Receptive field inference with localized priors

PLoS Computational Biology

Volumn 7, Issue 10, 2011, Pages

  Park, Mijung ^a   Pillow, Jonathan W ^b  

^a The University of Texas at Austin   (United States)

^b UNIVERSITY OF TEXAS AT AUSTIN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORKS; MARKOV PROCESSES;

BAYESIAN; BAYESIAN METHODS; LARGE AMOUNTS OF DATA; LINEAR RECEPTIVE FIELDS; LOCALISED; NEURON SPIKE; ONE-DIMENSIONAL; PRIOR INFORMATION; RECEPTIVE FIELDS; SENSORY STIMULUS;

INFERENCE ENGINES;

ARTICLE; BAYES THEOREM; LEARNING ALGORITHM; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; MONTE CARLO METHOD; PROBABILITY; RECEPTIVE FIELD; SIGNAL NOISE RATIO; SIMULATION; STATISTICAL DISTRIBUTION; ACTION POTENTIAL; ALGORITHM; ANIMAL; BIOLOGICAL MODEL; BIOLOGY; COMPUTER SIMULATION; METHODOLOGY; PHOTOSTIMULATION; PHYSIOLOGY; PRIMATE; REGRESSION ANALYSIS; REPRODUCIBILITY; RETINA GANGLION CELL;

ACTION POTENTIALS; ALGORITHMS; ANIMALS; BAYES THEOREM; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; MARKOV CHAINS; MODELS, NEUROLOGICAL; MONTE CARLO METHOD; PHOTIC STIMULATION; PRIMATES; REGRESSION ANALYSIS; REPRODUCIBILITY OF RESULTS; RETINAL GANGLION CELLS;

EID: 80055065461     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1002219     Document Type: Article

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