Ensembles of Spiking Neurons with Noise Support Optimal Probabilistic Inference in a Dynamically Changing Environment

PLoS Computational Biology

Volumn 10, Issue 10, 2014, Pages

  Legenstein, Robert ^a   Maass, Wolfgang ^a  

^a GRAZ UNIVERSITY OF TECHNOLOGY   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

NEURAL NETWORKS; NEURONS; PROBABILITY DISTRIBUTIONS; STOCHASTIC SYSTEMS;

CHANGING ENVIRONMENT; ENCODINGS; NETWORK STATE; PROBABILISTIC INFERENCE; PROBABILISTIC INFORMATION; PROBABILITY: DISTRIBUTIONS; SIMPLE++; SINGLE NEURON; SPIKING NEURONES; STOCHASTICS;

RANDOM VARIABLES;

ALGORITHM; ARTICLE; BAYESIAN LEARNING; BRAIN NERVE CELL; COMPUTER SIMULATION; CONTROLLED STUDY; ENVIRONMENTAL CHANGE; EXCITATORY POSTSYNAPTIC POTENTIAL; MATHEMATICAL COMPUTING; MONTE CARLO METHOD; NERVE CELL NETWORK; ONLINE SYSTEM; PREMOTOR CORTEX; PROBABILITY; REWARD; SIGNAL NOISE RATIO; SPIKE WAVE; STOCHASTIC MODEL; ACTION POTENTIAL; ANIMAL; BIOLOGICAL MODEL; BIOLOGY; CYTOLOGY; MOTOR CORTEX; NERVE CELL; PHYSIOLOGY; RAT; STATISTICAL MODEL;

ACTION POTENTIALS; ANIMALS; COMPUTATIONAL BIOLOGY; MARKOV CHAINS; MODELS, NEUROLOGICAL; MODELS, STATISTICAL; MONTE CARLO METHOD; MOTOR CORTEX; NEURONS; RATS;

EID: 84908345348     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1003859     Document Type: Article

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