Multisensory bayesian inference depends on synapse maturation during training: Theoretical analysis and neural modeling implementation

Neural Computation

Volumn 29, Issue 3, 2017, Pages 735-782

  Ursino, Mauro ^a   Cuppini, Cristiano ^a   Magosso, Elisa ^a  

^a UNIVERSITY OF BOLOGNA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

CHAINS; ENCODING (SYMBOLS); INFERENCE ENGINES; MAXIMUM LIKELIHOOD; MAXIMUM LIKELIHOOD ESTIMATION; NEURAL NETWORKS; NEURONS; TOPOLOGY;

AUDIO-VISUAL INTEGRATION; BAYESIAN INFERENCE; LIKELIHOOD FUNCTIONS; MAXIMUM LIKELIHOOD ESTIMATE; MODERATE-DEVIATIONS; NEURAL NETWORK MODEL; PRIOR PROBABILITY; PROBABILITY FUNCTIONS;

BAYESIAN NETWORKS;

ANIMAL; AUDITORY STIMULATION; BAYES THEOREM; BIOLOGICAL MODEL; BRAIN; COMPUTER SIMULATION; CYTOLOGY; HUMAN; LEARNING; NERVE CELL; PHOTOSTIMULATION; PHYSIOLOGY; SENSORY NERVE; SYNAPSE;

ACOUSTIC STIMULATION; AFFERENT PATHWAYS; ANIMALS; BAYES THEOREM; BRAIN; COMPUTER SIMULATION; HUMANS; LEARNING; MODELS, NEUROLOGICAL; NEURONS; PHOTIC STIMULATION; SYNAPSES;

EID: 85013683182     PISSN: 08997667     EISSN: 1530888X     Source Type: Journal    
DOI: 10.1162/NECO_a_00935     Document Type: Letter

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