Efficient Markov chain monte carlo methods for decoding neural spike trains

Neural Computation

Volumn 23, Issue 1, 2011, Pages 46-96

  Ahmadian, Yashar ^a   Pillow, Jonathan W ^b   Paninski, Liam ^a  

^a Och Spine at New York Presbyterian Hospitals   (United States)

^b UNIVERSITY OF TEXAS AT AUSTIN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACTION POTENTIAL; ALGORITHM; ANIMAL; ARTICLE; ARTIFICIAL NEURAL NETWORK; BAYES THEOREM; HUMAN; MONTE CARLO METHOD; NERVE CELL; NERVE CELL NETWORK; PHYSIOLOGY; PROBABILITY; RETINA GANGLION CELL; SIGNAL PROCESSING;

ACTION POTENTIALS; ALGORITHMS; ANIMALS; BAYES THEOREM; HUMANS; MARKOV CHAINS; MONTE CARLO METHOD; NERVE NET; NEURAL NETWORKS (COMPUTER); NEURONS; RETINAL GANGLION CELLS; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 78650592845     PISSN: 08997667     EISSN: 1530888X     Source Type: Journal    
DOI: 10.1162/NECO_a_00059     Document Type: Article

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