An analysis of hippocampal spatio-temporal representations using a Bayesian algorithm for neural spike train decoding

IEEE Transactions on Neural Systems and Rehabilitation Engineering

Volumn 13, Issue 2, 2005, Pages 131-136

  Barbieri, Riccardo ^a,d   Wilson, Matthew A ^b   Frank, Loren M ^c   Brown, Emery N ^a,b,d,e,f  

^a MASSACHUSETTS GENERAL HOSPITAL   (United States)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

^d HARVARD MEDICAL SCHOOL   (United States)

^e Neuroscience Statistics Research Laboratory   (United States)

^f NATIONAL ACADEMIES OF SCIENCES   (United States)

Author keywords

Bayesian algorithms; CA1 place cells; Decoding algorithms; Point process

Indexed keywords

NEURONS; OPEN CIRCULAR ENVIRONMENT; SPATIO-TEMPORAL ENVIRONMENT; TRAIN DECODING;

ALGORITHMS; DECODING; LIVING SYSTEMS STUDIES; STOCHASTIC CONTROL SYSTEMS;

NEURAL NETWORKS;

ALGORITHM; ANIMAL EXPERIMENT; ANIMAL TISSUE; ARTICLE; BAYES THEOREM; CONTROLLED STUDY; CORRELATION ANALYSIS; FORAGING; HIPPOCAMPUS; INFORMATION PROCESSING; LATENT PERIOD; LEARNING; MOTOR CORTEX; NONHUMAN; PARAMETER; PRIORITY JOURNAL; PYRAMIDAL NERVE CELL; RAT; STOCHASTIC MODEL; TASK PERFORMANCE;

ALGORITHMS; ANIMALS; BAYES THEOREM; COMPUTER SIMULATION; ELECTROENCEPHALOGRAPHY; HIPPOCAMPUS; MODELS, NEUROLOGICAL; MODELS, STATISTICAL; NERVE NET; NEURONS; RATS; RATS, LONG-EVANS; SPACE PERCEPTION;

EID: 22544487546     PISSN: 15344320     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNSRE.2005.847368     Document Type: Article

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