE ALGORITHM; INFORMATION FLOW NETWORKS; INFORMATION FLOWS; LEARN+; NEURAL INFORMATION; NEURAL INTERACTIONS;

ELECTROPHYSIOLOGY;

ALGORITHM; ANIMAL EXPERIMENT; ARTICLE; AUDITORY CORTEX; BAYES THEOREM; CONTROLLED STUDY; ELECTROPHYSIOLOGY; FEEDBACK SYSTEM; FEMALE; GENE EXPRESSION; MATHEMATICAL COMPUTING; MICROARRAY ANALYSIS; MICROELECTRODE; NERVE CELL NETWORK; NONHUMAN; SONGBIRD; SOUND; ACTION POTENTIAL; ANIMAL; BIOLOGICAL MODEL; COMPUTER SIMULATION; ELECTROENCEPHALOGRAPHY; EVOKED AUDITORY RESPONSE; FINCH; HEARING; INFORMATION SCIENCE; METHODOLOGY; PHYSIOLOGY; SYNAPTIC TRANSMISSION;

ANIMALIA; AVES; PASSERI;

ACTION POTENTIALS; ANIMALS; AUDITORY CORTEX; AUDITORY PERCEPTION; COMPUTER SIMULATION; ELECTROENCEPHALOGRAPHY; EVOKED POTENTIALS, AUDITORY; FINCHES; INFORMATION THEORY; MODELS, NEUROLOGICAL; NERVE NET; SYNAPTIC TRANSMISSION;

EID: 33751407959     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.0020161     Document Type: Article

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