Discrete- and continuous-time probabilistic models and algorithms for inferring neuronal UP and DOWN states

Neural Computation

Volumn 21, Issue 7, 2009, Pages 1797-1862

  Chen, Zhe ^a,b   Vijayan, Sujith ^b,c   Barbieri, Riccardo ^a   Wilson, Matthew A ^d   Brown, Emery N ^a,b,e  

^a MASSACHUSETTS GENERAL HOSPITAL   (United States)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^c HARVARD UNIVERSITY   (United States)

^d Riken MIT Neuroscience Research Center   (United States)

^e HARVARD MIT DIVISION OF HEALTH SCIENCES AND TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACTION POTENTIAL; ALGORITHM; ANIMAL; ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOLOGICAL MODEL; BRAIN CORTEX; COMPUTER SIMULATION; CYTOLOGY; ELECTROENCEPHALOGRAPHY; HUMAN; MONTE CARLO METHOD; NERVE CELL; PHYSIOLOGY; RAT; STATISTICAL MODEL; TIME;

ACTION POTENTIALS; ALGORITHMS; ANIMALS; CEREBRAL CORTEX; COMPUTER SIMULATION; ELECTROENCEPHALOGRAPHY; HUMANS; MODELS, NEUROLOGICAL; MODELS, STATISTICAL; MONTE CARLO METHOD; NEURAL NETWORKS (COMPUTER); NEURONS; RATS; TIME FACTORS;

EID: 68349146850     PISSN: 08997667     EISSN: 1530888X     Source Type: Journal    
DOI: 10.1162/neco.2009.06-08-799     Document Type: Article

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