Network Plasticity as Bayesian Inference

PLoS Computational Biology

Volumn 11, Issue 11, 2015, Pages

  Kappel, David ^a   Habenschuss, Stefan ^a   Legenstein, Robert ^a   Maass, Wolfgang ^a  

^a GRAZ UNIVERSITY OF TECHNOLOGY   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORKS; INFERENCE ENGINES; STOCHASTIC SYSTEMS;

BAYESIAN INFERENCE; BRAIN COMPUTATION; BRAIN PLASTICITY; CORTICAL NETWORK; NETWORK OF NEURONS; NETWORK PLASTICITY; PROBABILISTIC INFERENCE; STATISTICAL LEARNING THEORY; STOCHASTIC FEATURES; SYNAPTIC PLASTICITY;

MAXIMUM LIKELIHOOD;

EXPERIMENTAL MODEL; LEARNING THEORY; MAXIMUM LIKELIHOOD METHOD; MODEL; NERVE CELL PLASTICITY; PLASTICITY; PROBABILITY; SAMPLING; SPINE; STOCHASTIC MODEL; ACTION POTENTIAL; BAYES THEOREM; BIOLOGICAL MODEL; BIOLOGY; COMPUTER SIMULATION; NERVE CELL; NERVE CELL NETWORK; PHYSIOLOGY;

ACTION POTENTIALS; BAYES THEOREM; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; MODELS, NEUROLOGICAL; NERVE NET; NEURONAL PLASTICITY; NEURONS;

EID: 84949292982     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1004485     Document Type: Article

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